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PMC11276425_p12
|
PMC11276425
|
sec[2]/p[1]
|
3. Results
| 2.455078 |
biomedical
|
Study
|
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Data regarding anthropometric parameters are summarized in Table 2 . All measurements were significantly higher when comparing the normal weight and overweight categories and between overweight and obesity.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276425_p13
|
PMC11276425
|
sec[2]/p[2]
|
3. Results
| 3.525391 |
biomedical
|
Study
|
[
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Anthropometric and body composition variables were compared by sex, and a significant difference was found only in the values of neck circumference, being greater in boys (median of 28.6 vs. 26.5 cm; p = 0.02).
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276425_p14
|
PMC11276425
|
sec[2]/p[3]
|
3. Results
| 4.078125 |
biomedical
|
Study
|
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Correlations between %BF evaluated using BIA, NC, and other anthropometric variables are summarized in Table 3 . In the entire group, there was a direct and significant correlation between %BF and NC (r = 0.50, p < 0.001). However, this relationship lost statistical significance in the case of normal weight when separated according to body weight category. The relationship maintained its significance in subjects from the overweight and obesity groups; however, the r values were higher when combining these two groups (overweight and obesity, r = 0.37), probably due to the greater number of subjects in the analysis ( n = 62); as such, the results are reported in this way.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276425_p15
|
PMC11276425
|
sec[2]/p[4]
|
3. Results
| 4.085938 |
biomedical
|
Study
|
[
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In the entire group ( n = 112), %BF demonstrated a direct and significant correlation with all anthropometric parameters, being highest with BMI (0.73 for raw values and 0.71 for Z score). Again, these correlations were lower, and some were non-significant in subjects with normal weight; only BMI (both the raw value and the Z score) and TSF exhibited significant relationships, but with lower r values than for the total and the overweight/obesity groups. In the overweight/obese group, the correlations between %BF and all anthropometric parameters were direct and significant, with the highest values for BMI and WC as anthropometric indicators of adiposity. When analyzing the correlations by sex in the entire group, we again found differences with a higher r value in boys (0.67) than in girls (0.30) for the correlation between NC and %BF.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276425_p16
|
PMC11276425
|
sec[2]/p[5]
|
3. Results
| 4.078125 |
biomedical
|
Study
|
[
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[
0.99951171875,
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Finally, a multivariate analysis with %BF as the dependent variable and anthropometric indicators of adiposity as independent variables was performed. In all cases, BMI exhibited the highest correlation, with R 2 values of 0.50, followed by WC and MUAC (R 2 = 0.49 in both cases). For NC, the R 2 value was 0.30. Adjusted for all anthropometric variables, the R 2 value for this model was 0.57, while for the model that included only NC and MUAC, R 2 was 0.44 ( Table 4 ). Adjustment for sex did not modify the values reported in the model.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276425_p17
|
PMC11276425
|
sec[3]/p[0]
|
4. Discussion
| 1.932617 |
biomedical
|
Other
|
[
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[
0.01085662841796875,
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Obesity continues to be among the most significant public health problems worldwide, thus justifying efforts to identify indicators of this disease and its complications .
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276425_p18
|
PMC11276425
|
sec[3]/p[1]
|
4. Discussion
| 3.759766 |
biomedical
|
Review
|
[
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[
0.1201171875,
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For >20 years, BMI has been considered the best indicator for its identification, both clinically and in population studies, owing to its correlation with fat mass and its accessibility for use in clinical practice and in the community . However, some of its limitations have led to the evaluation of other anthropometric measures to identify those with excess body fat and considered indicators of metabolic risk, such as WC, WHR, and NC.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276425_p19
|
PMC11276425
|
sec[3]/p[2]
|
4. Discussion
| 3.96875 |
biomedical
|
Study
|
[
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Our results revealed that NC was a good indicator of adiposity because it correlated appropriately with %BF, although was not superior to BMI or WC, which exhibited higher correlation values in all cases, confirming them as the best anthropometric indicators of adiposity , even in the multivariate model in which the main contributor was BMI followed by WC.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276425_p20
|
PMC11276425
|
sec[3]/p[3]
|
4. Discussion
| 4.050781 |
biomedical
|
Study
|
[
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[
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Interestingly, NC did not exhibit a correlation with %BF in normal weight subjects. In the opinion of the authors, the age of the study subjects (5–10 years) was probably an influence in this regard given that, the accumulation of fat in the neck region should be minimal at this age and, therefore, not an accurate indicator of body fat, in addition to normal weight status in which fat accumulation is not excessive. In contrast, NC exhibited a direct and significant correlation with %BF in overweight and obese participants; therefore, it could be considered an adequate indicator of adiposity in children in these body weight categories. Similar to other studies, we found a direct correlation between NC and other anthropometric indicators of adiposity that was stronger when evaluating the entire group than when stratifying the subjects according to body weight category.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276425_p21
|
PMC11276425
|
sec[3]/p[4]
|
4. Discussion
| 4.042969 |
biomedical
|
Study
|
[
0.99951171875,
0.00018084049224853516,
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[
0.99951171875,
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Furthermore, as shown in the results, we tested a model with %BF as the dependent variable and NC and MUAC as independent variables because they are two measurements that do not require removing clothing for measurement and yielded an adequate correlation (R 2 = 0.44), which was higher than that obtained from NC but lower than that of MUAC, which had values close to BMI and WC. It is important to note that parameters, such as NC and MUAC, have the advantage of not requiring more than a tape measure for evaluation, which makes them more accessible than BMI. This can facilitate community evaluations where they could be used as screening tests for the diagnosis of overweight and obesity, with the purpose of referring those who exceed an established cut-off point for a complete evaluation .
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276425_p22
|
PMC11276425
|
sec[3]/p[5]
|
4. Discussion
| 4 |
biomedical
|
Study
|
[
0.99951171875,
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] |
[
0.99951171875,
0.00020134449005126953,
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0.00005179643630981445
] |
Few studies have evaluated the relationship between NC and %BF evaluated by BIA. In a cohort study from the United States, Phan et al. evaluated 75 predominantly Caucasian subjects (only 7% Hispanic) with obesity (mean age 13 ± 2.4 years) for the purpose of evaluating the correlation between changes in anthropometric measurements and fat mass evaluated using BIA in a follow-up ≥3 months. The only indicator that reflected changes in fat mass was BMI.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
PMC11276425_p23
|
PMC11276425
|
sec[3]/p[6]
|
4. Discussion
| 4.019531 |
biomedical
|
Study
|
[
0.99951171875,
0.0002123117446899414,
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] |
[
0.99658203125,
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0.0030803680419921875,
0.0000731348991394043
] |
In 2013, Bammann et al. evaluated 78 children 4–10 years of age from four countries in Europe, 35.8% of whom were overweight or obese. Neck circumference had an R 2 (unadjusted) value of 0.48 as a predictor of fat mass in a three-compartment model that included the use of BIA for the measurement of body mass. In multivariate models that included NC, WC, hip circumference, and arm circumference measurements, R 2 increased to 0.88, with WC as the main component of the model. Andrade et al. evaluated 2794 children and adolescents (6–19 years of age) in Brazil with a mean age of 11.1 ± 3.1 years and, in a manner similar to the present study, reported a direct and significant correlation between NC and BMI, and WC and %BF evaluated using BIA at all ages, with higher values in females than in males.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276425_p24
|
PMC11276425
|
sec[3]/p[7]
|
4. Discussion
| 3.335938 |
biomedical
|
Study
|
[
0.99853515625,
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] |
[
0.99755859375,
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0.00006461143493652344
] |
The differences that we observed when the analysis was carried out by sex have already been reported by other authors , although the results are not consistent with those of the present study. Andrade et al. reported higher NC values in boys, although in those over 10 years of age; furthermore, both in the report by Andrade et al., as in that of Kim et al., the correlation values between NC and %BF were higher in girls. It would be necessary to study a larger number of children to evaluate these differences.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276425_p25
|
PMC11276425
|
sec[3]/p[8]
|
4. Discussion
| 3.982422 |
biomedical
|
Study
|
[
0.99951171875,
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] |
[
0.9775390625,
0.0006508827209472656,
0.0215301513671875,
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] |
Neck circumference is a simple, rapid, low-cost measurement that is not influenced by fasting conditions, clothing, ambient temperature, or sociocultural limitations . It also has the advantage of not requiring the removal of clothing for evaluation, even partially as required to measure WC, which is especially useful in individuals stigmatized by their body weight, who may also have a phobia of weighing themselves, and in circumstances in which removing clothing to measure WC is not feasible or is uncomfortable. Furthermore, NC has been consistently associated in practically all studies, including the present work, with markers of general and central adiposity, such as BMI, WC, and waist/hip ratio, in both pediatric and adult populations . However, BMI appeared to be the best indicator of adiposity in children, even during longitudinal follow-up, regardless of age, sex, ethnicity, and limitations .
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276425_p26
|
PMC11276425
|
sec[3]/p[9]
|
4. Discussion
| 3.931641 |
biomedical
|
Study
|
[
0.99951171875,
0.0002684593200683594,
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[
0.99951171875,
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0.00005930662155151367
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The present study had some limitations, including its cross-sectional design, which precluded us from drawing causal inferences, the small number of subjects included, subjects who were identified in a hospital unit, and the fact of determining correlations with other indirect indicators of adiposity, such as BIA, which, although is a useful method and practical for estimating body fat, has limitations regarding its precision compared to other measurement methods . However, in everyday practice, it is not easy to estimate body fat using more precise methods, such as dual X-ray absorptiometry or other models with ≥3 components.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276425_p27
|
PMC11276425
|
sec[4]/p[0]
|
5. Conclusions
| 4.046875 |
biomedical
|
Study
|
[
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[
0.99755859375,
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Neck circumference exhibited a consistent relationship with other anthropometric indicators that indirectly reflected adiposity in school-age children and had an adequate correlation with %BF evaluated using BIA, particularly in overweight or obese subjects. Therefore, NC would be useful in the screening of population groups with the advantage of not requiring any specialized instruments for its measurement other than a tape measure. Its role as an indicator of metabolic risk is still being studied; however, according to our results, it could be considered in overweight or obese subjects, although it is not currently recommended for use as an isolated parameter. Body mass index and waist circumference were the best indicators of general and central adiposity, respectively.
