Genetics of Circulating Blood Lipids

Circulating blood lipids are well-established risk factors for cardiovascular diseases. Levels of high-density lipoprotein, low-density lipoprotein, total cholesterol, and triglycerides are affected by environmental and genetic factors. As the genetic factors explain around half of the population lipid variation based on twin studies, knowledge of the genetic determinants is crucial in prevention and early treatment of harmful lipid levels. In this thesis, genetic markers associated with lipid levels were screened using genome-wide marker datasets to better understand the biological and heritable mechanisms behind lipid levels. To identify different types of associated loci, genome-wide single nucleotide polymorphism (SNP) data from multiple European cohorts was combined. In addition, this thesis presents the effect of using Finnish imputation panel as reference on the quality of genotype imputation, which enables the usage of denser SNP marker sets in association analysis. In total, 95 genetic loci with genome-wide significant association (P-value less than 5×10-8, accounting for one million independent tests) on lipid levels were identified. In one of these loci, the SNP genotype modified the association between total cholesterol and waist-to-hip ratio. Common genetic markers found in the first publication together with the previously associated loci in publications of other research groups explained up to 4.8% of the lipid level variation. When combining all the genetic information available from different sources at the end of this thesis project, up to 16.6% of the trait variation could be explained, which corresponds to 33% of the trait heritability. In the work described in this thesis almost a hundred genetic loci associated to circulating blood lipids were successfully identified using large-scale genome-wide approaches. This thesis demonstrates new biology behind lipid levels, in addition to how large scale studies with dense SNP panels enabled by genotype imputation, can be a key in revealing biological determinants behind complex diseases and traits. Keywords: Circulating blood lipids, genome-wide association, gene-environment interaction, genotype data imputationVerestä mitattavat lipidiarvot ovat hyvin tunnettuja riskitekijöitä sydän- ja verisuonitaudeille. Veren hyvä kolesteroli, (high-density lipoprotein cholesterol), huono kolesteroli (low-density lipoprotein cholesterol), kokonaiskolesteroli sekä triglyseridit, ovat monitekijäisiä muuttujia, joihin vaikuttavat sekä ympäristö että perinnölliset tekijät. Koska perinnölliset tekijät selittävät noin puolet kolesterolitasojen normaalivaihtelusta, on hyvin olennaista ymmärtää kolesterolitasojen geneettinen tausta, jotta henkilöt joilla on korkeampi riski sairastua erilaisiin rasva-aineenvaihdunnan häiriöihin voitaisiin aikaisemmin tunnistaa ja siten epäsuotuisia kolesterolitasoja ehkäistä ja hoitaa. Jotta veren lipiditasojen taustalla olevia perinnöllisiä mekanismeja voitaisiin paremmin ymmärtää, tässä väitöstyössä on kartoitettu koko perimänlaajuisesti yleisiä, ympäristön kanssa vuorovaikuttavia sekä harvinaisia yhden emäksen variaatioita, joilla on yhteys mitattuihin lipidiarvoihin. Lisäksi on tutkittu populaatiokohtaisen referenssin käytön vaikutusta markkeritiedon tilastollisessa täydentämisessä, imputaatiossa, joka mahdollistaa tarkemman geenimarkkeriaineiston käyttämisen kartoitustutkimuksissa. Kaiken kaikkiaan onnistuimme löytämään 95 perimän kohtaa, joilla on tilastollisesti merkitsevä yhteys veren lipidiarvoihin ja yhdessä näistä kohdista löydetyn geneettisen markkerin eri muodot säätelivät vyötärö-lantio-suhteen ja kokonaiskolesterolin välistä yhteyttä. Ensimmäisessä osatyössä kartoitetut yleiset geneettiset markkerit selittivät 4.8% lipidien kokonaisvariaatiosta, mutta väitöstutkimuksen lopussa yhteen kerätyt geneettiset variaatiot selittivät jopa 16.6% kokonaisvariaatiosta, joka vastaa noin 33%:a kyseisen lipidin estimoidusta periytyvyydestä. Väitöstutkimuksessa saatujen tulosten avulla olemme oppineet paljon uutta veren rasva-aineenvaihdunnan biologiasta sekä näyttäneet, että suuret ja tiheämarkkeriset geneettiset aineistot voivat olla avain myös muiden monitekijäisten tautien periytyvyyden selvittämiseen. Avainsanat: Veren lipidimittaukset, perimänlaajuinen assosiaatioanalyysi, geeni-ympäristö-interaktio, geenimarkkeriaineiston imputaati

Genome-wide association studies reveal differences in genetic susceptibility between single events vs. recurrent events of atrial fibrillation and myocardial infarction: the HUNT study

