Genome-wide association studies: implications for multiethnic samples

Contribution of circulating Mfge8 to human T2DM and cardiovascular disease

MFGE8 is a major exosome (EV) protein known to mediate inflammation and atherosclerosis in type 2 diabetes mellitus (T2DM) in animal studies. The pathophysiological role of this protein in obesity, T2DM, and cardiovascular disease is less investigated in humans. Earlier we reported a rare Asian Indian population-specific missense variant (rs371227978; Arg148His) in the MFGE8 gene associated with increased circulating Mfge8 and T2DM. We have further investigated the role of Mfge8 with T2DM risk in additional Asian Indians (n = 4897) and Europeans and other multiethnic cohorts from UK Biobank (UKBB) (n = 455,808) and the US (n = 1150). We also evaluated the exposure of Mfge8-enriched human EVs in zebrafish (ZF) for their impact on cardiometabolic organ system. Most individual carriers of Arg148His variant not only had high circulating Mfge8 but also revealed a positive significant correlation with glucose (r = 0.42; p = 4.9 × 10-04), while the non-carriers showed a negative correlation of Mfge8 with glucose (r = -0.38; p = 0.001) in Asian Indians. The same variant was monomorphic in non-South Asian ethnicities. Even without the variant, serum Mfge8 correlated significantly with blood glucose in other non-South Asian ethnicities (r = 0.47; p = 2.2 × 10-13). Since Mfge8 is an EV marker, we tested the exposure of Mfge8-enriched human EVs to ZF larvae as an exploratory study. The ZF larvae showed rapid effects on insulin-sensitive organs, developing fatty liver disease, heart hypertrophy and exhibiting redundant growth with poor muscular architecture with and without the high-fat diet (HFD). In contrast, the control group fishes developed fatty liver disease and heart hypertrophy only after the HFD feeding. Backed with strong support from animal studies on the role of Mfge8 in obesity, insulin resistance, and atherosclerosis, the current research suggests that circulating Mfge8 may become a potential marker for predicting the risk of T2DM and cardiovascular disease in humans.

The Role of Airway Epithelial Cell Alarmins in Asthma

The airway epithelium is the first line of defense for the lungs, detecting inhaled environmental threats through pattern recognition receptors expressed transmembrane or intracellularly. Activation of pattern recognition receptors triggers the release of alarmin cytokines IL-25, IL-33, and TSLP. These alarmins are important mediators of inflammation, with receptors widely expressed in structural cells as well as innate and adaptive immune cells. Many of the key effector cells in the allergic cascade also produce alarmins, thereby contributing to the airways disease by driving downstream type 2 inflammatory processes. Randomized controlled clinical trials have demonstrated benefit when blockade of TSLP and IL-33 were added to standard of care medications, suggesting these are important new targets for treatment of asthma. With genome-wide association studies demonstrating associations between single-nucleotide polymorphisms of the TSLP and IL-33 gene and risk of asthma, it will be important to understand which subsets of asthma patients will benefit most from anti-alarmin therapy.

APOC3 genetic variation, serum triglycerides, and risk of coronary artery disease in Asian Indians, Europeans, and other ethnic groups

BACKGROUND

Hypertriglyceridemia has emerged as a critical coronary artery disease (CAD) risk factor. Rare loss-of-function (LoF) variants in apolipoprotein C-III have been reported to reduce triglycerides (TG) and are cardioprotective in American Indians and Europeans. However, there is a lack of data in other Europeans and non-Europeans. Also, whether genetically increased plasma TG due to ApoC-III is causally associated with increased CAD risk is still unclear and inconsistent. The objectives of this study were to verify the cardioprotective role of earlier reported six LoF variants of APOC3 in South Asians and other multi-ethnic cohorts and to evaluate the causal association of TG raising common variants for increasing CAD risk.

METHODS

We performed gene-centric and Mendelian randomization analyses and evaluated the role of genetic variation encompassing APOC3 for affecting circulating TG and the risk for developing CAD.

RESULTS

One rare LoF variant (rs138326449) with a 37% reduction in TG was associated with lowered risk for CAD in Europeans (p = 0.007), but we could not confirm this association in Asian Indians (p = 0.641). Our data could not validate the cardioprotective role of other five LoF variants analysed. A common variant rs5128 in the APOC3 was strongly associated with elevated TG levels showing a p-value 2.8 × 10- 424. Measures of plasma ApoC-III in a small subset of Sikhs revealed a 37% increase in ApoC-III concentrations among homozygous mutant carriers than the wild-type carriers of rs5128. A genetically instrumented per 1SD increment of plasma TG level of 15 mg/dL would cause a mild increase (3%) in the risk for CAD (p = 0.042).

CONCLUSIONS

Our results highlight the challenges of inclusion of rare variant information in clinical risk assessment and the generalizability of implementation of ApoC-III inhibition for treating atherosclerotic disease. More studies would be needed to confirm whether genetically raised TG and ApoC-III concentrations would increase CAD risk.

Genetic and Non-genetic Determinants of Cardiovascular Disease in South Asians

South Asians (SAs), people from the Indian subcontinent (e.g., India, Pakistan, Bangladesh, Sri Lanka, and Nepal) have a higher prevalence of cardiovascular disease (CVD) and suffer from a greater risk of CVD-associated mortality compared to other global populations. These problems are compounded by the alterations in lifestyles due to urbanization and changing cultural, social, economic, and political environments. Current methods of CV risk prediction are based on white populations that under-estimate the CVD risk in SAs. Prospective studies are required to obtain actual CVD morbidity/mortality rates so that comparisons between predicted CVD risk can be made with actual events. Overwhelming data support a strong influence of genetic factors. Genome-Wide Association Studies (GWAS) serve as a starting point for future genetic and functional studies since the mechanisms of action by which these associated loci influence CVD is still unclear. It is difficult to predict the potential implication of these findings in clinical settings. This review provides a systematic assessment of the risk factors, genetics, and environmental causes of CV health disparity in SAs, and highlights progress made in clinical and genomics discoveries in the rapidly evolving field, which has the potential to show clinical relevance in the near future.

A rare missense variant in the milk fat globule-EGF factor 8 (MFGE8) increases T2DM susceptibility and cardiovascular disease risk with population-specific effects

AIMS

The milk fat globule-epidermal growth factor 8 (MFGE8), also called lactadherin, is an integrin ligand and a known mediator of inflammation and atherosclerosis in T2DM in studies using animal models. However, its role in the pathophysiology of human T2DM, obesity, and cardiovascular disease has been poorly explored. Aim of this study  was to investigate the role of a missense variant (rs371227978 C/T: Arg148His) in the MFGE8 gene identified through exome sequencing for its association with T2DM and cardiometabolic traits.

METHODS

Exome-wide sequencing was performed using DNA samples from 68 Sikh individuals from multi-generation pedigrees affected with diabetes on Illumina's GAIIx using "SureSelect Human All Exon" panels. We further replicated this variant by de novo genotyping in a total of 4242 individuals of the Asian Indian Diabetic Heart Study/Sikh Diabetes Study using custom TaqMan genotyping assay. We also measured circulating concentrations of Mfge8 using frozen serum aliquots by enzyme-linked immunosorbent assay.

