Design and analysis of admixture mapping studies

Social determinants of health but not global genetic ancestry predict dementia prevalence in Latin America

INTRODUCTION

Leveraging the nonmonolithic structure of Latin America, which represents a large variability in social determinants of health (SDoH) and high levels of genetic admixture, we aim to evaluate the relative contributions of SDoH and genetic ancestry in predicting dementia prevalence in Latin American populations.

METHODS

Community-dwelling participants aged 65 and older (N = 3808) from Cuba, Dominican Republic, Mexico, and Peru completed the 10/66 protocol assessments. Dementia was diagnosed using the cross-culturally validated 10/66 algorithm. Multivariate linear regression models adjusted for SDoH were used in the main analysis. This study used cross-sectional data from the 1066 population-based study.

RESULTS

Individuals with higher proportions of Native American (>70%) and African American (>70%) ancestry were more likely to exhibit factors contributing to worse SDoH, such as lower educational levels (p < 0.001), lower socioeconomic status (p < 0.001), and higher frequency of vascular risk factors (p < 0.001). After adjusting for measures of SDoH, there was no association between ancestry proportion and dementia probability, and ancestry proportions no longer significantly accounted for the variance in cognitive performance (African predominant p = 0.31 [-0.19, 0.59] and Native predominant p = 0.74 [-0.24, 0.33]).

DISCUSSION

The findings suggest that social and environmental factors play a more crucial role than genetic ancestry in predicting dementia prevalence in Latin American populations. This underscores the need for public health strategies and policies that address these social determinants to effectively reduce dementia risk in these communities.

HIGHLIGHTS

Countries in Latin America express a large variability in social determinants of health and levels of admixture. After adjustment for downstream societal factors linked to SDoH, genetic ancestry shows no link to dementia. Population ancestry profiles alone do not influence cognitive performance. SDoH are key drivers of racial disparities in dementia and cognitive performance.

Understanding and applying gene-environment interactions: a guide for nutrition professionals with an emphasis on integration in African research settings

Noncommunicable diseases (NCDs) are influenced by the interplay between genetics and environmental exposures, particularly diet. However, many healthcare professionals, including nutritionists and dietitians, have limited genetic background and, therefore, they may lack understanding of gene-environment interactions (GxEs) studies. Even researchers deeply involved in nutrition studies, but with a focus elsewhere, can struggle to interpret, evaluate, and conduct GxE studies. There is an urgent need to study African populations that bear a heavy burden of NCDs, demonstrate unique genetic variability, and have cultural practices resulting in distinctive environmental exposures compared with Europeans or Americans, who are studied more. Although diverse and rapidly changing environments, as well as the high genetic variability of Africans and difference in linkage disequilibrium (ie, certain gene variants are inherited together more often than expected by chance), provide unparalleled potential to investigate the omics fields, only a small percentage of studies come from Africa. Furthermore, research evidence lags behind the practices of companies offering genetic testing for personalized medicine and nutrition. We need to generate more evidence on GxEs that also considers continental African populations to be able to prevent unethical practices and enable tailored treatments. This review aims to introduce nutrition professionals to genetics terms and valid methods to investigate GxEs and their challenges, and proposes ways to improve quality and reproducibility. The review also provides insight into the potential contributions of nutrigenetics and nutrigenomics to the healthcare sphere, addresses direct-to-consumer genetic testing, and concludes by offering insights into the field's future, including advanced technologies like artificial intelligence and machine learning.

IBD sharing patterns as intra-breed admixture indicators in small ruminants

In this study, we investigated how IBD patterns shared between individuals of the same breed could be informative of its admixture level, with the underlying assumption that the most admixed breeds, i.e. the least genetically isolated, should have a much more fragmented genome. We considered 111 goat breeds (i.e. 2501 individuals) and 156 sheep breeds (i.e. 3304 individuals) from Europe, Africa and Asia, for which beadchip SNP genotypes had been performed. We inferred the breed's level of admixture from: (i) the proportion of the genome shared by breed's members (i.e. "genetic integrity level" assessed from ADMIXTURE software analyses), and (ii) the "AV index" (calculated from Reynolds' genetic distances), used as a proxy for the "genetic distinctiveness". In both goat and sheep datasets, the statistical analyses (comparison of means, Spearman correlations, LM and GAM models) revealed that the most genetically isolated breeds, also showed IBD profiles made up of more shared IBD segments, which were also longer. These results pave the way for further research that could lead to the development of admixture indicators, based on the characterization of intra-breed shared IBD segments, particularly effective as they would be independent of the knowledge of the whole genetic landscape in which the breeds evolve. Finally, by highlighting the fragmentation experienced by the genomes subjected to crossbreeding carried out over the last few generations, the study reminds us of the need to preserve local breeds and the integrity of their adaptive architectures that have been shaped over the centuries.

Phase-free local ancestry inference mitigates the impact of switch errors on phase-based methods

Local ancestry inference (LAI) is an indispensable component of a variety of analyses in medical and population genetics, from admixture mapping to characterizing demographic history. However, the accuracy of LAI depends on a number of factors such as phase quality (for phase-based LAI methods), time since admixture of the population under study, and other factors. Here we present an empirical analysis of four LAI methods using simulated individuals of mixed African and European ancestry, examining the impact of variable phase quality and a range of demographic scenarios. We found that regardless of phasing options, calls from LAI methods that operate on unphased genotypes (phase-free LAI) have 2.6-4.6% higher Pearson correlation with the ground truth than methods that operate on phased genotypes (phase-based LAI). Applying the TRACTOR phase-correction algorithm led to modest improvements in phase-based LAI, but despite this, the Pearson correlation of phase-free LAI remained 2.4-3.8% higher than phase-corrected phase-based approaches (considering the best performing methods in each category). Phase-free and phase-based LAI accuracy differences can dramatically impact downstream analyses: estimates of the time since admixture using phase-based LAI tracts are upwardly biased by ≈10 generations using our highest quality phased data but have virtually no bias using phase-free LAI calls. Our study underscores the strong dependence of phase-based LAI accuracy on phase quality and highlights the merits of LAI approaches that analyze unphased genetic data.

