Selected Recently Published Papers
Body composition and atrial fibrillation: a Mendelian randomization study
Increases in fat-free mass and fat mass have been associated with higher risk of atrial fibrillation (AF) in observational studies. It is not known whether these associations reflect independent causal processes. Our aim was to evaluate independent causal roles of fat-free mass and fat mass on AF.
We conducted a large observational study to estimate the associations between fat-free mass and fat mass on incident AF in the UK Biobank (N = 487 404, N events = 10 365). Genome-wide association analysis was performed to obtain genetic instruments for Mendelian randomization (MR). We evaluated the causal effects of fat-free mass and fat mass on AF with two-sample method by using genetic associations from AFGen consortium as outcome. Finally, we evaluated independent causal effects of fat-free mass and fat mass with multivariate MR. Both fat-free mass and fat mass had observational associations with incident AF [hazard ratio (HR) = 1.77, 95% confidence interval (CI) 1.72–1.83; HR = 1.40, 95% CI 1.37–1.43 per standard deviation increase in fat-free and fat mass, respectively]. The causal effects using the inverse-variance weighted method were 1.55 (95% CI 1.38–1.75) for fat-free mass and 1.30 (95% CI 1.17–1.45) for fat mass. Weighted median, Egger regression, and penalized methods showed similar estimates. The multivariate MR analysis suggested that the causal effects of fat-free and fat mass were independent of each other (causal risk ratios: 1.37, 95% CI 1.06–1.75; 1.28, 95% CI 1.03–1.58).
In conclusion, genetically programmed increases in fat-free mass and fat mass independently cause an increased risk of AF.
Reference: Tikkanen E, Gustafsson S, Knowles JW, Perez M, Burgess S, Ingelsson E. Body composition and atrial fibrillation: a Mendelian randomization study. Eur Heart J. 2019. doi: 10.1093/eurheartj/ehz003
Associations of Circulating Protein Levels With Lipid Fractions in the General Population
Revealing patterns of associations between circulating protein and lipid levels could improve biological understanding of cardiovascular disease (CVD). In this study, we investigated the associations between proteins related to CVD and triglyceride (TG), total cholesterol, LDL (low-density lipoprotein), and HDL (high-density lipoprotein) cholesterol levels in individuals from the general population.
We measured plasma protein levels using the Olink ProSeek CVD I or II+III arrays and analyzed 57 proteins available in 3 population-based cohorts: EpiHealth (n=2029; 52% women; median age, 61 years), PIVUS (Prospective Study of the Vasculature in Uppsala Seniors; n=790; 51% women; all aged 70 years), and ULSAM (Uppsala Longitudinal Study of Adult Men; n=551; all men aged 77 years). A discovery analysis was performed in EpiHealth in a regression framework (adjusted for sex, age, body mass index, smoking, glucose levels, systolic blood pressure, blood pressure medication, diabetes mellitus medication, and CVD history), and associations with false discovery rate <0.05 were further tested in PIVUS and ULSAM, where a P value of 0.05 was considered a successful replication (validation false discovery rate of 0.1%). We used summary statistics from a genome-wide association study on each protein biomarker (meta-analysis of EpiHealth, PIVUS, ULSAM, and IMPROVE [Carotid Intima-Media Thickness and IMT-Progression as Predictors of Vascular Events in a High-Risk European Population]) and publicly available data from Global Lipids Genetics Consortium to perform Mendelian randomization analyses to address possible causality of protein levels.
Of 57 tested proteins, 42 demonstrated an association with at least 1 lipid fraction; 35 were associated with TG, 15 with total cholesterol, 9 with LDL cholesterol, and 24 with HDL cholesterol. Among these associations, we found KIM-1 (kidney injury molecule-1), TNFR (TNF [tumor necrosis factor] receptor) 1 and 2, TRAIL-R2 (TRAIL [TNF-related apoptosis-inducing ligand] receptor 2), and RETN (resistin) to be associated with all 4 lipid fractions. Further, 15 proteins were related to both TG and HDL cholesterol in a consistent and biologically expected manner, that is, higher TG and lower HDL cholesterol or vice versa. Another common pattern of associations was concomitantly higher TG, total cholesterol, and LDL cholesterol, which is associated with higher CVD risk. We did not find evidence of causal links for protein levels.
