Power comparison of admixture mapping and direct association analysis in genome-wide association studies

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.

Admixture Mapping in African Americans Identifies New Risk Loci for HCV-Related Cirrhosis

BACKGROUND & AIMS

Cirrhosis is the main predisposing condition for hepatocellular carcinoma. Host genetic risk factors have been reported for cirrhosis; however, whether there is a genetic contribution to racial disparities in cirrhosis requires further investigation.

METHODS

We used an affected-only mapping by admixture linkage disequilibrium analysis to characterize the genetic risk of cirrhosis in 227 African American patients with cirrhosis genotyped at 19,804 ancestry-informative marker single nucleotide polymorphisms. We additionally performed analyses stratified by hepatitis C virus (HCV) infection status. To replicate our findings, we conducted a case-control analysis in an external study population (452 cases and 196 controls).

RESULTS

The mean age of patients was 63.3 years and 98.2% were male. Risk factors for cirrhosis included HCV infection (83.7%) and alcohol abuse (56.4%). In the admixture mapping analysis, we found that European ancestry on chromosome 2q21.1 and African ancestry on chromosome 6p21.2 were associated with increased risk of cirrhosis in African Americans. In the fine-mapping analysis, we identified regions near POTEKP on 2q21.1 (P = .0001) and DNAH8 on 6p21.2 (P = .0017) that were associated with cirrhosis. As the admixture peaks in the HCV-positive patients were the same as those in the overall group, findings in the analysis are reflective of the HCV-positive group. In the replication analysis, the results on chromosome 2 were not significant after adjusting for multiple comparisons, and we could not replicate the results on chromosome 6.

CONCLUSIONS

We used admixture mapping to identify novel genomic regions on 2q21.1 and 6p21.2 that may be associated with HCV-related cirrhosis risk in African Americans.

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.

European genetic ancestry associated with risk of childhood ependymoma

BACKGROUND

Ependymoma is a histologically defined central nervous system tumor most commonly occurring in childhood. Population-level incidence differences by race/ethnicity are observed, with individuals of European ancestry at highest risk. We aimed to determine whether extent of European genetic ancestry is associated with ependymoma risk in US populations.

METHODS

In a multi-ethnic study of Californian children (327 cases, 1970 controls), we estimated the proportions of European, African, and Native American ancestry among recently admixed Hispanic and African American subjects and estimated European admixture among non-Hispanic white subjects using genome-wide data. We tested whether genome-wide ancestry differences were associated with ependymoma risk and performed admixture mapping to identify associations with local ancestry. We also evaluated race/ethnicity-stratified ependymoma incidence data from the Central Brain Tumor Registry of the United States (CBTRUS).

RESULTS

CBTRUS data revealed that African American and Native American children have 33% and 36%, respectively, reduced incidence of ependymoma compared with non-Hispanic whites. In genetic analyses, a 20% increase in European ancestry was associated with a 1.31-fold higher odds of ependymoma among self-reported Hispanics and African Americans (95% CI: 1.08-1.59, Pmeta = 6.7 × 10-3). Additionally, eastern European ancestral substructure was associated with increased ependymoma risk in non-Hispanic whites (P = 0.030) and in Hispanics (P = 0.043). Admixture mapping revealed a peak at 20p13 associated with increased local European ancestry, and targeted fine-mapping identified a lead variant at rs6039499 near RSPO4 (odds ratio = 1.99; 95% CI: 1.45-2.73; P = 2.2 × 10-5) but which was not validated in an independent set of posterior fossa type A patients.

CONCLUSIONS

Interethnic differences in ependymoma risk are recapitulated in the genomic ancestry of ependymoma patients, implicating regions to target in future association studies.

