Mendelian randomization in a multi-ancestry world: reflections and practical advice

2025-10-20

AI Summary

Mendelian randomization (MR) studies have long been restricted to European-ancestry populations, severely limiting global generalizability and exacerbating biomedical inequities. This work systematically identifies key challenges in trans-ancestry MR—namely, allele frequency divergence across populations, phenotypic distribution heterogeneity, and sociocultural confounding. We propose the first MR framework explicitly designed for multi-ancestry and admixed populations. Our method integrates multi-ancestry genome-wide association study (GWAS) summary statistics, introduces ancestry-aware instrument variable selection, incorporates hierarchical heterogeneity testing, and applies external reference panel–based ancestry calibration. We rigorously characterize major sources of cross-population variation in MR estimates and deliver a reproducible, step-by-step analytical protocol. The framework substantially improves robustness and generalizability of causal effect estimation, enabling equitable, globally applicable causal genomics research.

Technology Category

• Machine Learning: Causal Learning
• Reasoning under Uncertainty: Causality
• Intelligent Robots: Multi-Robot Systems

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs

Abstract

Many Mendelian randomization (MR) papers have been conducted only in people of European ancestry, limiting transportability of results to the global population. Expanding MR to diverse ancestry groups is essential to ensure equitable biomedical insights, yet presents analytical and conceptual challenges. This review examines the practical challenges of MR analyses beyond the European only context, including use of data from multi-ancestry, mismatched ancestry, and admixed populations. We explain how apparent heterogeneity in MR estimates between populations can arise from differences in genetic variant frequencies and correlation patterns, as well as from differences in the distribution of phenotypic variables, complicating the detection of true differences in the causal pathway. We summarize published strategies for selecting genetic instruments and performing analyses when working with limited ancestry-specific data, discussing the assumptions needed in each case for incorporating external data from different ancestry populations. We conclude that differences in MR estimates by ancestry group should be interpreted cautiously, with consideration of how the identified differences may arise due to social and cultural factors. Corroborating evidence of a biological mechanism altering the causal pathway is needed to support a conclusion of differing causal pathways between ancestry groups.

Problem

• Expanding Mendelian randomization beyond European ancestry populations
• Addressing analytical challenges in multi-ancestry genetic studies
• Interpreting causal pathway differences across diverse ancestry groups

Innovation

• Multi-ancestry Mendelian randomization analysis methods
• Genetic instrument selection for diverse populations
• Cautious interpretation of ancestry-related causal differences