Our comprehensive analysis of plasma proteins and lipid fractions of 3370 individuals from the general population provides new information about lipid metabolism.
Reference: Figarska SM, Gustafsson S, Sundström J, Ärnlöv J, Mälarstig A, Elmståhl S, Fall T, Lind L, Ingelsson E. Associations of Circulating Protein Levels With Lipid Fractions in the General Population. Arterioscler Thromb Vasc Biol. 2018;38(10):2505-2518. doi: 10.1161/ATVBAHA.118.311440.
Large-Scale Phenome-Wide Association Study of PCSK9 Variants Demonstrates Protection Against Ischemic Stroke
PCSK9 inhibition is a potent new therapy for hypercholesterolemia and cardiovascular disease. Although short-term clinical trial results have not demonstrated major adverse effects, long-term data will not be available for some time. Genetic studies in large biobanks offer a unique opportunity to predict drug effects and provide context for the evaluation of future clinical trial outcomes.
We tested the association of the PCSK9 missense variant rs11591147 with predefined phenotypes and phenome-wide, in 337 536 individuals of British ancestry in the UK Biobank, with independent discovery and replication. Using a Bayesian statistical method, we leveraged phenotype correlations to evaluate the phenome-wide impact of PCSK9 inhibition with higher power at a finer resolution.
The T allele of rs11591147 showed a protective effect on hyperlipidemia (odds ratio, 0.63±0.04; P=2.32×10-38), coronary heart disease (odds ratio, 0.73±0.09; P=1.05×10-6), and ischemic stroke (odds ratio, 0.61±0.18; P=2.40×10-3) and was associated with increased type 2 diabetes mellitus risk adjusted for lipid-lowering medication status (odds ratio, 1.24±0.10; P=1.98×10-7). We did not observe associations with cataracts, heart failure, atrial fibrillation, and cognitive dysfunction. Leveraging phenotype correlations, we observed evidence of a protective association with cerebral infarction and vascular occlusion. These results explore the effects of direct PCSK9 inhibition; off-target effects cannot be predicted using this approach.
This result represents the first genetic evidence in a large cohort for the protective effect of PCSK9 inhibition on ischemic stroke and corroborates exploratory evidence from clinical trials. PCSK9 inhibition was not associated with variables other than those related to LDL (low-density lipoprotein) cholesterol, atherosclerosis, and type 2 diabetes mellitus, suggesting that other effects are either small or absent.
Reference: Rao AS, Lindholm D, Rivas MA, Knowles JW, Montgomery SB, Ingelsson E. Large-Scale Phenome-Wide Association Study of PCSK9 Variants Demonstrates Protection Against Ischemic Stroke. Circ Genom Precis Med. 2018 Jul;11(7):e002162. doi: 10.1161/CIRCGEN.118.002162.
Bioimpedance and New-Onset Heart Failure: A Longitudinal Study of >500 000 Individuals From the General Population
Heart failure constitutes a high burden on patients and society, but although lifetime risk is high, it is difficult to predict without costly or invasive testing. We aimed to establish new risk factors of heart failure, which potentially could enable early diagnosis and preemptive treatment.
We applied machine learning in the UK Biobank in an agnostic search of risk factors for heart failure in 500 451 individuals, excluding individuals with prior heart failure. Novel factors were then subjected to several in-depth analyses, including multivariable Cox models of incident heart failure, and assessment of discrimination and calibration. Machine learning confirmed many known and putative risk factors for heart failure and identified several novel candidates. Mean reticulocyte volume appeared as one novel factor and leg bioimpedance another, the latter appearing as the most important new marker. Leg bioimpedance was lower in those who developed heart failure during an up to 9.8-year follow-up. When adjusting for known heart failure risk factors, leg bioimpedance was inversely related to heart failure (hazard ratio [95% confidence interval], 0.60 [0.48-0.73] and 0.75 [0.59-0.94], in age- and sex-adjusted and fully adjusted models, respectively, comparing the upper versus lower quartile). A model including leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good discrimination for future heart failure hospitalization (Concordance index [C-index]=0.82) and good calibration.
