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Background: Circulating levels of amino acids were associated with blood pressure (BP) in observational studies. However, the causation of such associations has been hypothesized but is difficult to prove in human studies. Here, we aimed to use two-sample Mendelian randomization analyses to evaluate the potential causal associations of circulating levels of amino acids with BP and risk of hypertension.Methods: We generated genetic instruments for circulating levels of nine amino acids by conducting meta-analyses of genome-wide association study (GWAS) in UK Biobank participants with metabolomic data (n = 98,317) and another published metabolomics GWAS (n = 24,925). Data on the associations of the genetic variants with BP and hypertension were obtained in the UK Biobank participants without metabolomic data (n = 286,390). The causal effects were estimated using inverse-variance weighted method.Results: Significant evidence consistently supported the causal effects of increased branched-chain amino acids (BCAAs, i.e., leucine, isoleucine, and valine) levels on higher BP and risk of hypertension (all P < 0.006 after Bonferroni correction except for Pleucine-on-diastolicBP = 0.008). For example, per standard deviation higher of genetically predicted isoleucine levels were associated with 2.71 ± 0.78 mmHg higher systolic BP and 1.24 ± 0.34 mmHg higher diastolic BP, as well as with 7% higher risk of hypertension (odds ratio: 1.07, [95% CI: 1.04-1.10]). In addition, per standard deviation higher of genetically predicted glycine level was associated with lower systolic BP (- 0.70 ± 0.17 mmHg, P = 4.04 × 10-5) and a lower risk of hypertension (0.99 [0.98-0.99], P = 6.46 × 10-5). In the reverse direction, genetically predicted higher systolic BP was associated with lower circulating levels of glycine (- 0.025±0.008, P = 0.001).Conclusions: This study provides evidence for causal impacts of genetically predicted circulating BCAAs and glycine levels on BP. Meanwhile, genetically predicted higher BP was associated with lower glycine levels. Further investigations are warranted to clarify the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Fat mass and fat-free mass are found to be associated with different health outcomes in observational studies, but the underlying causality remains unclear. We aimed to investigate the causal relationships between body composition and cardiometabolic traits using a two-sample Mendelian randomization (MR) approach. Independent genetic variants associated with body fat mass, fat-free mass, and fat percentage in UK Biobank population were used as genetic instrumental variables, and their causal effects on circulatory diseases, type 2 diabetes, glycemic traits, and lipid fractions were estimated from large-scale genome-wide association studies (GWAS) in European populations. Univariable, multivariable, and bidirectional MR analyses were performed. Genetically predicted high fat mass and fat percentage significantly increased risks of most cardiometabolic diseases, and high fat-free mass had protective effects on most cardiometabolic diseases after accounting for fat mass. Fat mass, fat-free mass, and fat percentage were all positively associated with higher risks of atrial fibrillation and flutter, varicose veins, and deep vein thrombosis and pulmonary embolism. High fat mass increased fasting glucose, homeostasis model assessment-insulin resistance (HOMA-IR), triglycerides, decreased high-density lipoprotein cholesterol, and high fat-free mass reduced HOMA-IR, triglycerides, and low-density lipoprotein cholesterol. Genetically predicted fat-free mass was bidirectionally negatively associated with 2-h glucose and total cholesterol. The findings may be helpful in risk stratification and tailoring management of body composition in patients with different cardiometabolic statuses. [ABSTRACT FROM AUTHOR]

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (F ROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of F ROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between F ROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%–18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity. [Display omitted] • Robust method to reduce confounding in autozygosity-phenotype association studies • Higher autozygosity associated with increased risk for common diseases such as T2D • Replication of findings including a within-sibling analysis • Consanguinity explains ∼10% of T2D cases in British Pakistanis Autozygosity resulting from consanguinity is causally associated with several complex diseases, including type 2 diabetes. [ABSTRACT FROM AUTHOR]