Differential admixture in Latin American populations and its impact on the study of colorectal cancer

Genome-wide association studies focused on searching genes responsible for several diseases. Admixture mapping studies proposed a more efficient alternative capable of detecting polymorphisms contributing with a small effect on the disease risk. This method focuses on the higher values of linkage disequilibrium in admixed populations. To test this, we analyzed 10 genomic regions previously defined as related with colorectal cancer among nine populations and studied the variation pattern of haplotypic structures and heterozygosity values on seven categories of SNPs. Both analyses showed differences among chromosomal regions and studied populations. Admixed Latin-American samples generally show intermediate values. Heterozygosity of the SNPs grouped in categories varies more in each gene than in each population. African related populations have more blocks per chromosomal region, coherently with their antiquity. In sum, some similarities were found among Latin American populations, but each chromosomal region showed a particular behavior, despite the fact that the study refers to genes and regions related with one particular complex disease. This study strongly suggests the necessity of developing statistical methods to deal with di- or tri-hybrid populations, as well as to carefully analyze the different historic and demographic scenarios, and the different characteristics of particular chromosomal regions and evolutionary forces.

Genomic Regions 10q22.2, 17q21.31, and 2p23.1 Can Contribute to a Lower Lung Function in African Descent Populations

Accumulated evidence supports the contribution of genetic factors in modulating airway function, especially ancestry. We investigated whether genetic polymorphisms can affect lung function in a mixed Brazilian child population using the admixture mapping strategy through RFMix software version 1.5.4 (Stanford University, Stanford, CA, USA), followed by fine mapping, to identify regions whereby local African or European ancestry is associated with lung function measured by the forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) ratio, an indicator of airway obstruction. The research cohort included 958 individuals aged 4 to 11 years enrolled in the SCAALA (Social Change, Asthma, Allergy in Latin America) Program. We identified that African ancestry at 17q21.31, 10q22.2, and 2p23.1 regions was associated with lower lung function measured by FEV1/FVC p < 1.9 × 10-4. In contrast, European ancestry at 17q21.31 showed an opposite effect. Fine mapping pointed out 5 single nucleotide polymorphisms (SNPs) also associated in our replication cohort (rs10999948, rs373831475, rs8068257, rs6744555, and rs1520322). Our results suggest that genomic regions associated with ancestry may contribute to differences in lung function measurements in African American children in Brazil replicated in a cohort of Brazilian adults. The analysis strategy used in this work is especially important for phenotypes, such as lung function, which has considerable disparities in terms of measurements across different populations.

Genetics of cognitive trajectory in Brazilians: 15 years of follow-up from the Bambuí-Epigen Cohort Study of Aging

Age-related cognitive decline (ACD) is the gradual process of decreasing of cognitive function over age. Most genetic risk factors for ACD have been identified in European populations and there are no reports in admixed Latin American individuals. We performed admixture mapping, genome-wide association analysis (GWAS), and fine-mapping to examine genetic factors associated with 15-year cognitive trajectory in 1,407 Brazilian older adults, comprising 14,956 Mini-Mental State Examination measures. Participants were enrolled as part of the Bambuí-Epigen Cohort Study of Aging. Our admixture mapping analysis identified a genomic region (3p24.2) in which increased Native American ancestry was significantly associated with faster ACD. Fine-mapping of this region identified a single nucleotide polymorphism (SNP) rs142380904 (β = -0.044, SE = 0.01, p = 7.5 × 10-5) associated with ACD. In addition, our GWAS identified 24 associated SNPs, most in genes previously reported to influence cognitive function. The top six associated SNPs accounted for 18.5% of the ACD variance in our data. Furthermore, our longitudinal study replicated previous GWAS hits for cognitive decline and Alzheimer's disease. Our 15-year longitudinal study identified both ancestry-specific and cosmopolitan genetic variants associated with ACD in Brazilians, highlighting the need for more trans-ancestry genomic studies, especially in underrepresented ethnic groups.

