Admixture mapping of pelvic organ prolapse in African Americans from the Women's Health Initiative Hormone Therapy trial

Pelvic Floor Disorders in Black Women: Prevalence, Clinical Care, and a Strategic Agenda to Prioritize Care

Pelvic floor disorders are a group of common conditions affecting women of all racial and ethnic groups. These disorders are undertreated in all women, but this is especially magnified in Black people who have been historically marginalized in the United States. This article seeks to highlight the prevalence of pelvic floor disorders in Black women, evaluate the clinical care they receive, examine barriers they face to equitable care, and present a strategic agenda to prioritize the care of Black women with pelvic floor disorders.

Race and genetics versus 'race' in genetics: A systematic review of the use of African ancestry in genetic studies

Social scientists have long understood race to be a social category invented to justify slavery and evolutionary biologists know the socially constructed racial categories do not align with our biological understanding of genetic variation. The completion of the Human Genome Project in 2003 confirmed humans are 99.9% identical at the DNA level and there is no genetic basis for race. A systematic review of the PubMed medical literature published since 2003 was conducted to assess the use of African ancestry to denote study populations in genetic studies categorized as clinical trials, to examine the stated rationale for its use and to assess the use of evolutionary principles to explain human genetic diversity. We searched for papers that included the terms 'African', 'African American' or 'Black' in studies of behavior (20 papers), physiological responses, the pharmacokinetics of drugs and/or disease associations (62 papers), and as a genetic category in studies, including the examination of genotypes associated with life stress, pain, stuttering and drug clearance (126 papers). Of these, we identified 74 studies in which self-reported race alone or in combination with admixture mapping was used to define the study population. However, none of these studies provided a genetic explanation for the use of the self-identified race as a genetic category and only seven proffered evolutionary explanations of their data. The concept of continuous genetic variation was not clearly articulated in any of these papers, presumably due to the paucity of evolutionary science in the college and medical school curricula.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.