|
[
"Enrique Romero-Velarde",
"Karen G. Córdova-García",
"Laura C. Robles-Robles",
"Ingrid J. Ventura-Gómez",
"Clío Chávez-Palencia"
] |
https://doi.org/10.3390/children11070868
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p0
|
PMC11276437
|
sec[0]/p[0]
|
1. Introduction
| 4.242188 |
biomedical
|
Study
|
[
0.99951171875,
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[
0.978515625,
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Breast cancer (BC) represents the most frequent malignancy worldwide and the most lethal in women, with 2 million new cases diagnosed each year . In addition to the biological features, including BC subtypes, tumor grading and other transversal biomarkers that directly and independently correlate with tumor aggressiveness, inherited genetic alteration plays a role in BC hereditary predisposition . Different epidemiological studies identified a set of eight genes ( ATM , BARD1 , BRCA1 , BRCA2 , CHEK2 , PALB2 , RAD51C and RAD51D ) mostly responsible for hereditary BC. Among these, the two main susceptibility genes correlated with a higher risk to develop breast and ovarian carcinoma are BRCA1 and BRCA2 .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p1
|
PMC11276437
|
sec[0]/p[1]
|
1. Introduction
| 4.316406 |
biomedical
|
Review
|
[
0.99853515625,
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[
0.16943359375,
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0.81640625,
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Germline BRCA1 and BRCA2 alterations increase the probability to develop BC and other tumor types, including ovarian, pancreatic, prostate, colorectal cancer and melanoma . Over the years, the availability of next generation sequencing (NGS) technologies led to an increase of BRCA1 and BRCA2 genetic testing requests to improve diagnoses, prognostic information, research and clinical practice. The currently accepted method for the BRCA1 and BRCA2 variants’ classification is based on the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium classification, supported by the ClinVar database, according to the International Agency for Research on Cancer (IARC)’s recommendations . This classification system includes five classes, as follows: (i) benign (class I); (ii) likely benign (class II); (iii) variant of uncertain significance (VUS, class III); (iv) likely pathogenic (class IV) and (v) pathogenic (PV, class V). A VUS or conflicting interpretation of pathogenicity (CIP) variant consists of an alteration in the gene sequence, with unknown consequences on the function of the gene product or on the potential risk for disease development. The identification of VUS is evaluated as inconclusive and clinically not actionable for the patients’ and unaffected carriers’ management.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p2
|
PMC11276437
|
sec[0]/p[2]
|
1. Introduction
| 3.910156 |
biomedical
|
Study
|
[
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] |
[
0.97705078125,
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To date, the frequency of VUS reporting is about 10–20% in women who have undergone BRCA analysis . This frequency depends on the testing prevalence and/or population ancestry . Several studies reported a VUS frequency of 21% in the African-American population, 5–6% in the European ancestry population and up to 15% in European subjects .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p3
|
PMC11276437
|
sec[0]/p[3]
|
1. Introduction
| 4.183594 |
biomedical
|
Study
|
[
0.99951171875,
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] |
[
0.87255859375,
0.004184722900390625,
0.12298583984375,
0.00036716461181640625
] |
The significant rate of CIP/VUS retrieval furthers a claim for an alternative approach of their annotation or re-classification as benign or pathogenic alterations. With the advances of bioinformatics biology, different groups have improved high-throughput pipelines and in silico tools to identify functionally germline CIP/VUS alterations . Among them, Polymorphism Phenotyping v.2 (PolyPhen-2) and Sorting Intolerant From Tolerant (SIFT) are two algorithms used to assess the functional impact of missense alterations, whereas the Mutation Taster (MT) and Protein Variation Effect Analyzer (PROVEAN) can be utilized also to improve potential deleterious effects of synonymous or intronic and indel mutations.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p4
|
PMC11276437
|
sec[0]/p[4]
|
1. Introduction
| 4.066406 |
biomedical
|
Study
|
[
0.99951171875,
0.0004565715789794922,
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] |
[
0.99951171875,
0.00021064281463623047,
0.00040602684020996094,
0.00009870529174804688
] |
In this study, we evaluated the in silico predictions of BRCA1 and BRCA2 CIP/VUS alterations in a cohort of BC patients, according to the ENIGMA or ClinVar database, using PolyPhen-2, SIFT, MT and PROVEAN tools. By doing so, we investigated whether these algorithms could predict the clinical effect and significance of CIP/VUS alterations, eventually impacting the clinical management of subjects diagnosed with BC.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276437_p5
|
PMC11276437
|
sec[1]/sec[0]/p[0]
|
2.1. Study Population
| 3.808594 |
biomedical
|
Study
|
[
0.99853515625,
0.0012540817260742188,
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] |
[
0.9990234375,
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0.00015342235565185547
] |
A retrospective collection of molecular data from a total of 1027 patients with breast and ovarian cancer, melanoma, pancreatic tumor or prostate carcinoma was carried out at the “Center of Experimental Oncology and Hematology” of the Hospital Policlinico “G. Rodolico—San Marco” of Catania from January 2017 to May 2023. The patients were referred to our Molecular Diagnostics Laboratory for BRCA1 and BRCA2 genetic testing. The present study was conducted in accordance with the Declaration of Helsinki and in accordance with the local legislation and institutional review board. All participants provided their written informed consent before undergoing molecular analysis and to participate in this study.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p6
|
PMC11276437
|
sec[1]/sec[0]/p[1]
|
2.1. Study Population
| 3.939453 |
biomedical
|
Study
|
[
0.97802734375,
0.0213165283203125,
0.0005965232849121094
] |
[
0.57421875,
0.41455078125,
0.004245758056640625,
0.00714111328125
] |
Oncogenetic counselling was carried out for each subject by a multidisciplinary team including an oncologist, a geneticist and a psychologist before performing BRCA1 and BRCA2 mutational analysis, with the purpose of identifying patients at high risk of harboring a PV in BRCA1 and/or BRCA2 genes. Patient selection was performed according to the Italian Association of Medical Oncology (AIOM) guidelines and the Sicily local recommendations, Percorso Diagnostico Terapeutico e Assistenziale (PDTA) relativo alla Sindrome dei tumori eredo-familiari della mammella e/o dell’ovaio ( http://pti.regione.sicilia.it/portal/page/portal/PIR_PORTALE/PIR_LaStrutturaRegionale/PIR_AssessoratoSalute/PIR_Infoedocumenti/PIR_DecretiAssessratoSalute/PIR_DecretiAssessoriali/PIR_DecretiAssessorialianno2019/Allegato%20al%20D.A.%20n.32.pdf . The latest version released on 11 July 2024.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11276437_p7
|
PMC11276437
|
sec[1]/sec[1]/p[0]
|
2.2. DNA Extraction from Patients
| 4.070313 |
biomedical
|
Study
|
[
0.99951171875,
0.0003325939178466797,
0.0001519918441772461
] |
[
0.99853515625,
0.0011844635009765625,
0.00025391578674316406,
0.0001157522201538086
] |
Each patient provided 20 milliliters (mL) of peripheral blood within a single blood draw, which was collected into EDTA tubes (BD Biosciences, Franklin Lakes, NJ, USA). After the blood draw, fenomic DNA was isolated from 0.7 mL of whole blood samples using the Qiasymphony DSP DNA Midi kit Isolation Kit (QIAGEN, Hilden, Italy), and quantified using a Qubit ® 3.0 or Qubit ® 3.0 fluorometer (Thermofisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276437_p8
|
PMC11276437
|
sec[1]/sec[2]/p[0]
|
2.3. Next Generation Sequencing Analysis for BRCA1/2 Genes
| 4.222656 |
biomedical
|
Study
|
[
0.9990234375,
0.0005927085876464844,
0.00018227100372314453
] |
[
0.98876953125,
0.0097198486328125,
0.0011129379272460938,
0.00037217140197753906
] |
Target enrichment and library preparation was performed using an Oncomine™ BRCA Research Assay Chef. After the preparation, the samples were loaded into an Ion AmpliSeq™ Chef Reagents DL8 cartridge for automated libraries preparation, as previously published . The kit contains two multiplex PCR primer pools, proficient to study all BRCA1 and BRCA2 genes. In brief, 10 ng of each DNA sample were placed in the barcode plate for library preparation. The plate, with all reagents and consumables, was loaded on the Ion Chef™ Instrument. An automated library preparation and pooling of barcoded sample libraries was then performed on the Ion Chef™ Instrument. The quantity of pooled libraries was evaluated using a Qubit ® 3.0 or 4.0 fluorometer. Lastly, the pooled libraries were mixed in an equimolar ratio in the Ion Chef™ Library Sample Tube and loaded onto the Ion Chef™ Instrument. The sequencing was performed with an Ion 510 or 520 Chip, using an Ion Gene Studio S5 Plus System instrument (Thermofisher Scientific, Waltham, MA, USA). Analysis of data was performed with Amplicon Suite (SmartSeq s.r.l., Alessandria, Italy) and Ion Reporter Software (v. 5.20.2.0).
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276437_p9
|
PMC11276437
|
sec[1]/sec[3]/p[0]
|
2.4. Data Analysis and Genetic Classification
| 4.171875 |
biomedical
|
Study
|
[
0.99951171875,
0.00030231475830078125,
0.0001329183578491211
] |
[
0.998046875,
0.0004668235778808594,
0.0011529922485351562,
0.00010538101196289062
] |
All alterations’ nomenclature followed current guidelines of the Human Genome Variation Society, available online . The clinical significance of BRCA1 and BRCA2 alterations was characterized using the classification of the consortium ENIGMA , and by consulting several databanks, such as ClinVar, ARUP, BRCA Exchange, IARC_LOVD and UMD. The classification includes the following five distinct classes of risk: benign (class I), likely benign (class II), variant of uncertain significance (VUS, class III), likely pathogenic (class IV) and pathogenic (class V). The alterations were classified with a conflicting interpretation of pathogenicity, and variants of uncertain significance were defined as CIP/VUS, respectively. The effect of alterations on protein structure and function was also analyzed by VarSome, an informatic tool that allows access to about 30 databases, as previously described .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p10
|
PMC11276437
|
sec[1]/sec[4]/p[0]
|
2.5. Sanger Sequencing
| 4.082031 |
biomedical
|
Study
|
[
0.99951171875,
0.0005083084106445312,
0.00016689300537109375
] |
[
0.99462890625,
0.004833221435546875,
0.0003592967987060547,
0.00031280517578125
] |
The presence of each CIP/VUS mutation was verified by Sanger sequencing. A specific primer forward and reverse were designed for each of the detected alterations by using the BRCA1 and BRCA2 gene reference sequences . After, a PCR specific to the target sequence was performed, followed by Sanger sequencing.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999994 |
PMC11276437_p11
|
PMC11276437
|
sec[1]/sec[5]/p[0]
|
2.6. In Silico Analysis
| 3.861328 |
biomedical
|
Study
|
[
0.99951171875,
0.00029540061950683594,
0.0001430511474609375
] |
[
0.9951171875,
0.0040740966796875,
0.0005984306335449219,
0.0002799034118652344
] |
To attribute a potential clinical significance to each CIP/VUS, the following in silico prediction tools were used: Protein Variation Effect Analyzer ; Sorting Intolerant From Tolerant , Mutation Taster and Polymorphism Phenotyping v.2 , as previously reported .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p12
|
PMC11276437
|
sec[1]/sec[5]/p[1]
|
2.6. In Silico Analysis
| 3.580078 |
biomedical
|
Other
|
[
0.99609375,
0.0023651123046875,
0.0016603469848632812
] |
[
0.0105438232421875,
0.9873046875,
0.0013017654418945312,
0.0009217262268066406
] |
PROVEAN is a bioinformatic tool for the screening of alterations in order to determine an amino acid substitution, nonsynonymous or indel variants that are predicted to have an impact on protein function.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999994 |
PMC11276437_p13
|
PMC11276437
|
sec[1]/sec[5]/p[2]
|
2.6. In Silico Analysis
| 4.242188 |
biomedical
|
Other
|
[
0.99560546875,
0.0032825469970703125,
0.0009684562683105469
] |
[
0.11602783203125,
0.798828125,
0.08013916015625,
0.004940032958984375
] |
PolyPhen-2 is a tool which predicts the effect of the amino acid change on a human protein function and structure. The algorithm identifies protein ID numbers and entry names using the UniProtKB database. The tool generates a report in which the alteration may be classified into three categories, as follows: benign, possibly damaging and probably damaging. A result of “benign” (score ≤ 0.5) suggests that the mutation is not likely to affect protein function. A result of “possibly damaging” (0.5 < score ≤ 0.9) points to a possible effect on protein function. A result of “probably damaging” (score > 0.9) indicates that the alteration is likely to impact protein function. The algorithm uses an amino acid alteration or a protein sequence as input, then performs a BLAST search to recognize homologous sequences and generates scores. The variants are classified into a functional category, either deleterious or neutral, based on a pre-set threshold, with a default threshold value fixed at −2.5. Therefore, variants with scores below this threshold are categorized as deleterious.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11276437_p14
|
PMC11276437
|
sec[1]/sec[5]/p[3]
|
2.6. In Silico Analysis
| 3.914063 |
biomedical
|
Other
|
[
0.99560546875,
0.003162384033203125,
0.0014476776123046875
] |
[
0.0165252685546875,
0.978515625,
0.0034198760986328125,
0.0015687942504882812
] |
MutationTaster is an online tool able to investigate the potential effect of DNA sequence variants on the gene products. The algorithm works on both protein and DNA level by testing substitutions of single amino acids, as well as synonymous or intronic variant. The alteration is predicted as one of four possible types: (i) disease causing (probably deleterious), (ii) disease causing automatic (variation known to be deleterious), (iii) polymorphism (probably neutral) and (iv) polymorphism automatic (known to be neutral).
