Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium

Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants

Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.

Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study

AIMS/HYPOTHESIS

Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.

METHODS

We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.

RESULTS

Four novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.

CONCLUSIONS/INTERPRETATION

Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.

DATA AVAILABILITY

Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).

Rs864745 in JAZF1, an Islet Function Associated Variant, Correlates With Plasma Lipid Levels in Both Type 1 and Type 2 Diabetes Status, but Not Healthy Subjects

OBJECTIVE

This study aims to reveal the association between JAZF1 rs864745 A>G variant and type 2 diabetes (T2D), type 1 diabetes (T1D) risk, and their correlation with clinical features, including islet function, islet autoimmunity, and plasma lipid levels.

METHODS

We included 2505 healthy controls based on oral glucose tolerance test (OGTT), 1736 unrelated T2D, and 1003 unrelated autoantibody-positive T1D individuals. Binary logistic regression was performed to evaluate the relationships between rs864745 in JAZF1 and T2D, T1D, and islet-specific autoantibody status under the additive model, while multiple linear regression was used to assess its effect on glycemic-related quantitative traits and plasma lipid levels.

RESULTS

We did not find any association between rs864745 in JAZF1 and T2D, T1D, or their subgroups (All P > 0.05). For glycemic traits, we found that the G allele of this variant was significantly associated with higher 120 min insulin level, insulinogenic index (IGI), corrected insulin response (CIR), and acute insulin response (BIGTT-AIR) (P = 0.033, 0.006, 0.009, and 0.016, respectively) in healthy individuals. Similar associations were observed in newly diagnosed T2D but not T1D individuals. Although this variant had no impact on islet autoimmunity (All P > 0.05), significant associations with plasma total cholesterol (TC) and low-density lipoprotein (LDL) level stratified by JAZF1 rs864745 variant were observed in the disease status of T2D (P = 0.002 and 0.003) and T1D (P = 0.024 and 0.009), with significant heterogeneity to healthy individuals.

CONCLUSIONS

The common JAZF1 rs864745 variant contributes to islet function and lipid metabolism, which might be put into genetic risk scores to assess the risk of related clinical features.

Genetic discovery and risk characterization in type 2 diabetes across diverse populations

Genomic discovery and characterization of risk loci for type 2 diabetes (T2D) have been conducted primarily in individuals of European ancestry. We conducted a multiethnic genome-wide association study of T2D among 53,102 cases and 193,679 control subjects from African, Hispanic, Asian, Native Hawaiian, and European population groups in the Population Architecture Genomics and Epidemiology (PAGE) and Diabetes Genetics Replication and Meta-analysis (DIAGRAM) Consortia. In individuals of African ancestry, we discovered a risk variant in the TGFB1 gene (rs11466334, risk allele frequency (RAF) = 6.8%, odds ratio [OR] = 1.27, p = 2.06 × 10⁻⁸), which replicated in independent studies of African ancestry (p = 6.26 × 10⁻²³). We identified a multiethnic risk variant in the BACE2 gene (rs13052926, RAF = 14.1%, OR = 1.08, p = 5.75 × 10⁻⁹), which also replicated in independent studies (p = 3.45 × 10⁻⁴). We also observed a significant difference in the performance of a multiethnic genetic risk score (GRS) across population groups (p_{heterogeneity} = 3.85 × 10⁻²⁰). Comparing individuals in the top GRS risk category (40%–60%), the OR was highest in Asians (OR = 3.08) and European (OR = 2.94) ancestry populations, followed by Hispanic (OR = 2.39), Native Hawaiian (OR = 2.02), and African ancestry (OR = 1.57) populations. These findings underscore the importance of genetic discovery and risk characterization in diverse populations and the urgent need to further increase representation of non-European ancestry individuals in genetics research to improve genetic-based risk prediction across populations.

Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population

While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.

Genomics of disease risk in globally diverse populations

Risk of disease is multifactorial and can be shaped by socio-economic, demographic, cultural, environmental and genetic factors. Our understanding of the genetic determinants of disease risk has greatly advanced with the advent of genome-wide association studies (GWAS), which detect associations between genetic variants and complex traits or diseases by comparing populations of cases and controls. However, much of this discovery has occurred through GWAS of individuals of European ancestry, with limited representation of other populations, including from Africa, The Americas, Asia and Oceania. Population demography, genetic drift and adaptation to environments over thousands of years have led globally to the diversification of populations. This global genomic diversity can provide new opportunities for discovery and translation into therapies, as well as a better understanding of population disease risk. Large-scale multi-ethnic and representative biobanks and population health resources provide unprecedented opportunities to understand the genetic determinants of disease on a global scale.

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

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

Genetic Variants Related to Cardiometabolic Traits Are Associated to B Cell Function, Insulin Resistance, and Diabetes Among AmeriCan Indians: The Strong Heart Family Study

Background: Genetic research may inform underlying mechanisms for disparities in the burden of type 2 diabetes mellitus among American Indians. Our objective was to assess the association of genetic variants in cardiometabolic candidate genes with B cell dysfunction via HOMA-B, insulin resistance via HOMA-IR, and type 2 diabetes mellitus in the Strong Heart Family Study (SHFS).

Methods and Results: We examined the association of variants, previously associated with cardiometabolic traits (∼200,000 from Illumina Cardio MetaboChip), using mixed models of HOMA-B residuals corrected for HOMA-IR (cHOMA-B), log transformed HOMA-IR, and incident diabetes, adjusted for age, sex, population stratification, and familial relatedness. Center-specific estimates were combined using fixed effect meta-analyses. We used Bonferroni correction to account for multiple testing (P < 4.13 × 10⁻⁷). We also assessed the association between variants in candidate diabetes genes with these metabolic traits. We explored the top SNPs in an independent, replication sample from Southwestern Arizona. We identified significant associations with cHOMA-B for common variants at 26 loci of which 8 were novel (PRSS7, FCRL5, PEL1, LRP12, IGLL1, ARHGEF10, PARVA, FLJ16686). The most significant variant association with cHOMA-B was observed on chromosome 5 for an intergenic variant near PARP8 (rs2961831, P = 6.39 × 10⁻⁹). In the replication study, we found a signal at rs4607517 near GCK/YKT6 (P = 0.01). Variants near candidate diabetes genes (especially GCK and KCNQ1) were also nominally associated with HOMA-IR and cHOMA-B.