LEI: A Novel Allele Frequency-Based Feature Selection Method for Multi-ancestry Admixed Populations

Next-generation sequencing technologies now make it possible to sequence and genotype hundreds of thousands of genetic markers across the human genome. Selection of informative markers for the comprehensive characterization of individual genomic makeup using a high dimensional genomics dataset has become a common practice in evolutionary biology and human genetics. Although several feature selection approaches exist to determine the ancestry proportion in two-way admixed populations including African Americans, there are limited statistical tools developed for the feature selection approaches in three-way admixed populations (including Latino populations). Herein, we present a new likelihood-based feature selection method called Lancaster Estimator of Independence (LEI) that utilizes allele frequency information to prioritize the most informative features useful to determine ancestry proportion from multiple ancestral populations in admixed individuals. The ability of LEI to leverage summary-level statistics from allele frequency data, thereby avoiding the many restrictions (and big data issues) that can accompany access to individual-level genotype data, is appealing to minimize the computation and time-consuming ancestry inference in an admixed population. We compared our allele-frequency based approach with genotype-based approach in estimating admixed proportions in three-way admixed population scenarios. Our results showed ancestry estimates using the top-ranked features from LEI were comparable with the estimates using features from genotype-based methods in three-way admixed population. We provide an easy-to-use R code to assist researchers in using the LEI tool to develop allele frequency-based informative features to conduct admixture mapping studies from mixed samples of multiple ancestry origin.

Identifying Rare Variant Associations in Admixed Populations

An admixed population and its ancestral populations bear different burdens of a complex disease. The ancestral populations may have different haplotypes of deleterious alleles and thus ancestry-gene interaction can influence disease risk in the admixed population. Among admixed individuals, deleterious haplotypes and their ancestries are dependent and can provide non-redundant association information. Herein we propose a local ancestry boosted sum test (LABST) for identifying chromosomal blocks that harbor rare variants but have no ancestry switches. For such a stable ancestral block, our LABST exploits ancestry-gene interaction and the number of rare alleles therein. Under the null of no genetic association, the test statistic asymptotically follows a chi-square distribution with one degree of freedom (1-df). Our LABST properly controlled type I error rates under extensive simulations, suggesting that the asymptotic approximation was accurate for the null distribution of the test statistic. In terms of power for identifying rare variant associations, our LABST uniformly outperformed several famed methods under four important modes of disease genetics over a large range of relative risks. In conclusion, exploiting ancestry-gene interaction can boost statistical power for rare variant association mapping in admixed populations.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

Ancient Ancestry Informative Markers for Identifying Fine-Scale Ancient Population Structure in Eurasians

The rapid accumulation of ancient human genomes from various areas and time periods potentially enables the expansion of studies of biodiversity, biogeography, forensics, population history, and epidemiology into past populations. However, most ancient DNA (aDNA) data were generated through microarrays designed for modern-day populations, which are known to misrepresent the population structure. Past studies addressed these problems by using ancestry informative markers (AIMs). It is, thereby, unclear whether AIMs derived from contemporary human genomes can capture ancient population structures, and whether AIM-finding methods are applicable to aDNA, provided that the high missingness rates in ancient-and oftentimes haploid-DNA can also distort the population structure. Here, we define ancient AIMs (aAIMs) and develop a framework to evaluate established and novel AIM-finding methods in identifying the most informative markers. We show that aAIMs identified by a novel principal component analysis (PCA)-based method outperform all of the competing methods in classifying ancient individuals into populations and identifying admixed individuals. In some cases, predictions made using the aAIMs were more accurate than those made with a complete marker set. We discuss the features of the ancient Eurasian population structure and strategies to identify aAIMs. This work informs the design of single nucleotide polymorphism (SNP) microarrays and the interpretation of aDNA results, which enables a population-wide testing of primordialist theories.

Genome-wide admixture and association study of subclinical atherosclerosis in the Women's Interagency HIV Study (WIHS)