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
PMC11276437_p15
|
PMC11276437
|
sec[1]/sec[5]/p[4]
|
2.6. In Silico Analysis
| 4.109375 |
biomedical
|
Other
|
[
0.99560546875,
0.0032062530517578125,
0.0012359619140625
] |
[
0.038330078125,
0.94970703125,
0.00946807861328125,
0.0023403167724609375
] |
SIFT is a bioinformatics program that predicts whether an amino acid alteration may have an impact on protein function. The software analyzes nonsynonymous polymorphisms and missense mutations based on sequence homology and the physical properties of amino acids. Therefore, SIFT chooses related proteins and elaborates an alignment of these proteins with the query. Finally, the software estimates the probability that the toleration of an amino acid at a position is conditional on the most frequent amino acid being tolerated. The score can range from 0 to 1, and substitutions with scores < 0.05 are considered deleterious.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p16
|
PMC11276437
|
sec[1]/sec[5]/p[5]
|
2.6. In Silico Analysis
| 3.783203 |
biomedical
|
Study
|
[
0.9990234375,
0.0006127357482910156,
0.000362396240234375
] |
[
0.66015625,
0.33642578125,
0.0018072128295898438,
0.0018072128295898438
] |
The CIP/VUS alterations predicted as “possibly/probably damaging/intolerant” were classified as a “damaging” variant, whereas the mutations predicted as “benign moderate or strong/tolerant” were classified as a “neutral” variant.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p17
|
PMC11276437
|
sec[2]/sec[0]/p[0]
|
3.1. Population Characteristics
| 3.880859 |
biomedical
|
Study
|
[
0.9990234375,
0.0008101463317871094,
0.0002294778823852539
] |
[
0.9990234375,
0.00048804283142089844,
0.00023305416107177734,
0.00012874603271484375
] |
A total of 1027 patients were screened for germline BRCA1/2 mutations between January 2017 and May 2024. Molecular analyses were performed at the Center of Experimental Oncology and Hematology of the Hospital Policlinico “G. Rodolico—San Marco” of Catania, according to Sicilian guidelines . Among the 1027 recruited, 860 subjects had breast cancer, 48 had ovarian cancer, 60 had pancreatic cancer, 47 had prostate cancer and 12 had melanomas. Patient distribution according to cancer type and data results is shown in Figure 1 .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p18
|
PMC11276437
|
sec[2]/sec[0]/p[1]
|
3.1. Population Characteristics
| 2.402344 |
biomedical
|
Study
|
[
0.99658203125,
0.0018758773803710938,
0.0014781951904296875
] |
[
0.99560546875,
0.00357818603515625,
0.00031876564025878906,
0.0002808570861816406
] |
We selectively focused our study on the breast cancer cohort. These patients displayed a median age of 55 years (interquartile range of 47–65) and were mainly females ( n = 831, 97%).
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p19
|
PMC11276437
|
sec[2]/sec[0]/p[2]
|
3.1. Population Characteristics
| 4.097656 |
biomedical
|
Study
|
[
0.9990234375,
0.0008525848388671875,
0.00020885467529296875
] |
[
0.9990234375,
0.0005044937133789062,
0.00020766258239746094,
0.00018548965454101562
] |
Among these subjects, 151 (18%) harbored a BRCA1/2 mutation, and only one patient was male, whereas all of the others were women. Fifty-nine (7%) had a PV, while ninety-two (10.6%) harbored a CIP/VUS. Moreover, 29 of the 58 pathogenic variants (49.2%) occurred in BRCA1, and 30 (50.8%) occurred in BRCA2 , while 11 CIP/VUSs were in BRCA1 (12%) and 81 (88%) were in BRCA2 . No large genomic rearrangements were detected by MLPA analysis.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
PMC11276437_p20
|
PMC11276437
|
sec[2]/sec[1]/p[0]
|
3.2. Description and Localization of BRCA1 and BRCA2 CIP/VUS Variants
| 4.046875 |
biomedical
|
Study
|
[
0.99951171875,
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[
0.99951171875,
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Next, we evaluated the type of BRCA1 and BRCA2 CIP/VUS variants. Among the ninety-two patients harboring CIP/VUS, two subjects presented the same alteration in the BRCA1 sequence; therefore, we found ten different BRCA1 CIP/VUS alterations. Nine of these alterations were single nucleotide variants (SNVs), whereas only one was a deletion ( Table 1 ).
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p21
|
PMC11276437
|
sec[2]/sec[1]/p[1]
|
3.2. Description and Localization of BRCA1 and BRCA2 CIP/VUS Variants
| 4.339844 |
biomedical
|
Study
|
[
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[
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Concerning BRCA2 , the genetic analysis showed a total of 55 different CIP/VUS mutations in 81 individuals. Furthermore, it is of interest that the c.3509C > T alteration was found in five subjects, the c.7871A > G mutation was found in seven patients, four individuals presented the c.8850G > T variation, the c.9586A > G variant was found in three patients and the c.9613_9614delGCinsCT del/ins was found in three subjects. Each of the other eight alterations were attained in two individuals. Moreover, in the case of the BRCA2 sequence, fifty-three of fifty-five alterations were SNVs, while only one was a deletion and another one a deletion/insertion ( Table 2 ). Specifically, the c.7871A > G alteration at the protein level, found in the majority of our patients, results in the change of a tyrosine to a cysteine located in the helical domain. It is of interest that the BRCA2 c.9052_9057delAGTAAA alteration deletes six nucleotides from exon 23 of the BRCA2 mRNA, and it is predicted to result in an in-frame deletion. Furthermore, the c.9613_9614delGCinsCT alteration replaces alanine with leucine at the codon 3205 of the BRCA2 protein. The alanine amino acid is moderately conserved, and it has similar physiochemical characteristic to leucine.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p22
|
PMC11276437
|
sec[2]/sec[1]/p[2]
|
3.2. Description and Localization of BRCA1 and BRCA2 CIP/VUS Variants
| 4.214844 |
biomedical
|
Study
|
[
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[
0.99951171875,
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Subsequently, we mapped the BRCA1 and BRCA2 CIP/VUS alterations through the proteins’ binding regions and functional domain . In the BRCA1 gene, the 10 CIP/VUS variants were distributed along the entire gene sequence. Among these, the c.4063_4065delAAT deletion was located inside the coiled-coil domain, which binds to the WD 40 domain of the PALB2 gene. Among the BRCA2 gene, 30.1% variants were located in the BCCR regions and 36.4% of CIP/VUS alterations in the OCCRs. For BRCA2 protein, we found that two CIP/VUS alterations were mapped in the DNA Binding Domain.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276437_p23
|
PMC11276437
|
sec[2]/sec[2]/p[0]
|
3.3. In Silico Evaluation of BRCA1 and BRCA2 CIP/VUS Variants
| 4.15625 |
biomedical
|
Study
|
[
0.99951171875,
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[
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] |
In order to investigate the prediction of the effects and potential clinical significance of BRCA1 and BRCA2 CIP/VUS variants, we compared the performance of four different in silico tools. Each missense alteration was analyzed with the PROVEAN, SIFT, PolyPhen-2 and Mutation Taster, whereas the BRCA1 deletion CIP/VUS mutation was interrogated with the PROVEAN and Mutation Taster and the only BRCA2 del/ins were interrogated with the PolyPhen-2 and Mutation Taster ( Table 1 ). The in silico analysis for BRCA1 CIP/VUS alterations predicted it as reaching a 3/10 (30%) damaging alteration of the variant with either PROVEAN or Mutation Taster, 4/9 (44.4%) with SIFT and 7/9 (77.8%) with PolyPhen-2 . Among BRCA2 CIP/VUS variations, the in silico prediction achieved a 9/54 (16.7%) damaging alteration with PROVEAN, 20/53 (37.8%) with SIFT, 23/54 (42.6%) with PolyPhen-2 and 14/55 (34.1%) with Mutation Taster .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p24
|
PMC11276437
|
sec[2]/sec[2]/p[1]
|
3.3. In Silico Evaluation of BRCA1 and BRCA2 CIP/VUS Variants
| 4.046875 |
biomedical
|
Study
|
[
0.99951171875,
0.00039958953857421875,
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[
0.99951171875,
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Next, we wanted to evaluate the agreement rate of the four in silico tools. To this end, we focused this analysis only on the 55 BRCA2 CIP/VUS alterations, due to the larger sample size. The analysis of all CIP/VUS variants by the four approaches showed that 42/55 alterations were predicted as damaging at least one in silico used tool. Prediction agreement was achieved in 25/55 (45.5%) CIP/VUS mutations, with 23 (92%) and 2 (8%) CIP/VUS alterations predicted as neutral and damaging, respectively .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276437_p25
|
PMC11276437
|
sec[2]/sec[2]/p[2]
|
3.3. In Silico Evaluation of BRCA1 and BRCA2 CIP/VUS Variants
| 4.117188 |
biomedical
|
Study
|
[
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] |
[
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Lasty, we assessed the consensus in prediction outcomes for the 42 tested CIP/VUS alterations with an estimated damaging effect. We found a concordance for all four in silico tools in two alterations . Moreover, the highest consensus was obtained in 12/42 (28.6%) mutations by considering three out four in silico tools. In detail, a concordance between SIFT, PolyPhen-2 and MT was observed for eight variants, whereas two CIP/VUS alterations were in agreement with PROVEAN, PolyPhen-2 and MT, or PROVEAN, SIFT and PolyPhen-2. Notably, 17/42 (40.5%) of the predicted variants were unique for being damaging in in silico tools alone .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
PMC11276437_p26
|
PMC11276437
|
sec[3]/p[0]
|
4. Discussion
| 4.390625 |
biomedical
|
Study
|
[
0.9990234375,
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] |
[
0.5830078125,
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] |
Accurate classification of molecular alterations with regard to their pathogenic potential is of pivotal importance, especially for patients presenting a familial cancer history. Recently, the development of high-throughput technologies determined unprecedented progress in BRCA1 and BRCA2 genetic testing. To this aim, the molecular analysis of BRCA1 and BRCA2 allows the identification of patients with high probability to develop different tumor types, including breast, ovarian and prostate cancer, among others. At the present time, approximately 20.000 BRCA1/2 variants have been recognized and categorized according to the American College of Medical Genetics and ENIGMA systems . With the recent increase in the use of NGS technology, the spectrum of missense and spicing alteration, described as CIP and VUS alterations, were increased in the BRCA1 and BRCA2 sequence by a genetic test. It was estimated that up to 15% of VUSs were identified among European subjects, with higher rates in African-American and Hispanic populations . To this regard, the useful approaches that measure the impact of CIP or VUS on biological processes represent an alternative method for pathogenic prediction and clinical annotations.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276437_p27
|
PMC11276437
|
sec[3]/p[1]
|
4. Discussion
| 4.386719 |
biomedical
|
Study
|
[
0.9990234375,
0.0007839202880859375,
0.00021719932556152344
] |
[
0.99853515625,
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0.00021886825561523438
] |
In this study, we used four in silico prediction tools in order to predict the effect and potential significance of the BRCA1 and BRCA2 CIP/VUS alterations for the patient’s clinical management. First, we characterized the CIP/VUS alterations according to the ENIGMA and ClinVar databases. Of the 860 BC patients analyzed, 10.6% harbored BRCA1 and BRCA2 CIP/VUS mutations. This frequency was concordant with previous data reported in the literature . The highest numbers of CIP/VUS were distributed in the BRCA2 sequence, and similar findings were observed in published studies . Our analysis showed a CIP/VUS landscape that is differently distributed in the studied population. Indeed, while some CIP/VUSs were detected only in a single subject, others were repeated in more individuals, such as the c.3509C > T and c.7871A > G, which were observed in two different groups of seven patients. For c.3509C > T, although this variant is still defined as a CIP mutation, several findings, including co-occurrence, have a lack of segregation with the disease of association in case-control studies, thus supporting its classification as benign . Moreover, it occurs at a poorly conserved position in BRCA protein. Concerning the c.7871A > G alteration, it was previously described in a cohort of breast and ovarian cancer. At the protein level, it causes the substitution of a conservative amino acid that results in a reduced stability of BRCA2 protein . Furthermore, two del/ins were identified in the BRCA2 gene. The first is represented by the deletion of c.9052_9057delAGTAAA, observed in a subject and previously reported in individuals with personal or family history of cancer related to BRCA . However, to date, its clinical significance remains unclear. The second del/ins is the c.9613_9614delGCinsCTdel/ins, also previously detected in both breast and prostate cancer subjects . This variant rises at a non-conserved position and in a domain of unknown function.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p28
|
PMC11276437
|
sec[3]/p[2]
|
4. Discussion
| 4.492188 |
biomedical
|
Study
|
[
0.9990234375,
0.0005292892456054688,
0.00022685527801513672
] |
[
0.99853515625,
0.00042939186096191406,
0.0005846023559570312,
0.00021636486053466797
] |
Subsequently, we mapped the BRCA1 and BRCA2 CIP/VUS alterations along the functional domains of the protein and the gene putative OCCR and BCCR regions, which were previously defined by Rebbeck et al. . These regions were defined as dangerous for developing breast and ovarian cancer, respectively. With regards to the gene localization of CIP/VUS, the c.4063_4065delAAT deletion interested the coiled-coil domain of the BRCA1 protein. This domain is crucial for the interaction with PALB2 that binds to BRCA2 and acts by recruiting BRCA2 to the chromatin and promoting the homologous recombination. Loss of this interaction results in an increase of tumorigenesis . The BRCA2 CIP/VUSs were distributed along the entire sequence. Among them, the c.7479G > A alteration is mapped in the DNA Binding Domain (DBD), as required for homologous recombination . This domain is located in the C-terminal region encompassed Helical domain, Tower domain and three OB folds. The DBD and RAD51 interacting sites of BRCA2 are able to promote the assembly of RAD51 toward single-strand DNA and single-strand DNA/double-strand DNA connection .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276437_p29
|
PMC11276437
|
sec[3]/p[3]
|
4. Discussion
| 4.460938 |
biomedical
|
Study
|
[
0.9990234375,
0.0005636215209960938,
0.00021386146545410156
] |
[
0.99853515625,
0.0003330707550048828,
0.0010595321655273438,
0.00020396709442138672
] |
To understand whether the CIP/VUS variants may potentially be damaging, we interrogated the four in silico prediction tools, PROVEAN, SIFT, PolyPhen-2 and Mutation Taster. Since CIP/VUSs are mostly a change of amino acid with residues with the same properties or in-frame ins/del alteration, their impact on protein function is often complex for the interpreter. The in silico interrogation is predicted as damaging few of the CIP/VUS alterations. Although a similar performance was observed, the PolyPhen-2 and SIFT tools were mostly predicted to damage alterations (47.6% and 39%), compared to the other two in silico approaches (MT = 26.1% and PROVEAN = 19%). Interestingly, both the c.7871A > G and c.9839C > A mutations were predicted to have a damaging effect by the four algorithms. The c.7871A > G alteration has been described in several breast and ovarian cancer patients. This mutation mapped at codon 2624 of the BRCA2 protein in the helical domain. This domain binds the 70 amino acids deleted in split-end/split food syndrome (DSS1) protein. This variation results in a significant decrease in structural stability, suggesting a damaging effect on protein function . To date, supporting evidence on its function is conflicting, because the clinical significance of this alteration is still unclear . Furthermore, the c.9839C > A alteration, located in exon 26 of the BRCA2 sequence, has been shown to modify a poorly conserved amino acid. Its clinical interpretation is still controversial, and a functional test suggested its neutral effect on protein function, whereas in silico approaches predicted a damaging impact, as previously reported .
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999994 |
PMC11276437_p30
|
PMC11276437
|
sec[3]/p[4]
|
4. Discussion
| 4.066406 |
biomedical
|
Study
|
[
0.99951171875,
0.0003540515899658203,
0.0002536773681640625
] |
[
0.99951171875,
0.00014793872833251953,
0.0003383159637451172,
0.00006371736526489258
] |
A limitation of the current study was the small size of the dataset of CIP/VUS alterations detected in the BRCA1 sequence. Consequently, we focused our next analysis on BRCA2 CIP/VUS mutations. When we considered the four approaches to predict the effect of the variants on the clinical outcome, a low consensus was achieved for the CIP/VUSs classified as damaging (8%), compared to neutral. The absence of agreement between the in silico tools can generate confusion in the interpretation of these variants. To this regard, there are studies with controversial results. Some of them suggested that the combination of different in silico algorithms may help to improve the prediction performance. Other researchers reported opposite data . In our study, a higher concordance was obtained (28.6%) when we used three of four in silico tools, suggesting that this approach may be more efficient than the previous one.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276437_p31
|
PMC11276437
|
sec[4]/p[0]
|
5. Conclusions
| 3.949219 |
biomedical
|
Study
|
[
0.99951171875,
0.00046825408935546875,
0.00018727779388427734
] |
[
0.9326171875,
0.0223846435546875,
0.04449462890625,
0.0007185935974121094
] |
The inherent uncertainty related to the nature of CIP/VUS does not allow us to classify these alterations as deleterious or benign, potentially influencing patients’ management. In this context, the use of bioinformatic in silico tools may help to identify variants with a potentially damaging effect. Still, the lack of a substantial agreement between the different algorithms suggests that these bioinformatic approaches should be combined with an accurate assessment of the family and clinical history of the proband.
|
[
"Stefania Stella",
"Silvia Rita Vitale",
"Michele Massimino",
"Federica Martorana",
"Irene Tornabene",
"Cristina Tomarchio",
"Melissa Drago",
"Giuliana Pavone",
"Cristina Gorgone",
"Chiara Barone",
"Sebastiano Bianca",
"Livia Manzella"
] |
https://doi.org/10.3390/genes15070943
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p0
|
PMC11276449
|
sec[0]/p[0]
|
1. Introduction
| 4.847656 |
biomedical
|
Study
|
[
0.99853515625,
0.0008754730224609375,
0.0006089210510253906
] |
[
0.8720703125,
0.00959014892578125,
0.1173095703125,
0.0011663436889648438
] |
In the retina, the photoreceptors (PRs) and retinal pigment epithelium (RPE) act as a functional unit. RPE cells form a monolayer between Bruch’s membrane above the choriocapillaris (CC) and the PRs, but the apical surface of RPE cells have microvillae that wrap PRs and increase the surface area to promote nutrient and waste exchange via transepithelial transport between PRs and CC layers. In addition to this morphological coupling, the PR-RPE complex engages in several key aspects of visual function that exemplify its intertwined nature . RPE is central to the visual cycle pathway for the regeneration of 11- cis -retinal from all- tran s-retinal produced during phototransduction, a capability lacking in PRs. Pigments (lutein, zeaxanthin, and lipofuscin) and melanin in the PR-RPE complex absorb light and protect against photo-oxidative damage via reactive oxygen species. The RPE promotes ion homeostasis in the subretinal space important for ion (K + , Na + , Cl − ) exchange during the visual cycle. The PR and RPE also work closely together during photoreceptor outer segment (OS) renewal, where shed segments are digested, recycled in the RPE, and specific molecules returned to the PR for use in rebuilding OS disks, maintaining an overall constant OS length over the diurnal cycle. The RPE secretes a variety of growth factors important to maintain the structural integrity of the retina (e.g., pigment epithelium-derived factor, PEDF) and CC (e.g., vascular endothelial growth factor, VEGF).