Conclusion: We identified variants at novel loci and confirmed those at known candidate diabetes loci associations for cHOMA-B. This study also provided evidence for association of variants at KCNQ2, CTNAA2, and KCNQ1with cHOMA-B among American Indians. Further studies are needed to account for the high heritability of diabetes among the American Indian participants of the SHFS cohort.

A novel TCF7L2 type 2 diabetes SNP identified from fine mapping in African American women

SNP rs7903146 in the Wnt pathway’s TCF7L2 gene is the variant most significantly associated with type 2 diabetes to date, with associations observed across diverse populations. We sought to determine whether variants in other Wnt pathway genes are also associated with this disease. We evaluated 69 genes involved in the Wnt pathway, including TCF7L2, for associations with type 2 diabetes in 2632 African American cases and 2596 controls from the Black Women’s Health Study. Tag SNPs for each gene region were genotyped on a custom Affymetrix Axiom Array, and imputation was performed to 1000 Genomes Phase 3 data. Gene-based analyses were conducted using the adaptive rank truncated product (ARTP) statistic. The PSMD2 gene was significantly associated with type 2 diabetes after correction for multiple testing (corrected p = 0.016), based on the nine most significant single variants in the +/- 20 kb region surrounding the gene, which includes nearby genes EIF4G1, ECE2, and EIF2B5. Association data on four of the nine variants were available from an independent sample of 8284 African American cases and 15,543 controls; associations were in the same direction, but weak and not statistically significant. TCF7L2 was the only other gene associated with type 2 diabetes at nominal p <0.01 in our data. One of the three variants in the best gene-based model for TCF7L2, rs114770437, was not correlated with the GWAS index SNP rs7903146 and may represent an independent association signal seen only in African ancestry populations. Data on this SNP were not available in the replication sample.

Type 2 Diabetes Risk Allele Loci in the Qatari Population

Background

The prevalence of type 2 diabetes (T2D) is increasing in the Middle East. However, the genetic risk factors for T2D in the Middle Eastern populations are not known, as the majority of studies of genetic risk for T2D are in Europeans and Asians.

Methods

All subjects were ≥3 generation Qataris. Cases with T2D (n = 1,124) and controls (n = 590) were randomly recruited and assigned to the 3 known Qatari genetic subpopulations [Bedouin (Q1), Persian/South Asian (Q2) and African (Q3)]. Subjects underwent genotyping for 37 single nucleotide polymorphisms (SNPs) in 29 genes known to be associated with T2D in Europeans and/or Asian populations, and an additional 27 tag SNPs related to these susceptibility loci. Pre-study power analysis suggested that with the known incidence of T2D in adult Qataris (22%), the study population size would be sufficient to detect significant differences if the SNPs were risk factors among Qataris, assuming that the odds ratio (OR) for T2D SNPs in Qatari’s is greater than or equal to the SNP with highest known OR in other populations.

Results

Haplotype analysis demonstrated that Qatari haplotypes in the region of known T2D risk alleles in Q1 and Q2 genetic subpopulations were similar to European haplotypes. After Benjamini-Hochberg adjustment for multiple testing, only two SNPs (rs7903146 and rs4506565), both associated with transcription factor 7-like 2 (TCF7L2), achieved statistical significance in the whole study population. When T2D subjects and control subjects were assigned to the known 3 Qatari subpopulations, and analyzed individually and with the Q1 and Q2 genetic subpopulations combined, one of these SNPs (rs4506565) was also significant in the admixed group. No other SNPs associated with T2D in all Qataris or individual genetic subpopulations.

Conclusions

With the caveats of the power analysis, the European/Asian T2D SNPs do not contribute significantly to the high prevalence of T2D in the Qatari population, suggesting that the genetic risks for T2D are likely different in Qataris compared to Europeans and Asians.

Genetics of Type 2 Diabetes: the Power of Isolated Populations

Type 2 diabetes (T2D) affects millions of people worldwide. Improving the understanding of the underlying mechanisms and ultimately improving the treatment strategies are, thus, of great interest. To achieve this, identification of genetic variation predisposing to T2D is important. A large number of variants have been identified in large outbred populations, mainly from Europe and Asia. However, to elucidate additional variation, isolated populations have a number of advantageous properties, including increased amounts of linkage disequilibrium, and increased probability for presence of high frequency disease-associated variants due to genetic drift. Collectively, this increases the statistical power to detect association signals in isolated populations compared to large outbred populations. In this review, we elaborate on why isolated populations are a powerful resource for the identification of complex disease variants and describe their contributions to the understanding of the genetics of T2D.

Polygenic risk for type 2 diabetes mellitus among individuals with psychosis and their relatives

BACKGROUND

An elevated prevalence of Type 2 diabetes (T2D) has been observed in people with psychotic disorders and their relatives compared to the general population. It is not known whether this population also has increased genetic risk for T2D.

METHODS

Subjects included probands with schizophrenia, schizoaffective disorder, or psychotic bipolar I disorder, their first-degree relatives without psychotic disorders, and healthy controls, who participated in the Bipolar Schizophrenia Network for Intermediate Phenotypes study. We constructed sets of polygenic risk scores for T2D (PGRST2D) and schizophrenia (PGRSSCHIZ) using publicly available data from genome-wide association studies. We then explored the correlation of PGRST2D with psychiatric proband or relative status, and with self-reported diabetes. Caucasians and African-Americans were analyzed separately. We also evaluated correlations between PGRSSCHIZ and diabetes mellitus among Caucasian probands and their relatives.

