Admixture mapping of 15,280 African Americans identifies obesity susceptibility loci on chromosomes 5 and X

On the number of genealogical ancestors tracing to the source groups of an admixed population

Members of genetically admixed populations possess ancestry from multiple source groups, and studies of human genetic admixture frequently estimate ancestry components corresponding to fractions of individual genomes that trace to specific ancestral populations. However, the same numerical ancestry fraction can represent a wide array of admixture scenarios within an individual's genealogy. Using a mechanistic model of admixture, we consider admixture genealogically: how many ancestors from the source populations does the admixture represent? We consider African-Americans, for whom continent-level estimates produce a 75-85% value for African ancestry on average and 15-25% for European ancestry. Genetic studies together with key features of African-American demographic history suggest ranges for parameters of a simple three-epoch model. Considering parameter sets compatible with estimates of current ancestry levels, we infer that if all genealogical lines of a random African-American born during 1960-1965 are traced back until they reach members of source populations, the mean over parameter sets of the expected number of genealogical lines terminating with African individuals is 314 (interquartile range 240-376), and the mean of the expected number terminating in Europeans is 51 (interquartile range 32-69). Across discrete generations, the peak number of African genealogical ancestors occurs in birth cohorts from the early 1700s, and the probability exceeds 50% that at least one European ancestor was born more recently than 1835. Our genealogical perspective can contribute to further understanding the admixture processes that underlie admixed populations. For African-Americans, the results provide insight both on how many of the ancestors of a typical African-American might have been forcibly displaced in the Transatlantic Slave Trade and on how many separate European admixture events might exist in a typical African-American genealogy.

Extensive set of African ancestry-informative markers (AIMs) to study ancestry and population health

Introduction: Human populations are often highly structured due to differences in genetic ancestry among groups, posing difficulties in associating genes with diseases. Ancestry-informative markers (AIMs) aid in the detection of population stratification and provide an alternative approach to map population-specific alleles to disease. Here, we identify and characterize a novel set of African AIMs that separate populations of African ancestry from other global populations including those of European ancestry. Methods: Using data from the 1000 Genomes Project, highly informative SNP markers from five African subpopulations were selected based on estimates of informativeness (In) and compared against the European population to generate a final set of 46,737 African ancestry-informative markers (AIMs). The AIMs identified were validated using an independent set and functionally annotated using tools like SIFT, PolyPhen. They were also investigated for representation of commonly used SNP arrays. Results: This set of African AIMs effectively separates populations of African ancestry from other global populations and further identifies substructure between populations of African ancestry. When a subset of these AIMs was studied in an independent dataset, they differentiated people who self-identify as African American or Black from those who identify their ancestry as primarily European. Most of the AIMs were found to be in their intergenic and intronic regions with only 0.6% in the coding regions of the genome. Most of the commonly used SNP array investigated contained less than 10% of the AIMs. Discussion: While several functional annotations of both coding and non-coding African AIMs are supported by the literature and linked these high-frequency African alleles to diseases in African populations, more effort is needed to map genes to diseases in these genetically diverse subpopulations. The relative dearth of these African AIMs on current genotyping platforms (the array with the highest fraction, llumina's Omni 5, harbors less than a quarter of AIMs), further demonstrates a greater need to better represent historically understudied populations.

Admixture mapping of anthropometric traits in the Black Women's Health Study: evidence of a shared African ancestry component with birth weight and type 2 diabetes

Prevalence of obesity, type 2 diabetes (T2D), and being born with low birth weight are much higher in African American women compared to U.S. white women. Genetic factors may contribute to the excess risk of these conditions. We conducted admixture mapping of body mass index (BMI) at age 18, adult BMI, and adult waist circumference and waist-to-hip ratio adjusted for BMI using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study. We also searched for evidence of shared African genetic ancestry components among the four examined anthropometric traits and among birth weight and T2D. We found that global percent African ancestry was associated with higher adult BMI. We also found that African ancestry at 9q34 was associated with lower BMI at age 18. Our shared ancestry analysis identified ten genomic regions with local African ancestry associated with multiple traits. Seven out of these ten genomic loci were related to T2D risk. Of special interest is the 12q14-21 region where local African ancestry was associated with low birth weight, low BMI, high BMI-adjusted waist-to-hip ratio, and high T2D risk. Findings in the 12q14-21 genomic locus are consistent with the fetal insulin hypothesis that postulates that low birth weight and T2D have a common genetic basis, and they support the hypothesis of a shared African genetic ancestry component linking low birth weight and T2D in African Americans. Future studies should identify the actual genetic variants responsible for the clustering of these conditions in African Americans.

Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass and fat mass indexes

BACKGROUND/OBJECTIVES

Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely underrepresented in genomic studies. Here, we study the genetic architecture of BMI in children, young adults, and elderly individuals from the admixed population of Brazil.

SUBJECTS/METHODS

Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European, and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of body mass index (BMI) in three Brazilian population-based cohorts from Northeast (Salvador), Southeast (Bambuí), and South (Pelotas).

RESULTS

We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p = 2.76e-06). This variant is rare in Europeans but with frequencies of ~3% in West Africa and has a strong female-specific effect (95% CI: 2.32-5.65 kg/m² per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from São Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains ~9% among women with morbid obesity from Pelotas, São Paulo, and Bambuí. The effect size of rs114066381 is at least five times higher than the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects.

CONCLUSIONS

We identified six candidate SNPs associated with BMI. rs114066381 stands out for its high effect that was replicated and its high frequency in women with morbid obesity. We demonstrate how admixed populations are a source of new relevant phenotype-associated genetic variants.

Genetic Variation, Diet, Inflammation, and the Risk for COVID-19

COVID-19, which is caused by SARS-CoV-2, is characterized by various symptoms, ranging from mild fatigue to life-threatening pneumonia, "cytokine storm," and multiorgan failure. The manifestation of COVID-19 may lead to a cytokine storm, i.e., it facilitates viral replication that triggers a strong release of cytokines, which then modulates the immune system and results in hyperinflammation. Today's diet is high in omega-6 fatty acids and deficient in omega-3 fatty acids; this, along with a high fructose intake, leads to obesity, which is a chronic state of low-grade inflammation. Omega-6 fatty acids are proinflammatory and prothrombotic whereas omega-3 fatty acids are less proinflammatory and thrombotic. Furthermore, omega-3 fatty acids make specialized lipid mediators, namely resolvins, protectins, and maresins, that are potent anti-inflammatory agents. Throughout evolution there was a balance between omega-6 and omega-3 fatty acids with a ratio of 1-2/1 omega-6/omega-3, but today this ratio is 16-20/1 omega-6/omega-3, leading to a proinflammatory state. In addition, genetic variants in FADS1, FADS2, ELOV-2, and ELOV-5 lead to a more efficient biosynthesis of long-chain polyunsaturated fatty acids (PUFAs), e.g., of linoleic acid (LA) to arachidonic acid (ARA), and (alpha-linolenic acid) (ALA) to eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), leading to higher ARA levels. Because the US diet is already high in omega-6 fatty acids, the increased biosynthesis of ARA in people with the derived FADS haplotype (haplotype D) leads to an increased production of leukotrienes, thromboxanes, C-reactive protein (CRP), and eventually elevated levels of cytokines, like interleukin (IL)-1, IL-6, and tumor necrosis factor (TNF), which may increase susceptibility to COVID-19. About 80% of African Americans, 50% of Hispanics, and 45% of European Americans have the FADS haplotype D and are thus efficient metabolizers, which could account for the higher vulnerability of these populations to COVID-19. Therefore, another reason that African Americans and Hispanics are more susceptible to COVID-19 is that they have a higher frequency of haplotype D, which is no longer beneficial in today's environment and diet. Genetic variation must be considered in all studies of disease development and therapy because it is important to the practice of precision nutrition by physicians and other health professionals. The objective of this commentary is to emphasize the importance of genetic variation within populations and its interaction with diet in the development of disease. Differences in the frequency of genes and their interactions with nutrients in various population groups must be considered among the factors contributing to health disparities in the development of COVID-19. A balanced omega-6/omega-3 ratio is essential to health. Physicians should measure their patients' fatty acids and recommend decreasing the intake of foods rich in omega-6 fatty acids and increasing the intake of omega-3 fatty acids along with fruits and vegetables.

