Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Author Correction: Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases.

Emmanuelle Souzeau, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this Article. This has now been corrected in both the PDF and HTML versions of the Article.

GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Author Correction: Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

In the version of the article published, the surname of author Aaron Isaacs is misspelled as Issacs.

A new perspective on lipid research in age-related macular degeneration.

There is an urgency to find new treatment strategies that could prevent or delay the onset or progression of AMD. Different classes of lipids and lipoproteins metabolism genes have been associated with AMD in a multiple ways, but despite the ever-increasing knowledge base, we still do not understand fully how circulating lipids or local lipid metabolism contribute to AMD. It is essential to clarify whether dietary lipids, systemic or local lipoprotein metabolismtrafficking of lipids in the retina should be targeted in the disease. In this article, we critically evaluate what has been reported in the literature and identify new directions needed to bring about a significant advance in our understanding of the role for lipids in AMD. This may help to develop potential new treatment strategies through targeting the lipid homeostasis.

Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases.

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r = -0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r = -0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation.

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

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.

New insights into the genetics of primary open-angle glaucoma based on meta-analyses of intraocular pressure and optic disc characteristics.

Primary open-angle glaucoma (POAG), the most common optic neuropathy, is a heritable disease. Siblings of POAG cases have a ten-fold increased risk of developing the disease. Intraocular pressure (IOP) and optic nerve head characteristics are used clinically to predict POAG risk. We conducted a genome-wide association meta-analysis of IOP and optic disc parameters and validated our findings in multiple sets of POAG cases and controls. Using imputation to the 1000 genomes (1000G) reference set, we identified 9 new genomic regions associated with vertical cup-disc ratio (VCDR) and 1 new region associated with IOP. Additionally, we found 5 novel loci for optic nerve cup area and 6 for disc area. Previously it was assumed that genetic variation influenced POAG either through IOP or via changes to the optic nerve head; here we present evidence that some genomic regions affect both IOP and the disc parameters. We characterized the effect of the novel loci through pathway analysis and found that pathways involved are not entirely distinct as assumed so far. Further, we identified a novel association between CDKN1A and POAG. Using a zebrafish model we show that six6b (associated with POAG and optic nerve head variation) alters the expression of cdkn1a. In summary, we have identified several novel genes influencing the major clinical risk predictors of POAG and showed that genetic variation in CDKN1A is important in POAG risk.

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 oxidation in muscle (P = 4.1 × 10-3). Look-ups in bioinformatics resources showed that expression of FCRL2 is associated with ARHGAP24 and SETBP1 expression. This finding was not replicated in the Rotterdam study. Combining the bioinformatics information with the association and linkage analyses, FCRL2 emerges as a strong candidate gene for QT interval.

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

Genome-wide associations for birth weight and correlations with adult disease.

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Diagnostic Yield and Clinical Utility of Sequencing Familial Hypercholesterolemia Genes in Patients With Severe Hypercholesterolemia.

BACKGROUND: Approximately 7% of American adults have severe hypercholesterolemia (untreated low-density lipoprotein [LDL] cholesterol ≥190 mg/dl), which may be due to familial hypercholesterolemia (FH). Lifelong LDL cholesterol elevations in FH mutation carriers may confer coronary artery disease (CAD) risk beyond that captured by a single LDL cholesterol measurement. OBJECTIVES: This study assessed the prevalence of an FH mutation among those with severe hypercholesterolemia and determined whether CAD risk varies according to mutation status beyond the observed LDL cholesterol level. METHODS: Three genes causative for FH (LDLR, APOB, and PCSK9) were sequenced in 26,025 participants from 7 case-control studies (5,540 CAD case subjects, 8,577 CAD-free control subjects) and 5 prospective cohort studies (11,908 participants). FH mutations included loss-of-function variants in LDLR, missense mutations in LDLR predicted to be damaging, and variants linked to FH in ClinVar, a clinical genetics database. RESULTS: Among 20,485 CAD-free control and prospective cohort participants, 1,386 (6.7%) had LDL cholesterol ≥190 mg/dl; of these, only 24 (1.7%) carried an FH mutation. Within any stratum of observed LDL cholesterol, risk of CAD was higher among FH mutation carriers than noncarriers. Compared with a reference group with LDL cholesterol <130 mg/dl and no mutation, participants with LDL cholesterol ≥190 mg/dl and no FH mutation had a 6-fold higher risk for CAD (odds ratio: 6.0; 95% confidence interval: 5.2 to 6.9), whereas those with both LDL cholesterol ≥190 mg/dl and an FH mutation demonstrated a 22-fold increased risk (odds ratio: 22.3; 95% confidence interval: 10.7 to 53.2). In an analysis of participants with serial lipid measurements over many years, FH mutation carriers had higher cumulative exposure to LDL cholesterol than noncarriers. CONCLUSIONS: Among participants with LDL cholesterol ≥190 mg/dl, gene sequencing identified an FH mutation in <2%. However, for any observed LDL cholesterol, FH mutation carriers had substantially increased risk for CAD.

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 genome-wide 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 resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene. CONCLUSIONS: This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.

Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA.

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk.

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

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 with two widely used tools: minimac and IMPUTE2. These guidelines were developed and used by the Genome of the Netherlands (GoNL) consortium, which has created a population-specific reference panel for genetic imputations and used this reference to impute various Dutch biobanks. We also describe several factors that might influence the final imputation quality. This protocol, which has been used by the largest Dutch biobanks, should take approximately several days, depending on the sample size of the biobank and the computer resources available.

WNT10A exonic variant increases the risk of keratoconus by decreasing corneal thickness.

Keratoconus is a degenerative eye condition which results from thinning of the cornea and causes vision distortion. Treatments such as ultraviolet (UV) cross-linking have proved effective for management of keratoconus when performed in early stages of the disease. The central corneal thickness (CCT) is a highly heritable endophenotype of keratoconus, and it is estimated that up to 95% of its phenotypic variance is due to genetics. Genome-wide association efforts of CCT have identified common variants (i.e. minor allele frequency (MAF) >5%). However, these studies typically ignore the large set of exonic variants whose MAF is usually low. In this study, we performed a CCT exome-wide association analysis in a sample of 1029 individuals from a population-based study in Western Australia. We identified a genome-wide significant exonic variant rs121908120 (P = 6.63 × 10(-10)) in WNT10A. This gene is 437 kb from a gene previously associated with CCT (USP37). We showed in a conditional analysis that the WNT10A variant completely accounts for the signal previously seen at USP37. We replicated our finding in independent samples from the Brisbane Adolescent Twin Study, Twin Eye Study in Tasmania and the Rotterdam Study. Further, we genotyped rs121908120 in 621 keratoconus cases and compared the frequency to a sample of 1680 unscreened controls from the Queensland Twin Registry. We found that rs121908120 increases the risk of keratoconus two times (odds ratio 2.03, P = 5.41 × 10(-5)).

Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels.

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P < 1.09 × 10(-9)) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N = 1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.