Erik Ingelsson

Background: Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease. Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual’s genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. Methods: We explored the association between 405 clinical conditions diagnosed before baseline and 9080 incident cases of ACS in 387 832 individuals from the UK Biobank. Results were replicated in 6430 incident cases of ACS in 177 876 individuals from FinnGen. Results: We identified 80 conventional (eg, stable angina pectoris and type 2 diabetes) and unconventional (eg, diaphragmatic hernia and inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of stable angina pectoris yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction P =2.87×10 ⁻⁸ ) risk for ACS in individuals with stable angina pectoris (hazard ratio, 1.163 [95% CI, 1.082–1.251]) compared with individuals without stable angina pectoris (hazard ratio, 1.531 [95% CI, 1.497–1.565]). These findings were replicated in FinnGen (interaction P =1.38×10 ⁻⁶ ). Conclusions: In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable coronary heart disease. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for coronary heart disease.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21276-3

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin atIRS1andZNF12loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

The clinical evaluation of a genetic syndrome relies upon recognition of a characteristic pattern of signs or symptoms to guide targeted genetic testing for confirmation of the diagnosis. However, individuals displaying a single phenotype of a complex syndrome may not meet criteria for clinical diagnosis or genetic testing. Here, we present a phenome-wide association study (PheWAS) approach to systematically explore the phenotypic expressivity of common and rare alleles in genes associated with four well-described syndromic diseases (Alagille (AS), Marfan (MS), DiGeorge (DS), and Noonan (NS) syndromes) in the general population. Using human phenotype ontology (HPO) terms, we systematically mapped 60 phenotypes related to AS, MS, DS and NS in 337,198 unrelated white British from the UK Biobank (UKBB) based on their hospital admission records, self-administrated questionnaires, and physiological measurements. We performed logistic regression adjusting for age, sex, and the first 5 genetic principal components, for each phenotype and each variant in the target genes (JAG1, NOTCH2 FBN1, PTPN1 and RAS-opathy genes, and genes in the 22q11.2 locus) and performed a gene burden test. Overall, we observed multiple phenotype-genotype correlations, such as the association between variation in JAG1, FBN1, PTPN11 and SOS2 with diastolic and systolic blood pressure; and pleiotropy among multiple variants in syndromic genes. For example, rs11066309 in PTPN11 was significantly associated with a lower body mass index, an increased risk of hypothyroidism and a smaller size for gestational age, all in concordance with NS-related phenotypes. Similarly, rs589668 in FBN1 was associated with an increase in body height and blood pressure, and a reduced body fat percentage as observed in Marfan syndrome. Our findings suggest that the spectrum of associations of common and rare variants in genes involved in syndromic diseases can be extended to individual phenotypes within the general population.

Background: Circulating biomarkers have been previously associated with atherosclerosis-related risk factors, but the nature of these associations is incompletely understood.Methods: We performed multivariable-adjusted regressions and 2-sample Mendelian randomization analyses to assess observational and causal associations of 27 circulating biomarkers with 7 cardiovascular traits in up to 451 933 participants of the UK Biobank.Results: After multiple-testing correction (alpha=1.3×10⁻⁴), we found a total of 15, 9, 21, 22, 26, 24, and 26 biomarkers strongly associated with coronary artery disease, ischemic stroke, atrial fibrillation, type 2 diabetes, systolic blood pressure, body mass index, and waist-to-hip ratio; respectively. The Mendelian randomization analyses confirmed strong evidence of previously suggested causal associations for several glucose- and lipid-related biomarkers with type 2 diabetes and coronary artery disease. Particularly interesting findings included a protective role of IGF-1 (insulin-like growth factor 1) in systolic blood pressure, and the strong causal association of lipoprotein(a) in coronary artery disease development (β, −0.13; per SD change in exposure and outcome and odds ratio, 1.28;P=2.6×10⁻⁴andP=7.4×10⁻³⁵, respectively). In addition, our results indicated a causal role of increased ALT (alanine aminotransferase) in the development of type 2 diabetes and hypertension (odds ratio, 1.59 and β, 0.06, per SD change in exposure and outcome;P=4.8×10⁻¹¹andP=6.0×10⁻⁵). Our results suggest that it is unlikely that CRP (C-reactive protein) and vitamin D play causal roles of any meaningful magnitude in development of cardiometabolic disease.Conclusions: We confirmed and extended known associations and reported several novel causal associations providing important insights about the cause of these diseases, which can help accelerate new prevention strategies.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Aims: Early prediction of acute coronary syndrome (ACS) is a major goal for prevention of coronary heart disease (CHD). Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual’s genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. Methods and Results: We explored the association between 405 clinical conditions diagnosed before baseline and 9,080 incident cases of ACS in 387,832 individuals from the UK Biobank. We identified 80 conventional (e.g., stable angina pectoris (SAP), type 2 diabetes mellitus) and unconventional (e.g., diaphragmatic hernia, inguinal hernia) associations with ACS. Results were replicated in 6,430 incident cases of ACS in 177,876 individuals from FinnGen. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of SAP yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction p-value=2.87×10 ⁻⁸ ) risk for ACS in individuals with SAP (HR=1.163 [95% CI: 1.082–1.251]) compared to individuals without SAP (HR=1.531 [95% CI: 1.497–1.565]). These findings were replicated in FinnGen (interaction p-value=1.38×10 ⁻⁶ ). Conclusion: In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable CHD. PS for ACS may be more appropriate for asymptomatic individuals than symptomatic individuals with clinical suspicion for CHD.