Putting RFMix and ADMIXTURE to the test in a complex admixed population

Background

Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The development and resulting accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios.

Results

Using simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions even in a complex 5-way admixed population, in addition to assigning local ancestry with an accuracy of 89%. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, particularly in admixed populations provides the opportunity for more accurate association analyses.

Conclusion

This study highlights the utility of the extension of computational tools to become more compatible to genetically structured populations, as well as the need to expand the sampling of diverse world-wide populations. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools and commonly used ancestral populations are less appropriate. Based on these caveats and the results presented here, we suggest that RFMix be used for both global and local ancestry estimation in world-wide complex admixture scenarios particularly when including these estimates in association studies.

Ancestry-Dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity

Runs of homozygosity (ROH) are important genomic features that manifest when an individual inherits two haplotypes that are identical by descent. Their length distributions are informative about population history, and their genomic locations are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. We have previously shown that ROH, and especially long ROH that are likely the result of recent parental relatedness, are enriched for homozygous deleterious coding variation in a worldwide sample of outbred individuals. However, the distribution of ROH in admixed populations and their relationship to deleterious homozygous genotypes is understudied. Here we analyze whole-genome sequencing data from 1,441 unrelated individuals from self-identified African American, Puerto Rican, and Mexican American populations. These populations are three-way admixed between European, African, and Native American ancestries and provide an opportunity to study the distribution of deleterious alleles partitioned by local ancestry and ROH. We re-capitulate previous findings that long ROH are enriched for deleterious variation genome-wide. We then partition by local ancestry and show that deleterious homozygotes arise at a higher rate when ROH overlap African ancestry segments than when they overlap European or Native American ancestry segments of the genome. These results suggest that, while ROH on any haplotype background are associated with an inflation of deleterious homozygous variation, African haplotype backgrounds may play a particularly important role in the genetic architecture of complex diseases for admixed individuals, highlighting the need for further study of these populations.

The role of country of birth, and genetic and self-identified ancestry, in obesity susceptibility among African and Hispanic Americans

BACKGROUND

African Americans (AAs) and Hispanic/Latinos (HLs) have higher risk of obesity than European Americans, possibly due to differences in environment and lifestyle, but also reflecting differences in genetic background.

OBJECTIVE

To gain insight into factors contributing to BMI (in kg/m2) and obesity risk (BMI ≥ 30) among ancestry groups, we investigate the role of self-reported ancestry, proportion of genetic African ancestry, and country of birth in 6368 self-identified AA and 7569 HL participants of the New York-based BioMe Biobank.

METHODS

AAs and HLs are admixed populations that trace their genetic ancestry to the Americas, Africa, and Europe. The proportion of African ancestry (PAA), quantified using ADMIXTURE, was higher among self-reported AA (median: 87%; IQR: 79-92%) than among HL (26%; 15-41%) participants. Approximately 18% of AA and 59% of HL participants were non-US-born.

RESULTS

Because of significant differences between sexes (PPAA*sex interaction = 4.8 × 10-22), we considered women and men separately. Among women, country of birth and genetic ancestry contributed independently to BMI. US-born women had a BMI 1.99 higher than those born abroad (P = 7.7 × 10-25). Every 10% increase in PAA was associated with a BMI 0.29 higher (P = 7.1 × 10-10). After accounting for PAA and country of birth, the contribution of self-reported ancestry was small (P = 0.046). The contribution of PAA to higher BMI was significantly more pronounced among US-born (0.35/10%PAA, P = 0.003) than among non-US-born (0.26/10%PAA, P = 0.01) women (PPAA*sex interaction = 0.004). In contrast, among men, only US-born status influenced BMI. US-born men had a BMI 1.33 higher than non-US-born men, whereas PAA and self-reported ancestry were not associated with BMI. Associations with obesity risk were similar to those observed for BMI.

CONCLUSIONS

Being US-born is associated with a substantially higher BMI and risk of obesity in both men and women. Genetic ancestry, but not self-reported ancestry, is associated with obesity susceptibility, but only among US-born women in this New York-based population.

PAMAM: Power analysis in multiancestry admixture mapping

Admixed populations arise when two or more previously isolated populations interbreed. Admixture mapping (AM) methods are used for tracing the ancestral origin of disease-susceptibility genetic loci in the admixed population such as African American and Latinos. AM is different from genome-wide association studies in that ancestry rather than genotypes are tracked in the association process. The power and sample size of AM primarily depend on proportion of admixture and differences in the risk allele frequencies among the ancestral populations. Ensuring sufficient power to detect the effect of ancestry on disease susceptibility is critical for interpretability and reliability of studies using AM approach. However, there is no power and sample size analysis tool existing for AM studies in admixed population. In this study, we developed power analysis of multiancestry AM (PAMAM) to estimate power and sample size for two-way and three-way population admixtures. PAMAM is the first web-based bioinformatics tool developed to calculate power and sample size in admixed population under a variety of genetic and disease phenotype models. It is a valuable resource for investigators to design a cost-efficient study and develop grant application to pursue AM studies. PAMAM is built on JavaScript back-end with HTML front-end. It is accessible through any modern web browser such as Firefox, Internet Explorer, and Google Chrome regardless of operating system. It is a user-friendly tool containing links for support information including user manual and examples, and freely available at https://research.cchmc.org/mershalab/PAMAM/login.html.

The Future of Genomic Studies Must Be Globally Representative: Perspectives from PAGE

The past decade has seen a technological revolution in human genetics that has empowered population-level investigations into genetic associations with phenotypes. Although these discoveries rely on genetic variation across individuals, association studies have overwhelmingly been performed in populations of European descent. In this review, we describe limitations faced by single-population studies and provide an overview of strategies to improve global representation in existing data sets and future human genomics research via diversity-focused, multiethnic studies. We highlight the successes of individual studies and meta-analysis consortia that have provided unique knowledge. Additionally, we outline the approach taken by the Population Architecture Using Genomics and Epidemiology (PAGE) study to develop best practices for performing genetic epidemiology in multiethnic contexts. Finally, we discuss how limiting investigations to single populations impairs findings in the clinical domain for both rare-variant identification and genetic risk prediction.

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.

An admixture mapping meta-analysis implicates genetic variation at 18q21 with asthma susceptibility in Latinos

BACKGROUND

Asthma is a common but complex disease with racial/ethnic differences in prevalence, morbidity, and response to therapies.

OBJECTIVE

We sought to perform an analysis of genetic ancestry to identify new loci that contribute to asthma susceptibility.

