Population Genetics & GWAS

Introduction

Population genetics and genome-wide association studies (GWAS) provide fundamental insights into human genetic variation, disease susceptibility, and evolutionary history. Traditional GWAS approaches have been limited by population diversity, statistical power, and ancestry inference accuracy, particularly for non-European populations underrepresented in genetic research.

BioInfera's population genetics platform addresses these limitations through advanced statistical genetics methodologies, comprehensive ancestry inference algorithms, and scalable association testing frameworks. The platform integrates high-density SNP arrays and whole genome sequencing data to support both population structure analysis and genome-wide trait association studies.

Platform Objectives

• Large-scale GWAS analysis across diverse global populations
• High-accuracy ancestry inference and population structure analysis
• Polygenic risk score computation with cross-population validation
• Fine-mapping and causal variant identification
• Population-specific genetic architecture characterization

Methodology

Study Populations and Data Sources

The validation study incorporated genetic data from 2.5+ million individuals across 100+ global populations, including major biobanks (UK Biobank, All of Us, FinnGen), population-specific cohorts (African Ancestry, Hispanic/Latino, East Asian), and indigenous populations. Both high-density SNP array data (Global Screening Array, UK Biobank Axiom) and whole genome sequencing were utilized for comprehensive variant coverage.

Population Group	Sample Size	Data Type	Variant Coverage	Ancestry Groups
European	1,200,000	SNP Array + WGS	50M variants	Northern, Southern, Eastern
African	400,000	SNP Array + WGS	80M variants	West, East, Southern
East Asian	500,000	SNP Array + WGS	45M variants	Chinese, Japanese, Korean
South Asian	200,000	SNP Array	35M variants	Indian, Pakistani, Bengali
Hispanic/Latino	150,000	SNP Array	40M variants	Mexican, Caribbean, South American
Other/Admixed	50,000	SNP Array + WGS	60M variants	Native American, Oceanian

Statistical Genetics Framework

Association testing utilized state-of-the-art mixed-model approaches including BOLT-LMM, SAIGE, and REGENIE for efficient genome-wide analysis with population structure and kinship correction. Quality control protocols included Hardy-Weinberg equilibrium testing, call rate filters, and population stratification assessment using principal component analysis (PCA).

Ancestry Inference and Population Structure

Ancestry inference employed supervised and unsupervised machine learning approaches including ADMIXTURE, STRUCTURE, and neural network-based methods. Reference panels from 1000 Genomes Project, Human Genome Diversity Project (HGDP), and population-specific cohorts provided comprehensive coverage of global genetic diversity.

Results

Ancestry Inference Performance

Comprehensive evaluation demonstrated exceptional ancestry inference performance across all population groups. Continental-level ancestry assignment achieved 91.7% accuracy, while sub-continental resolution reached 87.3% accuracy for fine-scale population structure. Admixture proportion estimation showed high concordance (r²=0.94) with reference populations.

Ancestry Level	Accuracy	Precision	Recall	F1-Score
Continental	91.7%	92.3%	91.1%	91.7%
Sub-Continental	87.3%	88.1%	86.9%	87.5%
Regional	82.6%	83.4%	81.8%	82.6%
Local Ancestry	78.9%	79.7%	78.1%	78.9%

GWAS Discovery Results

Genome-wide association studies identified 12,847 genome-wide significant associations (p < 5×10⁻⁸) across 500+ complex traits and diseases. Novel associations included 2,341 previously unreported loci, with particularly strong enrichment in non-European populations. Fine-mapping identified 4,567 credible causal variants with >95% posterior probability.

Polygenic Risk Score Performance

Polygenic risk scores (PRS) demonstrated robust performance across populations with cross-ancestry validation. Mean prediction accuracy (R²) reached 0.23 for height, 0.18 for BMI, and 0.15 for coronary artery disease. Population-specific PRS showed 15-30% improvement in non-European populations compared to European-trained models.

Population-Specific Findings

African Ancestry Populations

African ancestry analysis revealed the highest genetic diversity with 80 million variants identified across West, East, and Southern African populations. Novel associations included 349 African-specific loci for hypertension, sickle cell disease modifiers, and infectious disease resistance. Local ancestry deconvolution in African Americans identified population-specific risk factors with clinical relevance.

Population Group	Novel Loci	Top Association	P-value	Clinical Relevance
West African	186	Hypertension	3.2×10⁻⁴²	High
East African	127	Malaria Resistance	8.7×10⁻³⁶	High
Southern African	89	TB Susceptibility	1.4×10⁻²⁸	High
African American	163	Sickle Cell	2.1×10⁻⁵⁸	Very High

East Asian Populations

East Asian GWAS identified 267 population-specific associations for metabolic traits, cancer susceptibility, and pharmacogenomic variants. Notable discoveries included novel loci for gastric cancer, lactose intolerance adaptation, and drug metabolism pathways with significant clinical implications for precision medicine.

Hispanic/Latino Populations

Analysis of Hispanic/Latino populations revealed complex admixture patterns with significant local ancestry effects on disease risk. Indigenous American ancestry components showed protective effects for certain autoimmune diseases while conferring increased diabetes susceptibility. Population-specific PRS improved prediction accuracy by 25% compared to European-derived scores.

Conclusions

This comprehensive validation study demonstrates that BioInfera's population genetics and GWAS platform represents a significant advancement in understanding human genetic diversity and disease susceptibility across global populations. The platform's integration of sophisticated ancestry inference, robust association testing, and polygenic prediction enables unprecedented insights into population-specific genetic architecture.

Key Research Achievements

• Global Scale: 2.5+ million individuals across 100+ populations analyzed
• Ancestry Accuracy: 91.7% continental-level inference with robust validation
• Novel Discoveries: 2,341 previously unreported genome-wide significant associations
• Population Equity: 67% of discoveries in non-European ancestry groups
• Clinical Translation: Population-specific PRS with enhanced prediction accuracy

Scientific Impact

The platform's contributions to population genetics research include novel methodological advances in ancestry inference, improved understanding of population-specific disease architecture, and enhanced polygenic prediction across diverse populations. Results have informed precision medicine initiatives and contributed to reducing health disparities in genetic research.

Future Research Directions

Future development will expand to include rare variant association testing, multi-trait GWAS approaches, and integration with functional genomics data. Enhanced population coverage will incorporate additional indigenous populations and recently established biobanks to further advance global genetic diversity research.