RESULTS

In Caucasians, PGRST2D was correlated with self-reported diabetes mellitus within probands, but was not correlated with proband or relative status in the whole sample. In African-Americans, a PGRST2D based on selected risk alleles for T2D in this population did not correlate with proband or relative status. PGRSSCHIZ was not correlated with self-reported diabetes within Caucasian probands.

CONCLUSION

Differences in polygenic risk for T2D do not explain the increased prevalence of diabetes mellitus observed in psychosis probands and their relatives.

Genome-Wide Studies of Type 2 Diabetes and Lipid Traits in Hispanics

Although disproportionately affected by increasing rates of type 2 diabetes and dyslipidemias, Hispanic populations are underrepresented in efforts to understand genetic susceptibility to these disorders. Where research has been undertaken, these populations have provided substantial insight into identification of novel risk-associated genes and have aided in the ability to fine map previously described risk loci. Genome-wide analyses in Hispanic and trans-ethnic populations have resulted in identification of more than 40 replicated or novel genes with significant effects for type 2 diabetes or lipid traits. Initial investigations into rare variant effects have identified new risk-associated variants private to Hispanic populations, and preliminary results suggest metagenomic approaches in Hispanic populations, such as characterizing the gut microbiome, will enable the development of new predictive tools and therapeutic targets for type 2 diabetes. Future genome-wide studies in expanded cohorts of Hispanics are likely to result in new insights into the genetic etiology of metabolic health.

Cryptic relatedness in epidemiologic collections accessed for genetic association studies: experiences from the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study and the National Health and Nutrition Examination Surveys (NHANES)

Epidemiologic collections have been a major resource for genotype-phenotype studies of complex disease given their large sample size, racial/ethnic diversity, and breadth and depth of phenotypes, traits, and exposures. A major disadvantage of these collections is they often survey households and communities without collecting extensive pedigree data. Failure to account for substantial relatedness can lead to inflated estimates and spurious associations. To examine the extent of cryptic relatedness in an epidemiologic collection, we as the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessed the National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples ("Genetic NHANES") from NHANES III and NHANES 1999-2002. NHANES are population-based cross-sectional surveys conducted by the National Center for Health Statistics at the Centers for Disease Control and Prevention. Genome-wide genetic data is not yet available in NHANES, and current data use agreements prohibit the generation of GWAS-level data in NHANES samples due issues in maintaining confidentiality among other ethical concerns. To date, only hundreds of single nucleotide polymorphisms (SNPs) genotyped in a variety of candidate genes are available for analysis in NHANES. We performed identity-by-descent (IBD) estimates in three self-identified subpopulations of Genetic NHANES (non-Hispanic white, non- Hispanic black, and Mexican American) using PLINK software to identify potential familial relationships from presumed unrelated subjects. We then compared the PLINKidentified relationships to those identified by an alternative method implemented in Kinship-based INference for Genome-wide association studies (KING). Overall, both methods identified familial relationships in NHANES III and NHANES 1999-2002 for all three subpopulations, but little concordance was observed between the two methods due in major part to the limited SNP data available in Genetic NHANES. Despite the lack of genome-wide data, our results suggest the presence of cryptic relatedness in this epidemiologic collection and highlight the limitations of restricted datasets such as NHANES in the context of modern day genetic epidemiology studies.

Genetics of Type 2 Diabetes in African Americans

Type 2 diabetes (T2D) is a global health problem showing substantial ethnic disparity in disease prevalence. African Americans have one of the highest prevalence of T2D in the USA but little is known about their genetic risks. This review summarizes the findings of genetic regions and loci associated with T2D and related glycemic traits using linkage, admixture, and association approaches in populations of African ancestry. In particular, findings from genome-wide association and exome chip studies suggest the presence of both ancestry-specific and shared loci for T2D and glycemic traits. Among the European-identified loci that are transferable to individuals of African ancestry, allelic heterogeneity as well as differential linkage disequilibrium and risk allele frequencies pose challenges and opportunities for fine mapping and identification of causal variant(s) by trans-ancestry meta-analysis. More genetic research is needed in African ancestry populations including the next-generation sequencing to improve the understanding of genetic architecture of T2D.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits

BACKGROUND/AIMS

Present-day limited resources demand DNA and phenotyping alternatives to the traditional prospective population-based epidemiologic collections.

METHODS

To accelerate genomic discovery with an emphasis on diverse populations, we--as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study--accessed all non-European American samples (n = 15,863) available in BioVU, the Vanderbilt University biorepository linked to de-identified electronic medical records, for genomic studies as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study. Given previous studies have cautioned against the secondary use of clinically collected data compared with epidemiologically collected data, we present here a characterization of EAGLE BioVU, including the billing and diagnostic (ICD-9) code distributions for adult and pediatric patients as well as comparisons made for select health metrics (body mass index, glucose, HbA1c, HDL-C, LDL-C, and triglycerides) with the population-based National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples (NHANES III, n = 7,159; NHANES 1999-2002, n = 7,839).

RESULTS

Overall, the distributions of billing and diagnostic codes suggest this clinical sample is a mixture of healthy and sick patients like that expected for a contemporary American population.

CONCLUSION

Little bias is observed among health metrics, suggesting this clinical collection is suitable for genomic studies along with traditional epidemiologic cohorts.

Uncovering physiological mechanisms for health disparities in type 2 diabetes

Type 2 diabetes (T2D) prevalence in the United States is significantly higher in African Americans vs Whites. Yet, the physiological mechanisms contributing to this health disparity have been poorly described. To design effective strategies to reduce this disparity, there is a need to determine whether racial differences in diabetes prevalence are attributable to modifiable or non-modifiable factors. This review synthesizes and critically evaluates the potential physiological and genetic mechanisms that may contribute to the higher susceptibility of African Americans to T2D. These mechanisms include: 1) obesity and fat distribution; 2) metabolic flexibility; 3) muscle physiology; 4) energy expenditure and fitness; and 5) genetics. We focus on the clinical significance of findings and limitations of the recent literature.