Universal genome-wide association studies: Powerful joint ancestry and association testing

The vast majority of human populations and individuals have mixed ancestry. Consequently, adjustment for locus-specific ancestry is essential for genetic association studies. To empower association studies for all populations, it is necessary to integrate effects of locus-specific ancestry and genotype. We developed a joint test of ancestry and association that can be performed with summary statistics, is independent of study design, can take advantage of locus-specific ancestry effects to boost power in association testing, and can utilize association effects to fine map admixture peaks. We illustrate the test using the association between serum triglycerides and LPL. By combining data from African Americans, European Americans, and West Africans, we identify three conditionally independent variants with varying amounts of ancestrally differentiated allele frequencies. Using out-of-sample data, we demonstrate improved prediction achievable by accounting for multiple causal variants and locus-specific ancestry effects at a single locus.

Strategies for the Genomic Analysis of Admixed Populations

Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.

Creating Opportunities to Eliminate Disparities in Lung Cancer Outcomes: A Call for Diverse Study Populations. Comment on Kohan et al. Disparity and Diversity in NSCLC Imaging and Genomics: Evaluation of a Mature, Multicenter Database. Cancers 2023, 15, 2096

We read with extensive interest the recently published paper, by Kohan et al., "Disparity and Diversity in NSCLC Imaging and Genomics: Evaluation of a Mature, Multicenter Database" [...].

Overview of Admixture Mapping

Admixture mapping is a powerful method of gene mapping for diseases or traits that show differential risk by ancestry. Admixture mapping has been applied most often to Americans who trace ancestry to various combinations of Native Americans, Europeans, and West Africans. Recent developments in admixture mapping include improvements in the methods and reference data needed to make inferences about ancestry as well as extensions of the mapping approach in the framework of linear mixed models. This overview outlines the key concepts of admixture mapping. It describes approaches for inferring local ancestry and provides strategies for performing admixture mapping depending on the study design. Finally, linkage analysis, association analysis, and admixture mapping are compared, with an emphasis on integrating admixture mapping and association testing. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

Apolipoprotein E (APOE) genotype, dementia, and memory performance among Caribbean Hispanic versus US populations

INTRODUCTION

Apolipoprotein E (APOE) is considered the major susceptibility gene for developing Alzheimer's disease. However, the strength of this risk factor is not well established across diverse Hispanic populations.

METHODS

We investigated the associations among APOE genotype, dementia prevalence, and memory performance (immediate and delayed recall scores) in Caribbean Hispanics (CH), African Americans (AA), Hispanic Americans (HA) and non-Hispanic White Americans (NHW). Multivariable logistic regressions and negative binomial regressions were used to examine these associations by subsample.

RESULTS

Our final dataset included 13,516 participants (5198 men, 8318 women) across all subsamples, with a mean age of 74.8 years. Prevalence of APOE ε4 allele was similar in CHs, HAs, and NHWs (21.8%-25.4%), but was substantially higher in AAs (33.6%; P < 0.001). APOE ε4 carriers had higher dementia prevalence across all groups.

DISCUSSION

APOE ε4 was similarly associated with increased relative risk of dementia and lower memory performance in all subsamples.

A central limit theorem concerning uncertainty in estimates of individual admixture

The concept of individual admixture (IA) assumes that the genome of individuals is composed of alleles inherited from K ancestral populations. Each copy of each allele has the same chance q_k to originate from population k, and together with the allele frequencies p in all populations at all M markers, comprises the admixture model. Here, we assume a supervised scheme, i.e. allele frequencies p are given through a reference database of size N, and q is estimated via maximum likelihood for a single sample. We study laws of large numbers and central limit theorems describing effects of finiteness of both, M and N, on the estimate of q. We recall results for the effect of finite M, and provide a central limit theorem for the effect of finite N, introduce a new way to express the uncertainty in estimates in standard barplots, give simulation results, and discuss applications in forensic genetics.

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.

An Overview of Strategies for Detecting Genotype-Phenotype Associations Across Ancestrally Diverse Populations

Genome-wide association studies (GWAS) have been very successful at identifying genetic variants influencing a large number of traits. Although the great majority of these studies have been performed in European-descent individuals, it has been recognised that including populations with differing ancestries enhances the potential for identifying causal SNPs due to their differing patterns of linkage disequilibrium. However, when individuals from distinct ethnicities are included in a GWAS, it is necessary to implement a number of control steps to ensure that the identified associations are real genotype-phenotype relationships. In this Review, we discuss the analyses that are required when performing multi-ethnic studies, including methods for determining ancestry at the global and local level for sample exclusion, controlling for ancestry in association testing, and post-GWAS interrogation methods such as genomic control and meta-analysis. We hope that this overview provides a primer for those researchers interested in including distinct populations in their studies.

Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases

Admixed populations arise when two or more ancestral populations interbreed. As a result of this admixture, the genome of admixed populations is defined by tracts of variable size inherited from these parental groups and has particular genetic features that provide valuable information about their demographic history. Diverse methods can be used to derive the ancestry apportionment of admixed individuals, and such inferences can be leveraged for the discovery of genetic loci associated with diseases and traits, therefore having important biomedical implications. In this review article, we summarize the most common methods of global and local genetic ancestry estimation and discuss the use of admixture mapping studies in human diseases.

Race, genetic admixture and cognitive performance in the Cuban population

BACKGROUND

Population aging will lead to a dramatic increase in dementia prevalence, which will disproportionally affect racial minorities. The presence of racial differences in dementia prevalence has been widely reported in United States, but there are no relevant studies on this topic in low-middle income countries (LMIC).

METHODS

In a cross-sectional survey, 2,944 older Cubans were recruited at a community-based level aimed to identify the effects of self-identified race and genetic admixture on cognitive performance. Dementia diagnosis was established using 10/66 Dementia and DSM-IV criteria. APOE-ε4 genotype was determined in 2,511 (85%) and genetic admixture was completed for all dementia cases and in a randomly selected sample of cognitive healthy participants (218 dementia cases and 367 participants without dementia).

RESULTS

The overall prevalence of dementia was 8.7%, without large or statistically significant differences on dementia prevalence (p=0.12) by self-identified race. Mean cognitive scores were similar across racial groups (p=0.46). After controlling for age, sex and education, greater proportion of African ancestry was not associated with cognitive performance (p=0.17).

CONCLUSIONS

We found no evidence of an independent effect of self-identified race and/or population ancestry on dementia prevalence or cognitive performance. This suggests that observed differences in dementia prevalence among diverse populations may be driven primarily by social determinants of health.

Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power

Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.

Race, Ancestry, and Vitamin D Metabolism: The Multi-Ethnic Study of Atherosclerosis

CONTEXT

A comprehensive characterization of racial/ethnic variations in vitamin D metabolism markers may improve our understanding of differences in bone and mineral homeostasis and the risk of vitamin D-related diseases.

OBJECTIVE

Describe racial/ethnic differences in vitamin D metabolism markers and their associations with genetic ancestry.

DESIGN, SETTING, PARTICIPANTS

In a cross-sectional study within the Multi-Ethnic Study of Atherosclerosis (MESA), we compared a comprehensive panel of vitamin D metabolism markers across self-reported racial/ethnic groups of Black (N = 1759), White (N = 2507), Chinese (N = 788), and Hispanic (N = 1411). We evaluated associations of proportion African and European ancestry with this panel of markers in Black and Hispanic participants using ancestry informative markers. Latent class analysis evaluated associations between patterns of vitamin D measurements with race/ethnicity.

RESULTS

Compared with Black participants, White participants had significantly higher serum concentrations of 25-hydroxyvitamin D and fibroblast growth factor-23; lower concentrations of parathyroid hormone and 1,25-dihydroxyvitamin D; circulating vitamin D metabolite ratios suggesting lower CYP27B1 and higher CYP24A1 activity; higher urinary concentrations of calcium and phosphorus with higher urinary fractional excretion of phosphorus; and differences in vitamin D binding globulin haplotypes. Higher percent European ancestry was associated with higher 25-hydroxyvitamin D and lower parathyroid hormone concentrations among Black and Hispanic participants. Latent classes defined by vitamin D measurements reflected these patterns and differed significantly by race/ethnicity and ancestry.

CONCLUSIONS

Markers of vitamin D metabolism vary significantly by race/ethnicity, may serve to maintain bone and mineral homeostasis across ranges of 25-hydroxyvitamin D production, and be attributable, at least partly, to genetic ancestry.

A comprehensive survey of models for dissecting local ancestry deconvolution in human genome

Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods.

Versatile simulations of admixture and accurate local ancestry inference with mixnmatch and ancestryinfer

It has become clear that hybridization between species is much more common than previously recognized. As a result, we now know that the genomes of many modern species, including our own, are a patchwork of regions derived from past hybridization events. Increasingly researchers are interested in disentangling which regions of the genome originated from each parental species using local ancestry inference methods. Due to the diverse effects of admixture, this interest is shared across disparate fields, from human genetics to research in ecology and evolutionary biology. However, local ancestry inference methods are sensitive to a range of biological and technical parameters which can impact accuracy. Here we present paired simulation and ancestry inference pipelines, mixnmatch and ancestryinfer, to help researchers plan and execute local ancestry inference studies. mixnmatch can simulate arbitrarily complex demographic histories in the parental and hybrid populations, selection on hybrids, and technical variables such as coverage and contamination. ancestryinfer takes as input sequencing reads from simulated or real individuals, and implements an efficient local ancestry inference pipeline. We perform a series of simulations with mixnmatch to pinpoint factors that influence accuracy in local ancestry inference and highlight useful features of the two pipelines. mixnmatch is a powerful tool for simulations of hybridization while ancestryinfer facilitates local ancestry inference on real or simulated data.

Prospective avenues for human population genomics and disease mapping in southern Africa

Population substructure within human populations is globally evident and a well-known confounding factor in many genetic studies. In contrast, admixture mapping exploits population stratification to detect genotype-phenotype correlations in admixed populations. Southern Africa has untapped potential for disease mapping of ancestry-specific disease risk alleles due to the distinct genetic diversity in its populations compared to other populations worldwide. This diversity contributes to a number of phenotypes, including ancestry-specific disease risk and response to pathogens. Although the 1000 Genomes Project significantly improved our understanding of genetic variation globally, southern African populations are still severely underrepresented in biomedical and human genetic studies due to insufficient large-scale publicly available data. In addition to a lack of genetic data in public repositories, existing software, algorithms and resources used for imputation and phasing of genotypic data (amongst others) are largely ineffective for populations with a complex genetic architecture such as that seen in southern Africa. This review article, therefore, aims to summarise the current limitations of conducting genetic studies on populations with a complex genetic architecture to identify potential areas for further research and development.

Cardiac autonomic activity during sleep in high-altitude resident children compared with lowland residents

Study Objectives

We aimed to characterize heart-rate variability (HRV) during sleep in Andean children native to high altitude (HA) compared with age, gender, and genetic ancestry-similar low-altitude (LA) children. We hypothesized that the hypoxic burden of sleep at HA could induce variation in HRV. As children have otherwise healthy cardiovascular systems, such alterations could provide early markers of later cardiovascular disease.

Methods

Twenty-six LA (14F) and 18 HA (8F) children underwent a single night of attended polysomnography. Sleep parameters and HRV indices were measured. Linear mixed models were used to assess HRV differences across sleep stage and altitude group.

Results

All children showed marked fluctuations in HRV parameters across sleep stages, with higher vagal activity during nonrapid eye movement sleep and greater variability of the heart rate during rapid eye movement (REM). Moreover, HA children showed higher very low-frequency HRV in REM sleep and, after adjusting for heart rate, higher low-to-high frequency ratio in REM sleep compared with children living at lower altitude.

Conclusions

We confirmed previous findings of a stage-dependent modulation of HRV in Andean children living at both HA and LA. Moreover, we showed subtle alteration of HRV in sleep in HA children, with intriguing differences in the very low-frequency domain during REM sleep. Whether these differences are the results of an adaptation to high-altitude living, or an indirect effect of differences in oxyhemoglobin saturation remains unclear, and further research is required to address these questions.