METHODS

We leveraged the mixed ancestry of 3902 Latinos and performed an admixture mapping meta-analysis for asthma susceptibility. We replicated associations in an independent study of 3774 Latinos, performed targeted sequencing for fine mapping, and tested for disease correlations with gene expression in the whole blood of more than 500 subjects from 3 racial/ethnic groups.

RESULTS

We identified a genome-wide significant admixture mapping peak at 18q21 in Latinos (P = 6.8 × 10-6), where Native American ancestry was associated with increased risk of asthma (odds ratio [OR], 1.20; 95% CI, 1.07-1.34; P = .002) and European ancestry was associated with protection (OR, 0.86; 95% CI, 0.77-0.96; P = .008). Our findings were replicated in an independent childhood asthma study in Latinos (P = 5.3 × 10-3, combined P = 2.6 × 10-7). Fine mapping of 18q21 in 1978 Latinos identified a significant association with multiple variants 5' of SMAD family member 2 (SMAD2) in Mexicans, whereas a single rare variant in the same window was the top association in Puerto Ricans. Low versus high SMAD2 blood expression was correlated with case status (13.4% lower expression; OR, 3.93; 95% CI, 2.12-7.28; P < .001). In addition, lower expression of SMAD2 was associated with more frequent exacerbations among Puerto Ricans with asthma.

CONCLUSION

Ancestry at 18q21 was significantly associated with asthma in Latinos and implicated multiple ancestry-informative noncoding variants upstream of SMAD2 with asthma susceptibility. Furthermore, decreased SMAD2 expression in blood was strongly associated with increased asthma risk and increased exacerbations.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.

On the origin of obesity: identifying the biological, environmental and cultural drivers of genetic risk among human populations

Genetic predisposition to obesity presents a paradox: how do genetic variants with a detrimental impact on human health persist through evolutionary time? Numerous hypotheses, such as the thrifty genotype hypothesis, attempt to explain this phenomenon yet fail to provide a justification for the modern obesity epidemic. In this critical review, we appraise existing theories explaining the evolutionary origins of obesity and explore novel biological and sociocultural agents of evolutionary change to help explain the modern-day distribution of obesity-predisposing variants. Genetic drift, acting as a form of 'blind justice,' may randomly affect allele frequencies across generations while gene pleiotropy and adaptations to diverse environments may explain the rise and subsequent selection of obesity risk alleles. As an adaptive response, epigenetic regulation of gene expression may impact the manifestation of genetic predisposition to obesity. Finally, exposure to malnutrition and disease epidemics in the wake of oppressive social systems, culturally mediated notions of attractiveness and desirability, and diverse mating systems may play a role in shaping the human genome. As an important first step towards the identification of important drivers of obesity gene evolution, this review may inform empirical research focused on testing evolutionary theories by way of population genetics and mathematical modelling.

Ethnic and population differences in the genetic predisposition to human obesity

Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.

A methodological study of genome-wide DNA methylation analyses using matched archival formalin-fixed paraffin embedded and fresh frozen breast tumors

Background

DNA from archival formalin-fixed and paraffin embedded (FFPE) tissue is an invaluable resource for genome-wide methylation studies although concerns about poor quality may limit its use. In this study, we compared DNA methylation profiles of breast tumors using DNA from fresh-frozen (FF) tissues and three types of matched FFPE samples.

Results

For 9/10 patients, correlation and unsupervised clustering analysis revealed that the FF and FFPE samples were consistently correlated with each other and clustered into distinct subgroups. Greater than 84% of the top 100 loci previously shown to differentiate ER+ and ER– tumors in FF tissues were also FFPE DML. Weighted Correlation Gene Network Analyses (WCGNA) grouped the DML loci into 16 modules in FF tissue, with ~85% of the module membership preserved across tissue types.

Materials and Methods

Restored FFPE and matched FF samples were profiled using the Illumina Infinium HumanMethylation450K platform. Methylation levels (β-values) across all loci and the top 100 loci previously shown to differentiate tumors by estrogen receptor status (ER+ or ER−) in a larger FF study, were compared between matched FF and FFPE samples using Pearson's correlation, hierarchical clustering and WCGNA. Positive predictive values and sensitivity levels for detecting differentially methylated loci (DML) in FF samples were calculated in an independent FFPE cohort.

Conclusions

FFPE breast tumors samples show lower overall detection of DMLs versus FF, however FFPE and FF DMLs compare favorably. These results support the emerging consensus that the 450K platform can be employed to investigate epigenetics in large sets of archival FFPE tissues.

Genomic Disparities in Breast Cancer Among Latinas

BACKGROUND

Breast cancer is the most common cancer diagnosed among Latinas in the United States and the leading cause of cancer-related death among this population. Latinas tend to be diagnosed at a later stage and have worse prognostic features than their non-Hispanic white counterparts. Genetic and genomic factors may contribute to observed breast cancer health disparities in Latinas.

METHODS

We provide a landscape of our current understanding and the existing gaps that need to be filled across the cancer prevention and control continuum.

RESULTS

We summarize available data on mutations in high and moderate penetrance genes for inherited risk of breast cancer and the associated literature on disparities in awareness of and uptake of genetic counseling and testing in Latina populations. We also discuss common genetic polymorphisms and risk of breast cancer in Latinas. In the treatment setting, we examine tumor genomics and pharmacogenomics in Latina patients with breast cancer.

CONCLUSIONS

As the US population continues to diversify, extending genetic and genomic research into this underserved and understudied population is critical. By understanding the risk of breast cancer among ethnically diverse populations, we will be better positioned to make treatment advancements for earlier stages of cancer, identify more effective and ideally less toxic treatment regimens, and increase rates of survival.

Genetic architecture of age-related cognitive decline in African Americans

OBJECTIVE

To identify genetic risk factors associated with susceptibility to age-related cognitive decline in African Americans (AAs).

METHODS

We performed a genome-wide association study (GWAS) and an admixture-mapping scan in 3,964 older AAs from 5 longitudinal cohorts; for each participant, we calculated a slope of an individual's global cognitive change from neuropsychological evaluations. We also performed a pathway-based analysis of the age-related cognitive decline GWAS.

RESULTS

We found no evidence to support the existence of a genomic region which has a strongly different contribution to age-related cognitive decline in African and European genomes. Known Alzheimer disease (AD) susceptibility variants in the ABCA7 and MS4A loci do influence this trait in AAs. Of interest, our pathway-based analyses returned statistically significant results highlighting a shared risk from lipid/metabolism and protein tyrosine signaling pathways between cognitive decline and AD, but the role of inflammatory pathways is polarized, being limited to AD susceptibility.

CONCLUSIONS

The genetic architecture of aging-related cognitive in AA individuals is largely similar to that of individuals of European descent. In both populations, we note a surprising lack of enrichment for immune pathways in the genetic risk for cognitive decline, despite strong enrichment of these pathways among genetic risk factors for AD.

Admixture mapping identifies introgressed genomic regions in North American canids

Hybrid zones typically contain novel gene combinations that can be tested by natural selection in a unique genetic context. Parental haplotypes that increase fitness can introgress beyond the hybrid zone, into the range of parental species. We used the Affymetrix canine SNP genotyping array to identify genomic regions tagged by multiple ancestry informative markers that are more frequent in an admixed population than expected. We surveyed a hybrid zone formed in the last 100 years as coyotes expanded their range into eastern North America. Concomitant with expansion, coyotes hybridized with wolves and some populations became more wolflike, such that coyotes in the northeast have the largest body size of any coyote population. Using a set of 3102 ancestry informative markers, we identified 60 differentially introgressed regions in 44 canines across this admixture zone. These regions are characterized by an excess of exogenous ancestry and, in northeastern coyotes, are enriched for genes affecting body size and skeletal proportions. Further, introgressed wolf-derived alleles have penetrated into Southern US coyote populations. Because no wolves currently exist in this area, these alleles are unlikely to have originated from recent hybridization. Instead, they probably originated from intraspecific gene flow or ancient admixture. We show that grey wolf and coyote admixture has far-reaching effects and, in addition to phenotypically transforming admixed populations, allows for the differential movement of alleles from different parental species to be tested in new genomic backgrounds.

Population Genomics and the Statistical Values of Race: An Interdisciplinary Perspective on the Biological Classification of Human Populations and Implications for Clinical Genetic Epidemiological Research

The biological status and biomedical significance of the concept of race as applied to humans continue to be contentious issues despite the use of advanced statistical and clustering methods to determine continental ancestry. It is thus imperative for researchers to understand the limitations as well as potential uses of the concept of race in biology and biomedicine. This paper deals with the theoretical assumptions behind cluster analysis in human population genomics. Adopting an interdisciplinary approach, it demonstrates that the hypothesis that attributes the clustering of human populations to "frictional" effects of landform barriers at continental boundaries is empirically incoherent. It then contrasts the scientific status of the "cluster" and "cline" constructs in human population genomics, and shows how cluster may be instrumentally produced. It also shows how statistical values of race vindicate Darwin's argument that race is evolutionarily meaningless. Finally, the paper explains why, due to spatiotemporal parameters, evolutionary forces, and socio-cultural factors influencing population structure, continental ancestry may be pragmatically relevant to global and public health genomics. Overall, this work demonstrates that, from a biological systematic and evolutionary taxonomical perspective, human races/continental groups or clusters have no natural meaning or objective biological reality. In fact, the utility of racial categorizations in research and in clinics can be explained by spatiotemporal parameters, socio-cultural factors, and evolutionary forces affecting disease causation and treatment response.

The Genome Russia project: closing the largest remaining omission on the world Genome map

We are witnessing the great era of genome exploration of the world, as genetic variation in people is being detailed across multiple varied world populations in an effort unprecedented since the first human genome sequence appeared in 2001. However, these efforts have yet to produce a comprehensive mapping of humankind, because important regions of modern human civilization remain unexplored. The Genome Russia Project promises to fill one of the largest gaps, the expansive regions across the Russian Federation, informing not just medical genomics of the territories, but also the migration settlements  of historic and pre-historic Eurasian peoples.

Leveraging local ancestry to detect gene-gene interactions in genome-wide data

BACKGROUND

Although genome-wide association studies have successfully identified thousands of variants associated to complex traits, these variants only explain a small amount of the entire heritability of the trait. Gene-gene interactions have been proposed as a source to explain a significant percentage of the missing heritability. However, detecting gene-gene interactions has proven to be very difficult due to computational and statistical challenges. The vast number of possible interactions that can be tested induces very stringent multiple hypotheses corrections that limit the power of detection. These issues have been mostly highlighted for the identification of pairwise effects and are even more challenging when addressing higher order interaction effects. In this work we explore the use of local ancestry in recently admixed individuals to find signals of gene-gene interaction on human traits and diseases.

RESULTS

We introduce statistical methods that leverage the correlation between local ancestry and the hidden unknown causal variants to find distant gene-gene interactions. We show that the power of this test increases with the number of causal variants per locus and the degree of differentiation of these variants between the ancestral populations. Overall, our simulations confirm that local ancestry can be used to detect gene-gene interactions, solving the computational bottleneck. When compared to a single nucleotide polymorphism (SNP)-based interaction screening of the same sample size, the power of our test was lower on all settings we considered. However, accounting for the dramatic increase in sample size that can be achieve when genotyping only a set of ancestry informative markers instead of the whole genome, we observe substantial gain in power in several scenarios.

CONCLUSION

Local ancestry-based interaction tests offer a new path to the detection of gene-gene interaction effects. It would be particularly useful in scenarios where multiple differentiated variants at the interacting loci act in a synergistic manner.

Beyond 2/3 and 1/3: The Complex Signatures of Sex-Biased Admixture on the X Chromosome

Sex-biased demography, in which parameters governing migration and population size differ between females and males, has been studied through comparisons of X chromosomes, which are inherited sex-specifically, and autosomes, which are not. A common form of sex bias in humans is sex-biased admixture, in which at least one of the source populations differs in its proportions of females and males contributing to an admixed population. Studies of sex-biased admixture often examine the mean ancestry for markers on the X chromosome in relation to the autosomes. A simple framework noting that in a population with equally many females and males, two-thirds of X chromosomes appear in females, suggests that the mean X-chromosomal admixture fraction is a linear combination of female and male admixture parameters, with coefficients 2/3 and 1/3, respectively. Extending a mechanistic admixture model to accommodate the X chromosome, we demonstrate that this prediction is not generally true in admixture models, although it holds in the limit for an admixture process occurring as a single event. For a model with constant ongoing admixture, we determine the mean X-chromosomal admixture, comparing admixture on female and male X chromosomes to corresponding autosomal values. Surprisingly, in reanalyzing African-American genetic data to estimate sex-specific contributions from African and European sources, we find that the range of contributions compatible with the excess African ancestry on the X chromosome compared to autosomes has a wide spread, permitting scenarios either without male-biased contributions from Europe or without female-biased contributions from Africa.

Frequency of SMN1 deletion carriers in a Mestizo population of central and northeastern Mexico: A pilot study

Individuals who suffer from spinal muscular atrophy (SMA) exhibit progressive muscle weakness that frequently results in mortality in the most severe forms of the disease. In 98% of cases, there is a homozygous deletion of the survival of motor neuron 1 (SMN1) gene, and both parents carry the same heterozygous genetic abnormality in the majority of cases. Various population studies have been conducted to estimate the frequency of carriers and thereby identify the communities or countries in which children are at a high risk of being affected by SMA. However, the prevalence of SMA in Mexican populations has not yet been established. In the present pilot study, the frequency of the heterozygous deletion of the SMN1 gene was determined in two groups from northeastern (n=287) and central (n=133) Mexican Mestizo populations and compared with other ethnic populations. Amplification refractory mutation system polymerase chain reaction analysis yielded a disease carrier frequency of 11/420 (2.62%) healthy individuals, comprising 9/287 (3.14%) northeastern and 2/133 (1.5%) central Mexican individuals. In summary, no significant differences were identified between the northeastern and central populations of Mexico and other ethnic populations, with the exception of the general worldwide Hispanic population, which exhibited the lowest carrier frequency of 8/1,030. The results of the present study may be used to improve the evaluation procedure, and appear to justify further studies involving larger sample populations.

Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations

Genome-wide association studies (GWASs) are the method most often used by geneticists to interrogate the human genome, and they provide a cost-effective way to identify the genetic variants underpinning complex traits and diseases. Most initial GWASs have focused on genetically homogeneous cohorts from European populations given the limited availability of ethnic minority samples and so as to limit population stratification effects. Transethnic studies have been invaluable in explaining the heritability of common quantitative traits, such as height, and in examining the genetic architecture of complex diseases, such as type 2 diabetes. They provide an opportunity for large-scale signal replication in independent populations and for cross-population meta-analyses to boost statistical power. In addition, transethnic GWASs enable prioritization of candidate genes, fine-mapping of functional variants, and potentially identification of SNPs associated with disease risk in admixed populations, by taking advantage of natural differences in genomic linkage disequilibrium across ethnically diverse populations. Recent efforts to assess the biological function of variants identified by GWAS have highlighted the need for large-scale replication, meta-analyses and fine-mapping across worldwide populations of ethnically diverse genetic ancestries. Here, we review recent advances and new approaches that are important to consider when performing, designing or interpreting transethnic GWASs, and we highlight existing challenges, such as the limited ability to handle heterogeneity in linkage disequilibrium across populations and limitations in dissecting complex architectures, such as those found in recently admixed populations.

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 and subsequent fine-mapping suggests a biologically relevant and novel association on chromosome 11 for type 2 diabetes in African Americans

Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Genome-wide association studies (GWAS) have identified several loci that contribute to T2D in European Americans, but few studies have been performed in admixed populations. We first performed a GWAS of 1,563 African Americans from the Vanderbilt Genome-Electronic Records Project and Northwestern University NUgene Project as part of the electronic Medical Records and Genomics (eMERGE) network. We successfully replicate an association in TCF7L2, previously identified by GWAS in this African American dataset. We were unable to identify novel associations at p<5.0×10(-8) by GWAS. Using admixture mapping as an alternative method for discovery, we performed a genome-wide admixture scan that suggests multiple candidate genes associated with T2D. One finding, TCIRG1, is a T-cell immune regulator expressed in the pancreas and liver that has not been previously implicated for T2D. We performed subsequent fine-mapping to further assess the association between TCIRG1 and T2D in >5,000 African Americans. We identified 13 independent associations between TCIRG1, CHKA, and ALDH3B1 genes on chromosome 11 and T2D. Our results suggest a novel region on chromosome 11 identified by admixture mapping is associated with T2D in African Americans.

Association of SERPINA9 gene variants with carotid artery atherosclerosis: the Atherosclerosis Risk in Communities (ARIC) Carotid MRI Study

The SNP rs11628722 in the SERPINA9 gene was previously associated with incident ischemic stroke in the Atherosclerosis Risk in Communities (ARIC) study. Centerin, the protein encoded by SERPINA9, is involved in maturation and maintenance of naïve B cells, which play a role in atherogenesis. We investigated whether 21 tag SNPs in the SERPINA9 gene are associated with features of carotid artery atherosclerotic plaque measured by magnetic resonance imaging (MRI). Carotid MRI data were obtained from 1,282 European Americans and 341 African Americans of the ARIC Carotid MRI study, which recruited participants from ARIC by a stratified sampling plan that over-sampled participants with carotid intima-media thickening. Five MRI measures, focused on carotid wall volume, wall thickness, and lipid core, were analyzed. Genetic associations between the MRI measurements and each of the 21 SNPs were analyzed in linear regression models with adjustment for sample weights and traditional risk factors. Rs11628722 was tested a priori. In African Americans, rs11628722 was significantly associated with carotid wall volume (p < 0.05). Among the other 20 SNPs, adjusted for multiple testing, rs4905204, which encodes an Ala to Val amino acid change, was significantly associated with maximum wall thickness (p < 0.000625) and suggestively associated with total wall volume (p < 0.0026) in European Americans. In conclusion, SNPs in the SERPINA9 gene showed race-specific associations with characteristics of carotid atherosclerotic plaques. Replications in other populations are needed to validate findings of this study and to establish the SERPINA9 gene as a candidate in the etiology of carotid atherosclerosis.

Genetic admixture and obesity: recent perspectives and future applications

The process of the colonization of the New World that occurred centuries ago served as a natural experiment, creating unique combinations of genetic material in newly formed admixed populations. Through a genetic admixture approach, the identification and genotyping of ancestry informative markers have allowed for the estimation of proportions of ancestral parental populations among individuals in a sample. These admixture estimates have been used in different ways to understand the genetic contributions to individual variation in obesity and body composition parameters, particularly among diverse admixed groups known to differ in obesity prevalence within the United States. Although progress has been made through the use of genetic admixture approaches, further investigations are needed in order to explore the interaction of environmental factors with the degree of genetic ancestry in individuals. A challenge to confront at this time would be to further stratify and define environments in progressively more granular terms, including nutrients, muscle biology, stress responses at the cellular level, and the social and built environments.

Socioeconomic status and lung cancer: unraveling the contribution of genetic admixture

OBJECTIVES

We examined the relationship between genetic ancestry, socioeconomic status (SES), and lung cancer among African Americans and Latinos.

METHODS

We evaluated SES and genetic ancestry in a Northern California lung cancer case-control study (1998-2003) of African Americans and Latinos. Lung cancer case and control participants were frequency matched on age, gender, and race/ethnicity. We assessed case-control differences in individual admixture proportions using the 2-sample t test and analysis of covariance. Logistic regression models examined associations among genetic ancestry, socioeconomic characteristics, and lung cancer.

RESULTS

Decreased Amerindian ancestry was associated with higher education among Latino control participants and greater African ancestry was associated with decreased education among African lung cancer case participants. Education was associated with lung cancer among both Latinos and African Americans, independent of smoking, ancestry, age, and gender. Genetic ancestry was not associated with lung cancer among African Americans.

CONCLUSIONS

Findings suggest that socioeconomic factors may have a greater impact than genetic ancestry on lung cancer among African Americans. The genetic heterogeneity and recent dynamic migration and acculturation of Latinos complicate recruitment; thus, epidemiological analyses and findings should be interpreted cautiously.

African ancestry is a risk factor for asthma and high total IgE levels in African admixed populations

Characterization of genetic admixture of populations in the Americas and the Caribbean is of interest for anthropological, epidemiological, and historical reasons. Asthma has a higher prevalence and is more severe in populations with a high African component. Association of African ancestry with asthma has been demonstrated. We estimated admixture proportions of samples from six trihybrid populations of African descent and determined the relationship between African ancestry and asthma and total serum IgE levels (tIgE). We genotyped 237 ancestry informative markers in asthmatics and nonasthmatic controls from Barbados (190/277), Jamaica (177/529), Brazil (40/220), Colombia (508/625), African Americans from New York (207/171), and African Americans from Baltimore/Washington, D.C. (625/757). We estimated individual ancestries and evaluated genetic stratification using Structure and principal component analysis. Association of African ancestry and asthma and tIgE was evaluated by regression analysis. Mean ± SD African ancestry ranged from 0.76 ± 0.10 among Barbadians to 0.33 ± 0.13 in Colombians. The European component varied from 0.14 ± 0.05 among Jamaicans and Barbadians to 0.26 ± 0.08 among Colombians. African ancestry was associated with risk for asthma in Colombians (odds ratio (OR) = 4.5, P = 0.001) Brazilians (OR = 136.5, P = 0.003), and African Americans of New York (OR: 4.7; P = 0.040). African ancestry was also associated with higher tIgE levels among Colombians (β = 1.3, P = 0.04), Barbadians (β = 3.8, P = 0.03), and Brazilians (β = 1.6, P = 0.03). Our findings indicate that African ancestry can account for, at least in part, the association between asthma and its associated trait, tIgE levels.

Contribution of higher risk genes and European admixture to Crohn's disease in African Americans

BACKGROUND

African Americans (AAs) are an admixed population of West African (WA) and European ancestry (EA). Crohn's disease (CD) susceptibility genes have not been established. We therefore evaluated the contribution of European admixture and major established risk genes to AA CD.