RESULTS

Overall, only 1.78% of 4242 individuals were carriers of this variant with MAF being 0.009. Except for the significant correlation of this variant with T2DM and triglycerides, no other quantitative risk phenotype was significant. The minor per allele-associated increased risk for T2DM showed odds ratio of 1.95 (95% CI 1.18-3.23; p = 0.008) in unadjusted model and was 1.73 (95% CI 1.02-2.93; p = 0.043) after adjusting for the age, gender, and BMI. However, there was a strong correlation between serum Mfge8 concentrations with T2DM, (r2 = 0.38; p = 0.001), fasting glucose (r2= 0.36; p = 0.002), and triglycerides (r2 = 0.33; p = 0.005). Our data revealed a significant dose-related increase in MFGE8 genotypes for affecting serum Mfge8 (p = 2.1 × 10-3) and triglyceride concentrations (p = 3.2 × 10-3). For a per risk allele-associated increase of 4.74 ng/ml ± SD of 1.62 ng/ml of the Mfge8 concentration was found to increase T2DM risk to 1.7 fold (95% CI from 1 to 3 fold).

CONCLUSIONS

Here, we report for the first time a novel population-specific rare variant in the MFGE8 gene linked with the increased Mfge8 concentrations and the risk for developing T2DM and cardiovascular risk factors in a population of Punjabi Sikhs from India. In view of a strong evidence from animal studies supporting the role of Mfge8 in obesity, insulin resistance, and the development of atherosclerosis in T2DM, our findings are important and timely. If validated in a large independent dataset, early screening of Mfge8 in blood levels may especially benefit those patients with genetically elevated Mfge8 levels to preventing or reducing the risk of T2DM and cardiovascular disease.

Could rs4379368 be a genetic marker for North Indian migraine patients with aura?: Preliminary evidence by a replication study

BACKGROUND

Genome wide association studies (GWAS) have already found different migraine single nucleotide polymorphisms (SNPs). To further check if these variants differ by ethnicity, three single nucleotide polymorphisms (SNPs) (rs4379368, rs10504861and rs11172113) were genotyped here to find association with migraine susceptibility from North Indian population.

METHODS AND RESULTS

A case control study in 200 subjects was done by polymerase chain reaction and restriction-fragment-length polymorphism (PCR-RFLP) analysis. Univariate analysis was performed to check the association of different genotypic and allelic frequencies of these variants with migraine and its subtypes. We could not find any statistically relevant differences among frequencies at various levels of these selected SNPs between patients and healthy controls in this study (p > 0.05). However on subgroup analysis for rs4379368 SNP, the CT genotype was higher in migraine with aura (MA) (69.6%) than migraine without aura (MO) (51.9%) or control (42%) (p < 0.05). But this relation was not significant at allelic level. For other two SNPs, statistically significant differences were not observed in any of the two migraine subgroups.

CONCLUSIONS

This study was able to associate the role of rs4379368 SNP with migraine susceptibility and suggested that genotype CT in rs4379368 SNP could be a possible genetic marker for MA. More studies with larger sample size are needed to strengthen our results.

Cross-population analysis for functional characterization of type II diabetes variants

BACKGROUND

As Genome-Wide Association Studies (GWAS) have been increasingly used with data from various populations, it has been observed that data from different populations reveal different sets of Single Nucleotide Polymorphisms (SNPs) that are associated with the same disease. Using Type II Diabetes (T2D) as a test case, we develop measures and methods to characterize the functional overlap of SNPs associated with the same disease across populations.

RESULTS

We introduce the notion of an Overlap Matrix as a general means of characterizing the functional overlap between different SNP sets at different genomic and functional granularities. Using SNP-to-gene mapping, functional annotation databases, and functional association networks, we assess the degree of functional overlap across nine populations from Asian and European ethnic origins. We further assess the generalizability of the method by applying it to a dataset for another complex disease - Prostate Cancer. Our results show that more overlap is captured as more functional data is incorporated as we go through the pipeline, starting from SNPs and ending at network overlap analyses. We hypothesize that these observed differences in the functional mechanisms of T2D across populations can also explain the common use of different prescription drugs in different populations. We show that this hypothesis is concordant with the literature on the functional mechanisms of prescription drugs.

CONCLUSION

Our results show that although the etiology of a complex disease can be associated with distinct processes that are affected in different populations, network-based annotations can capture more functional overlap across populations. These results support the notion that it can be useful to take ethnicity into account in making personalized treatment decisions for complex diseases.

Genome-wide association analysis of HDL-C in a Lebanese cohort

Low serum levels of high-density lipoprotein cholesterol (HDL-C) have been shown to be a risk factor for coronary artery disease independent of low-density lipoprotein cholesterol (LDL-C) in different populations. In this study, we investigated genetic variants through genome-wide association studies to determine their association with HDL-C levels in a sample of 2,700 patients. We identified several SNPs associated with HDL-C levels in the Lebanese population using unadjusted and adjusted by biological factors models. We replicated the association of rs3764261 within CETP with HDL-C levels in the study population, and found other previously unidentified SNPs to be significant at the suggestive level, in both previously identified and unidentified genes. This paper reports the first genome-wide analysis of HDL-C in the Lebanese, Middle Eastern, population and supports the importance of genome-wide association studies across different and minor ethnicities to understand better the etiology of complex human diseases.

Clinical Utility and Practical Considerations of a Coronary Artery Disease Genetic Risk Score

Background

Coronary artery disease (CAD) risk traditionally has been assessed using clinical risk factors. We evaluated whether molecular genetic markers for CAD risk could add information to traditional variables.

Methods

We developed a false discovery rate 267-marker genetic risk score (FDR₂₆₇) from markers that were significantly associated with CAD in the UK Biobank cohort meta-analysis. FDR₂₆₇ was tested in the Atherosclerosis Risk in Communities cohort using logistic regression and Cox proportional hazards analyses in the European and African American groups.

Results

Our genetic risk score (FDR₂₆₇) was associated with a 1.45 (95% confidence interval, 1.39-1.51) increase in odds ratio and a 1.32 (95% confidence interval, 1.26-1.38) increase in hazard ratio per standard deviation of the score. The score modestly improved the area under the curve (AUC) statistic when added to a clinical model (ΔAUC = 0.0112, P = 0.0002). FDR₂₆₇ predicted incident CAD (C-index = 0.60), although it did not improve on clinical risk factors (ΔAUC = 0.0159, P = 0.0965). Individuals in the top quintile of FDR₂₆₇ genetic risk were at approximately 2-fold increased risk compared with the bottom quintile, which is comparable to risk associated with self-reported family history. The performance of FDR₂₆₇ was less robust in the African American sample.

Conclusions

FDR₂₆₇ is significantly associated with CAD in the European sample, with an effect size comparable to self-reported family history. FDR₂₆₇ discriminated between individuals with and without CAD, but did not improve CAD risk prediction over clinical variables. FDR₂₆₇ was less predictive of CAD risk in African Americans.

An Ancestry Informative Marker Set Which Recapitulates the Known Fine Structure of Populations in South Asia

The inference of genomic ancestry using ancestry informative markers (AIMs) can be useful for a range of studies in evolutionary genetics, biomedical research, and forensic analyses. However, the determination of AIMs for highly admixed populations with complex ancestries has remained a formidable challenge. Given the immense genetic heterogeneity and unique population structure of the Indian subcontinent, here we sought to derive AIMs that would yield a cohesive and faithful understanding of South Asian genetic origins. To discern the most optimal strategy for extracting AIMs for South Asians we compared three commonly used AIMs-determining methods namely, Infocalc, FST, and Smart Principal Component Analysis with ADMIXTURE, using previously published whole genome data from the Indian subcontinent. Our findings suggest that the Infocalc approach is likely most suitable for delineation of South Asian AIMs. In particular, Infocalc-2,000 (N = 2,000) appeared as the most informative South Asian AIMs panel that recapitulated the finer structure within South Asian genomes with high degree of sensitivity and precision, whereas a negative control with an equivalent number of randomly selected markers when used to interrogate the South Asian populations, failed to do so. We discuss the utility of all approaches under evaluation for AIMs derivation and interpreting South Asian genomic ancestries. Notably, this is the first report of an AIMs panel for South Asian ancestry inference. Overall these findings may aid in developing cost-effective resources for large-scale demographic analyses and foster expansion of our knowledge of human origins and disease, in the South Asian context.

