Faculty Bibliography

AIMS/OBJECTIVE:To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS/RESULTS:We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION/CONCLUSIONS:The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

BACKGROUND:Several retinal dystrophies are associated with syndromic features including such conditions as Bardet-Biedl and Joubert syndromes. Cohen syndrome is an autosomal recessive disorder associated with multiple clinical manifestations including developmental delay, acquired microcephaly, myopia, pigmentary retinopathy, joint hypermobility, truncal obesity, friendly disposition and intermittent neutropenia. In young patients, diagnosis is difficult, because several of the characteristic features may not be present until school age or later years and the intermittent neutropenia is not always detectable. DESIGN/METHODS:This was a prospective study using whole exome sequencing in syndromic retinal dystrophy. It was undertaken in a hospital and research institute setting. PARTICIPANTS/METHODS:Participants in this study were members of a consanguineous Australian family of Lebanese ethnicity with two siblings with retinal dystrophy, microcephaly and developmental delay. METHODS:Detailed clinical evaluation was undertaken. Whole exome capture and sequencing of patient genomic DNA samples was followed by sequence alignment, variant detection, comparison and prioritization. MAIN OUTCOME MEASURES/METHODS:Pathogenic variant identification in the disease-causing gene in affected individuals. RESULTS:We identified a novel homozygous deletion leading to a frameshift mutation in VPS13B, c.11327del, p.(Asn3776Thrfs*102), the disease gene associated with Cohen syndrome. CONCLUSIONS:This report emphasizes the value of a broad-based whole exome sequencing approach in disease gene identification in the syndromic retinal dystrophies, where all disease characteristics may not be present in young patients to allow a clinical diagnosis. This facilitates improved prognostic and genetic information for patients and families.

Clinical phenotypes of congenital myasthenic syndromes and primary mitochondrial disorders share significant overlap in their clinical presentations, leading to challenges in making the correct diagnosis. Next generation sequencing is transforming molecular diagnosis of inherited neuromuscular disorders by identifying novel disease genes and by identifying previously known genes in undiagnosed patients. This is evident in two patients who were initially suspected to have a mitochondrial myopathy, but in whom a clear diagnosis of congenital myasthenic syndromes was made through whole exome sequencing. In patient 1, whole exome sequencing revealed compound heterozygous mutations c.1228C > T (p.Arg410Trp) and c.679C > T (p.Arg227*) in collagen-like tail subunit (single strand of homotrimer) of asymmetric acetylcholinesterase (COLQ). In patient 2, in whom a deletion of exon 52 in Dystrophin gene was previously detected by multiplex ligation-dependent probe amplification, Sanger sequencing revealed an additional homozygous mutation c.1511_1513delCTT (p.Pro504Argfs*183) in docking protein7 (DOK7). These case reports highlight the need for careful diagnosis of clinically heterogeneous syndromes like congenital myasthenic syndromes, which are treatable, and for which delayed diagnosis is likely to have implications for patient health. The report also demonstrates that whole exome sequencing is an effective diagnostic tool in providing molecular diagnosis in patients with complex phenotypes.

OBJECTIVE:The study's purpose was to test if subclinical atherosclerosis was associated with the risk of developing HI in a large cohort of middle-aged participants. METHODS:Study subjects were members of the Beaver Dam Offspring Study (BOSS), a longitudinal study of adult children of participants in the population-based Epidemiology of Hearing Loss Study (1993-present). BOSS examinations took place in 2005-2008 (baseline) and 2010-2013 (5-year follow-up). The 5-year incidence of hearing impairment was defined as a pure-tone average (PTA) of thresholds at 0.5, 1, 2 and 4 kHz > 25 dB Hearing Level (dB HL) in either ear at follow-up among participants at risk (baseline PTA in both ears < = 25 dB HL; n = 2436, mean age = 47.7 years). Atherosclerosis was measured as the mean carotid intima-media thickness and the presence of carotid artery plaque. RESULTS:Among the 1984 participants at-risk with a follow-up audiometric examination, the 5-year incidence of hearing impairment was 8.3% (95% Confidence Interval (C.I.) 7.1, 9.5). With multivariable adjustment, carotid intima-media thickness was positively associated with hearing impairment incidence (Relative Risk (RR) = 1.14 per 0.1 mm, 95% C.I. 1.04, 1.24). The number of sites (0-6) with plaque was also positively associated with the incidence of impairment (RR = 1.16 per site, 95% C.I. 1.01, 1.32). CONCLUSION/CONCLUSIONS:Atherosclerosis was associated with the 5-year incidence of hearing impairment in this predominantly middle-aged cohort. Interventions targeting atherosclerosis prevention may help to prevent or delay the onset of hearing impairment.