METHODS

Ninety-seven admixture informative markers were genotyped for ancestry estimates using STRUCTURE. Overall, 354 AA CD cases and 354 ethnicity-matched controls were genotyped for total 21 single nucleotide polymorphisms (SNPs) in ATG16L1, NOD2, IBD5, IL23R and IRGM by TaqMan or direct sequencing. Association was evaluated by logistic regression, adjusted for ancestry.

RESULTS

Mean EA was similar among the CD cases and controls (20.9% and 20.4%, respectively, P = 0.58). No significant admixture differences were observed among 211 to 227 cases stratified by phenotypic subclassifications including onset, surgery, site, and behavior. CD was associated with NOD2 carrier (6.93% CD, 2.15% Controls, P = 0.007), ATG16L1 Thr300Ala (36.1% CD, 29.3% Controls, P = 0.003), SLC22A4 and SLC22A5 (IBD5 locus) functional SNPs (Leu503Phe [10.5% CD, 7.6% Controls, P = 0.05] and g-207c [41.3% CD, 35.7% Controls, P = 0.03], respectively), and IL23R rs2201841 (18.2% CD, 13.8% Controls, P = 0.03), but not IRGM variants, nor three African ancestral NOD2 nonsynonymous variants. IBD5 risk was recessive. An all-minor allele IBD5 haplotype from EA was associated (P = 0.05), whereas a more common haplotype isolating g-207c was not.

CONCLUSIONS

Specific functional gene variations contribute significantly to AA CD risk. Established NOD2, SLC22A4-A5, and ATG16L1 variants show increased CD risk, with IBD5 recessive. Although CD is more common in whites, European admixture is similar among AA cases and controls.

Genetic modifiers of nutritional status in cystic fibrosis

BACKGROUND

Improved nutrition early in life is associated with better pulmonary function for patients with cystic fibrosis (CF). However, nutritional status is poorly correlated with the CFTR genotype.

OBJECTIVE

We investigated the extent to which modifier genes influence nutrition in children with CF.

DESIGN

BMI data were longitudinally collected from the CF Twin-Sibling Study and Cystic Fibrosis Foundation Patient Registry for twins and siblings from 2000 to 2010. A nutritional phenotype was derived for 1124 subjects by calculating the average BMI z score from 5-10 y of age (BMI-z(5to10)). The genetic contribution to the variation in BMI-z(5to10) (ie, heritability) was estimated by comparing the similarity of the phenotype in monozygous twins to that in dizygous twins and siblings. Linkage analysis identified potential modifier-gene loci.

RESULTS

The median BMI-z(5to10) was -0.07 (range: -3.89 to 2.30), which corresponded to the 47th CDC percentile. BMI-z(5to10) was negatively correlated with pancreatic insufficiency, history of meconium ileus, and female sex but positively correlated with later birth cohorts and lung function. Monozygous twins showed greater concordance for BMI-z(5to10) than did dizygous twins and siblings; heritability estimates from same-sex twin-only analyses ranged from 0.54 to 0.82. For 1010 subjects with pancreatic insufficiency, genome-wide significant linkage was identified on chromosomes 1p36.1 [log of odds (LOD): 5.3] and 5q14 (LOD: 5.1). These loci explained ≥16% and ≥15%, respectively, of the BMI variance.

CONCLUSIONS

The analysis of twins and siblings with CF indicates a prominent role for genes other than CFTR to BMI variation. Specifically, regions on chromosomes 1 and 5 appear to harbor genetic modifiers of substantial effect.

Multiway admixture deconvolution using phased or unphased ancestral panels

We describe a novel method for inferring the local ancestry of admixed individuals from dense genome-wide single nucleotide polymorphism data. The method, called MULTIMIX, allows multiple source populations, models population linkage disequilibrium between markers and is applicable to datasets in which the sample and source populations are either phased or unphased. The model is based upon a hidden Markov model of switches in ancestry between consecutive windows of loci. We model the observed haplotypes within each window using a multivariate normal distribution with parameters estimated from the ancestral panels. We present three methods to fit the model-Markov chain Monte Carlo sampling, the Expectation Maximization algorithm, and a Classification Expectation Maximization algorithm. The performance of our method on individuals simulated to be admixed with European and West African ancestry shows it to be comparable to HAPMIX, the ancestry calls of the two methods agreeing at 99.26% of loci across the three parameter groups. In addition to it being faster than HAPMIX, it is also found to perform well over a range of extent of admixture in a simulation involving three ancestral populations. In an analysis of real data, we estimate the contribution of European, West African and Native American ancestry to each locus in the Mexican samples of HapMap, giving estimates of ancestral proportions that are consistent with those previously reported.

Estimating the contribution of genetic variants to difference in incidence of disease between population groups

Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene-environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal.

Case-control admixture mapping in Latino populations enriches for known asthma-associated genes

BACKGROUND

Polymorphisms in more than 100 genes have been associated with asthma susceptibility, yet much of the heritability remains to be explained. Asthma disproportionately affects different racial and ethnic groups in the United States, suggesting that admixture mapping is a useful strategy to identify novel asthma-associated loci.

OBJECTIVE

We sought to identify novel asthma-associated loci in Latino populations using case-control admixture mapping.

METHODS

We performed genome-wide admixture mapping by comparing levels of local Native American, European, and African ancestry between children with asthma and nonasthmatic control subjects in Puerto Rican and Mexican populations. Within candidate peaks, we performed allelic tests of association, controlling for differences in local ancestry.

RESULTS

Between the 2 populations, we identified a total of 62 admixture mapping peaks at a P value of less than 10(-3) that were significantly enriched for previously identified asthma-associated genes (P= .0051). One of the peaks was statistically significant based on 100 permutations in the Mexican sample (6q15); however, it was not significant in Puerto Rican subjects. Another peak was identified at nominal significance in both populations (8q12); however, the association was observed with different ancestries.

CONCLUSION

Case-control admixture mapping is a promising strategy for identifying novel asthma-associated loci in Latino populations and implicates genetic variation at 6q15 and 8q12 regions with asthma susceptibility. This approach might be useful for identifying regions that contribute to both shared and population-specific differences in asthma susceptibility.

Robust estimation of local genetic ancestry in admixed populations using a nonparametric Bayesian approach

We present a new haplotype-based approach for inferring local genetic ancestry of individuals in an admixed population. Most existing approaches for local ancestry estimation ignore the latent genetic relatedness between ancestral populations and treat them as independent. In this article, we exploit such information by building an inheritance model that describes both the ancestral populations and the admixed population jointly in a unified framework. Based on an assumption that the common hypothetical founder haplotypes give rise to both the ancestral and the admixed population haplotypes, we employ an infinite hidden Markov model to characterize each ancestral population and further extend it to generate the admixed population. Through an effective utilization of the population structural information under a principled nonparametric Bayesian framework, the resulting model is significantly less sensitive to the choice and the amount of training data for ancestral populations than state-of-the-art algorithms. We also improve the robustness under deviation from common modeling assumptions by incorporating population-specific scale parameters that allow variable recombination rates in different populations. Our method is applicable to an admixed population from an arbitrary number of ancestral populations and also performs competitively in terms of spurious ancestry proportions under a general multiway admixture assumption. We validate the proposed method by simulation under various admixing scenarios and present empirical analysis results from a worldwide-distributed dataset from the Human Genome Diversity Project.

Genome-wide ancestry association testing identifies a common European variant on 6q14.1 as a risk factor for asthma in African American subjects

BACKGROUND

Genetic variants that contribute to asthma susceptibility might be present at varying frequencies in different populations, which is an important consideration and advantage for performing genetic association studies in admixed populations.

OBJECTIVE

We sought to identify asthma-associated loci in African American subjects.

METHODS

We compared local African and European ancestry estimated from dense single nucleotide polymorphism genotype data in African American adults with asthma and nonasthmatic control subjects. Allelic tests of association were performed within the candidate regions identified, correcting for local European admixture.

RESULTS

We identified a significant ancestry association peak on chromosome 6q. Allelic tests for association within this region identified a single nucleotide polymorphism (rs1361549) on 6q14.1 that was associated with asthma exclusively in African American subjects with local European admixture (odds ratio, 2.2). The risk allele is common in Europe (42% in the HapMap population of Utah residents with Northern and Western European ancestry from the Centre d'Etude du Polymorphisme Humain collection) but absent in West Africa (0% in the HapMap population of Yorubans in Ibadan, Nigeria), suggesting the allele is present in African American subjects because of recent European admixture. We replicated our findings in Puerto Rican subjects and similarly found that the signal of association is largely specific to subjects who are heterozygous for African and non-African ancestry at 6q14.1. However, we found no evidence for association in European American or Puerto Rican subjects in the absence of local African ancestry, suggesting that the association with asthma at rs1361549 is due to an environmental or genetic interaction.

CONCLUSION

We identified a novel asthma-associated locus that is relevant to admixed populations with African ancestry and highlight the importance of considering local ancestry in genetic association studies of admixed populations.

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

When dense markers are available, one can interrogate almost every common variant across the genome via imputation and single nucleotide polymorphism (SNP) test, which has become a routine in current genome-wide association studies (GWASs). As a complement, admixture mapping exploits the long-range linkage disequilibrium (LD) generated by admixture between genetically distinct ancestral populations. It is then questionable whether admixture mapping analysis is still necessary in detecting the disease associated variants in admixed populations. We argue that admixture mapping is able to reduce the burden of massive comparisons in GWASs; it therefore can be a powerful tool to locate the disease variants with substantial allele frequency differences between ancestral populations. In this report we studied a two-stage approach, where candidate regions are defined by conducting admixture mapping at stage 1, and single SNP association tests are followed at stage 2 within the candidate regions defined at stage 1. We first established the genome-wide significance levels corresponding to the criteria to define the candidate regions at stage 1 by simulations. We next compared the power of the two-stage approach with direct association analysis. Our simulations suggest that the two-stage approach can be more powerful than the standard genome-wide association analysis when the allele frequency difference of a causal variant in ancestral populations, is larger than 0.4. Our conclusion is consistent with a theoretical prediction by Risch and Tang ([2006] Am J Hum Genet 79:S254). Surprisingly, our study also suggests that power can be improved when we use less strict criteria to define the candidate regions at stage 1.

African ancestry and its correlation to type 2 diabetes in African Americans: a genetic admixture analysis in three U.S. population cohorts

The risk of type 2 diabetes is approximately 2-fold higher in African Americans than in European Americans even after adjusting for known environmental risk factors, including socioeconomic status (SES), suggesting that genetic factors may explain some of this population difference in disease risk. However, relatively few genetic studies have examined this hypothesis in a large sample of African Americans with and without diabetes. Therefore, we performed an admixture analysis using 2,189 ancestry-informative markers in 7,021 African Americans (2,373 with type 2 diabetes and 4,648 without) from the Atherosclerosis Risk in Communities Study, the Jackson Heart Study, and the Multiethnic Cohort to 1) determine the association of type 2 diabetes and its related quantitative traits with African ancestry controlling for measures of SES and 2) identify genetic loci for type 2 diabetes through a genome-wide admixture mapping scan. The median percentage of African ancestry of diabetic participants was slightly greater than that of non-diabetic participants (study-adjusted difference = 1.6%, P<0.001). The odds ratio for diabetes comparing participants in the highest vs. lowest tertile of African ancestry was 1.33 (95% confidence interval 1.13-1.55), after adjustment for age, sex, study, body mass index (BMI), and SES. Admixture scans identified two potential loci for diabetes at 12p13.31 (LOD = 4.0) and 13q14.3 (Z score = 4.5, P = 6.6 × 10(-6)). In conclusion, genetic ancestry has a significant association with type 2 diabetes above and beyond its association with non-genetic risk factors for type 2 diabetes in African Americans, but no single gene with a major effect is sufficient to explain a large portion of the observed population difference in risk of diabetes. There undoubtedly is a complex interplay among specific genetic loci and non-genetic factors, which may both be associated with overall admixture, leading to the observed ethnic differences in diabetes risk.

Recent advances in obesity: genetics and beyond

The prevalence of obesity, which is a heritable trait that arises from the interactions of multiple genes and lifestyle factors, continues to increase worldwide, causing serious health problems and imposing a substantial economic burden on societies. For the past several years, various genetic epidemiological approaches have been utilized to identify genetic loci for obesity. Recent evidence suggests that development of obesity involves hormones and neurotransmitters (such as leptin, cocaine- and amphetamine-regulated transcript (CART), and ghrelin) that regulate appetite and energy expenditure. These hormones act on specific centers in the brain that regulate the sensations of satiety. Mutations in these hormones or their receptors can lead to obesity. Aberrant circadian rhythms and biochemical pathways in peripheral organs or tissues have also been implicated in the pathology of obesity. More interestingly, increasing evidence indicates a potential relation between obesity and central nervous system disorders (such as cognitive deficits). This paper discusses recent advances in the field of genetics of obesity with an emphasis on several established loci that influence obesity. These recently identified loci may hold the promise to substantially improve our insights into the pathophysiology of obesity and open up new therapeutic strategies to combat growing obesity epidemic facing the human population today.

Characterization of genome-wide association-identified variants for atrial fibrillation in African Americans

BACKGROUND

Despite a greater burden of risk factors, atrial fibrillation (AF) is less common among African Americans than European-descent populations. Genome-wide association studies (GWAS) for AF in European-descent populations have identified three predominant genomic regions associated with increased risk (1q21, 4q25, and 16q22). The contribution of these loci to AF risk in African American is unknown.

METHODOLOGY/PRINCIPAL FINDINGS

We studied 73 African Americans with AF from the Vanderbilt-Meharry AF registry and 71 African American controls, with no history of AF including after cardiac surgery. Tests of association were performed for 148 SNPs across the three regions associated with AF, and 22 SNPs were significantly associated with AF (P<0.05). The SNPs with the strongest associations in African Americans were both different from the index SNPs identified in European-descent populations and independent from the index European-descent population SNPs (r(2)<0.40 in HapMap CEU): 1q21 rs4845396 (odds ratio [OR] 0.30, 95% confidence interval [CI] 0.13-0.67, P = 0.003), 4q25 rs4631108 (OR 3.43, 95% CI 1.59-7.42, P = 0.002), and 16q22 rs16971547 (OR 8.1, 95% CI 1.46-45.4, P = 0.016). Estimates of European ancestry were similar among cases (23.6%) and controls (23.8%). Accordingly, the probability of having two copies of the European derived chromosomes at each region did not differ between cases and controls.

