A Study of the Complex Genetic Inheritance of Lipids

Hart- en vaatziekten vormen wereldwijd de belangrijkste oorzaak van morbiditeit en mortaliteit. Risicofactoren voor hart- en vaatziekten zijn vier typen circulerende lipide levels: high-density lipoproteïne cholesterol (HLD-C), low-density lipoproteïne cholesterol (LDL-C), totaal cholesterol (TC) en triglyceriden (TG). Deze vier typen circulerende lipide levels zijn in hoge mate erfelijk. Ondanks het vele onderzoek dat is gedaan naar circulerende lipide levels, is de meeste genetische variatie die de hoge erfelijkheid bepaald, nog steeds grotendeels onbekend. In dit proefschrift streef ik ernaar nieuwe variaties te ontdekken die geassocieerd kunnen worden met circulerende lipide levels. Daarvoor gebruikte ik meerdere genetische epidemiologische benaderingen: GWAS, genoomwijde interactie studies (GWIS) en exoomwijde associatie studies (ExWAS). GWAS heb ik toegepast op genoom-data van individuals die geimputeerd zijn met ofwel het Genoom van Nederland referentie panel ofwel het 1000 Genomes referentie panel. Deze individuen zijn deels afkomstig uit populatie gebaseerde cohorten en deels afkomstig uit familie gebaseerde cohorten. De hypothese vrije GWIS benadering was enkel toegepast op de Rotterdam Study, een lopende studie en de ExWAS benadering werd toegepast op een geisoleerde familie gebaseerde populatie. Alle methodes hebben nieuwe variaties gevonden die geassocieerd zijn met lipiden. Enkele varianten beinvloeden de functie en het structuur van het eiwit en hebben dus grote effecten en zijn daarom mogelijk nieuwe targets voor farmaceutische middelen

Population-specific genotype imputations using minimac or IMPUTE2

In order to meaningfully analyze common and rare genetic variants, results from genome-wide association studies (GWASs) of multiple cohorts need to be combined in a meta-analysis in order to obtain enough power. This requires all cohorts to have the same single-nucleotide polymorphisms (SNPs) in their GWASs. To this end, genotypes that have not been measured in a given cohort can be imputed on the basis of a set of reference haplotypes. This protocol provides guidelines for performing imputations

A combined linkage and exome sequencing analysis for electrocardiogram parameters in the Erasmus Rucphen family study

Electrocardiogram (ECG) measurements play a key role in the diagnosis and prediction of cardiac arrhythmias and sudden cardiac death. ECG parameters, such as the PR, QRS, and QT intervals, are known to be heritable and genome-wide association studies of these phenotypes have been successful in identifying common variants; however, a large proportion of the genetic variability of these traits remains to be elucidated. The aim of this study was to discover loci potentially harboring rare variants utilizing variance component linkage analysis in 1547 individuals from a large family-based study, the Erasmus Rucphen Family Study (ERF). Linked regions were further explored using exome sequencing. Five suggestive linkage peaks were identified: two for QT interval (1q24, LOD = 2.63; 2q34, LOD = 2.05), one for QRS interval (1p35, LOD = 2.52) and two for PR interval (9p22, LOD = 2.20; 14q11, LOD = 2.29). Fine-mapping using exome sequence data identified a C > G missense variant (c.713C > G, p.Ser238Cys) in the FCRL2 gene associated with QT (rs74608430; P = 2.8 × 10-4, minor allele frequency = 0.019). Heritability analysis demonstrated that the SNP explained 2.42% of the trait's genetic variability in ERF (P = 0.02). Pathway analysis suggested that the gene is involved in cytosolic Ca2+ levels (P = 3.3 × 10-3) and AMPK stimulated fatty acid oxidat

Haplotype reference consortium panel: Practical implications of imputations with large reference panels

Recently, the Haplotype Reference Consortium (HRC) released a large imputation panel that allows more accurate imputation of genetic variants. In this study, we compared a set of directly assayed common and rare variants from an exome array to imputed genotypes, that is, 1000 genomes project (1000GP) and HRC. We showed that imputation using the HRC panel improved the concordance between assayed and imputed genotypes at common, and especially, low-frequency variants. Furthermore, we performed a genome-wide association meta-analysis of vertical cup-disc ratio, a highly heritable endophenotype of glaucoma, in four cohorts using 1000GP and HRC imputations. We compared the results of the meta-analysis using 1000GP to the meta-analysis results using HRC. Overall, we found that using HRC imputation significantly improved P values (P = 3.07 × 10-61), particularly for suggestive variants. Both meta-analyses were performed in the same sample size, yet we found eight genome-wide significant loci in the HRC-based meta-analysis versus seven genome-wide significant loci in the 1000GP-based meta-analysis. This study provides supporting evidence of the new avenues for gene discovery and fine mapping that the HRC imputation panel offers

Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of the Netherlands'

Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with 'true' genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05-0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r 2, increased from 0.61 to 0.71. W

ARHGEF12 influences the risk of glaucoma by increasing intraocular pressure

Primary open-angle glaucoma (POAG) is a blinding disease. Two important risk factors for this disease are a positive family history and elevated intraocular pressure (IOP), which is also highly heritable. Genes found to date associated with IOP and POAG are ABCA1, CAV1/CAV2, GAS7 and TMCO1. However, these genes explain only a small part of the heritability of IOP and POAG.We performed a genome-wide association study of IOP in the population-based RotterdamStudy I and Rotterdam Study II using single nucleotide polymorphisms (SNPs) imputed to 1000 Genomes. In this discovery cohort (n = 8105), we identified a newlocus associated with IOP. The most significantly associated SNPwas rs58073046 (ß = 0.44, P-value = 1.87 × 10-8, minor allele frequency = 0.12), within the gene ARHGEF12. Independent replication in five population-based studies (n = 7471) resulted in an effect size in the same direction that was significantly associated (ß = 0.16, P-value = 0.04). The SNP was also significantly associated with POAG in two independent case-control studies [n = 1225 cases and n = 4117 controls; odds ratio (OR) = 1.53, P-value = 1.99 × 10-8], especially with high-tension glaucoma (OR = 1.66, P-value = 2.81 × 10-9; for normal-tension glaucoma OR = 1.29, P-value = 4.23 × 10-2). ARHGEF12 plays an important role in the RhoA/RhoA kinase pathway, which has been implicated in IOP regulation. Furthermore, it binds to ABCA1 and links the ABCA1, CAV1/CAV2 and GAS7 pathway to Mendelian POAG genes (MYOC, OPTN, WDR36). In conclusion, this study identified a novel association between IOP and ARHGEF12

The challenges of genome-wide interaction studies: Lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP6SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value, 1 · 1028 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30, 011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP6SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS

The Genome of the Netherlands: Design, and project goals

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project

A high-quality human reference panel reveals the complexity and distribution of genomic structural variants

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu