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SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a highly heterogenous reproductive endocrine disorder that affects up to 15% of women and is one of the leading causes of infertility. However, its genetic etiology remains poorly understood. Additionally, PCOS patients have a greater risk of having metabolic diso...

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Autores principales: Actkins, Ky’Era, Edwards, Digna Velez, Aldrich, Melinda, Davis, Lea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7208200/
http://dx.doi.org/10.1210/jendso/bvaa046.727
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author Actkins, Ky’Era
Edwards, Digna Velez
Aldrich, Melinda
Davis, Lea
author_facet Actkins, Ky’Era
Edwards, Digna Velez
Aldrich, Melinda
Davis, Lea
author_sort Actkins, Ky’Era
collection PubMed
description Polycystic ovary syndrome (PCOS) is a highly heterogenous reproductive endocrine disorder that affects up to 15% of women and is one of the leading causes of infertility. However, its genetic etiology remains poorly understood. Additionally, PCOS patients have a greater risk of having metabolic disorders, such as insulin resistance and cardiovascular diseases, but it is estimated that up to 75% of women remain undiagnosed. Delayed treatment and care can exacerbate comorbid conditions and be detrimental to high risk populations like African American and Hispanic women. We aim to characterize genetic and environmental variables contributing to PCOS and understand its shared etiological features with metabolic disorders. To do this, we developed two algorithms to identify diverse PCOS patients using medical records. The broad algorithm used a combination of PCOS-related billing codes (Code Based) and identified a large dataset (N = 8,340) who exhibited diverse PCOS symptoms, while the strict algorithm required PCOS keywords in addition to billing codes (Regex Based). The strict algorithm identified a smaller cohort of patients (N = 4,593) who exhibited more classically diagnoseable PCOS characteristics according to Rotterdam and NIH criteria. Using both datasets, we tested PCOS case status against 1,853 phenotypes in the medical database using a logistic regression model and identified comorbidity patterns for women of European and African descent. We observed that European descent women consistently had more distinct phenotypes associated with PCOS case status than African American women. Next, we examined the interacting effects of self-reported race on PCOS case status and found four significant phenotypes (p < 6.25e-4) in our Regex Based algorithm. African American women with PCOS had greater odds of being diagnosed with “Early onset of delivery” (p = 1.3e-4, OR = 1.86), “Hereditary hemolytic anemias” (p =1.8e-4, OR = 0.65), and “Other hereditary hemolytic anemias” (p = 3.7e-04, OR = 0.90). Meanwhile, European descent women had greater odds of being diagnosed with “Hypertensive chronic kidney disease” (p = 1.7e-04, OR = 0.68). Results show that European and African American women have unique metabolic comorbidity patterns and it may also indicate that clinical PCOS diagnostic standards vary between these groups with possible disparity-causing effects.
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spelling pubmed-72082002020-05-13 SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome Actkins, Ky’Era Edwards, Digna Velez Aldrich, Melinda Davis, Lea J Endocr Soc Reproductive Endocrinology Polycystic ovary syndrome (PCOS) is a highly heterogenous reproductive endocrine disorder that affects up to 15% of women and is one of the leading causes of infertility. However, its genetic etiology remains poorly understood. Additionally, PCOS patients have a greater risk of having metabolic disorders, such as insulin resistance and cardiovascular diseases, but it is estimated that up to 75% of women remain undiagnosed. Delayed treatment and care can exacerbate comorbid conditions and be detrimental to high risk populations like African American and Hispanic women. We aim to characterize genetic and environmental variables contributing to PCOS and understand its shared etiological features with metabolic disorders. To do this, we developed two algorithms to identify diverse PCOS patients using medical records. The broad algorithm used a combination of PCOS-related billing codes (Code Based) and identified a large dataset (N = 8,340) who exhibited diverse PCOS symptoms, while the strict algorithm required PCOS keywords in addition to billing codes (Regex Based). The strict algorithm identified a smaller cohort of patients (N = 4,593) who exhibited more classically diagnoseable PCOS characteristics according to Rotterdam and NIH criteria. Using both datasets, we tested PCOS case status against 1,853 phenotypes in the medical database using a logistic regression model and identified comorbidity patterns for women of European and African descent. We observed that European descent women consistently had more distinct phenotypes associated with PCOS case status than African American women. Next, we examined the interacting effects of self-reported race on PCOS case status and found four significant phenotypes (p < 6.25e-4) in our Regex Based algorithm. African American women with PCOS had greater odds of being diagnosed with “Early onset of delivery” (p = 1.3e-4, OR = 1.86), “Hereditary hemolytic anemias” (p =1.8e-4, OR = 0.65), and “Other hereditary hemolytic anemias” (p = 3.7e-04, OR = 0.90). Meanwhile, European descent women had greater odds of being diagnosed with “Hypertensive chronic kidney disease” (p = 1.7e-04, OR = 0.68). Results show that European and African American women have unique metabolic comorbidity patterns and it may also indicate that clinical PCOS diagnostic standards vary between these groups with possible disparity-causing effects. Oxford University Press 2020-05-08 /pmc/articles/PMC7208200/ http://dx.doi.org/10.1210/jendso/bvaa046.727 Text en © Endocrine Society 2020. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Reproductive Endocrinology
Actkins, Ky’Era
Edwards, Digna Velez
Aldrich, Melinda
Davis, Lea
SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome
title SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome
title_full SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome
title_fullStr SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome
title_full_unstemmed SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome
title_short SAT-024 Investigating Racial and Ethnic Comorbidity Patterns of Polycystic Ovary Syndrome
title_sort sat-024 investigating racial and ethnic comorbidity patterns of polycystic ovary syndrome
topic Reproductive Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7208200/
http://dx.doi.org/10.1210/jendso/bvaa046.727
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