Cardiovascular disease (CVD) is a major comorbidity among HIV-infected individuals. Common carotid artery intima-media thickness (cCIMT) is a valid and reliable subclinical measure of atherosclerosis and is known to predict CVD. We performed genome-wide association (GWA) and admixture analysis among 682 HIV-positive and 288 HIV-negative Black, non-Hispanic women from the Women’s Interagency HIV study (WIHS) cohort using a combined and stratified analysis approach. We found some suggestive associations but none of the SNPs reached genome-wide statistical significance in our GWAS analysis. The top GWAS SNPs were rs2280828 in the region intergenic to mediator complex subunit 30 and exostosin glycosyltransferase 1 (MED30 | EXT1) among all women, rs2907092 in the catenin delta 2 (CTNND2) gene among HIV-positive women, and rs7529733 in the region intergenic to family with sequence similarity 5, member C and regulator of G-protein signaling 18 (FAM5C | RGS18) genes among HIV-negative women. The most significant local European ancestry associations were in the region intergenic to the zinc finger and SCAN domain containing 5D gene and NADH: ubiquinone oxidoreductase complex assembly factor 1 (ZSCAN5D | NDUF1) pseudogene on chromosome 19 among all women, in the region intergenic to vomeronasal 1 receptor 6 pseudogene and zinc finger protein 845 (VN1R6P | ZNF845) gene on chromosome 19 among HIV-positive women, and in the region intergenic to the SEC23-interacting protein and phosphatidic acid phosphatase type 2 domain containing 1A (SEC23IP | PPAPDC1A) genes located on chromosome 10 among HIV-negative women. A number of previously identified SNP associations with cCIMT were also observed and included rs2572204 in the ryanodine receptor 3 (RYR3) and an admixture region in the secretion-regulating guanine nucleotide exchange factor (SERGEF) gene. We report several SNPs and gene regions in the GWAS and admixture analysis, some of which are common across HIV-positive and HIV-negative women as demonstrated using meta-analysis, and also across the two analytic approaches (i.e., GWA and admixture). These findings suggest that local European ancestry plays an important role in genetic associations of cCIMT among black women from WIHS along with other environmental factors that are related to CVD and may also be triggered by HIV. These findings warrant confirmation in independent samples.

Admixture mapping in the Hispanic Community Health Study/Study of Latinos reveals regions of genetic associations with blood pressure traits

Admixture mapping can be used to detect genetic association regions in admixed populations, such as Hispanics/Latinos, by estimating associations between local ancestry allele counts and the trait of interest. We performed admixture mapping of the blood pressure traits systolic and diastolic blood pressure (SBP, DBP), mean arterial pressure (MAP), and pulse pressure (PP), in a dataset of 12,116 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Hispanics/Latinos have three predominant ancestral populations (European, African, and Amerindian), for each of which we separately tested local ancestry intervals across the genome. We identified four regions that were significantly associated with a blood pressure trait at the genome-wide admixture mapping level. A 6p21.31 Amerindian ancestry association region has multiple known associations, but none explained the admixture mapping signal. We identified variants that completely explained this signal. One of these variants had p-values of 0.02 (MAP) and 0.04 (SBP) in replication testing in Pima Indians. A 11q13.4 Amerindian ancestry association region spans a variant that was previously reported (p-value = 0.001) in a targeted association study of Blood Pressure (BP) traits and variants in the vitamin D pathway. There was no replication evidence supporting an association in the identified 17q25.3 Amerindian ancestry association region. For a region on 6p12.3, associated with African ancestry, we did not identify any candidate variants driving the association. It may be driven by rare variants. Whole genome sequence data may be necessary to fine map these association signals, which may contribute to disparities in BP traits between diverse populations.

The Analysis of Ethnic Mixtures

Population of ethnic mixtures can be useful in genetic studies. Admixture mapping, or mapping by admixture linkage disequilibrium (MALD), is specially developed for admixed populations and can supplement traditional genome-wide association analyses in the search for genetic variants underlying complex traits. Admixture mapping tests the association between a trait and locus-specific ancestries. The locus-specific ancestries are in linkage disequilibrium (LD), which is generated by an admixture process between genetically distinct ancestral populations. Because of the highly correlated-locus specific ancestries, admixture mapping performs many fewer independent tests across the genome than current genome-wide association analysis. Therefore, admixture mapping can be more powerful because it reduces the penalty due to multiple tests. In this chapter, we introduce the theory behind admixture mapping and explain how to conduct the analysis in practice.

