Yeunjoo Song

Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma

Primary open-angle glaucoma (POAG) is a leading cause of blindness worldwide. To identify new susceptibility loci, we performed meta-analysis on genome-wide association study (GWAS) results from eight independent studies from the United States (3,853 cases and 33,480 controls) and investigated the most significantly associated SNPs in two Australian studies (1,252 cases and 2,592 controls), three European studies (875 cases and 4,107 controls) and a Singaporean Chinese study (1,037 cases and 2,543 controls). A meta-analysis of the top SNPs identified three new associated loci: rs35934224[T] in TXNRD2 (odds ratio (OR) = 0.78, P = 4.05 × 10−11) encoding a mitochondrial protein required for redox homeostasis; rs7137828[T] in ATXN2 (OR = 1.17, P = 8.73 × 10−10); and rs2745572[A] upstream of FOXC1 (OR = 1.17, P = 1.76 × 10−10). Using RT-PCR and immunohistochemistry, we show TXNRD2 and ATXN2 expression in retinal ganglion cells and the optic nerve head. These results identify new pathways underlying POAG susceptibility and suggest new targets for preventative therapies.

Structural equation model-based genome scan for the metabolic syndrome

BackgroundThe metabolic syndrome is characterized by the clustering of several traits, including obesity, hypertension, decreased levels of HDL cholesterol, and increased levels of glucose and triglycerides. Because these traits cluster, there are likely common genetic factors involved.ResultsWe used a multivariate structural equation model (SEM) approach to scan the genome for loci involved in the metabolic syndrome. We found moderate evidence for linkage on chromosomes 2, 3, 11, 13, and 15, and these loci appear to have different relative effects on the component traits of the metabolic syndrome.ConclusionOur results suggest that the metabolic syndrome components, diabetes, obesity, and hypertension, are under the pleiotropic control of several loci.

Assessing the impact of global versus local ancestry in association studies

BackgroundTo account for population stratification in association studies, principal-components analysis is often performed on single-nucleotide polymorphisms (SNPs) across the genome. Here, we use Framingham Heart Study (FHS) Genetic Analysis Workshop 16 data to compare the performance of local ancestry adjustment for population stratification based on principal components (PCs) estimated from SNPs in a local chromosomal region with global ancestry adjustment based on PCs estimated from genome-wide SNPs.MethodsStandardized height residuals from unrelated adults from the FHS Offspring Cohort were averaged from longitudinal data. PCs of SNP genotype data were calculated to represent individuals ancestry either 1) globally using all SNPs across the genome or 2) locally using SNPs in adjacent 20-Mbp regions within each chromosome. We assessed the extent to which there were differences in association studies of height depending on whether PCs for global, local, or both global and local ancestry were included as covariates.ResultsThe correlations between local and global PCs were low (r < 0.12), suggesting variability between local and global ancestry estimates. Genome-wide association tests without any ancestry adjustment demonstrated an inflated type I error rate that decreased with adjustment for local ancestry, global ancestry, or both. A known spurious association was replicated for SNPs within the lactase gene, and this false-positive association was abolished by adjustment with local or global ancestry PCs.ConclusionPopulation stratification is a potential source of bias in this seemingly homogenous FHS population. However, local and global PCs derived from SNPs appear to provide adequate information about ancestry.

The effect of multiple genetic variants in predicting the risk of type 2 diabetes

While recently performed genome-wide association studies have advanced the identification of genetic variants predisposing to type 2 diabetes (T2D), the potential application of these novel findings for disease prediction and prevention has not been well studied. Diabetes prediction and prevention have become urgent issues owing to the rapidly increasing prevalence of diabetes and its associated mortality, morbidity, and health care cost. New prediction approaches using genetic markers could facilitate early identification of high risk sub-groups of the population so that appropriate prevention methods could be effectively applied to delay, or even prevent, disease onset.This paper assessed 18 recently identified T2D loci for their potential role in diabetes prediction. We built a new predictive genetic test for T2D using the Framingham Heart Study dataset. Using logistic regression and 15 additional loci, the new test was slightly improved over the existing test using just three loci. A formal comparison between the two tests suggests no significant improvement. We further formed a predictive genetic test for identifying early onset T2D and found higher classification accuracy for this test, not only indicating that these 18 loci have great potential for predicting early onset T2D, but also suggesting that they may play important roles in causing early-onset T2D.To further improve the tests accuracy, we applied a newly developed nonparametric method capable of capturing high order interactions to the data, but it did not outperform a logistic regression that only considers single-locus effects. This could be explained by the absence of gene-gene interactions among the 18 loci.

