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Abstract Happiness is a fundamental human affective trait, but its biological basis is not well understood. Using a novel approach, we construct LDpred-inf polygenic scores of a general happiness measure in 2 cohorts: the Adolescent Brain Cognitive Development (ABCD) cohort (N = 15,924, age range 9.23–11.8 years), the Add Health cohort (N = 9129, age range 24.5–34.7) to determine associations with several well-being and happiness measures. Additionally, we investigated associations between genetic scores for happiness and brain structure in ABCD (N = 9626, age range (8.9–11) and UK Biobank (N = 16,957, age range 45–83). We detected significant (p.FDR

Abstract Total body fat and central fat distribution are heritable traits and well-established predictors of adverse metabolic outcomes. Lipolysis is the process responsible for the hydrolysis of triacylglycerols stored in adipocytes. To increase our understanding of the genetic regulation of body fat distribution and total body fat, we set out to determine if genetic variants associated with body mass index (BMI) or waist-hip-ratio adjusted for BMI (WHRadjBMI) in genome-wide association studies (GWAS) mediate their effect by influencing adipocyte lipolysis. We utilized data from the recent GWAS of spontaneous and isoprenaline-stimulated lipolysis in the unique GENetics of Adipocyte Lipolysis (GENiAL) cohort. GENiAL consists of 939 participants who have undergone abdominal subcutaneous adipose biopsy for the determination of spontaneous and isoprenaline-stimulated lipolysis in adipocytes. We report 11 BMI and 15 WHRadjBMI loci with SNPs displaying nominal association with lipolysis and allele-dependent gene expression in adipose tissue according to in silico analysis. Functional evaluation of candidate genes in these loci by small interfering RNAs (siRNA)-mediated knock-down in adipose-derived stem cells identified ZNF436 and NUP85 as intrinsic regulators of lipolysis consistent with the associations observed in the clinical cohorts. Furthermore, candidate genes in another BMI-locus (STX17) and two more WHRadjBMI loci (NID2, GGA3, GRB2) control lipolysis alone, or in conjunction with lipid storage, and may hereby be involved in genetic control of body fat. The findings expand our understanding of how genetic variants mediate their impact on the complex traits of fat storage and distribution.

Abstract The relationship between intake of saturated fats and subclinical atherosclerosis, as well as the possible influence of genetic variants, is poorly understood and investigated. We aimed to investigate this relationship, with a hypothesis that it would be positive, and to explore whether genetics may modulate it, using data from a European cohort including 3,407 participants aged 54–79 at high risk of cardiovascular disease. Subclinical atherosclerosis was assessed by carotid intima-media thickness (C-IMT), measured at baseline and after 30 months. Logistic regression (OR; 95% CI) was employed to assess the association between high intake of food rich in saturated fat (vs. low) and: (1) the mean and the maximum values of C-IMT in the whole carotid artery (C-IMTmean, C-IMTmax), in the bifurcation (Bif-), the common (CC-) and internal (ICA-) carotid arteries at baseline (binary, cut-point ≥ 75th), and (2) C-IMT progression (binary, cut-point > zero). For the genetic-diet interaction analyses, we considered 100,350 genetic variants. We defined interaction as departure from additivity of effects. After age- and sex-adjustment, high intake of saturated fat was associated with increased C-IMTmean (OR:1.27;1.06–1.47), CC-IMTmean (OR:1.22;1.04–1.44) and ICA-IMTmean (OR:1.26;1.07–1.48). However, in multivariate analysis results were no longer significant. No clear associations were observed between high intake of saturated fat and risk of atherosclerotic progression. There was no evidence of interactions between high intake of saturated fat and any of the genetic variants considered, after multiple testing corrections. High intake of saturated fats was not independently associated with subclinical atherosclerosis. Moreover, we did not identify any significant genetic-dietary fat interactions in relation to risk of subclinical atherosclerosis.

Abstract Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.