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p1
|
PMC11276449
|
sec[0]/p[1]
|
1. Introduction
| 4.355469 |
biomedical
|
Review
|
[
0.9990234375,
0.0006985664367675781,
0.0004482269287109375
] |
[
0.2474365234375,
0.0208740234375,
0.72998046875,
0.001605987548828125
] |
The delicate symbiotic interplay in the PR-RPE complex is disrupted with disease. Inherited retinal degenerations (IRDs) involve mutations in genes for proteins essential to the visual cycle . Atrophic (dry) age-related macular degeneration (AMD) involves the disruption of normal OS phagocytosis and enzymatic digestion in the RPE, leading to an accumulation of lipofuscin A2E, RPE cell loss, PR degeneration, and vision loss . The dysfunction of growth factor secretion is involved in choroidal neovascularization in proliferative diseases like neovascular (wet) AMD . Macular edema in diabetic retinopathy is, in part, a result of the disruption of the normal transport of water and glucose across the blood–retina barrier in the RPE and CC .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
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PMC11276449_p2
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PMC11276449
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|
1. Introduction
| 4.933594 |
biomedical
|
Review
|
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Only in the last few decades has a direct visualization of the PR-RPE complex in the live human eye become possible, first with optical coherence tomography (OCT), which provides high axial resolution and cross-sectional views amenable to retinal layer discrimination , and then with adaptive optics (AO)-enabled methodology, which corrects ocular aberrations for increased lateral resolution necessary to achieve cellular-level views. As the neurons where phototransduction starts, photoreceptors were the first cellular target for high-resolution in vivo human AO retinal imaging techniques and continue to be studied extensively . Only recently has the RPE mosaic been resolved in humans , a long-standing imaging challenge, owing primarily to the axial location of the RPE cell layer below the waveguiding and highly reflective photoreceptors (and incidentally, less from the size of the cells, which, at ~10–15 µm in diameter, are on scales accessible by non-AO methods). Various techniques have been introduced and demonstrated to increase the contrast of the RPE cell layer , usually in AO-enabled devices and with extensive image averaging. Visible (i.e., short wavelength autofluorescence, SWAF) and near-infrared autofluorescence (IRAF) adaptive optics–scanning laser ophthalmoscopy (AO-SLO) has been used to target endogenous melanin and lipofuscin localized only in RPE cells . While melanin content is high in RPE cells, it also exists in the choroid, which can confound the RPE signal. Exogenous fluorophores like indocyanine green (ICG), long used for choroidal vascular visualization, have also been used to image RPE cells with AO (AO-ICG) when sufficient time has been allowed for the dye to be taken up by the cells . ICG cellular uptake is variable and so AO-ICG images have a heterogeneous appearance that is localized to the RPE layer, providing cellular visualization. For reasons that are unclear, ICG dye appears hyper- or hypo-reflective in multiple adjacent cells, which makes the quantitation of individual cellular metrics somewhat difficult with AO-ICG. Non-confocal dark field AO-SLO methodology, which detects multi-scattered back-reflected light while suppressing single-backscattered ballistic photons, has also been demonstrated to resolve the RPE mosaic . Dark-field AO-SLO offers no specific localized signal sensitivity with respect to RPE cells and typically provides the best contrast in the fovea and increasingly poorer images with increasing eccentricity, owing to scattering noise from other targets, particularly rod photoreceptors. Transscleral (vs. transpupillary) optical illumination combined with AO (AO-TIO) has shown excellent ability to rapidly resolve the RPE mosaic using high oblique angle illumination to back-light RPE cells for improved contrast. AO-TIO is non-confocal and requires some high-pass filtering to remove out-of-focus light scattered from the choroid. AO-OCT takes advantage of the exceptional micron-scale depth sectioning capabilities of OCT to localize the signal to the RPE layer . Because the contrast mechanism for AO-OCT RPE imaging is organelle motility, Liu et al. found optimum cellular contrast is achieved if volumes are acquired with a time interval close to the average decorrelation time of RPE organelles .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999995 |
PMC11276449_p3
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PMC11276449
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sec[0]/p[3]
|
1. Introduction
| 4.058594 |
biomedical
|
Study
|
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While PR density variation across the human macula is well documented and AO measurements have matched canonical histological studies , less has been reported on RPE morphological topography. Recent studies have begun to shed light on RPE topographical variations across the macula , including new models on how the PR-RPE complex relates to other structural characteristics like foveal shape and the role it plays in diseases like AMD . Despite this progress, in vivo human cellular-level retinal imaging is in a nascent stage and there are still significant discrepancies in structural parameter measurements (RPE density, PR/RPE ratio, and OSL) depending on the AO imaging methodology.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
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PMC11276449_p4
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PMC11276449
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sec[0]/p[4]
|
1. Introduction
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biomedical
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Study
|
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The aim of this study was to measure several key cellular topographical parameters across the macula from the PR-RPE complex using AO-OCT, which simultaneously produces high-contrast images of the PR and RPE layers extracted from high axial resolution volumes. The reproducibility of these AO-OCT measures was also assessed in a subset of the cohort. AO-OCT PR-RPE topographical measures may prove to be reliable biomarkers for use in treating retinal disease.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
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PMC11276449_p5
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PMC11276449
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|
2.1. Approvals, Participants, and Eye Exam
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Study
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Eleven participants, ranging in age from 27.7 to 42.9 years and free of ocular disease, were recruited for the study. Additional details about these participants are provided in Table 1 . The study protocol was approved by the Institutional Review Board of the U.S. Food and Drug Administration (FDA). Written informed consent was obtained after the study procedures and potential risks were explained to each participant. Prior to the FDA AO imaging session, all participants underwent a comprehensive eye exam by the study ophthalmologists (OS and CC), including screening for fixational ability, ocular pathology, or contraindication to pupil dilation. For all participants who passed screening, the eye examination included the documentation of visual acuity (VA), fundus photography, biometry (IOLMaster 700; Carl Zeiss Meditec Inc., Dublin CA, USA), and OCT imaging (Spectralis, Heidelberg Engineering GmbH, Heidelberg, Germany).
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
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PMC11276449
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|
2.1. Approvals, Participants, and Eye Exam
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Study
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Inclusion criteria were adult participants (>21 years old) who were able to understand and sign an informed consent and follow instructions during imaging. Exclusion criteria were participants who had any condition that prevented adequate quality images from being obtained (e.g., unstable fixation or media opacity), who had visual correction outside the range of +4 diopters to −8 diopters, who had a history of adverse reaction to mydriatic drops, who had a predisposition to (e.g., narrow iridocorneal angle) or history of acute angle closure glaucoma, or who worked under the direct supervision of the investigators.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276449_p7
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PMC11276449
|
sec[1]/sec[1]/p[0]
|
2.2. AO-OCT Imaging
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Study
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The custom-built FDA Fourier domain mode-locked (FDML)-based AO imaging system used in the study was previously described . For this study, only data from the AO-OCT channel, which collects volumes at 13.0 Hz using the 3.4 MHz FDML swept source laser , were analyzed. The lateral and axial resolution of the system are estimated to be 2.9 µm and 8.4 µm, respectively.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
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PMC11276449_p8
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PMC11276449
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sec[1]/sec[1]/p[1]
|
2.2. AO-OCT Imaging
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One eye of each participant was imaged, and that eye was dilated and cycloplegia induced with Tropicamide 1%. After alignment in the system, the fixation target was set to direct the gaze of the participant to nine regions of interest (ROIs) from the fovea to 12° temporal (12T), where each imaging location was separated by 1.5° . At each location, three AO-OCT videos were collected with the field of view (FOV) set to 2° × 2° (a nominal overlap of 0.5° or 25%). Each video had 10 AO-OCT volumes separated by 6 s to allow for optimal contrast enhancement from RPE organelle speckle decorrelation . The participants were instructed to blink naturally during the 60 s video duration.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p9
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PMC11276449
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sec[1]/sec[1]/p[2]
|
2.2. AO-OCT Imaging
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Study
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Seven participants were re-imaged on two additional days for reproducibility assessment. Three videos (10 volumes each for 30 total volumes) were collected from two temporal locations (at the fovea and 7.5T) and averaged. These two locations were specifically chosen for quantification because RPE is known to have different melanin and lipofuscin concentrations that could affect RPE contrast at the locations sampled . AO-OCT measurement reproducibility was assessed at these two locations over the three AO-imaging sessions.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p10
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PMC11276449
|
sec[1]/sec[2]/p[0]
|
2.3. Image Processing and Analysis
| 4.097656 |
biomedical
|
Study
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The 30 AO-OCT volumes collected at each ROI were processed, dewarped to correct for sinusoidal scanner motion, registered to correct for eye and head motion , averaged, and flattened to the PR/RPE complex. AO-OCT volumes collected during blinks or excessive eye motion were excluded. Post-processing was performed on the FDA High-Performance Computing (HPC) cluster which is a multi-user Linux-based computing environment comprising over 500 compute nodes, with 8–96 threads/node and 24 GB-2 TB of RAM/node. The RPE and PR layers were segmented separately (manually and semi-automatically, respectively) for further processing.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p11
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PMC11276449
|
sec[1]/sec[2]/p[1]
|
2.3. Image Processing and Analysis
| 4.101563 |
biomedical
|
Study
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Outer retinal morphology was quantified at 13 selected ROIs from the fovea to 12T, with ~1° separation between adjacent selected regions . Cells from the segmented RPE layer (average of 2–3 axial pixels) were counted manually by two expert graders using custom software (Matlab, Mathworks, Natick, MA, USA). Cell markings were then processed using Voronoi analysis to derive RPE density and other metrics (cell-to-cell spacing, cell area). The values for the RPE metrics reported herein are mean values from the two graders. RPE cells were analyzed at all locations.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p12
|
PMC11276449
|
sec[1]/sec[2]/p[2]
|
2.3. Image Processing and Analysis
| 4.195313 |
biomedical
|
Study
|
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Cone PRs were counted from the AO-OCT volume using a previously reported automated machine learning (ML) algorithm . After automated analysis, a single expert grader revised the counts with any necessary manual corrections to add cells missed and remove cells erroneously counted by the algorithm. The lateral locations for the corrected cells were then input back to the same ML software, which automatically measured the outer segment length (OSL) for each PR by identifying the cell reflections (peak signal) at the cone inner segment/outer segment junction (IS/OS) and cone outer segment tip (COST). The expert grader inspected the automatically segmented OSL results and if necessary, revised the identified reflections. Using the segmented COST layer, only cone PRs were counted in this study—no attempt was made to quantify rod PRs, which can be discriminated (both in the automated algorithm and the manual human correction) from the cone PRs, owing to the deeper rod outer segment tip (ROST) layer . Final PR metrics extracted include PR density, PR OSL, and PR cell-to-cell spacing. PR-RPE ratios at each ROI are also reported. PR cone cells were analyzed at all locations except the fovea, where individual cells were not resolved with our AO-OCT system.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p13
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PMC11276449
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sec[1]/sec[2]/p[3]
|
2.3. Image Processing and Analysis
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biomedical
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Study
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Both the RPE and PR density values excluded regions with vessel shadows, and both were scaled for each participant to correct for magnification differences due to the axial length using the Bennett eye model .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p14
|
PMC11276449
|
sec[1]/sec[2]/p[4]
|
2.3. Image Processing and Analysis
| 4.074219 |
biomedical
|
Study
|
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For the reproducibility measurements, the regions for analysis were selected and graded independently, where, due to subject fixational imprecision, no attempt was made to track or map individual PRs or RPE cells over the three AO-OCT imaging sessions for the seven volunteers examined. RPE counts were obtained as described above but from only one expert grader at the two locations examined (fovea and 7.5T). Measures of PR counts and OSL were obtained at the 7.5T location for the three AO-OCT imaging sessions using the ML algorithm, with manual correction by an expert human grader as described above.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p15
|
PMC11276449
|
sec[1]/sec[3]/p[0]
|
2.4. Statistical Analysis
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All statistical analysis was performed in Microsoft Excel with the Real Statistics Resource Pack and Analysis ToolPak add-ins, which include data analysis tools for statistical and engineering analysis. General statistical analyses included the calculation of the mean, standard deviation, and standard error. Paired t -tests and ANOVA (two-factor without replication) were used to analyze some measures. Regression analysis with Pearson (R p ) or Spearman (R s ) correlation was used to assess the relationship between eccentricity and PR density, RPE density, OSL, and PR/RPE using power, linear, and polynomial functions. Intraclass correlation coefficients (ICCs) were used to characterize the precision of measured inter-session parameters. ICCs were calculated using a two-way mixed effects model and a mean rating (k = 3) with 95% confidence intervals on absolute agreement. Measured ICC > 0.9 indicates excellent reliability, ICC = 0.75–0.9 indicates good reliability, ICC = 0.5–0.75 indicates moderate reliability, and ICC < 0.5 indicates poor reliability . Lin’s concordance coefficient (LCC) was used to assess inter-rater variability between the graders for RPE counts . The threshold p -value for statistical significance was set to 0.05.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p16
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PMC11276449
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sec[2]/sec[0]/p[0]
|
3.1. Primary PR-RPE Complex Metrics
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Study
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The morphological variation in the PR-RPE complex as a function of retinal eccentricity in the temporal retina for all study volunteers (gray symbols) and the overall cohort mean value (black symbols) is shown in Figure 3 . Similar to other studies , the cone density followed a power function with eccentricity . The RPE density data were more variable, but a reasonable correlation was found using a linear relationship with eccentricity, where a negative slope of −123 cells/mm 2 per degree from a peak at the fovea of 6913 cells/mm 2 was observed . The slope of RPE density as a function of eccentricity was negative for all 11 healthy volunteers, with the slope ranging from −55 to −220 cells/mm 2 per degree ( R s 2 ranging from 0.16 to 0.77 for the individual slope fits).