Linkage analysis of alcohol dependence using both affected and discordant sib pairs

The basic idea of affected-sib-pair (ASP) linkage analysis is to test whether the inheritance pattern of a marker deviates from Mendelian expectation in a sample of ASPs. The test depends on an assumed Mendelian control distribution of the number of marker alleles shared identical by descent (IBD), i.e., 1/4, 1/2, and 1/4 for 2, 1, and 0 allele(s) IBD, respectively. However, Mendelian transmission may not always hold, for example because of inbreeding or meiotic drive at the marker or a nearby locus. A more robust and valid approach is to incorporate discordant-sib-pairs (DSPs) as controls to avoid possible false-positive results. To be robust to deviation from Mendelian transmission, here we analyzed Collaborative Study on the Genetics of Alcoholism data by modifying the ASP LOD score method to contrast the estimated distribution of the number of allele(s) shared IBD by ASPs with that by DSPs, instead of with the expected distribution under the Mendelian assumption. This strategy assesses the difference in IBD sharing between ASPs and the IBD sharing between DSPs. Further, it works better than the conventional LOD score ASP linkage method in these data in the sense of avoiding false-positive linkage evidence.

Interaction of gender and body mass index (BMI) reveals evidence of linkage for hypertension in the Framingham Heart Study

BackgroundGenetic heterogeneity and complex biologic mechanisms of blood pressure regulation pose significant challenges to the identification of susceptibility loci influencing hypertension. Previous linkage studies have reported regions of interest, but lack consistency across studies. Incorporation of covariates, in particular the interaction between two independent risk factors (gender and BMI) greatly improved our ability to detect linkage.ResultsWe report a highly significant signal for linkage to chromosome 2p, a region that has been implicated in previous linkage studies, along with several suggestive linkage regions.ConclusionWe demonstrate the importance of including covariates in the linkage analysis when the phenotype is complex.

Multivariate analysis of anthropometric traits using summary statistics of genome-wide association studies from GIANT consortium

Meta-analysis of single trait for multiple cohorts has been used for increasing statistical power in genome-wide association studies (GWASs). Although hundreds of variants have been identified by GWAS, these variants only explain a small fraction of phenotypic variation. Cross-phenotype association analysis (CPASSOC) can further improve statistical power by searching for variants that contribute to multiple traits, which is often relevant to pleiotropy. In this study, we performed CPASSOC analysis on the summary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) consortium using a novel method recently developed by our group. Sex-specific meta-analysis data for height, body mass index (BMI), and waist-to-hip ratio adjusted for BMI (WHRadjBMI) from discovery phase of the GIANT consortium study were combined using CPASSOC for each trait as well as 3 traits together. The conventional meta-analysis results from the discovery phase data of GIANT consortium studies were used to compare with that from CPASSOC analysis. The CPASSOC analysis was able to identify 17 loci associated with anthropometric traits that were missed by conventional meta-analysis. Among these loci, 16 have been reported in literature by including additional samples and 1 is novel. We also demonstrated that CPASSOC is able to detect pleiotropic effects when analyzing multiple traits.

A Common Variant in MIR182 Is Associated With Primary Open-Angle Glaucoma in the NEIGHBORHOOD ConsortiumAssociation of miR-182 and POAG in NEIGHBORHOOD

Purpose Noncoding microRNAs (miRNAs) have been implicated in the pathogenesis of glaucoma. We aimed to identify common variants in miRNA coding genes (MIR) associated with primary open-angle glaucoma (POAG). Methods Using the NEIGHBORHOOD data set (3853 cases/33,480 controls with European ancestry), we first assessed the relation between 85 variants in 76 MIR genes and overall POAG. Subtype-specific analyses were performed in high-tension glaucoma (HTG) and normal-tension glaucoma subsets. Second, we examined the expression of miR-182, which was associated with POAG, in postmortem human ocular tissues (ciliary body, cornea, retina, and trabecular meshwork [TM]), using miRNA sequencing (miRNA-Seq) and droplet digital PCR (ddPCR). Third, miR-182 expression was also examined in human aqueous humor (AH) by using miRNA-Seq. Fourth, exosomes secreted from primary human TM cells were examined for miR-182 expression by using miRNA-Seq. Fifth, using ddPCR we compared miR-182 expression in AH between five HTG cases and five controls. Results Only rs76481776 in MIR182 gene was associated with POAG after adjustment for multiple comparisons (odds ratio [OR] = 1.23, 95% confidence interval [CI]: 1.11–1.42, P = 0.0002). Subtype analysis indicated that the association was primarily in the HTG subset (OR = 1.26, 95% CI: 1.08–1.47, P = 0.004). The risk allele T has been associated with elevated miR-182 expression in vitro. Data from ddPCR and miRNA-Seq confirmed miR-182 expression in all examined ocular tissues and TM-derived exosomes. Interestingly, miR-182 expression in AH was 2-fold higher in HTG patients than nonglaucoma controls (P = 0.03) without controlling for medication treatment. Conclusions Our integrative study is the first to associate rs76481776 with POAG via elevated miR-182 expression.

An autosome-wide search using longitudinal data for loci linked to type 2 diabetes progression

A genome-wide screen was conducted for type 2 diabetes progression genes using measures of elevated fasting glucose levels as quantitative traits from the offspring enrolled in the Framingham Heart Study. We analyzed young (20–34 years) and old (≥ 35 years) subjects separately, using single-point and multipoint sibpair analysis, because of the possible differential impact of progression on the groups of interest. We observed significant linkage with change in fasting glucose levels on 1q25-32 (p = 5.21 × 10-8), 3p26.3-21.31 (p = 1 × 10-11), 8q23.1-24.13 (p = 2.94 × 10-6), 9p24.1-21.3 (p = 7 × 10-7), and 18p11.31-q22.1 (p < 10-11). The evidence for linkage on chromosomes 8 and 18 was consistent for the subset of study participants aged 43 through 55 years.

Association Between Germline Mutation in VSIG10L and Familial Barrett Neoplasia

Importance Esophageal adenocarcinoma and its precursor lesion Barrett esophagus have seen a dramatic increase in incidence over the past 4 decades yet marked genetic heterogeneity of this disease has precluded advances in understanding its pathogenesis and improving treatment. Objective To identify novel disease susceptibility variants in a familial syndrome of esophageal adenocarcinoma and Barrett esophagus, termed familial Barrett esophagus, by using high-throughput sequencing in affected individuals from a large, multigenerational family. Design, Setting, and Participants We performed whole exome sequencing (WES) from peripheral lymphocyte DNA on 4 distant relatives from our multiplex, multigenerational familial Barrett esophagus family to identify candidate disease susceptibility variants. Gene variants were filtered, verified, and segregation analysis performed to identify a single candidate variant. Gene expression analysis was done with both quantitative real-time polymerase chain reaction and in situ RNA hybridization. A 3-dimensional organotypic cell culture model of esophageal maturation was utilized to determine the phenotypic effects of our gene variant. We used electron microscopy on esophageal mucosa from an affected family member carrying the gene variant to assess ultrastructural changes. Main Outcomes and Measures Identification of a novel, germline disease susceptibility variant in a previously uncharacterized gene. Results A multiplex, multigenerational family with 14 members affected (3 members with esophageal adenocarcinoma and 11 with Barrett esophagus) was identified, and whole-exome sequencing identified a germline mutation (S631G) at a highly conserved serine residue in the uncharacterized gene VSIG10L that segregated in affected members. Transfection of S631G variant into a 3-dimensional organotypic culture model of normal esophageal squamous cells dramatically inhibited epithelial maturation compared with the wild-type. VSIG10L exhibited high expression in normal squamous esophagus with marked loss of expression in Barrett-associated lesions. Electron microscopy of squamous esophageal mucosa harboring the S631G variant revealed dilated intercellular spaces and reduced desmosomes. Conclusions and Relevance This study presents VSIG10L as a candidate familial Barrett esophagus susceptibility gene, with a putative role in maintaining normal esophageal homeostasis. Further research assessing VSIG10L function may reveal pathways important for esophageal maturation and the pathogenesis of Barrett esophagus and esophageal adenocarcinoma.