CONCLUSIONS/SIGNIFICANCE

Variable European admixture at known AF loci does not explain decreased AF susceptibility in African Americans. These data support the role of 1q21, 4q25, and 16q22 variants in AF risk for African Americans, although the index SNPs differ from those identified in European-descent populations.

Admixture mapping identifies a locus on 6q25 associated with breast cancer risk in US Latinas

Among US Latinas and Mexican women, those with higher European ancestry have increased risk of breast cancer. We combined an admixture mapping and genome-wide association mapping approach to search for genomic regions that may explain this observation. Latina women with breast cancer (n= 1497) and Latina controls (n= 1272) were genotyped using Affymetrix and Illumina arrays. We inferred locus-specific genetic ancestry and compared the ancestry between cases and controls. We also performed single nucleotide polymorphism (SNP) association analyses in regions of interest. Correction for multiple-hypothesis testing was conducted using permutations (P(corrected)). We identified one region where genetic ancestry was significantly associated with breast cancer risk: 6q25 [odds ratio (OR) per Indigenous American chromosome 0.75, 95% confidence interval (CI): 0.65-0.85, P= 1.1 × 10(-5), P(corrected)= 0.02]. A second region on 11p15 showed a trend towards association (OR per Indigenous American chromosome 0.77, 95% CI: 0.68-0.87, P= 4.3 × 10(-5), P(corrected)= 0.08). In both regions, breast cancer risk decreased with higher Indigenous American ancestry in concordance with observations made on global ancestry. The peak of the 6q25 signal includes the estrogen receptor 1 (ESR1) gene and 5' region, a locus previously implicated in breast cancer. Genome-wide association analysis found that a multi-SNP model explained the admixture signal in both regions. Our results confirm that the association between genetic ancestry and breast cancer risk in US Latinas is partly due to genetic differences between populations of European and Indigenous Americans origin. Fine-mapping within the 6q25 and possibly the 11p15 loci will lead to the discovery of the biologically functional variant/s behind this association.

The arrestin domain-containing 3 protein regulates body mass and energy expenditure

A human genome-wide linkage scan for obesity identified a linkage peak on chromosome 5q13-15. Positional cloning revealed an association of a rare haplotype to high body-mass index (BMI) in males but not females. The risk locus contains a single gene, "arrestin domain-containing 3" (ARRDC3), an uncharacterized α-arrestin. Inactivating Arrdc3 in mice led to a striking resistance to obesity, with greater impact on male mice. Mice with decreased ARRDC3 levels were protected from obesity due to increased energy expenditure through increased activity levels and increased thermogenesis of both brown and white adipose tissues. ARRDC3 interacted directly with β-adrenergic receptors, and loss of ARRDC3 increased the response to β-adrenergic stimulation in isolated adipose tissue. These results demonstrate that ARRDC3 is a gender-sensitive regulator of obesity and energy expenditure and reveal a surprising diversity for arrestin family protein functions.

Relationship between adiposity and admixture in African-American and Hispanic-American women

Objective

To investigate whether differences in admixture in African American (AFA) and Hispanic American (HA) adult women are associated with adiposity and adipose distribution.

Design

The proportion of European, sub– Saharan African and Amerindian admixture was estimated for AFA and HA women in the Women's Heath Initiative using 92 ancestry informative markers. Analyses assessed the relationship between admixture and adiposity indices.

Subjects

11712 AFA and 5088 HA self– identified post– menopausal women.

Results

There was a significant positive association between body mass index (BMI) and African admixture when BMI was considered as a continuous variable, and age, education, physical activity, parity, family income and smoking were included covariates (p < 10^{− 4}). A dichotomous model (upper and lower BMI quartiles) showed that African admixture was associated with a high odds ratio [OR = 3.27 (for 100% admixture compared to 0% admixture), 95% confidence interval (CI) 2.08 – 5.15]. For HA there was no association between BMI and admixture. In contrast, when waist to hip ratio (WHR) was used as a measure of adipose distribution, there was no significant association between WHR and admixture in AFA but there was a strong association in HA (p<10^{− 4}; OR Amerindian admixture = 5.93, CI = 3.52 – 9.97).

Conclusion

These studies show that 1) African admixture is associated with BMI in AFA women; 2) Amerindian admixture is associated with WHR but not BMI in HA women; and 3) it may be important to consider different measurements of adiposity and adipose distribution in different ethnic population groups.

Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

Combined admixture mapping and association analysis identifies a novel blood pressure genetic locus on 5p13: contributions from the CARe consortium

Admixture mapping based on recently admixed populations is a powerful method to detect disease variants with substantial allele frequency differences in ancestral populations. We performed admixture mapping analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP), followed by trait-marker association analysis, in 6303 unrelated African-American participants of the Candidate Gene Association Resource (CARe) consortium. We identified five genomic regions (P< 0.001) harboring genetic variants contributing to inter-individual BP variation. In follow-up association analyses, correcting for all tests performed in this study, three loci were significantly associated with SBP and one significantly associated with DBP (P< 10(-5)). Further analyses suggested that six independent single-nucleotide polymorphisms (SNPs) contributed to the phenotypic variation observed in the admixture mapping analysis. These six SNPs were examined for replication in multiple, large, independent studies of African-Americans [Women's Health Initiative (WHI), Maywood, Genetic Epidemiology Network of Arteriopathy (GENOA) and Howard University Family Study (HUFS)] as well as one native African sample (Nigerian study), with a total replication sample size of 11 882. Meta-analysis of the replication set identified a novel variant (rs7726475) on chromosome 5 between the SUB1 and NPR3 genes, as being associated with SBP and DBP (P< 0.0015 for both); in meta-analyses combining the CARe samples with the replication data, we observed P-values of 4.45 × 10(-7) for SBP and 7.52 × 10(-7) for DBP for rs7726475 that were significant after accounting for all the tests performed. Our study highlights that admixture mapping analysis can help identify genetic variants missed by genome-wide association studies because of drastically reduced number of tests in the whole genome.

Validation of a small set of ancestral informative markers for control of population admixture in African Americans

Confounding due to population stratification is a potential source of concern in population-based genetic association studies, particularly in recently admixed populations such as African Americans. Several methods have been developed to control for population stratification in the context of genome-wide association studies. Because these approaches require thousands of genotypes from genetic markers, they are not well suited to be used in genetic association analyses without genome-wide data. An alternative approach to control for population stratification is to estimate admixture proportions by using ancestral informative markers (AIMs). The authors evaluated whether a relatively small number of AIMs would be sufficient to estimate ancestral proportions in African Americans. They first estimated European admixture proportions in 1,757 subjects from the Black Women's Health Study (1995-2009) by genotyping an admixture panel of 1,373 AIMs; they then compared these results with those obtained using smaller sets of AIMs. The authors found that just 30 AIMs are needed to obtain very high correlation of estimates with the entire set (r = 0.89; P < 0.0001). A set of 200 AIMs gave an almost perfect correlation with the entire set (r = 0.98; P < 0.0001). These results show that a small number of AIMs are sufficiently precise to estimate European admixture in African Americans.

Dating the age of admixture via wavelet transform analysis of genome-wide data

We describe a PCA-based genome scan approach to analyze genome-wide admixture structure, and introduce wavelet transform analysis as a method for estimating the time of admixture. We test the wavelet transform method with simulations and apply it to genome-wide SNP data from eight admixed human populations. The wavelet transform method offers better resolution than existing methods for dating admixture, and can be applied to either SNP or sequence data from humans or other species.