Genetic association meta-analysis: a new classification to assess ethnicity using the association of MCP-1 -2518 polymorphism and tuberculosis susceptibility as a model

Background

In meta-analyses of genetic association studies, ancestry and ethnicity are not accurately investigated. Ethnicity is usually classified using conventional race/ethnic categories or continental groupings even though they could introduce bias increasing heterogeneity between and within studies; thus decreasing the external validity of the results. In this study, we performed a meta-analysis using a novel ethnic classification system to test the association between MCP-1 -2518 polymorphism and pulmonary tuberculosis. Our new classification considers genetic distance, migration and linguistic origins, which will increase homogeneity within ethnic groups.

Methods

We included thirteen studies from three continents (Asia, Africa and Latin America) and considered seven ethnic groups (West Africa, South Africa, Saharan Africa, East Asia, South Asia, Persia and Latin America).

Results

The results were compared to the continental group classification. We found a significant association between MCP-1 -2518 polymorphism and TB susceptibility only in the East Asian and Latin American groups (OR 3.47, P = 0.08; OR 2.73, P = 0.02). This association is not observed in other ethnic groups that are usually considered in the Asian group, such as India and Persia, or in the African group.

Conclusions

There is an association between MCP-1 -2518 polymorphism and TB susceptibility only in the East Asian and Latin American groups. We suggest the use of our new ethnic classification in future meta-analysis of genetic association studies when ancestry markers are not available. This new classification increases homogeneity for certain ethnic groups compared to the continental classification. We recommend considering previous data about migration, linguistics and genetic distance when classifying ethnicity in further studies.

A Generalized Sequential Bonferroni Procedure for GWAS in Admixed Populations Incorporating Admixture Mapping Information into Association Tests

OBJECTIVE

To develop effective methods for GWAS in admixed populations such as African Americans.

METHODS

We show that, when testing the null hypothesis that the test SNP is not in background linkage disequilibrium with the causal variants, several existing methods cannot control well the family-wise error rate (FWER) in the strong sense in GWAS. These existing methods include association tests adjusting for global ancestry and joint association tests that combine statistics from admixture mapping tests and association tests that correct for local ancestry. Furthermore, we describe a generalized sequential Bonferroni (smooth-GSB) procedure for GWAS that incorporates smoothed weights calculated from admixture mapping tests into association tests that correct for local ancestry. We have applied the smooth-GSB procedure to analyses of GWAS data on American Africans from the Atherosclerosis Risk in Communities (ARIC) Study.

RESULTS

Our simulation studies indicate that the smooth-GSB procedure not only control the FWER, but also improves statistical power compared with association tests correcting for local ancestry.

CONCLUSION

The smooth-GSB procedure can result in a better performance than several existing methods for GWAS in admixed populations.

Variants for HDL-C, LDL-C, and triglycerides identified from admixture mapping and fine-mapping analysis in African American families

BACKGROUND

Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African Americans.

METHODS AND RESULTS

The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. The analysis was performed in 1905 unrelated African American subjects from the National Heart, Lung and Blood Institute's Family Blood Pressure Program (FBPP). Regions showing admixture evidence were followed-up with family-based association analysis in 3556 African American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age(2), sex, body mass index, and genome-wide mean ancestry to minimize the confounding caused by population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (low-density lipoprotein cholesterol), 8 (high-density lipoprotein cholesterol), 14 (triglycerides), and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52 939 single-nucleotide polymorphisms (SNPs) were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with high-density lipoprotein cholesterol (2 SNPs), low-density lipoprotein cholesterol (4 SNPs), and triglycerides (5 SNPs). The family data were used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions, including genes with known associations for cardiovascular disease.

CONCLUSIONS

This study identified regions on chromosomes 7, 8, 14, and 19 and 11 SNPs from the fine-mapping analysis that were associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides for further studies of cardiovascular disease in African Americans.