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276449_p17
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PMC11276449
|
sec[2]/sec[0]/p[1]
|
3.1. Primary PR-RPE Complex Metrics
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The relationship between OSL and eccentricity was best fit with a polynomial relationship . It should be noted that the OSL values reported herein are extracted from individually segmented cells and not merely from averaged retinal layer bands. As expected from the PR and RPE data, the PR/RPE ratio also followed a power law relationship with eccentricity .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p18
|
PMC11276449
|
sec[2]/sec[1]/p[0]
|
3.2. Other PR-RPE Complex Measures
| 4.140625 |
biomedical
|
Study
|
[
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[
0.99951171875,
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0.00005745887756347656
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Power spectrum analysis has been used previously to rapidly assess the density of PR and RPE cells . We compared Voronoi and power spectrum analyses and found a reasonably good correlation between the measures ( R p 2 = 0.79 ). The slope of the fit was <1, indicating an underestimation of the power spectrum, as was previously observed , and could be attributed to an image windowing effect that causes the peak detection to skew toward lower frequencies (larger objects) and therefore lower densities. Secondary metrics including PR cell-to-cell spacing, RPE area, and RPE cell-to-cell spacing were also quantified . The RPE area and spacing were observed to increase gradually from the fovea to 6° and then plateau at high eccentricities to 12°.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p19
|
PMC11276449
|
sec[2]/sec[1]/p[1]
|
3.2. Other PR-RPE Complex Measures
| 4.117188 |
biomedical
|
Study
|
[
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[
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There was very good agreement between the two graders for the RPE counts, with an LCC of 0.89 (95% confidence interval 0.85–0.92) for RPE density, 0.88 (95% CI: 0.83–0.91) for the RPE area, and 0.87 (95% CI: 0.82–0.90) for RPE spacing .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p20
|
PMC11276449
|
sec[2]/sec[2]/p[0]
|
3.3. Reproducibility of PR-RPE Complex Measurements
| 4.140625 |
biomedical
|
Study
|
[
0.99951171875,
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[
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The mean separation between AO-imaging visits for the reproducibility cohort was 25 days (SD: 30, MIN: 2, MAX: 112). All measures showed low variance in repeat measurements, as illustrated in the individual participant measurements , as well as the values normalized to the mean . Excellent reproducibility was obtained for the two PR measures (PR density and OSL), with ICCs of 0.942 and 0.952, respectively. Owing to lower cell contrast, the ICC values for RPE density reproducibility were lower at 0.706 and 0.508 for the fovea and 7.5° regions, respectively. The overall standard deviation normalized to the mean was 1.6% for PR density, 2.0% for OSL, and 2.3% for RPE density (both locations).
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p21
|
PMC11276449
|
sec[3]/p[0]
|
4. Discussion
| 4.125 |
biomedical
|
Study
|
[
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[
0.99951171875,
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This study reports key PR-RPE complex measurements in the temporal macula of a healthy volunteer cohort using an AO-OCT imaging modality. Our observations represent the largest number of high-resolution, high-contrast AO-OCT images collected for this purpose, both in terms of sampled locations across the macula and also cohort size. We observed a tight grouping of cone PR density measurements following a power function with eccentricity, a more variable and linearly decreasing RPE density with eccentricity, a monotonically decreasing OSL with eccentricity, and a PR/RPE ratio following a power function with eccentricity.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p22
|
PMC11276449
|
sec[3]/p[1]
|
4. Discussion
| 4.15625 |
biomedical
|
Study
|
[
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[
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Our RPE density results are compared with other human in vivo and ex vivo reports from the literature in Figure 5 . In general, our data match previous AO-OCT single eccentricity values and compare favorably with SWAF, IRAF, and dark-field AO-SLO and AO-ICG results , albeit on the high side . In particular, Granger et al. and Baraas et al. found the RPE density at the fovea to be 6008 and 7926 cells/mm 2 , respectively, matching reasonably closely to the range of the current study: 7335 (±681) cells/mm 2 . Granger et al. found a density of 4489 cells/mm 2 at 12.5°, which was slightly lower than the 5755 (±852) cells/mm 2 at 12° found in the current study. Kowalczuk et al. reported much lower values and their slope with eccentricity was significantly shallower than our observations. This discrepancy is potentially because a low-pass filter was used by Kowalczuk et al. to remove regions of smaller cells from their overall counts, which could have led to an underestimation of density, particularly at the fovea (lowering the slope).
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276449_p23
|
PMC11276449
|
sec[3]/p[2]
|
4. Discussion
| 4.070313 |
biomedical
|
Study
|
[
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] |
[
0.99951171875,
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0.00005334615707397461
] |
Factors that may contribute to our slightly higher values than previous in vivo measurements include subject variability, age, and image modality. While subject variability is captured in our standard deviation range, which overlaps with most of the previously reported results (for variability ranges that were provided in previous reports), our cohort tended to be relatively young, which could have contributed to differences. Moreover, image modality differences, arising from different targeted sources of RPE cell contrast, could also contribute to different RPE density measurements. This methodology factor was recently explored by Bower et al. in a study imaging the same eyes with a multimodal adaptive optics imager .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p24
|
PMC11276449
|
sec[3]/p[3]
|
4. Discussion
| 4.105469 |
biomedical
|
Study
|
[
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[
0.9990234375,
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In comparison to ex vivo values , our in vivo results match reasonably well for eccentricities <5°, except at the fovea, which has a wide range of reported values from ~4000–8000 cell/mm 2 . We report slightly higher RPE density values at eccentricities >5°, which may be attributed to age-related changes, spatial differences, or subject variability. Most previous ex vivo studies included an age range higher than ours and also measured lower RPE cell density for older eyes.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999999 |
PMC11276449_p25
|
PMC11276449
|
sec[3]/p[4]
|
4. Discussion
| 3.816406 |
biomedical
|
Study
|
[
0.9990234375,
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[
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The cone PR density, OSL, and PR/RPE density are compared with other human studies in Figure 6 . The cone PR density compares favorably with the canonical results from Curcio et al. . Owing to our generally higher RPE densities, we report PR/RPE ratios that are generally lower than previously reported .
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276449_p26
|
PMC11276449
|
sec[3]/p[5]
|
4. Discussion
| 4.1875 |
biomedical
|
Study
|
[
0.99951171875,
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[
0.99951171875,
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0.00006103515625
] |
PR OSL values as a function of eccentricity match previous AO-OCT studies , as well as clinical OCT data . Our OSL values are measured from averaged volumes on a cone-to-cone basis using a previously published deep learning approach with manual correction . For our data and those studies with similar results, we defined OSL as the distance between the peak intensity of the signal from the IS/OS and COST, which for AO-OCT images are paired beaded reflectance signals and for clinical OCT, owing to lower lateral resolution and averaging, are the second and third bands in the outer retina. Our results generally also compare well with histology, which found the OSL to be 35 µm in the central fovea (foveola), 28 µm in the parafovea (1–1.5 mm or ~5° eccentricity), and 20–23 µm in the mid-periphery (4 mm or 13.7° eccentricity) . The distribution of PR OSL values for our cohort is shown for all locations in Figure S4 , where most participants showed a consistent unimodal distribution at all locations, while a few exhibited a bimodal distribution at some locations.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p27
|
PMC11276449
|
sec[3]/p[6]
|
4. Discussion
| 4.230469 |
biomedical
|
Study
|
[
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] |
[
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0.00009512901306152344
] |
Our definition of the boundaries of the outer segments may not be consistent with some previous published studies, however, and controversy over the origin of the OCT signals in the outer retina remains . Evidence to date, including animal studies, support the idea that the second and third bands in clinical OCT arise from the mitochondria in the ellipsoid region of the inner segments (ISe) and the interdigitation zone (IZ) between the photoreceptor outer segments and RPE . However, the PR signals in AO-OCT are thinner and beaded, and the second signal appears closer to the third PR-RPE complex signal, indicating it may arise from a slightly different anatomical structure and axial location . Other high-resolution OCT studies have used signal edges (the offset edge of the ellipsoid zone and onset edge of the phagosome zone) rather than peaks and reported lower values for the OSL . Other ultrahigh-resolution OCT studies have reported higher values for the OSL . If full consensus is achieved for the anatomical origins of OCT signals and the discrepancies between clinical OCT and AO-OCT are resolved, our OSL results can be updated using more precise axial locations from the averaged volumes.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276449_p28
|
PMC11276449
|
sec[3]/p[7]
|
4. Discussion
| 4.113281 |
biomedical
|
Study
|
[
0.99951171875,
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] |
[
0.9990234375,
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AO-OCT achieves very good reproducibility for PR-RPE measurements. As expected from the relative cellular contrast, the PR measures had excellent reliability, while the RPE density reliability was lower, achieving moderate reliability at the fovea and 7.5°. The lower reliability for RPE reproducibility, particularly at 7.5°, could be attributed to lower image contrast from intrasession eye rotation, the effect of the molecular origin of the RPE signal (melanin vs. lipofuscin) at each location, as well as actual density variations across the macula for participants, since the regions were not registered across visits. Nevertheless, our results demonstrate that AO-OCT-based cellular metrics are excellent candidates for further development as retinal disease biomarkers.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p29
|
PMC11276449
|
sec[3]/p[8]
|
4. Discussion
| 4.292969 |
biomedical
|
Study
|
[
0.9990234375,
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[
0.73583984375,
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Comparing imaging methodology for PR-RPE complex topographical quantitation, AO-OCT shares advantages with other multimodal approaches in its ability to simultaneously image both the PR and RPE layers, but for AO-OCT this is accomplished by its extraction of layers and quantitative metrics from a single (averaged) volume. AO-OCT has significant advantages over other techniques for PR-RPE complex topographical quantification. Because of the micron-scale depth resolution afforded by the low coherence interferometry approach, AO-OCT volumes can be precisely segmented to visualize retinal layers and sub-layers, making AO-OCT more immune to crosstalk and interference from other structures of interest (e.g., PR signal imprinted on RPE images in dark-field AO-SLO). This also allows the simultaneous extraction of PR metrics like OSL, which is currently not possible without the µm scale depth sectioning capabilities of OCT. AO-OCT uses intrinsic organelle motility as a contrast mechanism, which compares favorably against techniques that require extrinsic dyes. Furthermore, AO-OCT RPE images are generated with significantly less averaging using organelle motion contrast than those generated with the relatively weak SWAF or IRAF fluorescence signals.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p30
