Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids

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

Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland

Polygenic scores (PSs) are becoming a useful tool to identify individuals with high genetic risk for complex diseases, and several projects are currently testing their utility for translational applications. It is also tempting to use PSs to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how the population genetic properties of the training and target samples affect the geographic distribution of PSs. Here, we evaluate geographic differences, and related biases, of PSs in Finland in a geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PSs for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waist-hip ratio (WHR), body-mass index (BMI), and height, but not for Crohn disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PSs and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulations of geographic differences for CAD, WHR, BMI, and height, suggesting bias arising from the population's genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PSs are for small biases even within relatively homogeneous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PSs is essential for translational applications of PSs.Peer reviewe

Genetic Risk Score for Serum 25-Hydroxyvitamin D Concentration Helps to Guide Personalized Vitamin D Supplementation in Healthy Finnish Adults

Background Genetic factors modify serum 25-hydroxyvitamin D [25(OH)D] concentration and can affect the optimal intake of vitamin D. Objectives We aimed to personalize vitamin D supplementation by applying knowledge of genetic factors affecting serum 25(OH)D concentration. Methods We performed a genome-wide association study of serum 25(OH)D concentration in the Finnish Health 2011 cohort (n = 3339) using linear regression and applied the results to develop a population-matched genetic risk score (GRS) for serum 25(OH)D. This GRS was used to tailor vitamin D supplementation for 96 participants of a longitudinal Digital Health Revolution (DHR) Study. The GRS, serum 25(OH)D concentrations, and personalized supplementation and dietary advice were electronically returned to participants. Serum 25(OH)D concentrations were assessed using immunoassays and vitamin D intake using FFQs. In data analyses, cross-sectional and repeated-measures statistical tests and models were applied as described in detail elsewhere. Results GC vitamin D-binding protein and cytochrome P450 family 2 subfamily R polypeptide 1 genes showed genome-wide significant associations with serum 25(OH)D concentration. One single nucleotide polymorphism from each locus (rs4588 and rs10741657) was used to develop the GRS. After returning data to the DHR Study participants, daily vitamin D supplement users increased from 32.6% to 60.2% (P = 6.5 x 10(-6)) and serum 25(OH)D concentration from 64.4 +/- 20.9 nmol/L to 68.5 +/- 19.2 nmol/L (P = 0.006) between August and November. Notably, the difference in serum 25(OH)D concentrations between participants with no risk alleles and those with 3 or 4 risk alleles decreased from 20.7 nmol/L to 8.0 nmol/L (P = 0.0063). Conclusions We developed and applied a population-matched GRS to identify individuals genetically predisposed to low serum 25(OH)D concentration. We show how the electronic return of individual genetic risk, serum 25(OH)D concentrations, and factors affecting vitamin D status can be used to tailor vitamin D supplementation. This model could be applied to other populations and countries.Peer reviewe

Genetic analyses implicate complex links between adult testosterone levels and health and disease

BackgroundTestosterone levels are linked with diverse characteristics of human health, yet, whether these associations reflect correlation or causation remains debated. Here, we provide a broad perspective on the role of genetically determined testosterone on complex diseases in both sexes.MethodsLeveraging genetic and health registry data from the UK Biobank and FinnGen (total N = 625,650), we constructed polygenic scores (PGS) for total testosterone, sex-hormone binding globulin (SHBG) and free testosterone, associating these with 36 endpoints across different disease categories in the FinnGen. These analyses were combined with Mendelian Randomization (MR) and cross-sex PGS analyses to address causality.ResultsWe show testosterone and SHBG levels are intricately tied to metabolic health, but report lack of causality behind most associations, including type 2 diabetes (T2D). Across other disease domains, including 13 behavioral and neurological diseases, we similarly find little evidence for a substantial contribution from normal variation in testosterone levels. We nonetheless find genetically predicted testosterone affects many sex-specific traits, with a pronounced impact on female reproductive health, including causal contribution to PCOS-related traits like hirsutism and post-menopausal bleeding (PMB). We also illustrate how testosterone levels associate with antagonistic effects on stroke risk and reproductive endpoints between the sexes.ConclusionsOverall, these findings provide insight into how genetically determined testosterone correlates with several health parameters in both sexes. Yet the lack of evidence for a causal contribution to most traits beyond sex-specific health underscores the complexity of the mechanisms linking testosterone levels to disease risk and sex differences.Plain language summaryHormones, such as testosterone, travel around the body communicating between the different parts. Testosterone is present at higher levels in men, but also present in women. Variable testosterone levels explain some differences in human traits and disease prevalence. Here, we study how adult testosterone levels relate to health and disease. Genetic, i.e. inherited, differences in testosterone levels contribute to many traits specific to men or women, such as women's reproductive health, hormonal cancers, and hair growth typical in males. However, testosterone levels do not appear as a major cause of most traits studied, including psychiatric diseases and metabolic health. Normal variation in baseline testosterone levels thus seems to have a relatively minor impact on health and disease.Leinonen et al. investigate correlations between testosterone levels and disease using genetic and health registry data from the UK Biobank and FinnGen. There is a lack of evidence for normal variation in testosterone levels having a causal contribution to most non-sex-specific traits.Peer reviewe

