Local Ancestry Association, Admixture Mapping, and Ongoing Challenges

Impact of cross-ancestry genetic architecture on GWASs in admixed populations

Genome-wide association studies (GWASs) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWASs in admixed populations, such as the need to correctly adjust for population stratification. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing a GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes, we find that controlling for and conditioning effect sizes on local ancestry can reduce statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs, HetLanc is not large enough for GWASs to benefit from modeling heterogeneity in this way.

Impact of cross-ancestry genetic architecture on GWAS in admixed populations

Genome-wide association studies (GWAS) have identified thousands of variants for disease risk. These studies have predominantly been conducted in individuals of European ancestries, which raises questions about their transferability to individuals of other ancestries. Of particular interest are admixed populations, usually defined as populations with recent ancestry from two or more continental sources. Admixed genomes contain segments of distinct ancestries that vary in composition across individuals in the population, allowing for the same allele to induce risk for disease on different ancestral backgrounds. This mosaicism raises unique challenges for GWAS in admixed populations, such as the need to correctly adjust for population stratification to balance type I error with statistical power. In this work we quantify the impact of differences in estimated allelic effect sizes for risk variants between ancestry backgrounds on association statistics. Specifically, while the possibility of estimated allelic effect-size heterogeneity by ancestry (HetLanc) can be modeled when performing GWAS in admixed populations, the extent of HetLanc needed to overcome the penalty from an additional degree of freedom in the association statistic has not been thoroughly quantified. Using extensive simulations of admixed genotypes and phenotypes we find that modeling HetLanc in its absence reduces statistical power by up to 72%. This finding is especially pronounced in the presence of allele frequency differentiation. We replicate simulation results using 4,327 African-European admixed genomes from the UK Biobank for 12 traits to find that for most significant SNPs HetLanc is not large enough for GWAS to benefit from modeling heterogeneity.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Whole-Genome Sequencing Identifies Novel Functional Loci Associated with Lung Function in Puerto Rican Youth

Rationale: Puerto Ricans have the highest childhood asthma prevalence in the United States (23.6%); however, the etiology is uncertain.Objectives: In this study, we sought to uncover the genetic architecture of lung function in Puerto Rican youth with and without asthma who were recruited from the island (n = 836).Methods: We used admixture-mapping and whole-genome sequencing data to discover genomic regions associated with lung function. Functional roles of the prioritized candidate SNPs were examined with chromatin immunoprecipitation sequencing, RNA sequencing, and expression quantitative trait loci data.Measurements and Main Results: We discovered a genomic region at 1q32 that was significantly associated with a 0.12-L decrease in the lung volume of exhaled air (95% confidence interval, -0.17 to -0.07; P = 6.62 × 10-8) with each allele of African ancestry. Within this region, two SNPs were expression quantitative trait loci of TMEM9 in nasal airway epithelial cells and MROH3P in esophagus mucosa. The minor alleles of these SNPs were associated with significantly decreased lung function and decreased TMEM9 gene expression. Another admixture-mapping peak was observed on chromosome 5q35.1, indicating that each Native American ancestry allele was associated with a 0.15-L increase in lung function (95% confidence interval, 0.08-0.21; P = 5.03 × 10-6). The region-based association tests identified four suggestive windows that harbored candidate rare variants associated with lung function.Conclusions: We identified common and rare genetic variants that may play a critical role in lung function among Puerto Rican youth. We independently validated an inflammatory pathway that could potentially be used to develop more targeted treatments and interventions for patients with asthma.

Genome-defined African ancestry is associated with distinct mutations and worse survival in patients with diffuse large B-cell lymphoma

BACKGROUND

Significant racial differences have been observed in the incidence and clinical outcomes of diffuse large B-cell lymphoma (DLBCL) in the United States, but to the authors' knowledge it remains unclear whether genomic differences contribute to these disparities.

METHODS

To understand the influences of genetic ancestry on tumor genomic alterations, the authors estimated the genetic ancestry of 1001 previously described patients with DLBCL using unsupervised model-based Admixture global ancestry analysis applied to exome sequencing data and examined the mutational profile of 150 DLBCL driver genes in tumors obtained from this cohort.

RESULTS

Global ancestry prediction identified 619 patients with >90% European ancestry, 81 patients with >90% African ancestry, and 50 patients with >90% Asian ancestry. Compared with patients with DLBCL with European ancestry, patients with African ancestry were aged >10 years younger at the time of diagnosis and were more likely to present with B symptoms, elevated serum lactate dehydrogenase, extranodal disease, and advanced stage disease. Patients with African ancestry demonstrated worse overall survival compared with patients with European ancestry (median, 4.9 years vs 8.8 years; P = .04). Recurrent mutations of MLL2 (KMT2D), HIST1H1E, MYD88, BCL2, and PIM1 were found across all ancestry groups, suggesting shared mechanisms underlying tumor biology. The authors also identified 6 DLBCL driver genes that were more commonly mutated in patients with African ancestry compared with patients with European ancestry: ATM (21.0% vs 7.75%; P < .001), MGA (19.7% vs 5.33%; P < .001), SETD2 (17.3% vs 5.17%; P < .001), TET2 (12.3% vs 5.82%; P = .029), MLL3 (KMT2C) (11.1% vs 4.36%; P = .013), and DNMT3A (11.1% vs 4.52%; P = .016).

CONCLUSIONS

Distinct prevalence and patterns of mutation highlight an important difference in the mutational landscapes of DLBCL arising in different ancestry groups. To the authors' knowledge, the results of the current study provide the first-ever characterization of genetic alterations among patients with African descent who are diagnosed with DLBCL.

Admixture mapping of asthma in southwestern Europeans with North African ancestry influences

The prevalence of asthma symptoms in Canary Islanders, a southwestern European population from Spain, is almost three times higher than the country average. Because the genetic risks identified so far explain <5% of asthma heritability, here we aimed to discover new asthma loci by completing the first admixture mapping study in Canary Islanders leveraging their distinctive genetic makeup, where significant northwest African influences coexist in the European genetic diversity landscape. A 2-stage study was conducted in 1,491 unrelated individuals self-declaring having a Canary Islands origin for the 4 grandparents. Local ancestry estimates were obtained for the shared positions with reference data from putative ancestral populations from Europe, North Africa, and sub-Saharan Africa. Case-control deviations in local ancestry were tested for each ancestry separately using logistic regressions adjusted for principal components, followed by fine-mapping analyses based on imputed genotypes and analyses of the likely deleterious exonic variants. The admixture mapping analysis of asthma detected that local North African ancestry in a locus spanning 365 kb of chromosome 16q23.3 was associated with asthma risk at study-wide significance [lowest P = 1.12 × 10^-4; odds ratio (OR) = 2.05; 95% confidence interval (CI) = 1.41-3.00]. Fine-mapping studies identified a variant associated with asthma, and results were replicated in independent samples (rs3852738, OR = 1.34; 95% CI = 1.13-1.59, P = 7.58 × 10^-4). Whole exome sequencing data from a subset of individuals revealed an enrichment of likely deleterious variants among asthma cases in 16q23.3, particularly in the phospholipase Cγ2 (PLCG2) gene (P = 3.67 × 10^-4). By completing the first mapping study of asthma in admixed populations from Europe, our results revealed a new plausible asthma locus.