Leg bioimpedance is inversely associated with heart failure incidence in the general population. A simple model of exclusively noninvasive measures, combining leg bioimpedance with history of myocardial infarction, age, and sex provides accurate predictive capacity.
Reference: Lindholm D, Fukaya E, Leeper NJ, Ingelsson E. Bioimpedance and New-Onset Heart Failure: A Longitudinal Study of >500 000 Individuals From the General Population. J Am Heart Assoc. 2018 Jun 29;7(13). pii: e008970. doi: 10.1161/JAHA.118.008970.
Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance
Insulin resistance (IR) predisposes to type 2 diabetes and cardiovascular disease but its causes are incompletely understood. Metabolic challenges like the oral glucose tolerance test (OGTT) can reveal pathogenic mechanisms. We aimed to discover associations of IR with metabolite trajectories during OGTT. In 470 non-diabetic men (age 70.6 ± 0.6 years), plasma samples obtained at 0, 30 and 120 minutes during an OGTT were analyzed by untargeted liquid chromatography-mass spectrometry metabolomics. IR was assessed with the hyperinsulinemic-euglycemic clamp method. We applied age-adjusted linear regression to identify metabolites whose concentration change was related to IR. Nine trajectories, including monounsaturated fatty acids, lysophosphatidylethanolamines and a bile acid, were significantly associated with IR, with the strongest associations observed for medium-chain acylcarnitines C10 and C12, and no associations with L-carnitine or C2-, C8-, C14- or C16-carnitine. Concentrations of C10- and C12-carnitine decreased during OGTT with a blunted decline in participants with worse insulin resistance. Associations persisted after adjustment for obesity, fasting insulin and fasting glucose. In mouse 3T3-L1 adipocytes exposed to different acylcarnitines, we observed blunted insulin-stimulated glucose uptake after treatment with C10- or C12-carnitine. In conclusion, our results identify medium-chain acylcarnitines as possible contributors to IR.
Reference: Nowak C, Hetty S, Salihovic S, Castillejo-Lopez C, Ganna A, Cook NL, Broeckling CD, Prenni JE, Shen X, Giedraitis V, Ärnlöv J, Lind L, Berne C, Sundström J, Fall T, Ingelsson E. Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance. Sci Rep. 2018 Jun 6;8(1):8691. doi: 10.1038/s41598-018-26701-0.
Birthweight, Type 2 Diabetes Mellitus, and Cardiovascular Disease: Addressing the Barker Hypothesis With Mendelian Randomization
Low birthweight has been associated with a higher risk of hypertension, type 2 diabetes mellitus (T2D), and cardiovascular disease. The Barker hypothesis posits that intrauterine growth restriction resulting in lower birthweight is causal for these diseases, but causality is difficult to infer from observational studies.
We performed regression analyses to assess associations of birthweight with cardiovascular disease and T2D in 237 631 individuals from the UK Biobank. Further, we assessed the causal relationship of such associations using Mendelian randomization.
In the observational analyses, birthweight showed inverse associations with systolic and diastolic blood pressure (β, -0.83 and -0.26; per raw unit in outcomes and SD change in birthweight; 95% confidence interval [CI], -0.90 to -0.75 and -0.31 to -0.22, respectively), T2D (odds ratio, 0.83; 95% CI, 0.79-0.87), lipid-lowering treatment (odds ratio, 0.84; 95% CI, 0.81-0.86), and coronary artery disease (hazard ratio, 0.85; 95% CI, 0.78-0.94), whereas the associations with adult body mass index and body fat (β, 0.04 and 0.02; per SD change in outcomes and birthweight; 95% CI, 0.03-0.04 and 0.01-0.02, respectively) were positive. The Mendelian randomization analyses indicated inverse causal associations of birthweight with low-density lipoprotein cholesterol, 2-hour glucose, coronary artery disease, and T2D and positive causal association with body mass index but no associations with blood pressure.
Our study indicates that lower birthweight, used as a proxy for intrauterine growth retardation, is causally related with increased susceptibility to coronary artery disease and T2D. This causal relationship is not mediated by adult obesity or hypertension.
Reference: Zanetti D, Tikkanen E, Gustafsson S, Priest JR, Burgess S, Ingelsson E. Birthweight, Type 2 Diabetes Mellitus, and Cardiovascular Disease: Addressing the Barker Hypothesis With Mendelian Randomization. Circ Genom Precis Med. 2018 Jun;11(6):e002054. doi: 10.1161/CIRCGEN.117.002054.
Associations of Fitness, Physical Activity, Strength, and Genetic Risk With Cardiovascular Disease: Longitudinal Analyses in the UK Biobank Study
Observational studies have shown inverse associations among fitness, physical activity, and cardiovascular disease. However, little is known about these associations in individuals with elevated genetic susceptibility for these diseases.
We estimated associations of grip strength, objective and subjective physical activity, and cardiorespiratory fitness with cardiovascular events and all-cause death in a large cohort of 502 635 individuals from the UK Biobank (median follow-up, 6.1 years; interquartile range, 5.4-6.8 years). Then we further examined these associations in individuals with different genetic burden by stratifying individuals based on their genetic risk scores for coronary heart disease and atrial fibrillation. We compared disease risk among individuals in different tertiles of fitness, physical activity, and genetic risk using lowest tertiles as reference.
Grip strength, physical activity, and cardiorespiratory fitness showed inverse associations with incident cardiovascular events (coronary heart disease: hazard ratio [HR], 0.79; 95% confidence interval [CI], 0.77-0.81; HR, 0.95; 95% CI, 0.93-0.97; and HR, 0.68; 95% CI, 0.63-0.74, per SD change, respectively; atrial fibrillation: HR, 0.75; 95% CI, 0.73-0.76; HR, 0.93; 95% CI, 0.91-0.95; and HR, 0.60; 95% CI, 0.56-0.65, per SD change, respectively). Higher grip strength and cardiorespiratory fitness were associated with lower risk of incident coronary heart disease and atrial fibrillation in each genetic risk score group (Ptrend <0.001 in each genetic risk category). In particular, high levels of cardiorespiratory fitness were associated with 49% lower risk for coronary heart disease (HR, 0.51; 95% CI, 0.38-0.69) and 60% lower risk for atrial fibrillation (HR, 0.40; 95%, CI 0.30-0.55) among individuals at high genetic risk for these diseases.
Fitness and physical activity demonstrated inverse associations with incident cardiovascular disease in the general population, as well as in individuals with elevated genetic risk for these diseases.
Reference: Tikkanen E, Gustafsson S, Ingelsson E. Associations of Fitness, Physical Activity, Strength, and Genetic Risk With Cardiovascular Disease: Longitudinal Analyses in the UK Biobank Study. Circulation. 2018 Jun 12;137(24):2583-2591. doi: 10.1161/CIRCULATIONAHA.117.032432.
Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies
Genome-wide association studies have identified loci influencing circulating lipid concentrations in humans; further information on novel contributing genes, pathways, and biology may be gained through studies of epigenetic modifications.
To identify epigenetic changes associated with lipid concentrations, we assayed genome-wide DNA methylation at cytosine-guanine dinucleotides (CpGs) in whole blood from 2306 individuals from 2 population-based cohorts, with replication of findings in 2025 additional individuals. We identified 193 CpGs associated with lipid levels in the discovery stage (P<1.08E-07) and replicated 33 (at Bonferroni-corrected P<0.05), including 25 novel CpGs not previously associated with lipids. Genes at lipid-associated CpGs were enriched in lipid and amino acid metabolism processes. A differentially methylated locus associated with triglycerides and high-density lipoprotein cholesterol (HDL-C; cg27243685; P=8.1E-26 and 9.3E-19) was associated with cis-expression of a reverse cholesterol transporter (ABCG1; P=7.2E-28) and incident cardiovascular disease events (hazard ratio per SD increment, 1.38; 95% confidence interval, 1.15-1.66; P=0.0007). We found significant cis-methylation quantitative trait loci at 64% of the 193 CpGs with an enrichment of signals from genome-wide association studies of lipid levels (PTC=0.004, PHDL-C=0.008 and Ptriglycerides=0.00003) and coronary heart disease (P=0.0007). For example, genome-wide significant variants associated with low-density lipoprotein cholesterol and coronary heart disease at APOB were cis-methylation quantitative trait loci for a low-density lipoprotein cholesterol-related differentially methylated locus.