A meta-analysis of genome-wide association studies (GWAS) identified eight loci that are associated with heart rate variability (HRV), but candidate genes in these loci remain uncharacterized. We developed an image- and CRISPR/Cas9-based pipeline to systematically characterize candidate genes for HRV in live zebrafish embryos. Nine zebrafish orthologues of six human candidate genes were targeted simultaneously in eggs from fish that transgenically express GFP on smooth muscle cells (Tg[acta2:GFP]), to visualize the beating heart. An automated analysis of repeated 30 s recordings of beating atria in 381 live, intact zebrafish embryos at 2 and 5 days post-fertilization highlighted genes that influence HRV (hcn4 and si:dkey-65j6.2 [KIAA1755]); heart rate (rgs6 and hcn4); and the risk of sinoatrial pauses and arrests (hcn4). Exposure to 10 or 25 µM ivabradine—an open channel blocker of HCNs—for 24 h resulted in a dose-dependent higher HRV and lower heart rate at 5 days post-fertilization. Hence, our screen confirmed the role of established genes for heart rate and rhythm (RGS6 and HCN4); showed that ivabradine reduces heart rate and increases HRV in zebrafish embryos, as it does in humans; and highlighted a novel gene that plays a role in HRV (KIAA1755).

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Background: Updated prevalence and outcome data for nonobese NAFLD for the multi‐ethnic US population is limited.Objectives: We aimed to investigate the prevalence, clinical characteristics and mortality of obese and nonobese individuals with NAFLD in the United Sates.Methods: A retrospective study was conducted using the 1999–2016 NHANES databases. We determined hazard ratio stratified by obesity status in NAFLD individuals using Cox regression and log‐rank test.Results: Overall NAFLD prevalence was 32.3%: 22.7% were obese and 9.6% were nonobese, with increasing trend over time for obese NAFLD, but not nonobese NAFLD. Amongst those with NAFLD, 29.7% (95% CI: 27.8%‐31.7%) were nonobese, of which 13.6% had lean NAFLD. Nonobese NAFLD was more common in older (40.9% if ≥ 65 vs. 24.2% if < 65 years), male (34.0% vs. 24.2%) and foreign‐born Asian people (39.8% vs. 11.4%) and uncommon in black (11.5% vs 30–35% in other ethnicities, P < 0.001). Metabolic comorbidities were common in nonobese NAFLD individuals who also had more advanced fibrosis. Nonobese NAFLD individuals had higher 15‐year cumulative all‐cause mortality (51.7%) than obese NAFLD (27.2%) and non‐NAFLD (20.7%) (P < 0.001). However, DM and fibrosis, but neither obese nor nonobese NAFLD compared to non‐NAFLD was independently associated with higher mortality.Conclusion: Nonobese NAFLD makes up about one‐third of the NAFLD in the United States (even higher in older, male and foreign‐born individuals) and carries higher mortality than obese NAFLD. Screening for NAFLD should be considered in high‐risk groups even in the absence of obesity.