The pharmacoepigenomics informatics pipeline defines a pathway of novel and known warfarin pharmacogenomics variants

AIM

'Pharmacoepigenomics' methods informed by omics datasets and pre-existing knowledge have yielded discoveries in neuropsychiatric pharmacogenomics. Now we evaluate the generality of these methods by discovering an extended warfarin pharmacogenomics pathway.

MATERIALS & METHODS

We developed the pharmacoepigenomics informatics pipeline, a scalable multi-omics variant screening pipeline for pharmacogenomics, and conducted an experiment in the genomics of warfarin.

RESULTS

We discovered known and novel pharmacogenomics variants and genes, both coding and regulatory, for warfarin response, including adverse events. Such genes and variants cluster in a warfarin response pathway consolidating known and novel warfarin response variants and genes.

CONCLUSION

These results can inform a new warfarin test. The pharmacoepigenomics informatics pipeline may be able to discover new pharmacogenomics markers in other drug-disease systems.

Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

Impact of a Genetic Risk Score on Myocardial Infarction Risk Across Different Ethnic Populations

BACKGROUND

Myocardial infarction (MI) risk varies by ethnicity, although the influence of genetic factors remains unclear. Using a genetic risk score (GRS), we examined the association between 25 coronary artery disease (CAD)-related single nucleotide polymorphisms and MI across 6 ethnic groups.

METHODS

We studied 8556 participants in the INTERHEART case-control study from 6 ethnic groups: Europeans, South Asians, Southeast Asians, Arabs, Latin Americans, and Africans. Associations between the GRS and MI were tested in each group by logistic regression and overall by meta-analysis.

RESULTS

Overall, the GRS increased the odds of MI by 1.07 (95% confidence interval [CI], 1.04-1.09) per risk allele in the unadjusted model, with little change (odds ratio, 1.06; 95% CI, 1.04-1.09) after adjusting for demographic and modifiable factors. In Europeans, South Asians, Southeast Asians, and Arabs, the GRS was significantly associated with MI, with minimal heterogeneity observed. In these groups, a score > 23 risk alleles (highest 4 quintiles) was associated with only a 5% difference in population attributable risk (PAR) (36% to 41%) for MI. The GRS was not significant in Latin Americans or Africans. In the overall cohort, modest changes, beyond clinical factors, in PAR (88% to 91%), concordance statistic (0.73 to 0.74), and continuous net reclassification improvement (12%) were observed with the GRS.

CONCLUSIONS

A CAD GRS is associated with MI across a multiethnic cohort, with significant and consistent effects across 4 distinct ethnicities. However, it only modestly improves MI risk prediction beyond clinical factors.

A novel random effect model for GWAS meta-analysis and its application to trans-ethnic meta-analysis

Meta-analysis of trans-ethnic genome-wide association studies (GWAS) has proven to be a practical and profitable approach for identifying loci that contribute to the risk of complex diseases. However, the expected genetic effect heterogeneity cannot easily be accommodated through existing fixed-effects and random-effects methods. In response, we propose a novel random effect model for trans-ethnic meta-analysis with flexible modeling of the expected genetic effect heterogeneity across diverse populations. Specifically, we adopt a modified random effect model from the kernel regression framework, in which genetic effect coefficients are random variables whose correlation structure reflects the genetic distances across ancestry groups. In addition, we use the adaptive variance component test to achieve robust power regardless of the degree of genetic effect heterogeneity. Simulation studies show that our proposed method has well-calibrated type I error rates at very stringent significance levels and can improve power over the traditional meta-analysis methods. We reanalyzed the published type 2 diabetes GWAS meta-analysis (Consortium et al., 2014) and successfully identified one additional SNP that clearly exhibits genetic effect heterogeneity across different ancestry groups. Furthermore, our proposed method provides scalable computing time for genome-wide datasets, in which an analysis of one million SNPs would require less than 3 hours.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci.

Trans-ethnic study design approaches for fine-mapping

Studies that traverse ancestrally diverse populations may increase power to detect novel loci and improve fine-mapping resolution of causal variants by leveraging linkage disequilibrium differences between ethnic groups. The inclusion of African ancestry samples may yield further improvements because of low linkage disequilibrium and high genetic heterogeneity. We investigate the fine-mapping resolution of trans-ethnic fixed-effects meta-analysis for five type II diabetes loci, under various settings of ancestral composition (European, East Asian, African), allelic heterogeneity, and causal variant minor allele frequency. In particular, three settings of ancestral composition were compared: (1) single ancestry (European), (2) moderate ancestral diversity (European and East Asian), and (3) high ancestral diversity (European, East Asian, and African). Our simulations suggest that the European/Asian and European ancestry-only meta-analyses consistently attain similar fine-mapping resolution. The inclusion of African ancestry samples in the meta-analysis leads to a marked improvement in fine-mapping resolution.

A minimum set of ancestry informative markers for determining admixture proportions in a mixed American population: the Brazilian set

The Brazilian population is considered to be highly admixed. The main contributing ancestral populations were European and African, with Amerindians contributing to a lesser extent. The aims of this study were to provide a resource for determining and quantifying individual continental ancestry using the smallest number of SNPs possible, thus allowing for a cost- and time-efficient strategy for genomic ancestry determination. We identified and validated a minimum set of 192 ancestry informative markers (AIMs) for the genetic ancestry determination of Brazilian populations. These markers were selected on the basis of their distribution throughout the human genome, and their capacity of being genotyped on widely available commercial platforms. We analyzed genotyping data from 6487 individuals belonging to three Brazilian cohorts. Estimates of individual admixture using this 192 AIM panels were highly correlated with estimates using ~370 000 genome-wide SNPs: 91%, 92%, and 74% of, respectively, African, European, and Native American ancestry components. Besides that, 192 AIMs are well distributed among populations from these ancestral continents, allowing greater freedom in future studies with this panel regarding the choice of reference populations. We also observed that genetic ancestry inferred by AIMs provides similar association results to the one obtained using ancestry inferred by genomic data (370 K SNPs) in a simple regression model with rs1426654, related to skin pigmentation, genotypes as dependent variable. In conclusion, these markers can be used to identify and accurately quantify ancestry of Latin Americans or US Hispanics/Latino individuals, in particular in the context of fine-mapping strategies that require the quantification of continental ancestry in thousands of individuals.

Common genetic variants associated with resting oxygenation in chronic obstructive pulmonary disease

Hypoxemia is a major complication of chronic obstructive pulmonary disease (COPD) that correlates with disease prognosis. Identifying genetic variants associated with oxygenation may provide clues for deciphering the heterogeneity in prognosis among patients with COPD. However, previous genetic studies have been restricted to investigating COPD candidate genes for association with hypoxemia. To report results from the first genome-wide association study (GWAS) of resting oxygen saturation (as measured by pulse oximetry [Spo2]) in subjects with COPD, we performed a GWAS of Spo2 in two large, well characterized COPD populations: COPDGene, including both the non-Hispanic white (NHW) and African American (AA) groups, and Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). We identified several suggestive loci (P < 1 × 10(-5)) associated with Spo2 in COPDGene in the NHW (n = 2810) and ECLIPSE (n = 1758) groups, and two loci on chromosomes 14 and 15 in the AA group (n = 820) from COPDGene achieving a level of genome-wide significance (P < 5 × 10(-8)). The chromosome 14 single-nucleotide polymorphism, rs6576132, located in an intergenic region, was nominally replicated (P < 0.05) in the NHW group from COPDGene. The chromosome 15 single-nucleotide polymorphisms were rare in subjects of European ancestry, so the results could not be replicated. The chromosome 15 region contains several genes, including TICRR and KIF7, and is proximal to RHCG (Rh family C glyocoprotein gene). We have identified two loci associated with resting oxygen saturation in AA subjects with COPD, and several suggestive regions in subjects of European descent with COPD. Our study highlights the importance of investigating the genetics of complex traits in different racial groups.