BACKGROUND:Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target. METHODS:We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. FINDINGS/RESULTS:Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials). INTERPRETATION/CONCLUSIONS:The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. FUNDING/BACKGROUND:The funding sources are cited at the end of the paper.

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.

BACKGROUND:Leber congenital amaurosis (LCA) is a severe form of retinal dystrophy with marked underlying genetic heterogeneity. Until recently, allele-specific assays and Sanger sequencing of targeted segments were the only available approaches for attempted genetic diagnosis in this condition. A broader next-generation sequencing (NGS) strategy, such as whole exome sequencing, provides an improved molecular genetic diagnostic capacity for patients with these conditions. MATERIALS AND METHODS/METHODS:In a child with LCA, an allele-specific assay analyzing 135 known LCA-causing variations, followed by targeted segment sequencing of 61 regions in 14 causative genes was performed. Subsequently, exome sequencing was undertaken in the proband, unaffected consanguineous parents and two unaffected siblings. Bioinformatic analysis used two independent pipelines, BWA-GATK and SOAP, followed by Annovar and SnpEff to annotate the variants. RESULTS:No disease-causing variants were found using the allele-specific or targeted segment Sanger sequencing assays. Analysis of variants in the exome sequence data revealed a novel homozygous nonsense mutation (c.1081C > T, p.Arg361*) in TULP1, a gene with roles in photoreceptor function where mutations were previously shown to cause LCA and retinitis pigmentosa. The identified homozygous variant was the top candidate using both bioinformatic pipelines. CONCLUSIONS:This study highlights the value of the broad sequencing strategy of exome sequencing for disease gene identification in LCA, over other existing methods. NGS is particularly beneficial in LCA where there are a large number of causative disease genes, few distinguishing clinical features for precise candidate disease gene selection, and few mutation hotspots in any of the known disease genes.

This study aimed to identify the genetics underlying dominant forms of inherited retinal dystrophies using whole exome sequencing (WES) in six families extensively screened for known mutations or genes. Thirty-eight individuals were subjected to WES. Causative variants were searched among single nucleotide variants (SNVs) and insertion/deletion variants (indels) and whenever no potential candidate emerged, copy number variant (CNV) analysis was performed. Variants or regions harboring a candidate variant were prioritized and segregation of the variant with the disease was further assessed using Sanger sequencing in case of SNVs and indels, and quantitative PCR (qPCR) for CNVs. SNV and indel analysis led to the identification of a previously reported mutation in PRPH2. Two additional mutations linked to different forms of retinal dystrophies were identified in two families: a known frameshift deletion in RPGR, a gene responsible for X-linked retinitis pigmentosa and p.Ser163Arg in C1QTNF5 associated with Late-Onset Retinal Degeneration. A novel heterozygous deletion spanning the entire region of PRPF31 was also identified in the affected members of a fourth family, which was confirmed with qPCR. This study allowed the identification of the genetic cause of the retinal dystrophy and the establishment of a correct diagnosis in four families, including a large heterozygous deletion in PRPF31, typically considered one of the pitfalls of this method. Since all findings in this study are restricted to known genes, we propose that targeted sequencing using gene-panel is an optimal first approach for the genetic screening and that once known genetic causes are ruled out, WES might be used to uncover new genes involved in inherited retinal dystrophies.

BACKGROUND:Despite heritability estimates of 40-70 % for obesity, less than 2 % of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. METHODS:Using genotypic data from 18,686 individuals across five study cohorts - ARIC, CARDIA, FHS, CHS, MESA - we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of BMI. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects non-linear interactions associated with a quantitative trait. RESULTS:We identified seven novel, epistatic models with a Bonferroni corrected p-value of association < 0.1. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). Moreover, we found an 8.8 % increase in the variance in BMI explained by these seven SNP-SNP interactions, beyond what is explained by the main effects of an index FTO SNP and the SNPs within these interactions. We also replicated one of these interactions and 58 proxy SNP-SNP models representing it in an independent dataset from the eMERGE study. CONCLUSION/CONCLUSIONS:This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.