Race, Genetics, and Society

The paper develops and evaluates tailored illustrations to improve community understanding of genetics concepts through iterative feedback and analysis of engagement patterns.

This study evaluates genetic ancestry report concordance across providers, compares ancestry to self-identified race/ethnicity, and explores perspectives on integrating ancestry data into EHRs.

The paper introduces a dynamic clustering approach for genomics cohorts based on trait-specific genomic signals, revealing patterns beyond predefined racial or continental categories.

This study analyzes genetic ancestry in 93,419 individuals to show that ethnicity-based carrier-screening guidelines are incomplete and miss carriers in at-risk populations.

The paper highlights the lack of standard definitions and protocols for collecting and using race, ethnicity, and ancestry data in clinical genetics and precision medicine.

Eurocentric GWAS make polygenic scores less accurate in non-Europeans (mean 4.9-fold lower for UK Biobank Africans); equal-sized ancestry-matched GWAS predict better in Japanese and British individuals.

The paper analyzes REA data collection practices and disparities in gnomAD, highlighting the need for standardized frameworks to improve diversity and variant interpretation in clinical genomics.

The paper introduces a standardized framework for ancestry data representation in genomics studies and applies it to the NHGRI-EBI GWAS Catalog to improve data integration and analysis.

The paper evaluates the reliability of self-reported ethnicity versus genetic ancestry in carrier screening and finds discrepancies that affect carrier risk estimation.

The paper conducts a meta-analysis of 41 studies to examine the association between biogeographic ancestry and socioeconomic status in the Americas, finding consistent directional relationships.