Gut microbiota composition explains more variance in the host cardiometabolic risk than genetic ancestry

Cardiometabolic affections greatly contribute to the global burden of disease. The susceptibility to obesity, cardiovascular disease, and type-2 diabetes, conditions that add to the cardiometabolic syndrome (CMS), was associated with the ancestral genetic composition and gut microbiota. Studies explicitly testing associations between genetic ancestry and gut microbes are growing. We here examined whether the host genetic ancestry was associated with gut microbiota composition, and distinguished the effects of genetic ancestry and non-genetic factors on human cardiometabolic health. We performed a cross-sectional study with 441 community-dwelling Colombian mestizos from five cities spanning the Andes, Pacific, and Caribbean coasts. We characterized the host genetic ancestry by genotyping 40 ancestry informative markers; characterized gut microbiota through 16S rRNA gene sequencing; assessed diet intake, physical activity, cigarette, and medicament consumption; and measured cardiometabolic outcomes that allowed calculating a CMS risk scale. On average, each individual of our cohort was 67 ± 6% European, 21 ± 5% Native American and 12 ± 5% African. Multivariable-adjusted generalized linear models showed that individuals with higher Native American and African ancestries had increased fasting insulin, body mass index and CMS risk, as assessed by the CMS risk scale. Furthermore, we identified 21 OTUs associated to the host genetic ancestry and 20 to cardiometabolic health. While we highlight novel associations between genetic ancestry and gut microbiota, we found that the effect of intestinal microbes was more likely to explain the variance in CMS risk scale than the contributions of European, Native American and African genetic backgrounds.

The three-hybrid genetic composition of an Ecuadorian population using AIMs-InDels compared with autosomes, mitochondrial DNA and Y chromosome data

The history of Ecuador was marked by the arrival of Europeans with Africans, resulting in the mixture of Native Americans with Africans and Europeans. The present study contributes to the knowledge of the Ecuadorian mestizo population by offering information about ancestry and ethnic heterogeneity. Forty-six AIM-InDels (Ancestry Informative Insertion/Deletion Markers) were used to obtain information on 240 Ecuadorian individuals from three regions (Amazonia, the Highlands, and the Coast). As a result, the population involved a significant contribution from Native Americans (values up to 51%), followed by Europeans (values up to 33%) and Africans (values up to 13%). Furthermore, we compared the data obtained with nine previously reported scientific articles on autosomal, mitochondrial DNA and Y chromosomes. The admixture results correspond to Ecuador's historical background and vary slightly between regions.

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.

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.

Admixture mapping and fine-mapping of type 2 diabetes susceptibility loci in African American women

African American women are disproportionately affected by type 2 diabetes. Genetic factors may explain part of the excess risk. More than 100 genetic variants have been associated with risk of type 2 diabetes, but most studies have been conducted in white populations. Two genome-wide association studies (GWAS) in African Americans have identified three novel genetic variants only. We conducted admixture mapping using 2,918 ancestral informative markers in 2,632 cases of type 2 diabetes and 2,596 controls nested in the ongoing Black Women’s Health Study cohort, with the goal of identifying genomic loci with local African ancestry associated with type 2 diabetes. In addition, we performed replication analysis of 71 previously identified index SNPs, and fine-mapped those genetic loci to identify better or new genetic variants associated with type 2 diabetes in African Americans. We found that individual African ancestry was associated with higher risk of type 2 diabetes. In addition, we identified two genomic regions, 3q26 and 12q23, with excess of African ancestry associated with higher risk of type 2 diabetes. Lastly, we replicated 8 out of 71 index SNPs from previous GWAS, including, for the first time in African Americans, the X-linked rs5945326 SNP near the DUSP9 gene. In addition, our fine-mapping efforts suggest independent signals at five loci. Our detailed analysis identified two genomic regions associated with risk of type 2 diabetes, and showed that many genetic risk variants are shared across ancestries.

APOL1 risk variants and kidney disease: what we know so far

There are striking differences in chronic kidney disease between Caucasians and African descendants. It was widely accepted that this occurred due to socioeconomic factors, but recent studies show that apolipoprotein L-1 (APOL1) gene variants are strongly associated with focal segmental glomerulosclerosis, HIV-associated nephropathy, hypertensive nephrosclerosis, and lupus nephritis in the African American population. These variants made their way to South America trough intercontinental slave traffic and conferred an evolutionary advantage to the carries by protecting against forms of trypanosomiasis, but at the expense of an increased risk of kidney disease. The effect of the variants does not seem to be related to their serum concentration, but rather to local action on the podocytes. Risk variants are also important in renal transplantation, since grafts from donors with risk variants present worse survival.

Admixture mapping and fine-mapping of birth weight loci in the Black Women's Health Study

Several genome-wide association studies (GWAS) have identified genetic variants associated with birth weight. To date, however, most GWAS of birth weight have focused primarily on European ancestry samples even though prevalence of low birth weight is higher among African-Americans. We conducted admixture mapping using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study, with the goal of identifying novel genomic regions where local African ancestry is associated with birth weight. In addition, we performed a replication analysis of 11 previously identified index single nucleotide polymorphisms (SNPs), and fine-mapped those genetic loci to identify better or new genetic variants associated with birth weight in African-Americans. We found that high African ancestry at 12q14 was associated with low birth weight, and we identified multiple independent birth weight-lowering variants in this genomic region. We replicated the association of a previous GWAS SNP in ADRB1 and our fine-mapping efforts suggested the presence of new birth weight-associated variants in ADRB1, HMGA2, and SLC2A4. Further studies are needed to determine whether birth weight-associated loci can in part explain race-associated birth weight disparities.

A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus

Systemic lupus erythematosus (SLE or lupus) (OMIM: 152700) is a chronic autoimmune disease with debilitating inflammation that affects multiple organ systems. The STAT1-STAT4 locus is one of the first and most highly replicated genetic loci associated with lupus risk. We performed a fine-mapping study to identify plausible causal variants within the STAT1-STAT4 locus associated with increased lupus disease risk. Using complementary frequentist and Bayesian approaches in trans-ancestral Discovery and Replication cohorts, we found one variant whose association with lupus risk is supported across ancestries in both the Discovery and Replication cohorts: rs11889341. In B cell lines from patients with lupus and healthy controls, the lupus risk allele of rs11889341 was associated with increased STAT1 expression. We demonstrated that the transcription factor HMGA1, a member of the HMG transcription factor family with an AT-hook DNA-binding domain, has enriched binding to the risk allele compared with the non-risk allele of rs11889341. We identified a genotype-dependent repressive element in the DNA within the intron of STAT4 surrounding rs11889341. Consistent with expression quantitative trait locus (eQTL) analysis, the lupus risk allele of rs11889341 decreased the activity of this putative repressor. Altogether, we present a plausible molecular mechanism for increased lupus risk at the STAT1-STAT4 locus in which the risk allele of rs11889341, the most probable causal variant, leads to elevated STAT1 expression in B cells due to decreased repressor activity mediated by increased binding of HMGA1.

Genetic Ancestry and Susceptibility to Late-Onset Alzheimer Disease (LOAD) in the Admixed Colombian Population

INTRODUCTION

Differences in the prevalence of dementia among populations and in the effect of apolipoprotein E (APOE) on the emergence of Alzheimer disease (AD), which is the main type of dementia, have been reported.

METHODS

This study estimated the ancestry of a group of individuals with late-onset Alzheimer disease (LOAD) (N=280) and established whether there were any differences when compared with a control group (N=357) in a sample of the Colombian population.

RESULTS

When the analyses were adjusted for known risk factors such as age, sex, presence of APOE[Latin Small Letter Open E]4, socioeconomic status, educational attainment, and place of birth, African ancestry was associated with an increased LOAD risk (odds ratio: 1.55; 95% confidence interval, 1.09-2.03; P=0.029), whereas Native American ancestry was associated with lower risk (odds ratio: 0.75; 95% confidence interval, 0.61-0.98; P=0.046), for every 10% increase in ancestry. In addition, there were significant differences in the proportion of Native American ancestry between carriers and noncarriers of the APOE[Latin Small Letter Open E]4 allele (Mann-Whitney U test, P=0.047), with noncarriers having higher mean Native American ancestry when compared with carriers.

CONCLUSIONS

Our results are consistent with the presence of variants of African origin in the genome of the Colombian population and different from APOE[Latin Small Letter Open E]4 that represents a risk factor for the development of LOAD, whereas variants of Native American origin may be conferring protection. However, unknown environmental factors or epigenetic differences among continental groups could also explain the observed associations.

Linking genotype to phenotype in a changing ocean: inferring the genomic architecture of a blue mussel stress response with genome-wide association

A key component to understanding the evolutionary response to a changing climate is linking underlying genetic variation to phenotypic variation in stress response. Here, we use a genome-wide association approach (GWAS) to understand the genetic architecture of calcification rates under simulated climate stress. We take advantage of the genomic gradient across the blue mussel hybrid zone (Mytilus edulis and Mytilus trossulus) in the Gulf of Maine (GOM) to link genetic variation with variance in calcification rates in response to simulated climate change. Falling calcium carbonate saturation states are predicted to negatively impact many marine organisms that build calcium carbonate shells - like blue mussels. We sampled wild mussels and measured net calcification phenotypes after exposing mussels to a 'climate change' common garden, where we raised temperature by 3°C, decreased pH by 0.2 units and limited food supply by filtering out planktonic particles >5 μm, compared to ambient GOM conditions in the summer. This climate change exposure greatly increased phenotypic variation in net calcification rates compared to ambient conditions. We then used regression models to link the phenotypic variation with over 170 000 single nucleotide polymorphism loci (SNPs) generated by genotype by sequencing to identify genomic locations associated with calcification phenotype, and estimate heritability and architecture of the trait. We identified at least one of potentially 2-10 genomic regions responsible for 30% of the phenotypic variation in calcification rates that are potential targets of natural selection by climate change. Our simulations suggest a power of 13.7% with our study's average effective sample size of 118 individuals and rare alleles, but a power of >90% when effective sample size is 900.

Admixture mapping of uterine fibroid size and number in African American women

OBJECTIVE

To evaluate the relationship between genetic ancestry and uterine fibroid characteristics.

DESIGN

Cross-sectional study.

SETTING

Not applicable.

PATIENT(S)

A total of 609 African American participants with image- or surgery-confirmed fibroids in a biorepository at Vanderbilt University electronic health record biorepository and the Coronary Artery Risk Development in Young Adults studies were included.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Outcome measures include fibroid number (single vs. multiple), volume of largest fibroid, and largest fibroid dimension of all fibroid measurements.

RESULT(S)

Global ancestry meta-analyses revealed a significant inverse association between percentage of European ancestry and risk of multiple fibroids (odds ratio: 0.78; 95% confidence interval 0.66, 0.93; P=6.05 × 10-3). Local ancestry meta-analyses revealed five suggestive (P<4.80 × 10-3) admixture mapping peaks in 2q14.3-2q21.1, 3p14.2-3p14.1, 7q32.2-7q33, 10q21.1, 14q24.2-14q24.3, for number of fibroids and one suggestive admixture mapping peak (P<1.97 × 10-3) in 10q24.1-10q24.32 for volume of largest fibroid. Single variant association meta-analyses of the strongest associated region from admixture mapping of fibroid number (10q21.1) revealed a strong association at single nucleotide polymorphism variant rs12219990 (odds ratio: 0.41; 95% confidence interval 0.28, 0.60; P=3.82 × 10-6) that was significant after correction for multiple testing.

CONCLUSION(S)

Increasing African ancestry is associated with multiple fibroids but not with fibroid size. Local ancestry analyses identified several novel genomic regions not previously associated with fibroid number and increasing volume. Future studies are needed to explore the genetic impact that ancestry plays into the development of fibroid characteristics.

Genomic regions associated with susceptibility to Barrett's esophagus and esophageal adenocarcinoma in African Americans: The cross BETRNet admixture study

Background

Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) are far more prevalent in European Americans than in African Americans. Hypothesizing that this racial disparity in prevalence might represent a genetic susceptibility, we used an admixture mapping approach to interrogate disease association with genomic differences between European and African ancestry.

Methods

Formalin fixed paraffin embedded samples were identified from 54 African Americans with BE or EAC through review of surgical pathology databases at participating Barrett’s Esophagus Translational Research Network (BETRNet) institutions. DNA was extracted from normal tissue, and genotyped on the Illumina OmniQuad SNP chip. Case-only admixture mapping analysis was performed on the data from both all 54 cases and also on a subset of 28 cases with high genotyping quality. Haplotype phases were inferred with Beagle 3.3.2, and local African and European ancestries were inferred with SABER plus. Disease association was tested by estimating and testing excess European ancestry and contrasting it to excess African ancestry.

Results

Both datasets, the 54 cases and the 28 cases, identified two admixture regions. An association of excess European ancestry on chromosome 11p reached a 5% genome-wide significance threshold, corresponding to -log₁₀(P) = 4.28. A second peak on chromosome 8q reached -log₁₀(P) = 2.73. The converse analysis examining excess African ancestry found no genetic regions with significant excess African ancestry associated with BE and EAC. On average, the regions on chromosomes 8q and 11p showed excess European ancestry of 15% and 20%, respectively.

Conclusions

Chromosomal regions on 11p15 and 8q22-24 are associated with excess European ancestry in African Americans with BE and EAC. Because GWAS have not reported any variants in these two regions, low frequency and/or rare disease associated variants that confer susceptibility to developing BE and EAC may be driving the observed European ancestry association evidence.

Population Stratification in Genetic Association Studies

Population stratification (PS) is a primary consideration in studies of genetic determinants of human traits. Failure to control for PS may lead to confounding, causing a study to fail for lack of significant results, or resources to be wasted following false-positive signals. Here, historical and current approaches for addressing PS when performing genetic association studies in human populations are reviewed. Methods for detecting the presence of PS, including global and local ancestry methods, are described. Also described are approaches for accounting for PS when calculating association statistics, such that measures of association are not confounded. Many traits are being examined for the first time in minority populations, which may inherently feature PS. © 2017 by John Wiley & Sons, Inc.

Estimating Allele Frequencies

Methods of estimating allele frequencies from data on unrelated and related individuals are described in this chapter. For samples of unrelated individuals with simple codominant markers, the natural estimators of allele frequencies can be used. For genetic data on related individuals, maximum likelihood estimation (MLE) can be applied to compute allele frequencies. Factors that influence allele frequencies in populations are also explained.

Overview of Admixture Mapping

Admixture mapping is a powerful method of gene mapping for diseases or traits that show differential risk by ancestry. Admixture mapping has been applied most often to Americans who trace ancestry to various combinations of Native Americans, Europeans, and West Africans. Recent developments in admixture mapping include improvements in methods and the reference data needed to make inferences about ancestry, as well as extensions of the mapping approach in the framework of linear mixed models. In this unit, the key concepts of admixture mapping are outlined. Several approaches for inferring local ancestry are described, and strategies for performing admixture mapping depending on the study design are provided. Finally, comparisons and contrasts between linkage analysis, association analysis, and admixture mapping are provided, with an emphasis on integrating admixture mapping and association testing. © 2017 by John Wiley & Sons, Inc.

Examining for an association between candidate gene polymorphisms in the metabolic syndrome components on excess weight and adiposity measures in youth: a cross-sectional study

Background

A polymorphism in a gene may exert its effects on multiple phenotypes. The aim of this study is to explore the association of 10 metabolic syndrome candidate genes with excess weight and adiposity and evaluate the effect of perinatal and socioeconomic factors on these associations.

Methods

The anthropometry, socioeconomic and perinatal conditions and 10 polymorphisms were evaluated in 1081 young people between 10 and 18 years old. Genotypic associations were calculated using logistic and linear models adjusted by age, gender, and pubertal maturation, and a genetic risk score (GRS) was calculated by summing the number of effect alleles.

Results

We found that AGT-rs699 and the IRS2-rs1805097 variants were significantly associated with excess weight, OR = 1.25 (CI 95% 1.01–1.54; p = 0.034); OR = 0.77 (CI 95% 0.62–0.96; p = 0.022), respectively. AGT-rs699 and FTO-rs17817449 variants were significantly and directly associated with body mass index (BMI) (p = 0.036 and p = 0.031), while IRS2-rs1805097 and UCP3-rs1800849 were significantly and negatively associated with BMI and waist circumference, correspondingly. Each additional effect allele in GRS was associated with an increase of 0.020 log(BMI) (p = 0.004). No effects from the socioeconomic and perinatal factors evaluated on the association of the candidate genes with the phenotypes were detected.

Conclusions

Our observation suggests that AGT-rs699 and FTO-rs17817449 variants may contribute to the risk development of excess weight and an increase in the BMI, while IRS2-rs1805097 showed a protector effect; in addition, UCP3- rs1800849 showed a decreasing waist circumference. Socioeconomic and perinatal factors had no effect on the associations of the candidate gene.

Electronic supplementary material

The online version of this article (doi:10.1186/s12263-017-0567-1) contains supplementary material, which is available to authorized users.

Joint genotype- and ancestry-based genome-wide association studies in admixed populations

In genome-wide association studies (GWAS) genetic loci that influence complex traits are localized by inspecting associations between genotypes of genetic markers and the values of the trait of interest. On the other hand, admixture mapping, which is performed in case of populations consisting of a recent mix of two ancestral groups, relies on the ancestry information at each locus (locus-specific ancestry). Recently it has been proposed to jointly model genotype and locus-specific ancestry within the framework of single marker tests. Here, we extend this approach for population-based GWAS in the direction of multimarker models. A modified version of the Bayesian information criterion is developed for building a multilocus model that accounts for the differential correlation structure due to linkage disequilibrium (LD) and admixture LD. Simulation studies and a real data example illustrate the advantages of this new approach compared to single-marker analysis or modern model selection strategies based on separately analyzing genotype and ancestry data, as well as to single-marker analysis combining genotypic and ancestry information. Depending on the signal strength, our procedure automatically chooses whether genotypic or locus-specific ancestry markers are added to the model. This results in a good compromise between the power to detect causal mutations and the precision of their localization. The proposed method has been implemented in R and is available at http://www.math.uni.wroc.pl/~mbogdan/admixtures/.

Polygenic risk assessment reveals pleiotropy between sarcoidosis and inflammatory disorders in the context of genetic ancestry

Sarcoidosis is a complex disease of unknown etiology characterized by the presence of granulomatous inflammation. Though various immune system pathways have been implicated in disease, the relationship between the genetic determinants of sarcoidosis and other inflammatory disorders has not been characterized. Herein, we examined the degree of genetic pleiotropy common to sarcoidosis and other inflammatory disorders to identify shared pathways and disease systems pertinent to sarcoidosis onset. To achieve this, we quantify the association of common variant polygenic risk scores from nine complex inflammatory disorders with sarcoidosis risk. Enrichment analyses of genes implicated in pleiotropic associations were further used to elucidate candidate pathways. In European-Americans, we identify significant pleiotropy between risk of sarcoidosis and risk of asthma (R²=2.03%; p=8.89×10⁻⁹), celiac disease (R²=2.03%; p=8.21×10⁻⁹), primary biliary cirrhosis (R²=2.43%; p=2.01×10⁻¹⁰), and rheumatoid arthritis (R²=4.32%; p=2.50×10⁻¹⁷). These associations validate in African Americans only after accounting for the proportion of genome-wide European ancestry, where we demonstrate similar effects of polygenic risk for African-Americans with the highest levels of European ancestry. Variants and genes implicated in European-American pleiotropic associations were enriched for pathways involving interleukin-12, interleukin-27, and cell adhesion molecules, corroborating the hypothesized immunopathogenesis of disease.

Association of GWAS Top Genes With Late-Onset Alzheimer's Disease in Colombian Population

OBJECTIVE

The association of variants in CLU, CR1, PICALM, BIN1, ABCA7, and CD33 genes with late-onset Alzheimer's disease (LOAD) was evaluated and confirmed through genome-wide association study. However, it is unknown whether these associations can be replicated in admixed populations.

METHODS

The association of 14 single-nucleotide polymorphisms in those genes was evaluated in 280 LOAD cases and 357 controls from the Colombian population.

RESULTS

In a multivariate analysis using age, gender, APOE∊4 status, and admixture covariates, significant associations were obtained ( P < .05) for variants in BIN1 (rs744373, odds ratio [OR]: 1.42), CLU (rs11136000, OR: 0.66), PICALM (rs541458, OR: 0.69), ABCA7 (rs3764650, OR: 1.7), and CD33 (rs3865444, OR: 1.12). Likewise, a significant interaction effect was observed between CLU and CR1 variants with APOE.

CONCLUSION

This study replicated the associations previously reported in populations of European ancestry and shows that APOE variants have a regulatory role on the effect that variants in other loci have on LOAD, reflecting the importance of gene-gene interactions in the etiology of neurodegenerative diseases.

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.

Polysomnography in Bolivian Children Native to High Altitude Compared to Children Native to Low Altitude

STUDY OBJECTIVES

To compare polysomnographic parameters in high altitude (HA) native Andean children with low altitude (LA) native peers in order to explain the nocturnal oxyhemoglobin saturation (SpO2) instability reported in HA native children and to study the effect on sleep quality.

METHODS

Ninety-eight healthy children aged 7-10 y and 13-16 y were recruited at LA (500 m) or HA (3,650 m) above sea level. Physical examination was undertaken and genetic ancestry determined from salivary DNA to determine proportion of European ancestry, a risk factor for poor HA adaptation. Attended polysomnography was carried out over 1 night for 58 children at their resident location.

RESULTS

Of 98 children recruited, 85 met inclusion criteria, 58 of 85 (68.2%) completed polysomnography, of which 56 were adequate for analysis: 30 at LA (17 male) and 26 at HA (16 male). There were no altitude differences in genetic ancestry, but a high proportion of European admixture (median 50.6% LA; 44.0% HA). SpO2 was less stable at HA with mean 3% and 4% oxygen desaturation indices greater (both P < 0.001) than at LA. This was not explained by periodic breathing. However, more obstructive hypopnea was observed at HA (P < 0.001), along with a trend toward more central apnea (P = 0.053); neither was explained by clinical findings. There was no difference in sleep quality between altitudes.

CONCLUSIONS

HA native Andean children have more respiratory events when scoring relies on SpO2 desaturation due to inherent SpO2 instability. Use of American Academy of Sleep Medicine scoring criteria may yield false-positive results for obstructive sleep-disordered breathing at HA.

Decreased SMG7 expression associates with lupus-risk variants and elevated antinuclear antibody production

OBJECTIVES

Following up the systemic lupus erythematosus (SLE) genome-wide association studies (GWAS) identification of NMNAT2 at rs2022013, we fine-mapped its 150 kb flanking regions containing NMNAT2 and SMG7 in a 15 292 case-control multi-ancestry population and tested functions of identified variants.

METHODS

We performed genotyping using custom array, imputation by IMPUTE 2.1.2 and allele specific functions using quantitative real-time PCR and luciferase reporter transfections. SLE peripheral blood mononuclear cells (PBMCs) were cultured with small interfering RNAs to measure antinuclear antibody (ANA) and cyto/chemokine levels in supernatants using ELISA.

RESULTS

We confirmed association at NMNAT2 in European American (EA) and Amerindian/Hispanic ancestries, and identified independent signal at SMG7 tagged by rs2702178 in EA only (p=2.4×10-8, OR=1.23 (95% CI 1.14 to 1.32)). In complete linkage disequilibrium with rs2702178, rs2275675 in the promoter region robustly associated with SMG7 mRNA levels in multiple expression quantitative trait locus (eQTL) datasets. Its risk allele was dose-dependently associated with decreased SMG7 mRNA levels in PBMCs of 86 patients with SLE and 119 controls (p=1.1×10-3 and 6.8×10-8, respectively) and conferred reduced transcription activity in transfected HEK-293 (human embryonic kidney cell line) and Raji cells (p=0.0035 and 0.0037, respectively). As a critical component in the nonsense-mediated mRNA decay pathway, SMG7 could regulate autoantigens including ribonucleoprotein (RNP) and Smith (Sm). We showed SMG7 mRNA levels in PBMCs correlated inversely with ANA titres of patients with SLE (r=-0.31, p=0.01), and SMG7 knockdown increased levels of ANA IgG and chemokine (C-C motif) ligand 19 in SLE PBMCs (p=2.0×10-5 and 2.0×10-4, respectively).

CONCLUSION

We confirmed NMNAT2 and identified independent SMG7 association with SLE. The inverse relationship between levels of the risk allele-associated SMG7 mRNAs and ANA suggested the novel contribution of mRNA surveillance pathway to SLE pathogenesis.

FASN, dietary fat intake, and risk of uterine leiomyomata in the Black Women's Health Study

OBJECTIVE

To replicate results from a previous genome-wide association study of European ancestry women, in which a positive association was found between uterine leiomyomata (UL) and rs4247357, a single-nucleotide polymorphism located near the fatty acid synthase (FASN) gene.

DESIGN

Prospective cohort study.

SETTING

Not applicable.

PATIENT(S)

African-American women aged 23-50 years, who were premenopausal and had an intact uterus in 1997.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

We genotyped rs4247357 among 2,301 incident UL cases and 3,005 controls from the Black Women's Health Study (1997-2011). Odds ratios (ORs) and 95% confidence intervals (CI) were estimated using logistic regression with control for age, geographic region of residence, and percent European ancestry using a panel of validated ancestry informative markers.

RESULT(S)

Overall, rs4247357 was not associated with UL risk. Relative to the CC genotype, ORs were 1.04 (95% CI 0.92-1.19) for the AC genotype and 1.09 (95% CI 0.93-1.29) for the AA genotype. A positive association was found, however, among those with higher European ancestry (≥40%). Relative to the CC genotype, ORs were 2.03 (95% CI 1.12-3.69) for the AC genotype and 2.44 (95% CI 1.20-4.96) for the AA genotype. Dietary fat intake also appeared to modify the FASN-UL association.

CONCLUSION(S)

Although there was little overall association between rs4247357 and UL risk, a positive association was observed among women with ≥40% European ancestry. Direct sequencing of this genomic region might be warranted to determine whether rs4247357, or some other variant, is causally related to UL.

Admixture Mapping of African-American Women in the AMBER Consortium Identifies New Loci for Breast Cancer and Estrogen-Receptor Subtypes

Recent genetic admixture coupled with striking differences in incidence of estrogen receptor (ER) breast cancer subtypes, as well as severity, between women of African and European ancestry, provides an excellent rationale for performing admixture mapping in African American women with breast cancer risk. We performed the largest breast cancer admixture mapping study with in African American women to identify novel genomic regions associated with the disease. We conducted a genome-wide admixture scan using 2,624 autosomal ancestry informative markers (AIMs) in 3,629 breast cancer cases (including 1,968 ER-positive, 1093 ER-negative, and 601 triple-negative) and 4,658 controls from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, a collaborative study of four large geographically different epidemiological studies of breast cancer in African American women. We used an independent case-control study to test for SNP association in regions with genome-wide significant admixture signals. We found two novel genome-wide significant regions of excess African ancestry, 4p16.1 and 17q25.1, associated with ER-positive breast cancer. Two regions known to harbor breast cancer variants, 10q26 and 11q13, were also identified with excess of African ancestry. Fine-mapping of the identified genome-wide significant regions suggests the presence of significant genetic associations with ER-positive breast cancer in 4p16.1 and 11q13. In summary, we identified three novel genomic regions associated with breast cancer risk by ER status, suggesting that additional previously unidentified variants may contribute to the racial differences in breast cancer risk in the African American population.

Bayesian modeling for genetic association in case-control studies: accounting for unknown population substructure

A two-stage parametric Bayesian method is proposed to examine the association between a candidate gene and the occurrence of a disease after accounting for population substructure. This procedure, implemented via a Markov chain Monte Carlo numerical integration technique, first estimates the posterior probability of different unknown population substructures and then integrates this information into a disease-gene association model through the technique of Bayesian model averaging. The model relaxes certain assumptions of previous analyses and provides a unified computational framework to obtain an estimate of the log odds ratio parameter corresponding to the genetic factor after allowing for the allele frequencies to vary across subpopulations. The uncertainty in estimating the population substructure is taken into account while providing credible intervals for parameters in the disease-gene association model. Simulations on unmatched case-control studies that mimic an admixed Argentinean population are performed to demonstrate the statistical properties of our model. The method is also applied to a real data set coming from a genetic association study on obesity.

Genetic variation associated with preterm birth in African-American women

BACKGROUND

Preterm birth is considered a multifactorial condition; however, emerging evidence suggests that genetic variation among individuals may have an important role. Prior studies have suggested that single-nucleotide polymorphisms associated with genes related to the immune system, and particularly the maternal inflammatory response, may be associated with an increased risk of preterm delivery.

OBJECTIVE

The objective of the study was to identify single-nucleotide polymorphisms associated with spontaneous preterm birth <37 weeks within a cohort of African-American women.

STUDY DESIGN

This is a secondary analysis of a randomized trial that evaluated periodontal disease and preterm birth. Women were enrolled between 6 and 20 weeks' gestation at 3 prenatal care clinics between 2004 and 2007. Maternal DNA samples were collected and analyzed using a custom 1536 single-nucleotide polymorphismgenotyping array designed to assess genes involved in inflammation. Women were included in this study if they self-identified as African American. We excluded women with a multiple gestation or an indicated preterm delivery. We performed allele- and genotype-based analyses to evaluate the association between spontaneous preterm birth and tag single-nucleotide polymorphisms. We used a logistic regression to adjust for prior preterm birth in our genotype-based analysis. In a subgroup analysis, we compared women who delivered at <34 weeks' gestation to women who delivered at term. Within the microarray, we identified ancestry informative markers and compared global ancestry estimates among women who delivered preterm with those who delivered at term.

RESULTS

Of the 833 African-American women in the study with genotype data, 77 women (9.2%) had a spontaneous preterm birth, whereas 756 women delivered at term. In an allele-based analysis, 4 single-nucleotide polymorphisms related to the genes for protein kinase C-α (PRKCA) were associated with increased risk of spontaneous preterm birth <37 weeks, whereas a single single-nucleotide polymorphism related to fms-related tyrosine kinase 1 (FLT1) was associated with spontaneous preterm birth <34 weeks. A genotype-based analysis revealed similar associations between single-nucleotide polymorphisms related to the PRKCA genes and spontaneous premature delivery. Additionally, single-nucleotide polymorphisms related to matrix metalloproteinase-2 (MMP2), tissue inhibitor of matrix metalloproteinase-2 (TIMP2), and interleukin 16 (IL16) genes were associated with spontaneous preterm birth <37 weeks in genotype-based analysis. Genetic variants related to MMP2, matrix metalloproteinase-1 (MMP1), and leukemia inhibitory factor receptor antisense RNA 1 (LIFR-AS1) genes were associated with higher rates of preterm birth <34 weeks. Ancestry estimates were similar between the women who had a spontaneous preterm birth and those who delivered at term.

CONCLUSION

We identified tag single-nucleotide polymorphisms related to 7 genes that are critical to inflammation, extracellular remodeling, and cell signaling that were associated with spontaneous preterm birth in African-American women. Specifically, we found a strong association with the PRKCA gene. Genetic variation in these regions of the genome may be important in the pathogenesis of preterm birth. Our results should be considered in the design of future genomic studies in prematurity.