We report novel associations of DNA methylation with lipid levels, describe epigenetic mechanisms related to previous genome-wide association studies discoveries, and provide evidence implicating epigenetic regulation of reverse cholesterol transport in blood in relation to occurrence of cardiovascular disease events.
Reference: Hedman ÅK, Mendelson MM, Marioni RE, Gustafsson S, Joehanes R, [...], Arnett DK, Deary IJ, Lind L, Levy D, Ingelsson E. Epigenetic Patterns in Blood Associated With Lipid Traits Predict Incident Coronary Heart Disease Events and Are Enriched for Results From Genome-Wide Association Studies. Circ Cardiovasc Genet. 2017 Jan;10(1). pii: e001487. doi: 10.1161/CIRCGENETICS.116.001487.
Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci
Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.
Reference: Walford GA*, Gustafsson S*, Rybin D*, Stančáková A, Chen H, [...], Laakso M, Meigs JB, Dupuis J, Ingelsson E*, Florez JC*. Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci. Diabetes. 2016 Oct;65(10):3200-11. doi: 10.2337/db16-0199.
5 year mortality predictors in 498,103 UK Biobank participants: a prospective population-based study
To our knowledge, a systematic comparison of predictors of mortality in middle-aged to elderly individuals has not yet been done. We investigated predictors of mortality in UK Biobank participants during a 5 year period. We aimed to investigate the associations between most of the available measurements and 5 year all-cause and cause-specific mortality, and to develop and validate a prediction score for 5 year mortality using only self-reported information.
Participants were enrolled in the UK Biobank from April, 2007, to July, 2010, from 21 assessment centres across England, Wales, and Scotland with standardised procedures. In this prospective population-based study, we assessed sex-specific associations of 655 measurements of demographics, health, and lifestyle with all-cause mortality and six cause-specific mortality categories in UK Biobank participants using the Cox proportional hazard model. We excluded variables that were missing in more than 80% of the participants and all cardiorespiratory fitness test measurements because summary data were not available. Validation of the prediction score was done in participants enrolled at the Scottish centres. UK life tables and census information were used to calibrate the score to the overall UK population.
About 500,000 participants were included in the UK Biobank. We excluded participants with more than 80% variables missing (n=746). Of 498,103 UK Biobank participants included (54% of whom were women) aged 37-73 years, 8532 (39% of whom were women) died during a median follow-up of 4.9 years (IQR 4.33-5.22). Self-reported health (C-index including age 0.74 [95% CI 0.73-0.75]) was the strongest predictor of all-cause mortality in men and a previous cancer diagnosis (0.73 [0.72-0.74]) was the strongest predictor of all-cause mortality in women. When excluding individuals with major diseases or disorders (Charlson comorbidity index >0; n=355 043), measures of smoking habits were the strongest predictors of all-cause mortality. The prognostic score including 13 self-reported predictors for men and 11 for women achieved good discrimination (0.80 [0.77-0.83] for men and 0.79 [0.76-0.83] for women) and significantly outperformed the Charlson comorbidity index (p<0.0001 in men and p=0.0007 in women). A dedicated website allows the interactive exploration of all results along with calculation of individual risk through an online questionnaire.
Measures that can simply be obtained by questionnaires and without physical examination were the strongest predictors of all-cause mortality in the UK Biobank population. The prediction score we have developed accurately predicts 5 year all-cause mortality and can be used by individuals to improve health awareness, and by health professionals and organisations to identify high-risk individuals and guide public policy.
Reference: Ganna A, Ingelsson E. 5 year mortality predictors in 498,103 UK Biobank participants: a prospective population-based study. Lancet. 2015 Aug 8;386(9993):533-40. doi: 10.1016/S0140-6736(15)60175-1.