Biobanks increasingly include individuals with admixed genomes, yet conventional genome-wide association study frameworks either exclude participants who cannot be confidently assigned to a discrete ancestry group or ignore ancestry-specific effects. We present FELIX, a scalable framework for local-ancestry-aware genetic analysis that retains all participants without requiring discrete ancestry assignment. FELIX combines a compact ancestry-resolved genotype representation (FELIXla) with an adaptive association test that jointly evaluates shared-effect and ancestry-specific models at each variant (FELIXassoc). Simulations demonstrated well-calibrated inference under case-control imbalance and power that adapted to the locus-optimal model. Across 24 phenotypes in 240,038 All of Us participants, FELIX analyzed the 12.1% of individuals excluded by global-ancestry clustering and identified 15.4% more genome-wide significant loci than global-ancestry meta-analysis. Additional discoveries arose from recovering ancestry-specific haplotypes carried by admixed participants and from detecting ancestry-dependent marginal effects. Full-cohort effect estimates also improved polygenic score prediction across ancestries and traits.
L. Hu, T. Tan, K. Yuan et al.· medRxiv· 0 citations
Many disease-associated variants are thought to act through gene regulation, yet conventional eQTL mapping explains only a fraction of GWAS loci, potentially because regulatory effects vary across cellular states and environments. We present CASTIE, a scalable Poisson mixed-model framework that directly models sparse single-cell read counts and enables genome-wide testing of genotype-by-context interactions without pre-screening for static effects. Applying CASTIE to 1.2 million peripheral blood mononuclear cells from 982 OneK1K donors identified 3,155 context-dependent eQTL associations, including 2,022 eGenes without detectable static effects. These associations yielded 374 colocalizations across 94 traits, representing 270 unique loci, of which 197 were not recovered using the corresponding static eQTLs. The colocalizations linked trait associations to specific cellular contexts and genes including GCHFR, RNASET2 and ATP1A3. In adipose-derived mesenchymal stem cells exposed to metabolic stimulations, CASTIE increased eGene discovery by 36-92% across cell populations and identified stimulation-dependent regulatory effects at metabolic trait loci. Thus, modeling cellular context reveals disease-relevant regulatory variation beyond static eQTL mapping.
Y.-C. Liu, A. Cuomo, Y. Huang et al.· medRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
