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Abstract Background It is unclear to what extent genetics explain the familial clustering and the co-occurrence of distinct cardiometabolic disorders in the general population. We therefore aimed to quantify the familial (co-)aggregation of various cardiometabolic disorders and to estimate the heritability of cardiometabolic traits and their genetic correlations using the large, multi-generational Lifelines Cohort Study. Methods We used baseline data of 162,416 participants from Lifelines. Cardiometabolic disorders including type 2 diabetes (T2D), cardiovascular diseases, hypertension, obesity, hypercholesterolemia, and metabolic syndrome (MetS), were defined in adult participants. Fifteen additional cardiometabolic traits indexing obesity, blood pressure, inflammation, glucose regulation, and lipid levels were measured in all included participants. Recurrence risk ratios (λR) for first-degree relatives (FDR) indexed familial (co-)aggregation of cardiometabolic disorders using modified conditional Cox proportional hazards models and were compared to those of spouses. Heritability (h2), shared environment, and genetic correlation (rg) were estimated using restricted maximum likelihood variance decomposition methods, adjusted for age, age2, and sex. Results Individuals with a first-degree relative with a cardiometabolic disorder had a higher risk of the same disorder, ranging from λFDR of 1.23 (95% CI 1.20–1.25) for hypertension to λFDR of 2.48 (95% CI 2.15–2.86) for T2D. Most of these were higher than in spouses (λSpouses

Background:Serum calciprotein particle maturation time (T50), a measure of vascular calcification propensity, is associated with cardiovascular morbidity and mortality. We aimed to identify genetic loci associated with serum T50 and study their association with cardiovascular disease and mortality.Methods:We performed a genome-wide association study of serum T50 in 2,739 individuals of European descent participating in the Prevention of REnal and Vascular ENd-stage Disease (PREVEND) study, followed by a two-sample Mendelian randomization (MR) study to examine causal effects of T50 on cardiovascular outcomes. Finally, we examined associations between T50 loci and cardiovascular outcomes in 8,566 community-dwelling participants in the Rotterdam study.Results:We identified three independent genome-wide significant single nucleotide polymorphism (SNPs) in the AHSG gene encoding fetuin-A: rs4917 (p = 1.72 × 10−101), rs2077119 (p = 3.34 × 10−18), and rs9870756 (p = 3.10 × 10−8), together explaining 18.3% of variation in serum T50. MR did not demonstrate a causal effect of T50 on cardiovascular outcomes in the general population. Patient-level analyses revealed that the minor allele of rs9870756, which explained 9.1% of variation in T50, was associated with a primary composite endpoint of all-cause mortality or cardiovascular disease [odds ratio (95% CI) 1.14 (1.01–1.28)] and all-cause mortality alone [1.14 (1.00–1.31)]. The other variants were not associated with clinical outcomes. In patients with type 2 diabetes or chronic kidney disease, the association between rs9870756 and the primary composite endpoint was stronger [OR 1.40 (1.06–1.84), relative excess risk due to interaction 0.54 (0.01–1.08)].Conclusions:We identified three SNPs in the AHSG gene that explained 18.3% of variability in serum T50 levels. Only one SNP was associated with cardiovascular outcomes, particularly in individuals with type 2 diabetes or chronic kidney disease.