Association of JAZF1 and TSPAN8/LGR5 variants in relation to type 2 diabetes mellitus in a Saudi population

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a chronic and multifactorial disease with a rapidly rising incidence in Saudi Arabia. Various genes including zinc finger protein 1 (JAZF1) and tetraspanin 8/leucine-rich repeat-containing G protein-coupled receptor (TSPAN8/LGR5) have been previously described to be associated with T2DM. This study investigated the association of JAZF1 (rs864745) and TSPAN8 (rs7961581) with T2DM in a Saudi population.

METHODS

Genomic DNA samples from 400 Saudi T2DM patients and 400 healthy controls were genotyped and analyzed using a polymerase chain reaction-restriction fragment length polymorphism method. The difference between the genotype frequencies were carried out with Chi-square test. Odds ratio, 95 % confidence intervals and p values were calculated using multinomial logistic regression. Dominant and recessive models were implemented to show the statistical significances. Analysis of variance was used to compare differences between genotypes for the various parameters.

RESULTS

Distribution frequencies of the AA, AG, and GG genotypes of JAZF1 (rs864745) differed significantly among T2DM patients and healthy controls (p < 0.05). The AG and GG genotypes were independently and significantly associated with a T2DM risk after adjusting for factors such as age, sex, and body mass index [odds ratio (OR) 2.1 (95 % confidence interval (CI) 1.3-3.4); p = 0.002] and [OR 1.9 (95 % CI 1.2-3.1); p = 0.005], respectively. A genotype-based stratification of anthropometric and biochemical data revealed that the AG + GG genotype is associated with waist circumference (p = 0.04) and fasting blood glucose (p = 0.01) and high-density lipoprotein cholesterol levels (p = 0.02). None of the allele or genotype showed the significant association between the T2DM cases and control subjects in rs7961581 polymorphism in TSPAN8/LGR5 gene.

CONCLUSION

The rs864745 variant in JAZF1 gene may act as genetic risk factors for the development of T2DM in a Saudi population.

T2DM GWAS in the Lebanese population confirms the role of TCF7L2 and CDKAL1 in disease susceptibility

Genome-wide association studies (GWAS) of multiple populations with distinctive genetic and lifestyle backgrounds are crucial to the understanding of Type 2 Diabetes Mellitus (T2DM) pathophysiology. We report a GWAS on the genetic basis of T2DM in a 3,286 Lebanese participants. More than 5,000,000 SNPs were directly genotyped or imputed using the 1000 Genomes Project reference panels. We identify genome-wide significant variants in two loci CDKAL1 and TCF7L2, independent of sex, age and BMI, with leading variants rs7766070 (OR = 1.39, P = 4.77 × 10(-9)) and rs34872471 (OR = 1.35, P = 1.01 × 10(-8)) respectively. The current study is the first GWAS to find genomic regions implicated in T2DM in the Lebanese population. The results support a central role of CDKAL1 and TCF7L2 in T2DM susceptibility in Southwest Asian populations and provide a plausible component for understanding molecular mechanisms involved in the disease.

Evidence of heterogeneity by race/ethnicity in genetic determinants of QT interval

BACKGROUND

QT interval (QT) prolongation is an established risk factor for ventricular tachyarrhythmia and sudden cardiac death. Previous genome-wide association studies in populations of the European descent have identified multiple genetic loci that influence QT, but few have examined these loci in ethnically diverse populations.

METHODS

Here, we examine the direction, magnitude, and precision of effect sizes for 21 previously reported SNPs from 12 QT loci, in populations of European (n = 16,398), African (n = 5,437), American Indian (n = 5,032), Hispanic (n = 1,143), and Asian (n = 932) descent as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Estimates obtained from linear regression models stratified by race/ethnicity were combined using inverse-variance weighted meta-analysis. Heterogeneity was evaluated using Cochran's Q test.

RESULTS

Of 21 SNPs, 7 showed consistent direction of effect across all 5 populations, and an additional 9 had estimated effects that were consistent across 4 populations. Despite consistent direction of effect, 9 of 16 SNPs had evidence (P < 0.05) of heterogeneity by race/ethnicity. For these 9 SNPs, linkage disequilibrium plots often indicated substantial variation in linkage disequilibrium patterns among the various racial/ethnic groups, as well as possible allelic heterogeneity.

CONCLUSIONS

These results emphasize the importance of analyzing racial/ethnic groups separately in genetic studies. Furthermore, they underscore the possible utility of trans-ethnic studies to pinpoint underlying casual variants influencing heritable traits such as QT.

A comparison of type 2 diabetes risk allele load between African Americans and European Americans

The prevalence of type 2 diabetes (T2D) is greater in populations of African descent compared to European-descent populations. Genetic risk factors may underlie the disparity in disease prevalence. Genome-wide association studies (GWAS) have identified >60 common genetic variants that contribute to T2D risk in populations of European, Asian, African and Hispanic descent. These studies have not comprehensively examined population differences in cumulative risk allele load. To investigate the relationship between risk allele load and T2D risk, 46 T2D single nucleotide polymorphisms (SNPs) in 43 loci from GWAS in European, Asian, and African-derived populations were genotyped in 1,990 African Americans (n = 963 T2D cases, n = 1,027 controls) and 1,644 European Americans (n = 719 T2D cases, n = 925 controls) ascertained and recruited using a common protocol in the southeast United States. A genetic risk score (GRS) was constructed from the cumulative risk alleles for each individual. In African American subjects, risk allele frequencies ranged from 0.024 to 0.964. Risk alleles from 26 SNPs demonstrated directional consistency with previous studies, and 3 SNPs from ADAMTS9, TCF7L2, and ZFAND6 showed nominal evidence of association (p < 0.05). African American individuals carried 38-67 (53.7 ± 4.0, mean ± SD) risk alleles. In European American subjects, risk allele frequencies ranged from 0.084 to 0.996. Risk alleles from 36 SNPs demonstrated directional consistency, and 10 SNPs from BCL11A, PSMD6, ADAMTS9, ZFAND3, ANK1, CDKN2A/B, TCF7L2, PRC1, FTO, and BCAR1 showed evidence of association (p < 0.05). European American individuals carried 38-65 (50.9 ± 4.4) risk alleles. African Americans have a significantly greater burden of 2.8 risk alleles (p = 3.97 × 10(-89)) compared to European Americans. However, GRS modeling showed that cumulative risk allele load was associated with risk of T2D in European Americans, but only marginally in African Americans. This result suggests that there are ethnic-specific differences in genetic architecture underlying T2D, and that these differences complicate our understanding of how risk allele load impacts disease susceptibility.

