Person:

Pasquale, Louis

Background: Loss of vision in glaucoma is due to apoptotic retinal ganglion cell loss. While p53 modulates apoptosis, gene association studies between p53 variants and glaucoma have been inconsistent. In this study we evaluate the association between a p53 variant functionally known to influence apoptosis (codon 72 Pro/Arg) and the subset of primary open angle glaucoma (POAG) patients with early loss of central visual field. Methods: Genotypes for the p53 codon 72 polymorphism (Pro/Arg) were obtained for 264 POAG patients and 400 controls from the U.S. and in replication studies for 308 POAG patients and 178 controls from Australia (GIST). The glaucoma patients were divided into two groups according to location of initial visual field defect (either paracentral or peripheral). All cases and controls were Caucasian with European ancestry. Results: The p53-PRO/PRO genotype was more frequent in the U.S. POAG patients with early visual field defects in the paracentral regions compared with those in the peripheral regions or control group (p = 2.7×(10^{−5})). We replicated this finding in the GIST cohort (p = 7.3×(10^{−3}), and in the pooled sample (p = 6.6×(10^{−7})) and in a meta-analysis of both the US and GIST datasets (1.3×(10^{−6}), OR 2.17 (1.58–2.98 for the PRO allele). Conclusions: These results suggest that the p53 codon 72 PRO/PRO genotype is potentially associated with early paracentral visual field defects in primary open-angle glaucoma patients.

Primary open angle glaucoma (POAG) is a leading cause of blindness worldwide. The molecular signaling involved in the pathogenesis of POAG remains unknown. Here, we report that mice lacking the (α_1) subunit of the nitric oxide receptor soluble guanylate cyclase represent a novel and translatable animal model of POAG, characterized by thinning of the retinal nerve fiber layer and loss of optic nerve axons in the context of an open iridocorneal angle. The optic neuropathy associated with soluble guanylate cyclase (α_1)–deficiency was accompanied by modestly increased intraocular pressure and retinal vascular dysfunction. Moreover, data from a candidate gene association study suggests that a variant in the locus containing the genes encoding for the (α_1) and (β_1) subunits of soluble guanylate cyclase is associated with POAG in patients presenting with initial paracentral vision loss, a disease subtype thought to be associated with vascular dysregulation. These findings provide new insights into the pathogenesis and genetics of POAG and suggest new therapeutic strategies for POAG.

Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self-administered questionnaires. Multiplicative interactions between the GRS and physical activity on BMI were tested in linear and logistic regression models in each cohort, with adjustment for age, age2, sex, study center (for multicenter studies), and the marginal terms for physical activity and the GRS. These results were combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39,810, Pinteraction = 0.014 vs. n = 71,611, Pinteraction = 0.275 for Europeans). In secondary analyses, both the FTO rs1121980 (Pinteraction = 0.003) and the SEC16B rs10913469 (Pinteraction = 0.025) variants showed evidence of SNP × physical activity interactions. This meta-analysis of 111,421 individuals provides further support for an interaction between physical activity and a GRS in obesity disposition, although these findings hinge on the inclusion of cohorts from North America, indicating that these results are either population-specific or non-causal.

Glaucoma is a leading cause of blindness worldwide. Primary open-angle glaucoma (POAG) is the most common subtype and is a complex trait with multigenic inheritance. Genome-wide association studies have previously identified a significant association between POAG and the SIX6 locus (rs10483727, odds ratio (OR) = 1.32, p = 3.87×10−11). SIX6 plays a role in ocular development and has been associated with the morphology of the optic nerve. We sequenced the SIX6 coding and regulatory regions in 262 POAG cases and 256 controls and identified six nonsynonymous coding variants, including five rare and one common variant, Asn141His (rs33912345), which was associated significantly with POAG (OR = 1.27, p = 4.2×10−10) in the NEIGHBOR/GLAUGEN datasets. These variants were tested in an in vivo Danio rerio (zebrafish) complementation assay to evaluate ocular metrics such as eye size and optic nerve structure. Five variants, found primarily in POAG cases, were hypomorphic or null, while the sixth variant, found only in controls, was benign. One variant in the SIX6 enhancer increased expression of SIX6 and disrupted its regulation. Finally, to our knowledge for the first time, we have identified a clinical feature in POAG patients that appears to be dependent upon SIX6 genotype: patients who are homozygous for the SIX6 risk allele (His141) have a statistically thinner retinal nerve fiber layer than patients homozygous for the SIX6 non-risk allele (Asn141). Our results, in combination with previous SIX6 work, lead us to hypothesize that SIX6 risk variants disrupt the development of the neural retina, leading to a reduced number of retinal ganglion cells, thereby increasing the risk of glaucoma-associated vision loss.

Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.

The Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79–2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.