Operationalizing language-based population stratification for widening access to precision genomics in Africa.

ABSTRACT:

Background

Despite remarkable advancements in genomic technologies, individuals of predominant African-related genetic similarity remain significantly under-represented, accounting for only 2.4% of published genome-wide association studies. This disparity limits our understanding of human biology and hinders equitable translation of genomic advances into healthcare.

Methods

We exploited a quantitative framework using normalized Levenshtein distance (LDN) to analyse lexical similarity patterns across Kenya's ethnolinguistic landscape, comprising Bantu, Nilotic, and Cushitic language groups. We compared lexical distance matrices with available genetic population differentiation data and geographic proximity to evaluate their relative efficacy in predicting genetic relationship

SUBMITTER: Kulohoma BW 

PROVIDER: S-EPMC12463837 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature