Complex effects of sequence variants on lipid levels and coronary artery disease.

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.

Large-scale plasma proteomics comparisons through genetics and disease associations.

High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.

The sequences of 150,119 genomes in the UK Biobank.

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

The power of genetic diversity in genome-wide association studies of lipids.

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

Actionable Genotypes and Their Association with Life Span in Iceland.

BACKGROUND: In 2021, the American College of Medical Genetics and Genomics (ACMG) recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available. Evaluations of the association of actionable genotypes in these genes with life span are currently lacking. METHODS: We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings, version 3.0 (ACMG SF v3.0), list in the genomes of 57,933 Icelanders. We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database, the frequency of variants, and their associations with disease to create a manually curated set of actionable genotypes (variants). We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers. RESULTS: Through manual curation of 4405 sequence variants in the ACMG SF v3.0 genes, we identified 235 actionable genotypes in 53 genes. Of the 57,933 participants, 2306 (4.0%) carried at least one actionable genotype. We found shorter median survival among persons carrying actionable genotypes than among noncarriers. Specifically, we found that carrying an actionable genotype in a cancer gene was associated with survival that was 3 years shorter than that among noncarriers, with causes of death among carriers attributed primarily to cancer-related conditions. Furthermore, we found evidence of association between carrying an actionable genotype in certain genes in the cardiovascular disease group and a reduced life span. CONCLUSIONS: On the basis of the ACMG SF v3.0 guidelines, we found that approximately 1 in 25 Icelanders carried an actionable genotype and that carrying such a genotype was associated with a reduced life span. (Funded by deCODE Genetics-Amgen.).

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids.

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Genetic variants associated with syncope implicate neural and autonomic processes.

AIMS: Syncope is a common and clinically challenging condition. In this study, the genetics of syncope were investigated to seek knowledge about its pathophysiology and prognostic implications. METHODS AND RESULTS: This genome-wide association meta-analysis included 56 071 syncope cases and 890 790 controls from deCODE genetics (Iceland), UK Biobank (United Kingdom), and Copenhagen Hospital Biobank Cardiovascular Study/Danish Blood Donor Study (Denmark), with a follow-up assessment of variants in 22 412 cases and 286 003 controls from Intermountain (Utah, USA) and FinnGen (Finland). The study yielded 18 independent syncope variants, 17 of which were novel. One of the variants, p.Ser140Thr in PTPRN2, affected syncope only when maternally inherited. Another variant associated with a vasovagal reaction during blood donation and five others with heart rate and/or blood pressure regulation, with variable directions of effects. None of the 18 associations could be attributed to cardiovascular or other disorders. Annotation with regard to regulatory elements indicated that the syncope variants were preferentially located in neural-specific regulatory regions. Mendelian randomization analysis supported a causal effect of coronary artery disease on syncope. A polygenic score (PGS) for syncope captured genetic correlation with cardiovascular disorders, diabetes, depression, and shortened lifespan. However, a score based solely on the 18 syncope variants performed similarly to the PGS in detecting syncope risk but did not associate with other disorders. CONCLUSION: The results demonstrate that syncope has a distinct genetic architecture that implicates neural regulatory processes and a complex relationship with heart rate and blood pressure regulation. A shared genetic background with poor cardiovascular health was observed, supporting the importance of a thorough assessment of individuals presenting with syncope.

Dyslipidemia, inflammation, calcification, and adiposity in aortic stenosis: a genome-wide study.

AIMS: Although highly heritable, the genetic etiology of calcific aortic stenosis (AS) remains incompletely understood. The aim of this study was to discover novel genetic contributors to AS and to integrate functional, expression, and cross-phenotype data to identify mechanisms of AS. METHODS AND RESULTS: A genome-wide meta-analysis of 11.6 million variants in 10 cohorts involving 653 867 European ancestry participants (13 765 cases) was performed. Seventeen loci were associated with AS at P ≤ 5 × 10-8, of which 15 replicated in an independent cohort of 90 828 participants (7111 cases), including CELSR2-SORT1, NLRP6, and SMC2. A genetic risk score comprised of the index variants was associated with AS [odds ratio (OR) per standard deviation, 1.31; 95% confidence interval (CI), 1.26-1.35; P = 2.7 × 10-51] and aortic valve calcium (OR per standard deviation, 1.22; 95% CI, 1.08-1.37; P = 1.4 × 10-3), after adjustment for known risk factors. A phenome-wide association study indicated multiple associations with coronary artery disease, apolipoprotein B, and triglycerides. Mendelian randomization supported a causal role for apolipoprotein B-containing lipoprotein particles in AS (OR per g/L of apolipoprotein B, 3.85; 95% CI, 2.90-5.12; P = 2.1 × 10-20) and replicated previous findings of causality for lipoprotein(a) (OR per natural logarithm, 1.20; 95% CI, 1.17-1.23; P = 4.8 × 10-73) and body mass index (OR per kg/m2, 1.07; 95% CI, 1.05-1.9; P = 1.9 × 10-12). Colocalization analyses using the GTEx database identified a role for differential expression of the genes LPA, SORT1, ACTR2, NOTCH4, IL6R, and FADS. CONCLUSION: Dyslipidemia, inflammation, calcification, and adiposity play important roles in the etiology of AS, implicating novel treatments and prevention strategies.

Spread of SARS-CoV-2 in the Icelandic Population.

BACKGROUND: During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was first diagnosed in Iceland at the end of February. However, data are limited on how SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population. METHODS: We targeted testing to persons living in Iceland who were at high risk for infection (mainly those who were symptomatic, had recently traveled to high-risk countries, or had contact with infected persons). We also carried out population screening using two strategies: issuing an open invitation to 10,797 persons and sending random invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples. RESULTS: As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening. CONCLUSIONS: In a population-based study in Iceland, children under 10 years of age and females had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males. The proportion of infected persons identified through population screening did not change substantially during the screening period, which was consistent with a beneficial effect of containment efforts. (Funded by deCODE Genetics-Amgen.).

Humoral Immune Response to SARS-CoV-2 in Iceland.

BACKGROUND: Little is known about the nature and durability of the humoral immune response to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We measured antibodies in serum samples from 30,576 persons in Iceland, using six assays (including two pan-immunoglobulin [pan-Ig] assays), and we determined that the appropriate measure of seropositivity was a positive result with both pan-Ig assays. We tested 2102 samples collected from 1237 persons up to 4 months after diagnosis by a quantitative polymerase-chain-reaction (qPCR) assay. We measured antibodies in 4222 quarantined persons who had been exposed to SARS-CoV-2 and in 23,452 persons not known to have been exposed. RESULTS: Of the 1797 persons who had recovered from SARS-CoV-2 infection, 1107 of the 1215 who were tested (91.1%) were seropositive; antiviral antibody titers assayed by two pan-Ig assays increased during 2 months after diagnosis by qPCR and remained on a plateau for the remainder of the study. Of quarantined persons, 2.3% were seropositive; of those with unknown exposure, 0.3% were positive. We estimate that 0.9% of Icelanders were infected with SARS-CoV-2 and that the infection was fatal in 0.3%. We also estimate that 56% of all SARS-CoV-2 infections in Iceland had been diagnosed with qPCR, 14% had occurred in quarantined persons who had not been tested with qPCR (or who had not received a positive result, if tested), and 30% had occurred in persons outside quarantine and not tested with qPCR. CONCLUSIONS: Our results indicate that antiviral antibodies against SARS-CoV-2 did not decline within 4 months after diagnosis. We estimate that the risk of death from infection was 0.3% and that 44% of persons infected with SARS-CoV-2 in Iceland were not diagnosed by qPCR.

Polygenic risk score for ACE-inhibitor-associated cough based on the discovery of new genetic loci.

AIMS: To search for sequence variants associated with ACEi discontinuation and to test their association with ACEi-associated adverse drug reactions (ADRs). METHODS AND RESULTS: A genome-wide association study (GWAS) on ACEi discontinuation was conducted, including 33 959 ACEi-discontinuers and 44 041 controls. Cases were defined as persons who switched from an ACEi treatment to an angiotensin receptor blocker. Controls were defined as persons who continued ACEi treatment for at least 1 year. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were computed for ACEi discontinuation risk by mixed model regression analysis. Summary statistics from the individual cohorts were meta-analyzed with a fixed-effects model. To test for association with specific ACEi-associated ADRs, any genome-wide significant (P < 5 × 10-8) ACEi discontinuation variants was tested for association with ACEi-associated cough and angioedema. A polygenetic risk score (PRS) based on ACEi discontinuation GWAS data was constructed and tested for association with ACEi-associated cough and angioedema in two population-based samples. In total, seven genetic genome-wide loci were identified, of which six were previously unreported. The strongest association with ACEi discontinuation was at 20q13.3 (NTSR1; OR: 1.21; 95% CI: 1.17-1.24; P = 2.1 × 10-34). Five of seven lead variants were associated with ACEi-associated cough, whereas none were associated with ACEi-associated angioedema. The ACEi discontinuation PRS was associated with ACEi-associated cough in a dose-response manner but not with ACEi-associated angioedema. ACEi discontinuation was genetically correlated with important causes for cough, including gastro-esophageal reflux disease, allergic rhinitis, hay fever, and asthma, which indicates partly shared genetic underpinning between these traits. CONCLUSION: This study showed the advantage of using prescription patterns to discover genetic links with ADRs. In total, seven genetic loci that associated with ACEi discontinuation were identified. There was evidence of a strong association between our ADR phenotype and ACEi-associated cough. Taken together, these findings increase insight into the pathophysiological processes that underlie ACEi-associated ADRs.

Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events.

Importance: Whether protein risk scores derived from a single plasma sample could be useful for risk assessment for atherosclerotic cardiovascular disease (ASCVD), in conjunction with clinical risk factors and polygenic risk scores, is uncertain. Objective: To develop protein risk scores for ASCVD risk prediction and compare them to clinical risk factors and polygenic risk scores in primary and secondary event populations. Design, Setting, and Participants: The primary analysis was a retrospective study of primary events among 13 540 individuals in Iceland (aged 40-75 years) with proteomics data and no history of major ASCVD events at recruitment (study duration, August 23, 2000 until October 26, 2006; follow-up through 2018). We also analyzed a secondary event population from a randomized, double-blind lipid-lowering clinical trial (2013-2016), consisting of individuals with stable ASCVD receiving statin therapy and for whom proteomic data were available for 6791 individuals. Exposures: Protein risk scores (based on 4963 plasma protein levels and developed in a training set in the primary event population); polygenic risk scores for coronary artery disease and stroke; and clinical risk factors that included age, sex, statin use, hypertension treatment, type 2 diabetes, body mass index, and smoking status at the time of plasma sampling. Main Outcomes and Measures: Outcomes were composites of myocardial infarction, stroke, and coronary heart disease death or cardiovascular death. Performance was evaluated using Cox survival models and measures of discrimination and reclassification that accounted for the competing risk of non-ASCVD death. Results: In the primary event population test set (4018 individuals [59.0% women]; 465 events; median follow-up, 15.8 years), the protein risk score had a hazard ratio (HR) of 1.93 per SD (95% CI, 1.75 to 2.13). Addition of protein risk score and polygenic risk scores significantly increased the C index when added to a clinical risk factor model (C index change, 0.022 [95% CI, 0.007 to 0.038]). Addition of the protein risk score alone to a clinical risk factor model also led to a significantly increased C index (difference, 0.014 [95% CI, 0.002 to 0.028]). Among White individuals in the secondary event population (6307 participants; 432 events; median follow-up, 2.2 years), the protein risk score had an HR of 1.62 per SD (95% CI, 1.48 to 1.79) and significantly increased C index when added to a clinical risk factor model (C index change, 0.026 [95% CI, 0.011 to 0.042]). The protein risk score was significantly associated with major adverse cardiovascular events among individuals of African and Asian ancestries in the secondary event population. Conclusions and Relevance: A protein risk score was significantly associated with ASCVD events in primary and secondary event populations. When added to clinical risk factors, the protein risk score and polygenic risk score both provided statistically significant but modest improvement in discrimination.

Large-Scale Screening for Monogenic and Clinically Defined Familial Hypercholesterolemia in Iceland.

Objective: Familial hypercholesterolemia (FH) is traditionally defined as a monogenic disease characterized by severely elevated LDL-C (low-density lipoprotein cholesterol) levels. In practice, FH is commonly a clinical diagnosis without confirmation of a causative mutation. In this study, we sought to characterize and compare monogenic and clinically defined FH in a large sample of Icelanders. Approach and Results: We whole-genome sequenced 49 962 Icelanders and imputed the identified variants into an overall sample of 166 281 chip-genotyped Icelanders. We identified 20 FH mutations in LDLR, APOB, and PCSK9 with combined prevalence of 1 in 836. Monogenic FH was associated with severely elevated LDL-C levels and increased risk of premature coronary disease, aortic valve stenosis, and high burden of coronary atherosclerosis. We used a modified version of the Dutch Lipid Clinic Network criteria to screen for the clinical FH phenotype among living adult participants (N=79 058). Clinical FH was found in 2.2% of participants, of whom only 5.2% had monogenic FH. Mutation-negative clinical FH has a strong polygenic basis. Both individuals with monogenic FH and individuals with mutation-negative clinical FH were markedly undertreated with cholesterol-lowering medications and only a minority attained an LDL-C target of <2.6 mmol/L (<100 mg/dL; 11.0% and 24.9%, respectively) or <1.8 mmol/L (<70 mg/dL; 0.0% and 5.2%, respectively), as recommended for primary prevention by European Society of Cardiology/European Atherosclerosis Society cholesterol guidelines. Conclusions: Clinically defined FH is a relatively common phenotype that is explained by monogenic FH in only a minority of cases. Both monogenic and clinical FH confer high cardiovascular risk but are markedly undertreated.

Genetic insight into sick sinus syndrome.

AIMS: The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. METHODS AND RESULTS: We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1-1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10-20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). CONCLUSION: We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Genetic insight into sick sinus syndrome.

AIMS: The aim of this study was to use human genetics to investigate the pathogenesis of sick sinus syndrome (SSS) and the role of risk factors in its development. METHODS AND RESULTS: We performed a genome-wide association study of 6469 SSS cases and 1 000 187 controls from deCODE genetics, the Copenhagen Hospital Biobank, UK Biobank, and the HUNT study. Variants at six loci associated with SSS, a reported missense variant in MYH6, known atrial fibrillation (AF)/electrocardiogram variants at PITX2, ZFHX3, TTN/CCDC141, and SCN10A and a low-frequency (MAF = 1.1-1.8%) missense variant, p.Gly62Cys in KRT8 encoding the intermediate filament protein keratin 8. A full genotypic model best described the p.Gly62Cys association (P = 1.6 × 10-20), with an odds ratio (OR) of 1.44 for heterozygotes and a disproportionally large OR of 13.99 for homozygotes. All the SSS variants increased the risk of pacemaker implantation. Their association with AF varied and p.Gly62Cys was the only variant not associating with any other arrhythmia or cardiovascular disease. We tested 17 exposure phenotypes in polygenic score (PGS) and Mendelian randomization analyses. Only two associated with the risk of SSS in Mendelian randomization, AF, and lower heart rate, suggesting causality. Powerful PGS analyses provided convincing evidence against causal associations for body mass index, cholesterol, triglycerides, and type 2 diabetes (P > 0.05). CONCLUSION: We report the associations of variants at six loci with SSS, including a missense variant in KRT8 that confers high risk in homozygotes and points to a mechanism specific to SSS development. Mendelian randomization supports a causal role for AF in the development of SSS.

Sequence variants associating with urinary biomarkers.

Urine dipstick tests are widely used in routine medical care to diagnose kidney and urinary tract and metabolic diseases. Several environmental factors are known to affect the test results, whereas the effects of genetic diversity are largely unknown. We tested 32.5 million sequence variants for association with urinary biomarkers in a set of 150 274 Icelanders with urine dipstick measurements. We detected 20 association signals, of which 14 are novel, associating with at least one of five clinical entities defined by the urine dipstick: glucosuria, ketonuria, proteinuria, hematuria and urine pH. These include three independent glucosuria variants at SLC5A2, the gene encoding the sodium-dependent glucose transporter (SGLT2), a protein targeted pharmacologically to increase urinary glucose excretion in the treatment of diabetes. Two variants associating with proteinuria are in LRP2 and CUBN, encoding the co-transporters megalin and cubilin, respectively, that mediate proximal tubule protein uptake. One of the hematuria-associated variants is a rare, previously unreported 2.5 kb exonic deletion in COL4A3. Of the four signals associated with urine pH, we note that the pH-increasing alleles of two variants (POU2AF1, WDR72) associate significantly with increased risk of kidney stones. Our results reveal that genetic factors affect variability in urinary biomarkers, in both a disease dependent and independent context.

Genetic variability in the absorption of dietary sterols affects the risk of coronary artery disease.

AIMS: To explore whether variability in dietary cholesterol and phytosterol absorption impacts the risk of coronary artery disease (CAD) using as instruments sequence variants in the ABCG5/8 genes, key regulators of intestinal absorption of dietary sterols. METHODS AND RESULTS: We examined the effects of ABCG5/8 variants on non-high-density lipoprotein (non-HDL) cholesterol (N up to 610 532) and phytosterol levels (N = 3039) and the risk of CAD in Iceland, Denmark, and the UK Biobank (105 490 cases and 844 025 controls). We used genetic scores for non-HDL cholesterol to determine whether ABCG5/8 variants confer greater risk of CAD than predicted by their effect on non-HDL cholesterol. We identified nine rare ABCG5/8 coding variants with substantial impact on non-HDL cholesterol. Carriers have elevated phytosterol levels and are at increased risk of CAD. Consistent with impact on ABCG5/8 transporter function in hepatocytes, eight rare ABCG5/8 variants associate with gallstones. A genetic score of ABCG5/8 variants predicting 1 mmol/L increase in non-HDL cholesterol associates with two-fold increase in CAD risk [odds ratio (OR) = 2.01, 95% confidence interval (CI) 1.75-2.31, P = 9.8 × 10-23] compared with a 54% increase in CAD risk (OR = 1.54, 95% CI 1.49-1.59, P = 1.1 × 10-154) associated with a score of other non-HDL cholesterol variants predicting the same increase in non-HDL cholesterol (P for difference in effects = 2.4 × 10-4). CONCLUSIONS: Genetic variation in cholesterol absorption affects levels of circulating non-HDL cholesterol and risk of CAD. Our results indicate that both dietary cholesterol and phytosterols contribute directly to atherogenesis.