|
PMC11276449
|
sec[3]/p[9]
|
4. Discussion
| 4.117188 |
biomedical
|
Study
|
[
0.99951171875,
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[
0.99951171875,
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This study implemented several essential technical advances to allow the mapping of PR-RPE topography over the temporal macula for a relatively large cohort in contrast to the more moderate amount of data collected in previous AO-OCT RPE imaging studies . The 3.4 MHz OCT acquisition speed provides high volume rates to significantly mitigate eye motion artifact and enables a 2° imaging FOV with sufficient lateral pixel density for cellular resolution. Our novel programmed saving scheme with variable volume time separation (6 s in the current study) improves the imaging efficiency by reducing the number of AO-OCT videos acquired from a few dozen to only three. Overall, we produced a total of 125 averaged AO-OCT volumes and quantified PR-PRE topography at 178 ROIs. This represents three times more information than that collected from all previous AO-OCT RPE studies, adding significant new, more comprehensive knowledge on PR-RPE cellular structure.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276449_p31
|
PMC11276449
|
sec[3]/p[10]
|
4. Discussion
| 4.078125 |
biomedical
|
Study
|
[
0.99951171875,
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[
0.99853515625,
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There are a few limitations to using AO-OCT for mapping PR-RPE topography. The use of organelle motility places a temporal (decorrelation) constraint on the acquisition time, particularly when significant averaging is required. A recent demonstration of AI to obviate the collection of multiple AO-OCT volumes for RPE imaging may lessen the impact of this disadvantage. Also, as seen in our data, speckle noise and longer imaging wavelengths make the resolution of PRs in the foveola (central 0.25°) extremely difficult, and this is a task better suited for AO-SLO. Super-resolution techniques may eventually prove to be effective at overcoming this limitation . While our device includes AO-OCT and AO-SLO channels , we did not collect small field videos from the foveola with AO-SLO to extract PR density values, and this is a limitation in our dataset.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276449_p32
|
PMC11276449
|
sec[4]/p[0]
|
5. Conclusions
| 3.914063 |
biomedical
|
Study
|
[
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[
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The quantification of the topographical morphology of the PR-RPE complex in live human volunteers is a feat made possible only in the last few years with the help of AO methodology. The characterization of this important structure is important to better understand the anatomy of the normal retina, its variability across the population, for the construction of models of vision and visual pathways, as normative measures in comparison to eyes with retinal disease, in biomarker development, for other diagnostic purposes, and in the development of new therapies.
|
[
"Zhuolin Liu",
"Samira Aghayee",
"Somayyeh Soltanian-Zadeh",
"Katherine Kovalick",
"Anant Agrawal",
"Osamah Saeedi",
"Catherine Cukras",
"Emily Y. Chew",
"Sina Farsiu",
"Daniel X. Hammer"
] |
https://doi.org/10.3390/diagnostics14141518
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276461_p0
|
PMC11276461
|
sec[0]/p[0]
|
1. Introduction
| 3.65625 |
biomedical
|
Study
|
[
0.998046875,
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] |
[
0.6865234375,
0.140625,
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0.0008406639099121094
] |
The prolonged duration of the Coronavirus Disease 2019 (COVID-19) pandemic, coupled with the associated stressors, disruptions to daily life, and limited access to healthcare, exacerbated adverse mental health conditions . According to the Centers for Disease Control and Prevention (CDC), a considerable number of adults reported symptoms of anxiety or depression, increased substance use, and serious thoughts of suicide during the COVID-19 outbreak . Vulnerable populations, including those facing socioeconomic disparities and residing in rural areas, were particularly challenged by this situation .
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999994 |
PMC11276461_p1
|
PMC11276461
|
sec[0]/p[1]
|
1. Introduction
| 3.742188 |
biomedical
|
Review
|
[
0.78515625,
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[
0.010223388671875,
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] |
Tele-mental health (TMH) services emerged as a viable solution. TMH leverages telecommunication and videoconferencing technologies to facilitate decentralized mental and behavioral healthcare services, allowing patients in remote locations to overcome the lack of access to healthcare imposed by physical distance. A systematic review examining the role of TMH services, which includes studies from multiple countries such as Austria, Australia, China, the Dominican Republic, Spain, and the United States (U.S), demonstrates that TMH helped reduce the burden of mental health diseases and promoted individual wellbeing during the COVID-19 pandemic . Initially, the Centers for Medicare & Medicaid Services (CMS) telehealth reimbursement policy focused on rural residents, requiring encounters to take place at a clinic or facility in a rural area . In response to the COVID-19 Public Health Emergency (PHE), CMS expanded its telehealth reimbursement policy to cover a broader range of TMH services, enabling beneficiaries from diverse geographic areas and locations, including their homes, to access TMH services. Other payers, such as United Healthcare and Cigna, also updated their reimbursement policies, including the elimination of cost-sharing for telehealth services .
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p2
|
PMC11276461
|
sec[0]/p[2]
|
1. Introduction
| 4.015625 |
biomedical
|
Study
|
[
0.96484375,
0.00258636474609375,
0.032684326171875
] |
[
0.444580078125,
0.36376953125,
0.19091796875,
0.0007643699645996094
] |
Sociodemographic disparities, characterized by factors such as age, race, and socioeconomic status, severely challenge the provision of health equity in mental health care, particularly in underserved populations and rural areas . Mississippi, a predominantly rural and economically disadvantaged state, faces grave disparities and a shortage of mental health services . With the fourth highest income inequality in the nation, the top 20% of households in Mississippi accounted for 52% of all statewide earnings, while the bottom 20% of households only accounted for 3% of earnings . Moreover, Mississippi has the fourth highest rate of uninsured adults with mental illness (18.2%) and a low number of mental health treatment centers (36.33 per 10,000 businesses) . The COVID-19 pandemic and associated lockdown measures further exacerbated mental health conditions in Mississippi, with 44.3% of adults exhibiting symptoms of anxiety or depressive disorder, the highest rate in the nation . Addressing disparities and promoting health equity is crucial in ensuring that all individuals, regardless of sociodemographic characteristics or geographic locations, have access to quality mental health services.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p3
|
PMC11276461
|
sec[0]/p[3]
|
1. Introduction
| 4.125 |
biomedical
|
Study
|
[
0.99853515625,
0.0010194778442382812,
0.0004410743713378906
] |
[
0.99609375,
0.00035309791564941406,
0.0032482147216796875,
0.00012934207916259766
] |
A body of literature has reported the feasibility and efficacy of TMH in diagnosing and managing mental illness conditions . A systematic review further highlighted its wide variety of innovative and inexpensive choices for providers, as well as its value in augmenting primary care and emergency consultations . However, a recent scoping review points to a gap in research concerning disparities in digital equity and the associated healthcare resource utilization (HCRU) and costs . Previous studies among Mississippi Medicare and Medicaid beneficiaries and the general American population have shown the value of TMH in reducing all-cause HCRU and expenditures . A difference-in-difference study of commercially insured American patients further indicates the causal impact of TMH on increasing mental health-related costs without significantly affecting total healthcare costs . However, studies specifically focusing on patients facing sociodemographic disparities and residing in rural areas are still lacking. The objective of this study is to evaluate the usage of TMH services in a rural patient population facing sociodemographic disparities. We aimed to examine the associations between TMH usage and sociodemographic factors, as well as the impact of TMH on all-cause and mental and behavioral health-related HCRU and medical expenditures during the COVID-19 pandemic. By focusing on a specific population within Mississippi, this study provides insights into the potential benefits of TMH services in addressing mental health needs in an underserved, resource-limited setting.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276461_p4
|
PMC11276461
|
sec[1]/sec[0]/p[0]
|
2.1. Ethical Considerations
| 1.769531 |
biomedical
|
Study
|
[
0.9921875,
0.00220489501953125,
0.005756378173828125
] |
[
0.8603515625,
0.136474609375,
0.002010345458984375,
0.00121307373046875
] |
This study was approved by the University of Mississippi Medical Center (UMMC) institutional review board with a waiver of informed consent. We report this study following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline .
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276461_p5
|
PMC11276461
|
sec[1]/sec[1]/p[0]
|
2.2. Study Design, Setting, and Participants
| 3.470703 |
biomedical
|
Study
|
[
0.994140625,
0.004459381103515625,
0.0016193389892578125
] |
[
0.99853515625,
0.0007281303405761719,
0.0002598762512207031,
0.0002474784851074219
] |
We conducted a retrospective cohort study to compare sociodemographic characteristics, HCRU, and medical expenditures among patients who used TMH services and those who did not at the UMMC between 1 January 2020 and 30 June 2023.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p6
|
PMC11276461
|
sec[1]/sec[1]/p[1]
|
2.2. Study Design, Setting, and Participants
| 1.398438 |
other
|
Other
|
[
0.26318359375,
0.09356689453125,
0.6435546875
] |
[
0.0018014907836914062,
0.9970703125,
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0.0008716583251953125
] |
UMMC, Mississippi’s only academic medical center, provides patient-centered treatment, clinical excellence, and an advanced level of care unavailable anywhere else in the state . It has been at the forefront of mental health care. With the declaration of the COVID-19 PHE, UMMC, including its affiliated sites, transitioned most mental health services to TMH within a week, demonstrating its commitment to maintaining healthcare access during the pandemic. Located in the Jackson metropolitan area, UMMC serves a patient population with various sociodemographic backgrounds, including economically disadvantaged and underserved populations from rural areas.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p7
|
PMC11276461
|
sec[1]/sec[1]/p[2]
|
2.2. Study Design, Setting, and Participants
| 4.058594 |
biomedical
|
Study
|
[
0.9970703125,
0.0021762847900390625,
0.0008134841918945312
] |
[
0.99951171875,
0.0004143714904785156,
0.0001722574234008789,
0.00009149312973022461
] |
The study cohort consisted of insured adult patients who regularly sought healthcare from UMMC. This was conducted to minimize potential bias, as patients may seek healthcare services from multiple institutions . Specifically, patients who met the following criteria were included in this study: (1) aged 18 years or older, (2) had at least one mental and behavioral health service primarily paid by insurance, (3) had at least three scheduled visits per year for two years during the study period, and (4) completed at least two visits, either TMH or in-person outpatient, with a gap of at least 3 months between these two visits. Mental and behavioral health-associated encounters were identified through the provider’s academic department, the Department of Psychiatry and Human Behavior at UMMC, along with at least one of the first two diagnosis codes of a visit falling in the F01 to F99 range of the International Classification of Diseases, Tenth Revision (ICD-10).