Genetic research into atrial fibrillation (AF) and myocardial infarction (MI) has predominantly focused on comparing afflicted individuals with their healthy counterparts. However, this approach lacks granularity, thus overlooking subtleties within patient populations. In this study, we explore the distinction between AF and MI patients who experience only a single disease event and those experiencing recurrent events. Integrating hospital records, questionnaire data, clinical measurements, and genetic data from more than 500,000 HUNT and United Kingdom Biobank participants, we compare both clinical and genetic characteristics between the two groups using genome-wide association studies (GWAS) meta-analyses, phenome-wide association studies (PheWAS) analyses, and gene co-expression networks. We found that the two groups of patients differ in both clinical characteristics and genetic risks. More specifically, recurrent AF patients are significantly younger and have better baseline health, in terms of reduced cholesterol and blood pressure, than single AF patients. Also, the results of the GWAS meta-analysis indicate that recurrent AF patients seem to be at greater genetic risk for recurrent events. The PheWAS and gene co-expression network analyses highlight differences in the functions associated with the sets of single nucleotide polymorphisms (SNPs) and genes for the two groups. However, for MI patients, we found that those experiencing single events are significantly younger and have better baseline health than those with recurrent MI, yet they exhibit higher genetic risk. The GWAS meta-analysis mostly identifies genetic regions uniquely associated with single MI, and the PheWAS analysis and gene co-expression networks support the genetic differences between the single MI and recurrent MI groups. In conclusion, this work has identified novel genetic regions uniquely associated with single MI and related PheWAS analyses, as well as gene co-expression networks that support the genetic differences between the patient subgroups of single and recurrent occurrence for both MI and AF.publishedVersio

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression

Motivation: A typical genome-wide association study searches for associations between single nucleotide polymorphisms (SNPs) and a univariate phenotype. However, there is a growing interest to investigate associations between genomics data and multivariate phenotypes, for example, in gene expression or metabolomics studies. A common approach is to perform a univariate test between each genotype–phenotype pair, and then to apply a stringent significance cutoff to account for the large number of tests performed. However, this approach has limited ability to uncover dependencies involving multiple variables. Another trend in the current genetics is the investigation of the impact of rare variants on the phenotype, where the standard methods often fail owing to lack of power when the minor allele is present in only a limited number of individuals. Results: We propose a new statistical approach based on Bayesian reduced rank regression to assess the impact of multiple SNPs on a high-dimensional phenotype. Because of the method’s ability to combine information over multiple SNPs and phenotypes, it is particularly suitable for detecting associations involving rare variants. We demonstrate the potential of our method and compare it with alternatives using the Northern Finland Birth Cohort with 4702 individuals, for whom genome-wide SNP data along with lipoprotein profiles comprising 74 traits are available. We discovered two genes (XRCC4 and MTHFD2L) without previously reported associations, which replicated in a combined analysis of two additional cohorts: 2390 individuals from the Cardiovascular Risk in Young Finns study and 3659 individuals from the FINRISK study. Availability and implementation: R-code freely available for download at http://users.ics.aalto.fi/pemartti/gene_metabolome/. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries.

Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans

Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries.

The original version of this article contained an error in the name of the author Ramachandran S. Vasan, which was incorrectly given as Vasan S. Ramachandran. This has now been corrected in both the PDF and HTML versions of the article

Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD

Impact of Common Variation in Bone-Related Genes on Type 2 Diabetes and Related Traits

Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r2 > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post–oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations

ANGPTL8 protein-truncating variant associated with lower serum triglycerides and risk of coronary disease

Protein-truncating variants (PTVs) affecting dyslipidemia risk may point to therapeutic targets for cardiometabolic disease. Our objective was to identify PTVs that were associated with both lipid levels and the risk of coronary artery disease (CAD) or type 2 diabetes (T2D) and assess their possible associations with risks of other diseases. To achieve this aim, we leveraged the enrichment of PTVs in the Finnish population and tested the association of low-frequency PTVs in 1,209 genes with serum lipid levels in the Finrisk Study (n = 23,435). We then tested which of the lipid-associated PTVs were also associated with the risks of T2D or CAD, as well as 2,683 disease endpoints curated in the FinnGen Study (n = 218,792). Two PTVs were associated with both lipid levels and the risk of CAD or T2D: triglyceride-lowering variants in ANGPTL8 (-24.0[-30.4 to -16.9] mg/dL per rs760351239-T allele, P = 3.4 x 10(-9)) and ANGPTL4 (-14.4[-18.6 to -9.8] mg/dL per rs746226153-G allele, P = 4.3 x 10(-9)). The risk of T2D was lower in carriers of the ANGPTL4 PTV (OR = 0.70[0.60-0.81], P = 2.2 x 10(-6)) than noncarriers. The odds of CAD were 47% lower in carriers of a PTV in ANGPTL8 (OR = 0.53[0.37-0.76], P = 4.5 x 10(-4)) than noncarriers. Finally, the phenome-wide scan of the ANGPTL8 PTV showed that the ANGPTL8 PTV carriers were less likely to use statin therapy (68,782 cases, OR = 0.52[0.40-0.68], P = 1.7 x 10(-6)) compared to noncarriers. Our findings provide genetic evidence of potential long-term efficacy and safety of therapeutic targeting of dyslipidemias. Author summary Studying the health impacts of protein-truncating variants (PTVs) enables detecting the health impact of drugs that inhibit these same genes. Our study aimed to expand our knowledge of genes associated with cardiometabolic disease, along with the side effects of these genes. To detect PTVs associated with cardiometabolic disease, we first performed a genome-wide scan of PTVs associated with serum lipid levels in Finns. We found PTVs in two genes highly enriched in Finns, which were associated with both serum lipid levels and a lower risk of type 2 diabetes or coronary artery disease: ANGPTL4 and ANGPTL8. To evaluate the other health effects of these PTVs, we performed an association scan between the PTVs and 2,683 disease endpoints curated in the FinnGen Study (n = 218,792). We demonstrate that using human populations with PTV-enrichment, such as Finns, offers considerable boosts in statistical power to detect potential long-term efficacy and safety of pharmacologically targeting genes.Peer reviewe