Admixture mapping identifies a quantitative trait locus associated with FEV1/FVC in the COPDGene Study

African Americans are admixed with genetic contributions from European and African ancestral populations. Admixture mapping leverages this information to map genes influencing differential disease risk across populations. We performed admixture and association mapping in 3,300 African American current or former smokers from the COPDGene Study. We analyzed estimated local ancestry and SNP genotype information to identify regions associated with FEV1 /FVC, the ratio of forced expiratory volume in one second to forced vital capacity, measured by spirometry performed after bronchodilator administration. Global African ancestry inversely associated with FEV1 /FVC (P = 0.035). Genome-wide admixture analysis, controlling for age, gender, body mass index, current smoking status, pack-years smoked, and four principal components summarizing the genetic background of African Americans in the COPDGene Study, identified a region on chromosome 12q14.1 associated with FEV1 /FVC (P = 2.1 × 10(-6) ) when regressed on local ancestry. Allelic association in this region of chromosome 12 identified an intronic variant in FAM19A2 (rs348644) as associated with FEV1 /FVC (P = 1.76 × 10(-6) ). By combining admixture and association mapping, a marker on chromosome 12q14.1 was identified as being associated with reduced FEV1 /FVC ratio among African Americans in the COPDGene Study.

Enhanced methods for local ancestry assignment in sequenced admixed individuals

Inferring the ancestry at each locus in the genome of recently admixed individuals (e.g., Latino Americans) plays a major role in medical and population genetic inferences, ranging from finding disease-risk loci, to inferring recombination rates, to mapping missing contigs in the human genome. Although many methods for local ancestry inference have been proposed, most are designed for use with genotyping arrays and fail to make use of the full spectrum of data available from sequencing. In addition, current haplotype-based approaches are very computationally demanding, requiring large computational time for moderately large sample sizes. Here we present new methods for local ancestry inference that leverage continent-specific variants (CSVs) to attain increased performance over existing approaches in sequenced admixed genomes. A key feature of our approach is that it incorporates the admixed genomes themselves jointly with public datasets, such as 1000 Genomes, to improve the accuracy of CSV calling. We use simulations to show that our approach attains accuracy similar to widely used computationally intensive haplotype-based approaches with large decreases in runtime. Most importantly, we show that our method recovers comparable local ancestries, as the 1000 Genomes consensus local ancestry calls in the real admixed individuals from the 1000 Genomes Project. We extend our approach to account for low-coverage sequencing and show that accurate local ancestry inference can be attained at low sequencing coverage. Finally, we generalize CSVs to sub-continental population-specific variants (sCSVs) and show that in some cases it is possible to determine the sub-continental ancestry for short chromosomal segments on the basis of sCSVs.

Advances in sequencing technologies are dramatically changing the volume and type of data collected in genetic studies. Although most genetic studies so far have focused on individuals of European ancestry, recent studies are increasingly being performed in individuals of admixed ancestry (i.e., with recent ancestors from multiple continents, e.g., Latino Americans). A key component in such studies is the accurate inference of continental ancestry at each segment in the genome of these individuals. In this work we present accurate and robust methods that use continent-specific variants (i.e., genetic variants observed only in individuals of a given continent), now readily accessible through sequencing technology, to perform extremely fast and accurate inference of the ancestral origin of each genomic segment in recently admixed individuals.

Admixture mapping of prostate cancer in African Americans participating in the North Carolina-Louisiana Prostate Cancer Project (PCaP)

BACKGROUND

Few genetic risk factors have been uncovered that contribute specifically to the racial disparity in prostate cancer (CaP) observed in African Americans (AA). With the advent of ancestry informative marker (AIM) single nucleotide polymorphism (SNP) panels and powerful genetic strategies such as mapping by admixture linkage disequilibrium (MALD) it is possible to discover genes that underlie ethnic variation in disease risk.

METHODS

One thousand one hundred thirty AA CaP cases enrolled in the North Carolina-Louisiana Prostate Cancer Project (PCaP) were genotyped using a 1,509 AIM SNP panel. MALD was performed using ADMIXMAP to test for linkage between CaP risk and ancestry estimates at each AIM SNP.

RESULTS

The largest increase of African ancestry was observed at marker rs12543473 (P = 0.0011), located on chromosome 8q24.21, and the greatest excess of European ancestry was observed at marker rs10768140 (P = 0.0004) at chromosome 11p13.

CONCLUSIONS

The study confirmed the 8q24 risk loci and identified a novel genomic region on 11p13 that is associated with CaP risk. These findings should be replicated in larger AA populations and combined with fine mapping data to further refine the novel 11p13 CaP risk loci.