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276461_p8
|
PMC11276461
|
sec[1]/sec[1]/p[3]
|
2.2. Study Design, Setting, and Participants
| 2.488281 |
biomedical
|
Study
|
[
0.99169921875,
0.004085540771484375,
0.0042724609375
] |
[
0.99755859375,
0.0017881393432617188,
0.00021946430206298828,
0.0002033710479736328
] |
Furthermore, the study subjects were categorized into two cohorts based on their utilization of TMH services throughout the study period. Subjects who had completed at least one TMH service were assigned to the TMH cohort, whereas all others were assigned to the non-TMH cohort. We identified TMH services based on the visit type documented for each encounter. Subgroup analysis was conducted to evaluate subjects from rural areas in further detail.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276461_p9
|
PMC11276461
|
sec[1]/sec[2]/p[0]
|
2.3. Variables and Data Sources
| 4.007813 |
biomedical
|
Study
|
[
0.99755859375,
0.001277923583984375,
0.0014057159423828125
] |
[
0.99951171875,
0.0002434253692626953,
0.00018155574798583984,
0.00006514787673950195
] |
Medical records were extracted from the UMMC enterprise data warehouse to examine sociodemographic characteristics, HCRU, and medical expenditures between TMH and non-TMH cohorts. Sociodemographic characteristics considered in this study include age, sex, race, primary insurance, rurality, and household income. Age was categorized into four groups: 18 to 34 years, 35 to 49 years, 50 to 64 years, and 65 years or older. Race was categorized into three groups: White/Caucasian, Black/African American, and other. The other race group included subjects identifying as American Indian, Alaska Native, Native Hawaiian, other Pacific Islander, Mississippi Band Choctaw Indian, Asian, Hispanic, Multiracial, and others. Subjects of unknown race or those who refused to provide this information were considered missing. Primary insurance was defined as the insurance most frequently used for mental and behavioral health visits during the study period and was categorized into four groups: commercial insurance, Medicare, Medicaid, and others, including workers’ compensation insurance, managed care, and contractual agreement coverage. Rurality was defined using the Rural–Urban Commuting Area (RUCA) Codes, with codes greater than 3 indicating rural areas. Household income was estimated through the median household income data from the U.S. Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) program .
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p10
|
PMC11276461
|
sec[1]/sec[2]/p[1]
|
2.3. Variables and Data Sources
| 3.679688 |
biomedical
|
Study
|
[
0.9833984375,
0.00783538818359375,
0.0086212158203125
] |
[
0.99462890625,
0.004764556884765625,
0.0003104209899902344,
0.00023114681243896484
] |
HCRU was assessed using mental and behavioral health-related and all-cause outpatient visits, inpatient admissions, and emergency department (ED) visits. Given the variability in payment by insurance and self-pay, the Medicare Physician Fee Schedule (MPFS) was used to estimate the standardized pricing for medical expenditures in Mississippi. Specifically, the facility fee schedule amount for 2023 was applied through Current Procedural Terminology (CPT) and Level II Healthcare Common Procedure Coding System (HCPCS) codes, with locality 00 and carrier 0730200 for Mississippi. Due to the variation in the length of follow-up, HCRU and medical expenditures were reported as per-patient-per-month (PPPM).
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276461_p11
|
PMC11276461
|
sec[1]/sec[3]/p[0]
|
2.4. Statistical Analysis
| 3.988281 |
biomedical
|
Study
|
[
0.99951171875,
0.00041484832763671875,
0.0003161430358886719
] |
[
0.99951171875,
0.0003554821014404297,
0.00029587745666503906,
0.000059664249420166016
] |
Descriptive statistics, including mean with standard deviation (SD) and frequency with percentage (%), were used to summarize continuous and categorical variables. The Shapiro–Wilk test was used to examine the normality of continuous variables for HCRU and medical expenditures. We examined the association between sociodemographic factors and the utilization of TMH services using Pearson’s χ 2 test. The odds ratio (OR) with its 95% confidence interval (CI) was also reported to present the strength of the association.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276461_p12
|
PMC11276461
|
sec[1]/sec[3]/p[1]
|
2.4. Statistical Analysis
| 4.078125 |
biomedical
|
Study
|
[
0.99951171875,
0.00034999847412109375,
0.0003070831298828125
] |
[
0.9990234375,
0.00043201446533203125,
0.0002779960632324219,
0.000055909156799316406
] |
The Wilcoxon rank sum test was employed to compare the non-normally distributed variables of HCRU and medical expenditures. To adjust for the sociodemographic factors, generalized linear regression models (GLMs) with log links were constructed to assess the impact of TMH usage on HCRU and medical expenditures. Specifically, we fitted Poisson regression models, negative binomial regression models, or zero-inflated Poisson regression models for HCRU outcomes, depending on their distributions, and Gamma regression models for medical expenditures.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p13
|
PMC11276461
|
sec[1]/sec[3]/p[2]
|
2.4. Statistical Analysis
| 2.697266 |
biomedical
|
Study
|
[
0.99609375,
0.0010156631469726562,
0.0029659271240234375
] |
[
0.99853515625,
0.00122833251953125,
0.00019693374633789062,
0.00011199712753295898
] |
In addition, a subgroup analysis was conducted for subjects residing in rural areas. Sociodemographic characteristics, HCRU, and medical expenditures between TMH and non-TMH cohorts within this subgroup were compared using the same subgroup analysis. In GLMs, we control for all sociodemographic factors except for rurality, as all subjects were from rural areas.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276461_p14
|
PMC11276461
|
sec[1]/sec[3]/p[3]
|
2.4. Statistical Analysis
| 2.089844 |
biomedical
|
Study
|
[
0.9931640625,
0.0007233619689941406,
0.00598907470703125
] |
[
0.837890625,
0.15966796875,
0.0018320083618164062,
0.0008034706115722656
] |
Statistical significance was determined using two-sided tests with an alpha level of 0.05. All statistical analyses were conducted using SAS statistical software (version 9.4, SAS Institute Inc., Cary, NC, USA).
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999998 |
PMC11276461_p15
|
PMC11276461
|
sec[2]/sec[0]/p[0]
|
3.1. Sociodemographic Characteristics
| 3.644531 |
biomedical
|
Study
|
[
0.9951171875,
0.0009093284606933594,
0.003971099853515625
] |
[
0.99951171875,
0.0002186298370361328,
0.00011163949966430664,
0.0000432133674621582
] |
A total of 6787 subjects were included in this study, with 3065 utilizing TMH services and 3722 not. Table 1 presents the sociodemographic characteristics of all subjects and by cohort. The majority of subjects were in the age group of 50 to 64 years (31.87%), female (67.91%), and identified as Black/African American (55.70%). Additionally, the majority had commercial insurance as the primary insurance (40.77%), resided in urban areas (77.97%), and had an annual household income between $42,000 and $50,000 (51.26%). All sociodemographic factors significantly varied between the TMH and non-TMH cohorts, including age, sex, race, primary insurance, rural residency, and household income (all p < 0.001).
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276461_p16
|
PMC11276461
|
sec[2]/sec[0]/p[1]
|
3.1. Sociodemographic Characteristics
| 3.976563 |
biomedical
|
Study
|
[
0.99462890625,
0.0006341934204101562,
0.0047607421875
] |
[
0.99951171875,
0.0003840923309326172,
0.0001347064971923828,
0.00003790855407714844
] |
In the TMH cohort, the largest age group was 35 to 49 years (29.82%), followed by 50 to 64 years (28.74%) and 18 to 34 years (27.86%). In contrast, the largest age group in the non-TMH cohort was 50 to 64 years (34.44%), followed by 35 to 49 years (27.22%) and 18 to 34 (18.57%). While the over-65 age group constitutes the smallest proportion in both cohorts, it was less prominent in the TMH cohort (13.57% vs. 19.77%). Compared to the non-TMH cohort, the TMH cohort had a higher proportion of females (72.76% vs. 63.92%), a higher proportion of White/Caucasian subjects (51.18% vs. 35.48%), a lower proportion of Black/African American subjects (47.17% vs. 62.69%), and a lower proportion of subjects with other races (1.65% vs. 1.84%). Furthermore, the TMH cohort had higher odds of using other insurance than Medicare with an OR of 1.93 (95% CI: 1.60–2.34) and higher odds of residing in rural areas with an OR of 1.22 (95% CI: 1.09–1.37). In terms of household income, the TMH cohort had a similar proportion of subjects with household incomes of less than $42,000 (13.12% vs. 12.60%), a greater proportion with incomes over $50,000 (38.30% vs. 33.93%), but a lower proportion with incomes in the range of $42,000 to $50,000 (48.58% vs. 53.47%), compared to the non-TMH cohort.
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
PMC11276461_p17
|
PMC11276461
|
sec[2]/sec[1]/p[0]
|
3.2. HCRU and Expenditures
| 4.105469 |
biomedical
|
Study
|
[
0.99853515625,
0.0008931159973144531,
0.0004818439483642578
] |
[
0.99951171875,
0.0002396106719970703,
0.00027298927307128906,
0.00006371736526489258
] |
Compared to the non-TMH cohort, the TMH cohort had significantly more mental and behavioral health-related outpatient visits (mean (SD): 0.43 (0.46) vs. 0.13 (0.31) PPPM), inpatient admissions (mean (SD): 0.0027 (0.02) vs. 0.0019 (0.02) PPPM), ED visits (mean (SD): 0.0028 (0.01) vs. 0.0023 (0.02) PPPM), and medical expenditures (mean (SD): $28.18 (33.26) vs. $11.89 (34.91) PPPM), all with p < 0.001. Regarding the all-cause HCRU and medical expenditures, the TMH cohort had lower medical expenditures (mean (SD): $129.16 (176.86) vs. $149.50 (230.43) PPPM; p < 0.001) .
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999997 |
PMC11276461_p18
|
PMC11276461
|
sec[2]/sec[1]/p[1]
|
3.2. HCRU and Expenditures
| 4.015625 |
biomedical
|
Study
|
[
0.9990234375,
0.0005407333374023438,
0.0006508827209472656
] |
[
0.99951171875,
0.00027680397033691406,
0.0002970695495605469,
0.00005042552947998047
] |
After adjusting for sociodemographic factors, TMH utilization was estimated to be associated with a 190% increase in mental and behavioral health-related outpatient visits, a 17% increase in mental and behavioral health-related medical expenditures, and a 12% decrease in all-cause medical expenditures (all p < 0.001) ( Table 2 ).
|
[
"Yunxi Zhang",
"Lincy S. Lal",
"Yueh-Yun Lin",
"J. Michael Swint",
"Ying Zhang",
"Richard L. Summers",
"Barbara F. Jones",
"Saurabh Chandra",
"Mark E. Ladner"
] |
https://doi.org/10.3390/ijerph21070819
|
N/A
|
https://creativecommons.org/licenses/by/4.0/
|
en
| 0.999996 |
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