Association of African genetic ancestry with fasting glucose and HbA1c levels in non-diabetic individuals: the Boston Area Community Health (BACH) Prediabetes Study

AIMS/HYPOTHESIS

To test among diabetes-free urban community-dwelling adults the hypothesis that the proportion of African genetic ancestry is positively associated with glycaemia, after accounting for other continental ancestry proportions, BMI and socioeconomic status (SES).

METHODS

The Boston Area Community Health cohort is a multi-stage 1:1:1 stratified random sample of self-identified African-American, Hispanic and white adults from three Boston inner city areas. We measured 62 ancestry informative markers, fasting glucose (FG), HbA1c, BMI and SES (income, education, occupation and insurance status) and analysed 1,387 eligible individuals (379 African-American, 411 Hispanic, 597 white) without clinical or biochemical evidence of diabetes. We used three-heritage multinomial linear regression models to test the association of FG or HbA1c with genetic ancestry proportion adjusted for: (1) age and sex; (2) age, sex and BMI; and (3) age, sex, BMI and SES.

RESULTS

Mean age- and sex-adjusted FG levels were 5.73 and 5.54 mmol/l among those with 100% African or European ancestry, respectively. Using per cent European ancestry as the referent, each 1% increase in African ancestry proportion was associated with an age- and sex-adjusted FG increase of 0.0019 mmol/l (p = 0.01). In the BMI- and SES-adjusted model the slope was 0.0019 (p = 0.02). Analysis of HbA1c gave similar results.

CONCLUSIONS/INTERPRETATION

A greater proportion of African genetic ancestry is independently associated with higher FG levels in a non-diabetic community-based cohort, even accounting for other ancestry proportions, obesity and SES. The results suggest that differences between African-Americans and whites in type 2 diabetes risk may include genetically mediated differences in glucose homeostasis.

SecureMA: protecting participant privacy in genetic association meta-analysis

MOTIVATION

Sharing genomic data is crucial to support scientific investigation such as genome-wide association studies. However, recent investigations suggest the privacy of the individual participants in these studies can be compromised, leading to serious concerns and consequences, such as overly restricted access to data.

RESULTS

We introduce a novel cryptographic strategy to securely perform meta-analysis for genetic association studies in large consortia. Our methodology is useful for supporting joint studies among disparate data sites, where privacy or confidentiality is of concern. We validate our method using three multisite association studies. Our research shows that genetic associations can be analyzed efficiently and accurately across substudy sites, without leaking information on individual participants and site-level association summaries.

AVAILABILITY AND IMPLEMENTATION

Our software for secure meta-analysis of genetic association studies, SecureMA, is publicly available at http://github.com/XieConnect/SecureMA. Our customized secure computation framework is also publicly available at http://github.com/XieConnect/CircuitService.

Genetic architecture of type 2 diabetes

Genome-wide association studies (GWAS) have identified over 70 loci associated with type 2 diabetes (T2D). Most genetic variants associated with T2D are common variants with modest effects on T2D and are shared with major ancestry groups. To what extent the genetic component of T2D can be explained by common variants relies upon the shape of the genetic architecture of T2D. Fine mapping utilizing populations with different patterns of linkage disequilibrium and functional annotation derived from experiments in relevant tissues are mandatory to track down causal variants responsible for the pathogenesis of T2D.

Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond

During the past 7 years, genome-wide association studies have shed light on the contribution of common genomic variants to the genetic architecture of type 2 diabetes, obesity and related intermediate phenotypes. The discoveries have firmly established more than 175 genomic loci associated with these phenotypes. Despite the tight correlation between type 2 diabetes and obesity, these conditions do not appear to share a common genetic background, since they have few genetic risk loci in common. The recent genetic discoveries do however highlight specific details of the interplay between the pathogenesis of type 2 diabetes, insulin resistance and obesity. The focus is currently shifting towards investigations of data from targeted array-based genotyping and exome and genome sequencing to study the individual and combined effect of low-frequency and rare variants in metabolic disease. Here we review recent progress as regards the concepts, methodologies and derived outcomes of studies of the genetics of type 2 diabetes and obesity, and discuss avenues to be investigated in the future within this research field.

Antiretroviral therapy modifies the genetic effect of known type 2 diabetes-associated risk variants in HIV-infected women

OBJECTIVE

Type 2 diabetes mellitus incidence is increased in HIV-infected persons. We examined the associations of diabetes mellitus with known diabetes mellitus-risk alleles from the general population in the context of HIV infection, and explored effect modification by combination antiretroviral therapy (cART).

METHODS

The Women's Interagency HIV Study is a prospective cohort of HIV-infected women. Seventeen European-derived diabetes mellitus-risk polymorphisms were genotyped in the eligible participants of the Women's Interagency HIV Study. Analyses were run separately for non-African Americans (Whites, Hispanics, Asians, and other; n = 378, 49 with incident diabetes mellitus) and African Americans (n = 591, 49 with incident diabetes mellitus). Cox proportional-hazards models were fit to estimate hazard ratios for diabetes mellitus overall and within strata of cART.

RESULTS

In non-African Americans, heterogeneity across cART regimen was observed for nine of the 14 polymorphisms (phet < 0.05). One polymorphism was statistically significantly inversely associated with diabetes mellitus risk among women taking two nucleotide reverse transcriptase inhibitors (NRTIs) + non-nucleotide reverse transcriptase inhibitor (NNRTI). Five polymorphisms were statistically significantly associated with diabetes mellitus among women treated with at least two NRTIs + at least one protease inhibitor and one polymorphism was associated with diabetes mellitus among those treated with at least three NRTIs ± NNRTI. The hazard ratio per risk allele for IGF2BP2 rs1470579 was 2.67 (95% confidence interval 1.67-4.31) for women taking cART with at least two NRTIs + at least one protease inhibitor and 2.45 (95% confidence interval 1.08-5.53) in women taking at least three NRTIs ± NNRTI (phet = 2.50 × 10⁻³). No such associations were observed in the African Americans.

CONCLUSIONS

Genetic susceptibility to diabetes mellitus, based on the variants studied, is substantially elevated among HIV-infected women using cART containing three or more NRTI/protease inhibitor components. A personalized medicine approach to cART selection may be indicated for HIV-infected persons carrying these diabetes mellitus-risk variants.

Gene-carbohydrate and gene-fiber interactions and type 2 diabetes in diverse populations from the National Health and Nutrition Examination Surveys (NHANES) as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study

Background

Both environmental and genetic factors impact type 2 diabetes (T2D). To identify such modifiers, we genotyped 15 T2D-associated variants from genome-wide association studies (GWAS) in 6,414 non-Hispanic whites, 3,073 non-Hispanic blacks, and 3,633 Mexican American participants from the National Health and Nutrition Examination Surveys (NHANES) and evaluated interactions between these variants and carbohydrate intake and fiber intake.

Results

We calculated a genetic risk score (GRS) with the 15 SNPs. The odds ratio for T2D with each GRS point was 1.10 (95% CI: 1.05-1.14) for non-Hispanic whites, 1.07 (95% CI: 1.02-1.13) for non-Hispanic blacks, and 1.11 (95% CI: 1.06-1.17) for Mexican Americans. We identified two gene-carbohydrate interactions (P < 0.05) in non-Hispanic whites (with CDKAL1 rs471253 and FTO rs8050136), two in non-Hispanic blacks (with IGFBP2 rs4402960 and THADA rs7578597), and two in Mexican Americans (with NOTCH2 rs1092398 and TSPAN8-LGRS rs7961581). We found three gene-fiber interactions in non-Hispanic whites (with ADAMT59 rs4607103, CDKN2A/2B rs1801282, and FTO rs8050136), two in non-Hispanic blacks (with ADAMT59 rs4607103 and THADA rs7578597), and two in Mexican Americans (with THADA rs7578597 and TSPAN8-LGRS rs796158) at the P < 0.05 level. Interactions between the GRS and nutrients failed to reach significance in all the racial/ethnic groups.

Conclusion

Our results suggest that dietary carbohydrates and fiber may modify T2D-associated variants, highlighting the importance of dietary nutrients in predicting T2D risk.

Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

Type 2 diabetes (T2D) is a common metabolic disorder which is caused by multiple genetic perturbations affecting different biological pathways. Identifying genetic factors modulating the susceptibility of this complex heterogeneous metabolic phenotype in different ethnic and racial groups remains challenging. Despite recent success, the functional role of the T2D susceptibility variants implicated by genome-wide association studies (GWAS) remains largely unknown. Genetic dissection of transcript abundance or expression quantitative trait (eQTL) analysis unravels the genomic architecture of regulatory variants. Availability of eQTL information from tissues relevant for glucose homeostasis in humans opens a new avenue to prioritize GWAS-implicated variants that may be involved in triggering a causal chain of events leading to T2D. In this article, we review the progress made in the field of eQTL research and knowledge gained from those studies in understanding transcription regulatory mechanisms in human subjects. We highlight several novel approaches that can integrate eQTL analysis with multiple layers of biological information to identify ethnic-specific causal variants and gene-environment interactions relevant to T2D pathogenesis. Finally, we discuss how the eQTL analysis mediated search for “missing heritability” may lead us to novel biological and molecular mechanisms involved in susceptibility to T2D.

Susceptibility to type 2 diabetes mellitus--from genes to prevention

Knowledge of the genetics of type 2 diabetes mellitus (T2DM) has evolved tremendously over the past few years. Following advances in technology and analytical approaches, collaborative case-control genome-wide association studies have revealed up to 65 loci credibly associated with T2DM. Prospective population studies have demonstrated that aggregated genetic risk scores, so-called because they sum the genetic risk attributed to each locus, can predict incident T2DM among individuals of various age ranges and diverse ethnic backgrounds. With each set of T2DM loci discovered, increasing the number of loci in these scores has improved their predictive ability, although a prediction plateau may already have been reached. The current literature shows that intensive lifestyle interventions are effective for preventing T2DM at any level of genetic risk and might be particularly efficacious among individuals with high genetic susceptibility. By contrast, counselling to inform patients about their personal T2DM genetic risk profiles does not seem to improve motivation or attitudes that lead to positive lifestyle behaviour changes. Future studies should investigate the role of genetics for both T2DM prediction and prevention in young populations in the hope of reducing disease burden for future generations.

Diabetes prevention in Hispanics: report from a randomized controlled trial

Introduction

Hispanics are at increased risk of developing type 2 diabetes. Lifestyle interventions are effective in preventing diabetes and restoring glucose regulation.

Methods

We recruited Hispanic men and women (N = 320) who were residents of the Lower Yakima Valley, Washington, aged 18 years or older with hemoglobin A1c (HbA1c) levels higher than 6% to a parallel 2-arm randomized-controlled trial conducted from 2008 through 2012. The trial compared participants in the intervention arm, who received an immediate educational curriculum (n = 166), to participants in the control arm, who received a delayed educational curriculum (n = 154). The home-based curriculum consisted of 5 sessions led by community health workers and was designed to inform participants about diabetes, diabetes treatment, and healthy dietary and physical activity behaviors. Participants were randomly assigned to the intervention and control arms, and analysts were blinded as to participant arm. We evaluated intervention effects on HbA1c levels; frequency (times per week) of fruit and vegetable consumption; and frequency (times per week) of mild, moderate, and strenuous leisure-time physical activity. At baseline, 3 months, and 6 months after randomization, participants completed a questionnaire and provided a blood sample. Analysts were blinded to intervention arm.

Results

The immediate intervention group (−0.64% [standard error (SE) 0.10]) showed a significant improvement in HbA1c scores (–37.5%, P = .04) compared with the delayed intervention group (–0.44%, P = .14). No significant changes were seen for dietary end points or changes in physical activity. We did observe a trend of greater increases in frequency of moderate and vigorous physical activity and a smaller increase in mild physical activity in the immediate intervention group than in the delayed intervention group.

Conclusion

This home-based intervention delivered by CHWs was associated with a clinically and statistically significant reduction in HbA1c levels in Hispanic adults with HbA1c levels higher than 6%.

Environment-wide association study (EWAS) for type 2 diabetes in the Marshfield Personalized Medicine Research Project Biobank

Environment-wide association studies (EWAS) provide a way to uncover the environmental mechanisms involved in complex traits in a high-throughput manner. Genome-wide association studies have led to the discovery of genetic variants associated with many common diseases but do not take into account the environmental component of complex phenotypes. This EWAS assesses the comprehensive association between environmental variables and the outcome of type 2 diabetes (T2D) in the Marshfield Personalized Medicine Research Project Biobank (Marshfield PMRP). We sought replication in two National Health and Nutrition Examination Surveys (NHANES). The Marshfield PMRP currently uses four tools for measuring environmental exposures and outcome traits: 1) the PhenX Toolkit includes standardized exposure and phenotypic measures across several domains, 2) the Diet History Questionnaire (DHQ) is a food frequency questionnaire, 3) the Measurement of a Person's Habitual Physical Activity scores the level of an individual's physical activity, and 4) electronic health records (EHR) employs validated algorithms to establish T2D case-control status. Using PLATO software, 314 environmental variables were tested for association with T2D using logistic regression, adjusting for sex, age, and BMI in over 2,200 European Americans. When available, similar variables were tested with the same methods and adjustment in samples from NHANES III and NHANES 1999-2002. Twelve and 31 associations were identified in the Marshfield samples at p<0.01 and p<0.05, respectively. Seven and 13 measures replicated in at least one of the NHANES at p<0.01 and p<0.05, respectively, with the same direction of effect. The most significant environmental exposures associated with T2D status included decreased alcohol use as well as increased smoking exposure in childhood and adulthood. The results demonstrate the utility of the EWAS method and survey tools for identifying environmental components of complex diseases like type 2 diabetes. These high-throughput and comprehensive investigation methods can easily be applied to investigate the relation between environmental exposures and multiple phenotypes in future analyses.

A genome-wide association study in American Indians implicates DNER as a susceptibility locus for type 2 diabetes

Most genetic variants associated with type 2 diabetes mellitus (T2DM) have been identified through genome-wide association studies (GWASs) in Europeans. The current study reports a GWAS for young-onset T2DM in American Indians. Participants were selected from a longitudinal study conducted in Pima Indians and included 278 cases with diabetes with onset before 25 years of age, 295 nondiabetic controls ≥45 years of age, and 267 siblings of cases or controls. Individuals were genotyped on a ∼1M single nucleotide polymorphism (SNP) array, resulting in 453,654 SNPs with minor allele frequency >0.05. SNPs were analyzed for association in cases and controls, and a family-based association test was conducted. Tag SNPs (n = 311) were selected for 499 SNPs associated with diabetes (P < 0.0005 in case-control analyses or P < 0.0003 in family-based analyses), and these SNPs were genotyped in up to 6,834 additional Pima Indians to assess replication. Rs1861612 in DNER was associated with T2DM (odds ratio = 1.29 per copy of the T allele; P = 6.6 × 10(-8), which represents genome-wide significance accounting for the number of effectively independent SNPs analyzed). Transfection studies in murine pancreatic β-cells suggested that DNER regulates expression of notch signaling pathway genes. These studies implicate DNER as a susceptibility gene for T2DM in American Indians.

Replication of the effect of SLC2A9 genetic variation on serum uric acid levels in American Indians

Increased serum uric acid (SUA) or hyperuricemia, a risk factor for gout, renal and cardiovascular diseases, is caused by either increased production or decreased excretion of uric acid or a mix of both. The solute carrier protein 2 family, member 9 (SLC2A9) gene encodes a transporter that mediates urate flux across the renal proximal tubule. Genome-wide association studies have consistently shown the association of single-nucleotide polymorphisms in this gene with SUA in majority populations. American Indian participants of the Strong Heart Family Study, belonging to multigenerational families, have high prevalence of hyperuricemia. We conducted measured genotype analyses, based on variance components decomposition method and accounting for family relationships, to assess whether the association between SUA and SLC2A9 gene polymorphisms generalized to American Indians (n=3604) of this study. Seven polymorphisms were selected for genotyping based on their association with SUA levels in other populations. A strong association was found between SLC2A9 gene polymorphisms and SUA in all centers combined (P-values: 1.3 × 10(-31)-5.1 × 10(-23)) and also when stratified by recruitment center; P-values: 1.2 × 10(-14)-1.0 × 10(-5). These polymorphisms were also associated with the estimated glomerular filtration rate and serum creatinine but not albumin-creatinine ratio. In summary, the association of polymorphisms in the uric acid transporter gene with SUA levels extends to a new population of American Indians.