Genetic Risk Score for Serum 25-Hydroxyvitamin D Concentration Helps to Guide Personalized Vitamin D Supplementation in Healthy Finnish Adults

Background Genetic factors modify serum 25-hydroxyvitamin D [25(OH)D] concentration and can affect the optimal intake of vitamin D. Objectives We aimed to personalize vitamin D supplementation by applying knowledge of genetic factors affecting serum 25(OH)D concentration. Methods We performed a genome-wide association study of serum 25(OH)D concentration in the Finnish Health 2011 cohort (n = 3339) using linear regression and applied the results to develop a population-matched genetic risk score (GRS) for serum 25(OH)D. This GRS was used to tailor vitamin D supplementation for 96 participants of a longitudinal Digital Health Revolution (DHR) Study. The GRS, serum 25(OH)D concentrations, and personalized supplementation and dietary advice were electronically returned to participants. Serum 25(OH)D concentrations were assessed using immunoassays and vitamin D intake using FFQs. In data analyses, cross-sectional and repeated-measures statistical tests and models were applied as described in detail elsewhere. Results GC vitamin D-binding protein and cytochrome P450 family 2 subfamily R polypeptide 1 genes showed genome-wide significant associations with serum 25(OH)D concentration. One single nucleotide polymorphism from each locus (rs4588 and rs10741657) was used to develop the GRS. After returning data to the DHR Study participants, daily vitamin D supplement users increased from 32.6% to 60.2% (P = 6.5 x 10(-6)) and serum 25(OH)D concentration from 64.4 +/- 20.9 nmol/L to 68.5 +/- 19.2 nmol/L (P = 0.006) between August and November. Notably, the difference in serum 25(OH)D concentrations between participants with no risk alleles and those with 3 or 4 risk alleles decreased from 20.7 nmol/L to 8.0 nmol/L (P = 0.0063). Conclusions We developed and applied a population-matched GRS to identify individuals genetically predisposed to low serum 25(OH)D concentration. We show how the electronic return of individual genetic risk, serum 25(OH)D concentrations, and factors affecting vitamin D status can be used to tailor vitamin D supplementation. This model could be applied to other populations and countries.Peer reviewe

An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease

Multivariate methods are known to increase the statistical power to detect associations in the case of shared genetic basis between phenotypes. They have, however, lacked essential analytic tools to follow-up and understand the biology underlying these associations. We developed a novel computational workflow for multivariate GWAS follow-up analyses, including fine-mapping and identification of the subset of traits driving associations (driver traits). Many follow-up tools require univariate regression coefficients which are lacking from multivariate results. Our method overcomes this problem by using Canonical Correlation Analysis to turn each multivariate association into its optimal univariate Linear Combination Phenotype (LCP). This enables an LCP-GWAS, which in turn generates the statistics required for follow-up analyses. We implemented our method on 12 highly correlated inflammatory biomarkers in a Finnish population-based study. Altogether, we identified 11 associations, four of which (F5, ABO, C1orf140 and PDGFRB) were not detected by biomarker-specific analyses. Fine-mapping identified 19 signals within the 11 loci and driver trait analysis determined the traits contributing to the associations. A phenome-wide association study on the 19 representative variants from the signals in 176,899 individuals from the FinnGen study revealed 53 disease associations (p <1 x 10(-4)). Several reported pQTLs in the 11 loci provided orthogonal evidence for the biologically relevant functions of the representative variants. Our novel multivariate analysis workflow provides a powerful addition to standard univariate GWAS analyses by enabling multivariate GWAS follow-up and thus promoting the advancement of powerful multivariate methods in genomics.Peer reviewe

Chromosome Xq23 Is Associated with Lower Atherogenic Lipid Concentrations and Favorable Cardiometabolic Indices

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids

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 &gt;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

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