Tamar Sofer

Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMMs constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs.

A-clustering: A Novel Method for the Detection of Co-regulated Methylation Regions, and Regions Associated with Exposure

MOTIVATION DNA methylation is a heritable modifiable chemical process that affects gene transcription and is associated with other molecular markers (e.g. gene expression) and biomarkers (e.g. cancer or other diseases). Current technology measures methylation in hundred of thousands, or millions of CpG sites throughout the genome. It is evident that neighboring CpG sites are often highly correlated with each other, and current literature suggests that clusters of adjacent CpG sites are co-regulated. RESULTS We develop the Adjacent Site Clustering (A-clustering) algorithm to detect sets of neighboring CpG sites that are correlated with each other. To detect methylation regions associated with exposure, we propose an analysis pipeline for high-dimensional methylation data in which CpG sites within regions identified by A-clustering are modeled as multivariate responses to environmental exposure using a generalized estimating equation approach that assumes exposure equally affects all sites in the cluster. We develop a correlation preserving simulation scheme, and study the proposed methodology via simulations. We study the clusters detected by the algorithm on high dimensional dataset of peripheral blood methylation of pesticide applicators. AVAILABILITY We provide the R package Aclust that efficiently implements the A-clustering and the analysis pipeline, and produces analysis reports. The package is found on http://www.hsph.harvard.edu/tamar-sofer/packages/ CONTACT tsofer@hsph.harvard.edu

Exposure to airborne particulate matter is associated with methylation pattern in the asthma pathway

BACKGROUND Asthma exacerbation and other respiratory symptoms are associated with exposure to air pollution. Since environment affects gene methylation, it is hypothesized that asthmatic responses to pollution are mediated through methylation. MATERIALS & METHODS We study the possibility that airborne particulate matter affects gene methylation in the asthma pathway. We measured methylation array data in clinic visits of 141 subjects from the Normative Aging Study. Black carbon and sulfate measures from a central monitoring site were recorded and 30-day averages were calculated for each clinic visit. Gene-specific methylation scores were calculated for the genes in the asthma pathway, and the association between the methylation in the asthma pathway and the pollution measures was analyzed using sparse Canonical Correlation Analysis. RESULTS The analysis found that exposures to black carbon and sulfate were significantly associated with the methylation pattern in the asthma pathway (p-values 0.05 and 0.02, accordingly). Specific genes that contributed to this association were identified. CONCLUSION These results suggest that the effect of air pollution on asthmatic and respiratory responses may be mediated through gene methylation.

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.

GENOME‐WIDE ASSOCIATION STUDY (GWAS) AND GENOME‐WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN

Genome‐wide association studies (GWAS) have made little progress in identifying variants linked to depression. We hypothesized that examining depressive symptoms and considering gene–environment interaction (GxE) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome‐wide by environment interaction study (GWEIS) of depressive symptoms.

Chronic Periodontitis Genome-wide Association Study in the Hispanic Community Health Study / Study of Latinos

Chronic periodontitis (CP) has a genetic component, particularly its severe forms. Evidence from genome-wide association studies (GWASs) has highlighted several potential novel loci. Here, the authors report the first GWAS of CP among a large community-based sample of Hispanics/Latinos. The authors interrogated a quantitative trait of CP (mean interproximal clinical attachment level determined by full-mouth periodontal examinations) among 10,935 adult participants (mean age: 45 y, range: 18 to 76 y) from the Hispanic Community Health Study / Study of Latinos. Genotyping was done with a custom Illumina Omni2.5M array, and imputation to approximately 20 million single-nucleotide polymorphisms was based on the 1000 Genomes Project phase 1 reference panel. Analyses were based on linear mixed models adjusting for sex, age, study design features, ancestry, and kinship and employed a conventional P < 5 × 10−8 statistical significance threshold. The authors identified a genome-wide significant association signal in the 1q42.2 locus (TSNAX-DISC1 noncoding RNA, lead single-nucleotide polymorphism: rs149133391, minor allele [C] frequency = 0.01, P = 7.9 × 10−9) and 4 more loci with suggestive evidence of association (P < 5 × 10−6): 1q22 (rs13373934), 5p15.33 (rs186066047), 6p22.3 (rs10456847), and 11p15.1 (rs75715012). We tested these loci for replication in independent samples of European-American (n = 4,402) and African-American (n = 908) participants of the Atherosclerosis Risk in Communities study. There was no replication among the European Americans; however, the TSNAX-DISC1 locus replicated in the African-American sample (rs149133391, minor allele frequency = 0.02, P = 9.1 × 10−3), while the 1q22 locus was directionally concordant and nominally significant (rs13373934, P = 4.0 × 10−2). This discovery GWAS of interproximal clinical attachment level—a measure of lifetime periodontal tissue destruction—was conducted in a large, community-based sample of Hispanic/Latinos. It identified a genome-wide significant locus that was independently replicated in an African-American population. Identifying this genetic marker offers direction for interrogation in subsequent genomic and experimental studies of CP.

A powerful statistical framework for generalization testing in GWAS, with application to the HCHS/SOL

In genome‐wide association studies (GWAS), “generalization” is the replication of genotype‐phenotype association in a population with different ancestry than the population in which it was first identified. Current practices for declaring generalizations rely on testing associations while controlling the family‐wise error rate (FWER) in the discovery study, then separately controlling error measures in the follow‐up study. This approach does not guarantee control over the FWER or false discovery rate (FDR) of the generalization null hypotheses. It also fails to leverage the two‐stage design to increase power for detecting generalized associations. We provide a formal statistical framework for quantifying the evidence of generalization that accounts for the (in)consistency between the directions of associations in the discovery and follow‐up studies. We develop the directional generalization FWER (FWERg) and FDR (FDRg) controlling r‐values, which are used to declare associations as generalized. This framework extends to generalization testing when applied to a published list of Single Nucleotide Polymorphism‐(SNP)‐trait associations. Our methods control FWERg or FDRg under various SNP selection rules based on P‐values in the discovery study. We find that it is often beneficial to use a more lenient P‐value threshold than the genome‐wide significance threshold. In a GWAS of total cholesterol in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), when testing all SNPs with P‐values <5×10−8 (15 genomic regions) for generalization in a large GWAS of whites, we generalized SNPs from 15 regions. But when testing all SNPs with P‐values <6.6×10−5 (89 regions), we generalized SNPs from 27 regions.

Trans-ethnic Fine Mapping Highlights Kidney-Function Genes Linked to Salt Sensitivity

We analyzed genome-wide association studies (GWASs), including data from 71,638 individuals from four ancestries, for estimated glomerular filtration rate (eGFR), a measure of kidney function used to define chronic kidney disease (CKD). We identified 20 loci attaining genome-wide-significant evidence of association (p < 5 × 10−8) with kidney function and highlighted that allelic effects on eGFR at lead SNPs are homogeneous across ancestries. We leveraged differences in the pattern of linkage disequilibrium between diverse populations to fine-map the 20 loci through construction of “credible sets” of variants driving eGFR association signals. Credible variants at the 20 eGFR loci were enriched for DNase I hypersensitivity sites (DHSs) in human kidney cells. DHS credible variants were expression quantitative trait loci for NFATC1 and RGS14 (at the SLC34A1 locus) in multiple tissues. Loss-of-function mutations in ancestral orthologs of both genes in Drosophila melanogaster were associated with altered sensitivity to salt stress. Renal mRNA expression of Nfatc1 and Rgs14 in a salt-sensitive mouse model was also reduced after exposure to a high-salt diet or induced CKD. Our study (1) demonstrates the utility of trans-ethnic fine mapping through integration of GWASs involving diverse populations with genomic annotation from relevant tissues to define molecular mechanisms by which association signals exert their effect and (2) suggests that salt sensitivity might be an important marker for biological processes that affect kidney function and CKD in humans.

Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos

Prior GWAS have identified loci associated with red blood cell (RBC) traits in populations of European, African, and Asian ancestry. These studies have not included individuals with an Amerindian ancestral background, such as Hispanics/Latinos, nor evaluated the full spectrum of genomic variation beyond single nucleotide variants. Using a custom genotyping array enriched for Amerindian ancestral content and 1000 Genomes imputation, we performed GWAS in 12,502 participants of Hispanic Community Health Study and Study of Latinos (HCHS/SOL) for hematocrit, hemoglobin, RBC count, RBC distribution width (RDW), and RBC indices. Approximately 60% of previously reported RBC trait loci generalized to HCHS/SOL Hispanics/Latinos, including African ancestral alpha- and beta-globin gene variants. In addition to the known 3.8kb alpha-globin copy number variant, we identified an Amerindian ancestral association in an alpha-globin regulatory region on chromosome 16p13.3 for mean corpuscular volume and mean corpuscular hemoglobin. We also discovered and replicated three genome-wide significant variants in previously unreported loci for RDW (SLC12A2 rs17764730, PSMB5 rs941718), and hematocrit (PROX1 rs3754140). Among the proxy variants at the SLC12A2 locus we identified rs3812049, located in a bi-directional promoter between SLC12A2 (which encodes a red cell membrane ion-transport protein) and an upstream anti-sense long-noncoding RNA, LINC01184, as the likely causal variant. We further demonstrate that disruption of the regulatory element harboring rs3812049 affects transcription of SLC12A2 and LINC01184 in human erythroid progenitor cells. Together, these results reinforce the importance of genetic study of diverse ancestral populations, in particular Hispanics/Latinos.

Genetics of type 2 diabetes in U.S. Hispanic/Latino individuals: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Few genome-wide association studies (GWAS) of type 2 diabetes (T2D) have been conducted in U.S. Hispanics/Latinos of diverse backgrounds who are disproportionately affected by diabetes. We conducted a GWAS in 2,499 T2D case subjects and 5,247 control subjects from six Hispanic/Latino background groups in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Our GWAS identified two known loci (TCF7L2 and KCNQ1) reaching genome-wide significance levels. Conditional analysis on known index single nucleotide polymorphisms (SNPs) indicated an additional independent signal at KCNQ1, represented by an African ancestry–specific variant, rs1049549 (odds ratio 1.49 [95% CI 1.27–1.75]). This association was consistent across Hispanic/Latino background groups and replicated in the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium. Among 80 previously known index SNPs at T2D loci, 66 SNPs showed consistency with the reported direction of associations and 14 SNPs significantly generalized to the HCHS/SOL. A genetic risk score based on these 80 index SNPs was significantly associated with T2D (odds ratio 1.07 [1.06–1.09] per risk allele), with a stronger effect observed in nonobese than in obese individuals. Our study identified a novel independent signal suggesting an African ancestry–specific allele at KCNQ1 for T2D. Associations between previously identified loci and T2D were generally shown in a large cohort of U.S. Hispanics/Latinos.