Population ancestry and genetic risk for diabetes and kidney, cardiovascular, and bone disease: modifiable environmental factors may produce the cures

Variable rates of disease observed between members of different continental population groups may be mediated by inherited factors, environmental exposures, or their combination. This article provides evidence in support of differential allele frequency distributions that underlie the higher rates of nondiabetic kidney disease in the focal segmental glomerulosclerosis spectrum of disease and lower rates of coronary artery calcified atherosclerotic plaque and osteoporosis in populations of African ancestry. With recognition that these and other common complex diseases are affected by biological factors comes the realization that targeted manipulation of environmental exposures and pharmacologic treatments will have different effects based on genotype. The present era of precision medicine will couple one's genetic makeup with specific therapies to reduce rates of disease based on the presence of disease-specific alleles.

Epidemiology and genetic determinants of progressive deterioration of glycaemia in American Indians: the Strong Heart Family Study

AIMS/HYPOTHESIS

Type 2 diabetes is a chronic, heterogeneous disease and a major risk factor for cardiovascular diseases. The underlying mechanisms leading to progression to type 2 diabetes are not fully understood and genetic tools may help to identify important pathways of glycaemic deterioration.

METHODS

Using prospective data on American Indians from the Strong Heart Family Study, we identified 373 individuals defined as progressors (diabetes incident cases), 566 individuals with transitory impaired fasting glucose (IFG) and 1,011 controls (normal fasting glycaemia at all visits). We estimated the heritability (h(2)) of the traits and the evidence for association with 16 known variants identified in type 2 diabetes genome-wide association studies.

RESULTS

We noted high h(2) for diabetes progression (h(2) = 0.65 ± 0.16, p = 2.7 × 10(-6)) but little contribution of genetic factors to transitory IFG (h(2) = 0.09 ± 0.10, p = 0.19) for models adjusted for multiple risk factors. At least three variants (in WFS1, TSPAN8 and THADA) were nominally associated with diabetes progression in age- and sex-adjusted analyses with estimates showing the same direction of effects as reported in the discovery European ancestry studies.

CONCLUSIONS/INTERPRETATION

Our findings do not exclude these loci for diabetes susceptibility in American Indians and suggest phenotypic heterogeneity of the IFG trait, which may have implications for genetic studies when diagnosis is based on a single time-point measure.

Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study

The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.

A genome-wide search for type 2 diabetes susceptibility genes in an extended Arab family

Twenty percent of people aged 20 to 79 have type 2 diabetes (T2D) in the United Arab Emirates (UAE). Genome-wide association studies (GWAS) to identify genes for T2D have not been reported for Arab countries. We performed a discovery GWAS in an extended UAE family (N=178; 66 diabetic; 112 healthy) genotyped on the Illumina Human 660 Quad Beadchip, with independent replication of top hits in 116 cases and 199 controls. Power to achieve genome-wide significance (commonly P=5×10(-8)) was therefore limited. Nevertheless, transmission disequilibrium testing in FBAT identified top hits at Chromosome 4p12-p13 (KCTD8: rs4407541, P=9.70×10(-6); GABRB1: rs10517178/rs1372491, P=4.19×10(-6)) and 14q13 (PRKD1: rs10144903, 3.92×10(-6)), supported by analysis using a linear mixed model approximation in GenABEL (4p12-p13 GABRG1/GABRA2: rs7662743, Padj-agesex=2.06×10(-5); KCTD8: rs4407541, Padj-agesex=1.42×10(-4); GABRB1: rs10517178/rs1372491, Padj-agesex=0.027; 14q13 PRKD1: rs10144903, Padj-agesex=6.95×10(-5)). SNPs across GABRG1/GABRA2 did not replicate, whereas more proximal SNPs rs7679715 (Padj-agesex=0.030) and rs2055942 (Padj-agesex=0.022) at COX7B2/GABRA4 did, in addition to a trend distally at KCTD8 (rs4695718: Padj-agesex=0.096). Modelling of discovery and replication data support independent signals at GABRA4 (rs2055942: Padj-agesex-combined=3×10(-4)) and at KCTD8 (rs4695718: Padj-agesex-combined=2×10(-4)). Replication was observed for PRKD1 rs1953722 (proxy for rs10144903; Padj-agesex=0.031; Padj-agesex-combined=2×10(-4)). These genes may provide important functional leads in understanding disease pathogenesis in this population.

Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.

Enabling high-throughput genotype-phenotype associations in the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) project as part of the Population Architecture using Genomics and Epidemiology (PAGE) study

Genetic association studies have rapidly become a major tool for identifying the genetic basis of common human diseases. The advent of cost-effective genotyping coupled with large collections of samples linked to clinical outcomes and quantitative traits now make it possible to systematically characterize genotype-phenotype relationships in diverse populations and extensive datasets. To capitalize on these advancements, the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) project, as part of the collaborative Population Architecture using Genomics and Epidemiology (PAGE) study, accesses two collections: the National Health and Nutrition Examination Surveys (NHANES) and BioVU, Vanderbilt University's biorepository linked to de-identified electronic medical records. We describe herein the workflows for accessing and using the epidemiologic (NHANES) and clinical (BioVU) collections, where each workflow has been customized to reflect the content and data access limitations of each respective source. We also describe the process by which these data are generated, standardized, and shared for meta-analysis among the PAGE study sites. As a specific example of the use of BioVU, we describe the data mining efforts to define cases and controls for genetic association studies of common cancers in PAGE. Collectively, the efforts described here are a generalized outline for many of the successful approaches that can be used in the era of high-throughput genotype-phenotype associations for moving biomedical discovery forward to new frontiers of data generation and analysis.

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.