Admixture mapping identifies a locus at 15q21.2-22.3 associated with keloid formation in African Americans

Keloids are benign dermal tumors that occur ~20 times more often in African versus Caucasian descent individuals. While most keloids occur sporadically, a genetic predisposition is supported by both familial aggregation of some keloids and the large differences in risk among populations. Yet, no well-established genetic risk factors for keloids have been identified. In this study, we conducted admixture mapping and whole-exome association using 478 African Americans (AAs) samples (122 cases, 356 controls) with exome genotyping data to identify regions where local ancestry associated with keloid risk. Logistic regression was used to evaluate associations under admixture peaks. A significant mapping peak was observed on chr15q21.2-22.3. This peak included NEDD4, a gene previously implicated in a keloid genome-wide association study (GWAS) of Japanese individuals later validated in a Chinese cohort. While we observed modest evidence for association with NEDD4, a more significant association was observed at (myosin 1E) MYO1E. A genome scan not including the 15q21-22 region also identified associations at MYO7A (rs35641839, odds ratio [OR] = 4.71, 95% confidence interval [CI] 2.38-9.32, p = 8.34 × 10(-6)) at 11q13.5. The identification of SNPs in two myosin genes strongly associated with keloid formation suggests that an altered cytoskeleton contributes to the enhanced migratory and invasive properties of keloid fibroblasts. Our findings support the admixture mapping approach for the study of keloid risk, and indicate potentially common genetic elements on chr15q21.2-22.3 in causation of keloids in AAs, Japanese, and Chinese populations.

Genetic risk score for prediction of newborn adiposity and large-for-gestational-age birth

CONTEXT

Macrosomic infants are at increased risk for adverse metabolic outcomes. Improving prediction of large-for-gestational-age (LGA) birth may help prevent these outcomes.

OBJECTIVE

This study sought to determine whether genes associated with obesity-related traits in adults are associated with newborn size, and whether a genetic risk score (GRS) predicts LGA birth.

SETTING AND DESIGN

Single nucleotide polymorphisms (SNPs) in 40 regions associated with adult obesity-related traits were tested for association with newborn size. GRS's for birth weight and sum of skinfolds (SSF) specific to ancestry were calculated using the most highly associated SNP for each ancestry in genomic regions with one or more SNPs associated with birth weight and/or SSF in at least one ancestry group or meta-analyses.

PARTICIPANTS

Newborns from the Hyperglycemia Adverse Pregnancy Outcomes Study were studied (942 Afro-Caribbean, 1294 Northern European, 573 Mexican-American, and 1182 Thai).

OUTCOME MEASURES

Birth weight >90th percentile (LGA) and newborn SSF >90th percentile were primary outcomes.

RESULTS

After adjustment for ancestry, sex, gestational age at delivery, parity, maternal genotype, maternal smoking/alcohol intake, age, body mass index, height, blood pressure and glucose, 25 and 23 SNPs were associated (P < .001) with birth weight and newborn SSF, respectively. The GRS was highly associated with both phenotypes as continuous variables across all ancestries (P ≤ 1.6 × 10(-19)) and improved prediction of birth weight and SSF >90th percentile when added to a baseline model incorporating the covariates listed above.

CONCLUSIONS

A GRS comprised of SNPs associated with adult obesity-related traits may provide an approach for predicting LGA birth and newborn adiposity beyond established risk factors.

Transethnic replication of association of CTG18.1 repeat expansion of TCF4 gene with Fuchs' corneal dystrophy in Chinese implies common causal variant

PURPOSE

To test the association between the CTG18.1 trinucleotide repeat expansion of TCF4 gene and Fuchs' endothelial corneal dystrophy (FECD) in a Chinese population.

METHODS

The trinucleotide repeat polymorphism CTG18.1 was genotyped using short tandem repeat and triplet repeat primed polymerase chain reaction assays in 57 Chinese subjects with FECD and 121 controls. Statistical association of the expanded CTG18.1 allele and 18 single nucleotide polymorphisms (SNPs) across TCF4 with FECD was evaluated. To investigate the linkage disequilibrium structure of the TCF4 region, haplotype analysis was performed on our study subjects and compared with genotyping data of 97 Han Chinese and 85 Caucasians in the 1000 Genomes Project.

RESULTS

The expanded CTG18.1 allele was associated with FECD (P = 4.7 × 10(-14)), with the odds ratio of each copy of the expanded allele estimated to be 66.5 (95% confidence interval: 12.6-350.1). Five TCF4 SNPs showed association with FECD at a nominal level (P < 5.0 × 10(-2)); however, conditional on the expanded CTG18.1 polymorphism, none of the SNPs showed association with FECD. The only haplotype associated with the disease was the one with the expansion at the CTG18.1 locus.

CONCLUSIONS

Transethnic replication of the association between the CTG18.1 repeat expansion in the TCF4 gene and FECD suggests it is a common, causal variant shared in Eurasian populations conferring significant risk for the development of FECD. Our data suggest that the expanded CTG18.1 allele is the main, if not sole, causal variant at this gene locus in the Chinese population.

Whole-exome imputation of sequence variants identified two novel alleles associated with adult body height in African Americans

Adult body height is a quantitative trait for which genome-wide association studies (GWAS) have identified numerous loci, primarily in European populations. These loci, comprising common variants, explain <10% of the phenotypic variance in height. We searched for novel associations between height and common (minor allele frequency, MAF ≥5%) or infrequent (0.5% < MAF < 5%) variants across the exome in African Americans. Using a reference panel of 1692 African Americans and 471 Europeans from the National Heart, Lung, and Blood Institute's (NHLBI) Exome Sequencing Project (ESP), we imputed whole-exome sequence data into 13 719 African Americans with existing array-based GWAS data (discovery). Variants achieving a height-association threshold of P < 5E-06 in the imputed dataset were followed up in an independent sample of 1989 African Americans with whole-exome sequence data (replication). We used P < 2.5E-07 (=0.05/196 779 variants) to define statistically significant associations in meta-analyses combining the discovery and replication sets (N = 15 708). We discovered and replicated three independent loci for association: 5p13.3/C5orf22/rs17410035 (MAF = 0.10, β = 0.64 cm, P = 8.3E-08), 13q14.2/SPRYD7/rs114089985 (MAF = 0.03, β = 1.46 cm, P = 4.8E-10) and 17q23.3/GH2/rs2006123 (MAF = 0.30; β = 0.47 cm; P = 4.7E-09). Conditional analyses suggested 5p13.3 (C5orf22/rs17410035) and 13q14.2 (SPRYD7/rs114089985) may harbor novel height alleles independent of previous GWAS-identified variants (r(2) with GWAS loci <0.01); whereas 17q23.3/GH2/rs2006123 was correlated with GWAS-identified variants in European and African populations. Notably, 13q14.2/rs114089985 is infrequent in African Americans (MAF = 3%), extremely rare in European Americans (MAF = 0.03%), and monomorphic in Asian populations, suggesting it may be an African-American-specific height allele. Our findings demonstrate that whole-exome imputation of sequence variants can identify low-frequency variants and discover novel variants in non-European populations.

Association of common genetic variants with lipid traits in the Indian population

Genome-wide association studies (GWAS) have been instrumental in identifying novel genetic variants associated with altered plasma lipid levels. However, these quantitative trait loci have not been tested in the Indian population, where there is a poorly understood and growing burden of cardiometabolic disorders. We present the association of six single nucleotide polymorphisms in 1671 sib pairs (3342 subjects) with four lipid traits: total cholesterol, triglycerides, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C). We also investigated the interaction effects of gender, location, fat intake and physical activity. Each copy of the risk allele of rs964184 at APOA1 was associated with 1.06 mmol/l increase in triglycerides (SE = 0.049; p = 0.006), rs3764261 at CETP with 1.02 mmol/l increase in both total cholesterol (SE = 0.042; p = 0.017) and HDL-C (SE = 0.041; p = 0.008), rs646776 at CELSR2-PSRC1-SORT1 with 0.96 mmol/l decrease in cholesterol (SE = 0.043; p = 0.0003) and 0.15 mmol/l decrease in LDL-C levels (SE = 0.043; p = 0.0003) and rs2954029 at TRIB1 with 1.02 mmol/l increase in HDL-C (SE = 0.039; p = 0.047). A combined risk score of APOA1 and CETP loci predicted an increase of 1.25 mmol/l in HDL-C level (SE = 0.312; p = 0.0007). Urban location and sex had strong interaction effects on the genetic association of most of the studied loci with lipid traits. To conclude, we validated four genetic variants (identified by GWAS in western populations) associated with lipid traits in the Indian population. The interaction effects found here may explain the sex-specific differences in lipid levels and their heritability. Urbanization appears to influence the nature of the association with GWAS lipid loci in this population. However, these findings will require replication in other Indian populations.

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS) including 26,488 cases and 83,964 controls of European, East Asian, South Asian, and Mexican and Mexican American ancestry. We observed significant excess in directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven novel T2D susceptibility loci. Furthermore, we observed considerable improvements in fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterisation of complex trait loci, and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Replication and fine mapping of asthma-associated loci in individuals of African ancestry

Asthma originates from genetic and environmental factors with about half the risk of disease attributable to heritable causes. Genome-wide association studies, mostly in populations of European ancestry, have identified numerous asthma-associated single nucleotide polymorphisms (SNPs). Studies in populations with diverse ancestries allow both for identification of robust associations that replicate across ethnic groups and for improved resolution of associated loci due to different patterns of linkage disequilibrium between ethnic groups. Here we report on an analysis of 745 African-American subjects with asthma and 3,238 African-American control subjects from the Candidate Gene Association Resource (CARe) Consortium, including analysis of SNPs imputed using 1,000 Genomes reference panels and adjustment for local ancestry. We show strong evidence that variation near RAD50/IL13, implicated in studies of European ancestry individuals, replicates in individuals largely of African ancestry. Fine mapping in African ancestry populations also refined the variants of interest for this association. We also provide strong or nominal evidence of replication at loci near ORMDL3/GSDMB, IL1RL1/IL18R1, and 10p14, all previously associated with asthma in European or Japanese populations, but not at the PYHIN1 locus previously reported in studies of African-American samples. These results improve the understanding of asthma genetics and further demonstrate the utility of genetic studies in populations other than those of largely European ancestry.

IHH gene polymorphism among three horse breeds and its application for association test in horses with osteochondrosis

Genetic polymorphism of IHH gene were investigated in Angloarabian, Polish Coldblood and Polish Halfbred horses with the inclusion of a group of Polish Halfbreds affected by osteochondrosis. IHH is a good candidate gene for association study of developmental disorders mainly affecting skeleton development. DNA sequence spanning IHH gene annotated in the horse genome and its putative promoter were investigated using SANGER sequencing. Analysis of genetic variability at polymorphic sites in the IHH gene body and the promoter region confirmed genetic differences between warmblood and coldblood horse breeds. A test for allelic and genotypic association at particular SNP sites revealed no association with osteochondrosis in investigated group of Polish Halfbreds. It was concluded that participation of different warmblood breeds in pedigrees of Polish Halfbreds make it difficult to search for genetic variants being associated with this complex disorder in this breed. IHH gene polymorphism investigated among three different horse populations would be valuable for further studies on equine bone developmental disorders.

Genetics of obesity and type 2 diabetes in African Americans

Obesity and type 2 diabetes are highly prevalent and lead to significant morbidity and mortality. In the United States, the impact of these conditions may be worse on historically underserved minorities, particularly African Americans. Genetic ancestry and differences in physiology are unlikely to be the sole or primary determinants of these disparities. In addition, research in this area has the ethically problematic possibility of conflating race with biology. Despite these important considerations and the challenges of conducting this work, population-based approaches for investigating the etiology of obesity and T2D may yield useful information about the pathophysiology of disease, and have implications that extend to all affected individuals. The purpose of this paper is to describe what is understood about the genetic variation that underlies obesity and T2D in African Americans and other individuals of more recent African descent and to highlight several examples that illustrate how ensuring adequate minority representation in genetic research improves its quality. For a variety of reasons a number of unique insights have been possible as a result of these efforts.

Transethnic meta-analysis of genomewide association studies

The detection of loci contributing effects to complex human traits, and their subsequent fine-mapping for the location of causal variants, remains a considerable challenge for the genetics research community. Meta-analyses of genomewide association studies, primarily ascertained from European-descent populations, have made considerable advances in our understanding of complex trait genetics, although much of their heritability is still unexplained. With the increasing availability of genomewide association data from diverse populations, transethnic meta-analysis may offer an exciting opportunity to increase the power to detect novel complex trait loci and to improve the resolution of fine-mapping of causal variants by leveraging differences in local linkage disequilibrium structure between ethnic groups. However, we might also expect there to be substantial genetic heterogeneity between diverse populations, both in terms of the spectrum of causal variants and their allelic effects, which cannot easily be accommodated through traditional approaches to meta-analysis. In order to address this challenge, I propose novel transethnic meta-analysis methodology that takes account of the expected similarity in allelic effects between the most closely related populations, while allowing for heterogeneity between more diverse ethnic groups. This approach yields substantial improvements in performance, compared to fixed-effects meta-analysis, both in terms of power to detect association, and localization of the causal variant, over a range of models of heterogeneity between ethnic groups. Furthermore, when the similarity in allelic effects between populations is well captured by their relatedness, this approach has increased power and mapping resolution over random-effects meta-analysis. Genet. Epidemiol. 2011. © 2011 Wiley Periodicals, Inc.35: 809–;822, 2011.

A replication study of GWAS-derived lipid genes in Asian Indians: the chromosomal region 11q23.3 harbors loci contributing to triglycerides

Recent genome-wide association scans (GWAS) and meta-analysis studies on European populations have identified many genes previously implicated in lipid regulation. Validation of these loci on different global populations is important in determining their clinical relevance, particularly for development of novel drug targets for treating and preventing diabetic dyslipidemia and coronary artery disease (CAD). In an attempt to replicate GWAS findings on a non-European sample, we examined the role of six of these loci (CELSR2-PSRC1-SORT1 rs599839; CDKN2A-2B rs1333049; BUD13-ZNF259 rs964184; ZNF259 rs12286037; CETP rs3764261; APOE-C1-C4-C2 rs4420638) in our Asian Indian cohort from the Sikh Diabetes Study (SDS) comprising 3,781 individuals (2,902 from Punjab and 879 from the US). Two of the six SNPs examined showed convincing replication in these populations of Asian Indian origin. Our study confirmed a strong association of CETP rs3764261 with high-density lipoprotein cholesterol (HDL-C) (p = 2.03×10⁻²⁶). Our results also showed significant associations of two GWAS SNPs (rs964184 and rs12286037) from BUD13-ZNF259 near the APOA5-A4-C3-A1 genes with triglyceride (TG) levels in this Asian Indian cohort (rs964184: p = 1.74×10⁻¹⁷; rs12286037: p = 1.58×10⁻²). We further explored 45 SNPs in a ∼195 kb region within the chromosomal region 11q23.3 (encompassing the BUD13-ZNF259, APOA5-A4-C3-A1, and SIK3 genes) in 8,530 Asian Indians from the London Life Sciences Population (LOLIPOP) (UK) and SDS cohorts. Five more SNPs revealed significant associations with TG in both cohorts individually as well as in a joint meta-analysis. However, the strongest signal for TG remained with BUD13-ZNF259 (rs964184: p = 1.06×10⁻³⁹). Future targeted deep sequencing and functional studies should enhance our understanding of the clinical relevance of these genes in dyslipidemia and hypertriglyceridemia (HTG) and, consequently, diabetes and CAD.

Conceptual approaches to the study of health disparities

Scientific and policy interest in health disparities, defined as systematic, plausibly avoidable health differences adversely affecting socially disadvantaged groups, has increased markedly over the past few decades. Like other research, research in health disparities is strongly influenced by the underlying conceptual model of the hypothetical causes of disparities. Conceptual models are important and a major source of debate because multiple types of factors and processes may be involved in generating disparities, because different disciplines emphasize different types of factors, and because the conceptual model often drives what is studied, how results are interpreted, and which interventions are identified as most promising. This article reviews common conceptual approaches to health disparities including the genetic model, the fundamental cause model, the pathways model, and the interaction model. Strengths and limitations of the approaches are highlighted. The article concludes by outlining key elements and implications of an integrative systems-based conceptual model.

Genome-wide association study of body height in African Americans: the Women's Health Initiative SNP Health Association Resource (SHARe)

Height is a complex trait under strong genetic influence. To date, numerous genetic loci have been associated with height in individuals of European ancestry. However, few large-scale discovery genome-wide association studies (GWAS) of height in minority populations have been conducted and thus information about population-specific height regulation is limited. We conducted a GWA analysis of height in 8149 African-American (AA) women from the Women's Health Initiative. Genetic variants with P< 5 × 10(-5) (n = 169) were followed up in a replication data set (n = 20 809) and meta-analyzed in a total of 28 958 AAs and African-descent individuals. Twelve single-nucleotide polymorphisms (SNPs) representing 7 independent loci were significantly associated with height at P < 5 × 10(-8). We identified novel SNPs in 17q23 (TMEM100/PCTP) and Xp22.3 (ARSE) reflecting population-specific regulation of height in AAs and replicated five loci previously reported in European-descent populations [4p15/LCORL, 11q13/SERPINH1, 12q14/HMGA2, 17q23/MAP3K3 (mitogen-activated protein kinase3) and 18q21/DYM]. In addition, we performed an admixture mapping analysis of height which is both complementary and supportive to the GWA analysis and suggests potential associations between ancestry and height on chromosomes 4 (4q21), 15 (15q26) and 17 (17q23). Our findings provide insight into the genetic architecture of height and support the investigation of non-European-descent populations for identifying genetic factors associated with complex traits. Specifically, we identify new loci that may reflect population-specific regulation of height and report several known height loci that are important in determining height in African-descent populations.

Multi-ethnic studies in complex traits

The successes of genome-wide association (GWA) studies have mainly come from studies performed in populations of European descent. Since complex traits are characterized by marked genetic heterogeneity, the findings so far may provide an incomplete picture of the genetic architecture of complex traits. However, the recent GWA studies performed on East Asian populations now allow us to globally assess the heterogeneity of association signals between populations of European ancestry and East Asians, and the possible obstacles for multi-ethnic GWA studies. We focused on four different traits that represent a broad range of complex phenotypes, which have been studied in both Europeans and East Asians: type 2 diabetes, systemic lupus erythematosus, ulcerative colitis and height. For each trait, we observed that most of the risk loci identified in East Asians were shared with Europeans. However, we also observed that a significant part of the association signals at these shared loci seems to be independent between populations. This suggests that disease aetiology is common between populations, but that risk variants are often population specific. These variants could be truly population specific and result from natural selection, genetic drift and recent mutations, or they could be spurious, caused by the limitations of the method of analysis employed in the GWA studies. We therefore propose a three-stage framework for multi-ethnic GWA analyses, starting with the commonly used single-nucleotide polymorphism-based analysis, and followed by a gene-based approach and a pathway-based analysis, which will take into account the heterogeneity of association between populations at different levels.

Implication of European-derived adiposity loci in African Americans

OBJECTIVE

Recent genome-wide association studies (GWAS) have identified multiple novel loci associated with adiposity in European-derived study populations. Limited study of these loci has been reported in African Americans. Here we examined the effects of these previously identified adiposity loci in African Americans.

METHODS

A total of 46 representative single-nucleotide polymorphisms (SNPs) in 19 loci that were previously reported in GWAS in Europeans (including FTO and MC4R) were genotyped in 4992 subjects from six African-American cohorts. These SNPs were tested for association with body mass index (BMI) after adjustment for age, gender, disease status and population structure in each cohort. Meta-analysis was conducted to combine the results.

RESULTS

Meta-analysis of 4992 subjects revealed seven SNPs near four loci, including NEGR1, TMEM18, SH2B1 /ATP2A1 and MC4R, showing significant association at 0.005<P<0.05, and had effect sizes between 0.04 and 0.06 s.d. units (or 0.30 to 0.44  g m(-2)) of BMI for each copy of the BMI-increasing allele. The most significantly associated SNPs (rs9424977, rs3101336 and rs2568958) are located in the NEGR1 gene (P=0.005, 0.020 and 0.019, respectively).

CONCLUSION

We replicated the association of variants at four loci in six African-American cohorts that demonstrated a consistent direction of association with previous studies of adiposity in Europeans. These loci are all highly expressed in the brain, consistent with an important role for central nervous system processes in weight regulation. However, further comprehensive examination of these regions may be necessary to fine map and elucidate for possible genetic differences between these two populations.

Differences in candidate gene association between European ancestry and African American asthmatic children

Background

Candidate gene case-control studies have identified several single nucleotide polymorphisms (SNPs) that are associated with asthma susceptibility. Most of these studies have been restricted to evaluations of specific SNPs within a single gene and within populations from European ancestry. Recently, there is increasing interest in understanding racial differences in genetic risk associated with childhood asthma. Our aim was to compare association patterns of asthma candidate genes between children of European and African ancestry.

Methodology/Principal Findings

Using a custom-designed Illumina SNP array, we genotyped 1,485 children within the Greater Cincinnati Pediatric Clinic Repository and Cincinnati Genomic Control Cohort for 259 SNPs in 28 genes and evaluated their associations with asthma. We identified 14 SNPs located in 6 genes that were significantly associated (p-values <0.05) with childhood asthma in African Americans. Among Caucasians, 13 SNPs in 5 genes were associated with childhood asthma. Two SNPs in IL4 were associated with asthma in both races (p-values <0.05). Gene-gene interaction studies identified race specific sets of genes that best discriminate between asthmatic children and non-allergic controls.

Conclusions/Significance

We identified IL4 as having a role in asthma susceptibility in both African American and Caucasian children. However, while IL4 SNPs were associated with asthma in asthmatic children with European and African ancestry, the relative contributions of the most replicated asthma-associated SNPs varied by ancestry. These data provides valuable insights into the pathways that may predispose to asthma in individuals with European vs. African ancestry.

Admixture mapping: from paradigms of race and ethnicity to population history

Admixture mapping is a whole genome association strategy that takes advantage of population history-or genetic ancestry-to map genes for complex diseases. However, because it uses racial/ethnic groupings to examine differential disease risk, admixture mapping raises ethical and social concerns. While there has been much theoretical commentary regarding the ethical and social implications of population-based genetic research, empirical data from stakeholders most closely involved with these studies is limited. One of the first admixture mapping studies carried out was a scan for Multiple Sclerosis (MS) risk factors in an African-American population. Applying qualitative research methods, we used this example to explore developing views, experiences and perceptions of the ethical and social implications of admixture mapping and other population-based research-their value, risks and benefits, and the future prospects of the field. Additionally, we sought to understand how social and ethical risks might be mitigated, and the benefits of this research optimized. We draw on in-depth, one-on-one interviews with leading population geneticists, genome scientists, bioethicists, and African-Americans with MS. Here we present our findings from this unique group of key informants and stakeholders.

The potential for enhancing the power of genetic association studies in African Americans through the reuse of existing genotype data

We consider the feasibility of reusing existing control data obtained in genetic association studies in order to reduce costs for new studies. We discuss controlling for the population differences between cases and controls that are implicit in studies utilizing external control data. We give theoretical calculations of the statistical power of a test due to Bourgain et al (Am J Human Genet 2003), applied to the problem of dealing with case-control differences in genetic ancestry related to population isolation or population admixture. Theoretical results show that there may exist bounds for the non-centrality parameter for a test of association that places limits on study power even if sample sizes can grow arbitrarily large. We apply this method to data from a multi-center, geographically-diverse, genome-wide association study of breast cancer in African-American women. Our analysis of these data shows that admixture proportions differ by center with the average fraction of European admixture ranging from approximately 20% for participants from study sites in the Eastern United States to 25% for participants from West Coast sites. However, these differences in average admixture fraction between sites are largely counterbalanced by considerable diversity in individual admixture proportion within each study site. Our results suggest that statistical correction for admixture differences is feasible for future studies of African-Americans, utilizing the existing controls from the African-American Breast Cancer study, even if case ascertainment for the future studies is not balanced over the same centers or regions that supplied the controls for the current study.

This paper discusses and provides unique insight into an important problem raised by the current state of genetic studies into disease susceptibility, namely whether we can reuse genetic data from participants genotyped as controls in one study when cases (people with a disease of interest) are obtained from other studies, or whether each new study needs its own controls. We are interested in whether studies where cases and controls are sampled differently will give correct answers and are as powerful statistically as when new control data is also genotyped. Because of the huge investments made recently in large scale genotyping of cases and controls for various diseases, this is a timely question. This question is especially important in understanding the genetic causes of disease in as-yet relatively understudied population groups, such as African-Americans, in order to speed up progress when this is possible. We give theoretical results about the power of studies that reuse existing control genotypes based on statistical considerations. We also provide analysis of real data from a major study of the genetic causes of breast cancer in African-American women in order to shed practical light upon this issue.

Genetics of focal segmental glomerulosclerosis and human immunodeficiency virus-associated collapsing glomerulopathy: the role of MYH9 genetic variation

Until recently, knowledge of genetic causes of glomerular disease was limited to certain rare or uncommon inherited diseases, and to genes, either rare or with small effect, identified in candidate gene studies. These genetic factors accounted for only a very small fraction of kidney disease. However, the striking differences in frequency of many forms of kidney disease between African Americans and European Americans, which could not be explained completely by cultural or economic factors, pointed to a large unidentified genetic influence. Because focal segmental glomerulosclerosis (FSGS) and human immunodeficiency virus-associated collapsing glomerulopathy have striking racial disparities, we performed an admixture mapping study to identify contributing genetic factors. Admixture mapping identified genetic variants in the nonmuscle myosin heavy chain 9 gene (MYH9) as having a major influence on both FSGS and human immunodeficiency virus-associated collapsing glomerulopathy, with odds ratios from 4 to 8 and attributable fractions of 70% to 100%. Previously identified, rare, inherited MYH9 disorders point to a mechanism by which MYH9 variation disrupts the actin-myosin filaments responsible for maintaining the structure of podocytes, the cells that provide one of three filtration barriers in the glomeruli. MYH9 variation has a smaller but still highly significant effect on nondiabetic kidney disease, and a weaker but significant effect on diabetic kidney disease; it is unclear whether underlying cryptic FSGS is responsible for the MYH9 association with these diseases. The strong predicted power of MYH9 variation for disease indicates a clear role for genetic testing for these variants in personalized medicine, for assessment of genetic risk, and potentially for diagnosis.

Genome-wide association studies in diverse populations

Genome-wide association (GWA) studies have identified a large number of SNPs associated with disease phenotypes. As most GWA studies have been performed in populations of European descent, this Review examines the issues involved in extending the consideration of GWA studies to diverse worldwide populations. Although challenges exist with issues such as imputation, admixture and replication, investigation of a greater diversity of populations could make substantial contributions to the goal of mapping the genetic determinants of complex diseases for the human population as a whole.

Fine mapping of the association with obesity at the FTO locus in African-derived populations

Genome-wide association studies have identified many common genetic variants that are associated with polygenic traits, and have typically been performed with individuals of recent European ancestry. In these populations, many common variants are tightly correlated, with the perfect or near-perfect proxies for the functional or true variant showing equivalent evidence of association, considerably limiting the resolution of fine mapping. Populations with recent African ancestry often have less extensive and/or different patterns of linkage disequilibrium (LD), and have been proposed to be useful in fine-mapping studies. Here, we strongly replicate and fine map in populations of predominantly African ancestry the association between variation at the FTO locus and body mass index (BMI) that is well established in populations of European ancestry. We genotyped single nucleotide polymorphisms that are correlated with the signal of association in individuals of European ancestry but that have varying degrees of correlation in African-derived individuals. Most of the variants, including one previously proposed as functionally important, have no significant association with BMI, but two variants, rs3751812 and rs9941349, show strong evidence of association (P = 2.58 x 10(-6) and 3.61 x 10(-6) in a meta-analysis of 9881 individuals). Thus, we have both strongly replicated this association in African-ancestry populations and narrowed the list of potentially causal variants to those that are correlated with rs3751812 and rs9941349 in African-derived populations. This study illustrates the potential of using populations with different LD patterns to fine map associations and helps pave the way for genetically guided functional studies at the FTO locus.

Genome-wide association of anthropometric traits in African- and African-derived populations

Genome-wide association (GWA) studies have identified common variants that are associated with a variety of traits and diseases, but most studies have been performed in European-derived populations. Here, we describe the first genome-wide analyses of imputed genotype and copy number variants (CNVs) for anthropometric measures in African-derived populations: 1188 Nigerians from Igbo-Ora and Ibadan, Nigeria, and 743 African-Americans from Maywood, IL. To improve the reach of our study, we used imputation to estimate genotypes at approximately 2.1 million single-nucleotide polymorphisms (SNPs) and also tested CNVs for association. No SNPs or common CNVs reached a genome-wide significance level for association with height or body mass index (BMI), and the best signals from a meta-analysis of the two cohorts did not replicate in approximately 3700 African-Americans and Jamaicans. However, several loci previously confirmed in European populations showed evidence of replication in our GWA panel of African-derived populations, including variants near IHH and DLEU7 for height and MC4R for BMI. Analysis of global burden of rare CNVs suggested that lean individuals possess greater total burden of CNVs, but this finding was not supported in an independent European population. Our results suggest that there are not multiple loci with strong effects on anthropometric traits in African-derived populations and that sample sizes comparable to those needed in European GWA studies will be required to identify replicable associations. Meta-analysis of this data set with additional studies in African-ancestry populations will be helpful to improve power to detect novel associations.

Human studies on genetics of the age at natural menopause: a systematic review

BACKGROUND Timing of natural menopause has great implications for fertility and women's health. Age at natural menopause (ANM) is largely influenced by genetic factors. In the past decade, several genetic studies have been conducted to identify genes in ANM, which can help us unravel the biological pathways underlying this trait and the associated infertility and health risks. After providing an overview of the results of the genetic studies performed so far, we give recommendations for future studies in identifying genetic factors involved in determining the variation in timing of natural menopause. METHODS The electronic databases of Pubmed and Embase were systematically searched until September 2009 for genetic studies on ANM, using relevant keywords on the subject. Additional papers identified through hand search were also included. RESULTS Twenty-eight papers emerged from our literature search. A number of genetic regions and variants involved in several possible pathways underlying timing of ANM were identified, including two possible interesting regions (9q21.3 and chromosome 8 at 26 cM) in linkage analyses. Recent genome-wide association studies have identified two genomic regions (19q13.42 and 20p12.3), containing two promising candidate genes (BRKS1 and MCM). In the candidate gene association studies on ANM, very few consistent associations were found. CONCLUSION A number of genetic variants have been discovered in association with ANM, although the overall results have been rather disappointing. We have described possible new strategies for future genetic studies to identify more genetic loci involved in the variation in menopausal age.

Genome-wide association study identifies ALDH7A1 as a novel susceptibility gene for osteoporosis

Osteoporosis is a major public health problem. It is mainly characterized by low bone mineral density (BMD) and/or low-trauma osteoporotic fractures (OF), both of which have strong genetic determination. The specific genes influencing these phenotypic traits, however, are largely unknown. Using the Affymetrix 500K array set, we performed a case-control genome-wide association study (GWAS) in 700 elderly Chinese Han subjects (350 with hip OF and 350 healthy matched controls). A follow-up replication study was conducted to validate our major GWAS findings in an independent Chinese sample containing 390 cases with hip OF and 516 controls. We found that a SNP, rs13182402 within the ALDH7A1 gene on chromosome 5q31, was strongly associated with OF with evidence combined GWAS and replication studies (P = 2.08×10⁻⁹, odds ratio = 2.25). In order to explore the target risk factors and potential mechanism underlying hip OF risk, we further examined this candidate SNP's relevance to hip BMD both in Chinese and Caucasian populations involving 9,962 additional subjects. This SNP was confirmed as consistently associated with hip BMD even across ethnic boundaries, in both Chinese and Caucasians (combined P = 6.39×10⁻⁶), further attesting to its potential effect on osteoporosis. ALDH7A1 degrades and detoxifies acetaldehyde, which inhibits osteoblast proliferation and results in decreased bone formation. Our findings may provide new insights into the pathogenesis of osteoporosis.

Osteoporosis is a major health concern worldwide. It is a highly heritable disease characterized mainly by low bone mineral density (BMD) and/or osteoporotic fractures. However, the specific genetic variants determining risk for low BMD or OF are largely unknown. Here, taking advantage of recent technological advances in human genetics, we performed a genome-wide association study and follow-up validation studies to identify genetic variants for osteoporosis. By examining a total of 11,568 individuals from Chinese and Caucasian populations, we discovered a susceptibility gene, ALDH7A1, which is associated with hip osteoporotic fracture and BMD. ALDH7A1 might inhibit osteoblast proliferation and decrease bone formation. Our finding opens a new avenue for exploring the pathophysiology of osteoporosis.

Transferability and fine-mapping of genome-wide associated loci for adult height across human populations

Human height is the prototypical polygenic quantitative trait. Recently, several genetic variants influencing adult height were identified, primarily in individuals of East Asian (Chinese Han or Korean) or European ancestry. Here, we examined 152 genetic variants representing 107 independent loci previously associated with adult height for transferability in a well-powered sample of 1,016 unrelated African Americans. When we tested just the reported variants originally identified as associated with adult height in individuals of East Asian or European ancestry, only 8.3% of these loci transferred (p-values≤0.05 under an additive genetic model with directionally consistent effects) to our African American sample. However, when we comprehensively evaluated all HapMap variants in linkage disequilibrium (r²≥0.3) with the reported variants, the transferability rate increased to 54.1%. The transferability rate was 70.8% for associations originally reported as genome-wide significant and 38.0% for associations originally reported as suggestive. An additional 23 loci were significantly associated but failed to transfer because of directionally inconsistent effects. Six loci were associated with adult height in all three groups. Using differences in linkage disequilibrium patterns between HapMap CEU or CHB reference data and our African American sample, we fine-mapped these six loci, improving both the localization and the annotation of these transferable associations.

The relationship between imputation error and statistical power in genetic association studies in diverse populations

Genotype-imputation methods provide an essential technique for high-resolution genome-wide association (GWA) studies with millions of single-nucleotide polymorphisms. For optimal design and interpretation of imputation-based GWA studies, it is important to understand the connection between imputation error and power to detect associations at imputed markers. Here, using a 2x3 chi-square test, we describe a relationship between genotype-imputation error rates and the sample-size inflation required for achieving statistical power at an imputed marker equal to that obtained if genotypes at the marker were known with certainty. Surprisingly, typical imputation error rates (approximately 2%-6%) lead to a large increase in the required sample size (approximately 10%-60%), and in some African populations whose genotypes are particularly difficult to impute, the required sample-size increase is as high as approximately 30%-150%. In most populations, each 1% increase in imputation error leads to an increase of approximately 5%-13% in the sample size required for maintaining power. These results imply that in GWA sample-size calculations investigators will need to account for a potentially considerable loss of power from even low levels of imputation error and that development of additional genomic resources that decrease imputation error will translate into substantial reduction in the sample sizes needed for imputation-based detection of the variants that underlie complex human diseases.

Correcting for cryptic relatedness in population-based association studies of continuous traits

Cryptic relatedness was suggested to be an important source of confounding in population-based association studies (PBAS). The magnitude and manner of cryptic relatedness affecting the performance of PBAS of continuous traits remain to be investigated. We simulated a set of related samples through biased sampling and inbreeding, and evaluated the power and type I error rates of simple association tests (SAT) without correcting for cryptic relatedness. We also used extended likelihood ratio tests (ELRT) to conduct PBAS accounting for cryptic relatedness, and compared it with genomic control (GC). Cryptic relatedness decreased the power as well as increased the type I error rates of SAT in both biased sampling and inbreeding models. The impact of cryptic relatedness on the performance of SAT appeared to be limited in the biased sampling model. However, cryptic relatedness in inbred populations may result in excessive false positive results of SAT. Compared with SAT and GC, ELRT obtained improved power and type I error rates under various scenarios. Ignoring cryptic relatedness may increase spurious association results in PBAS. Our ELRT provides a novel approach to control cryptic relatedness in PBAS of human continuous traits.

Planning for translational research in genomics

Translation of research findings into clinical practice is an important aspect of medical progress. Even for the early stages of genomics, research aiming to deepen understandings of underlying mechanisms of disease, questions about the ways in which such research ultimately can be useful in medical treatment and public health are of key importance. Whilst some research data may not apparently lend themselves to immediate clinical benefit, being aware of the issues surrounding translation at an early stage can enhance the delivery of the research to the clinic if a medical application is later found. When simple steps are taken during initial project planning, the pathways towards the translation of genomic research findings can be managed to optimize long-term benefits to health. This piece discusses the key areas of collaboration agreements, distribution of revenues and recruitment and sample collection that are increasingly important to successful translational research in genomics.