Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness. - Willems, Sara M; Wright, Daniel J; Day, Felix R; Trajanoska, Katerina; Joshi, Peter K; Morris, John A; Matteini, Amy M; Garton, Fleur C; Grarup, Niels; Oskolkov, Nikolay; Thalamuthu, Anbupalam; Mangino, Massimo; et al. (Nat Commun, 2017)
Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 × 10) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality.

Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study. - Trajanoska, Katerina; Morris, John A; Oei, Ling; Zheng, Hou-Feng; Evans, David M; Kiel, Douglas P; Ohlsson, Claes; Richards, J Brent; Rivadeneira, Fernando (BMJ, 2018)
OBJECTIVES: To identify the genetic determinants of fracture risk and assess the role of 15 clinical risk factors on osteoporotic fracture risk. DESIGN: Meta-analysis of genome wide association studies (GWAS) and a two-sample mendelian randomisation approach. SETTING: 25 cohorts from Europe, United States, east Asia, and Australia with genome wide genotyping and fracture data. PARTICIPANTS: A discovery set of 37 857 fracture cases and 227 116 controls; with replication in up to 147 200 fracture cases and 150 085 controls. Fracture cases were defined as individuals (>18 years old) who had fractures at any skeletal site confirmed by medical, radiological, or questionnaire reports. Instrumental variable analyses were performed to estimate effects of 15 selected clinical risk factors for fracture in a two-sample mendelian randomisation framework, using the largest previously published GWAS meta-analysis of each risk factor. RESULTS: Of 15 fracture associated loci identified, all were also associated with bone mineral density and mapped to genes clustering in pathways known to be critical to bone biology (eg, , , and ) or novel pathways (, , and ). Mendelian randomisation analyses showed a clear effect of bone mineral density on fracture risk. One standard deviation decrease in genetically determined bone mineral density of the femoral neck was associated with a 55% increase in fracture risk (odds ratio 1.55 (95% confidence interval 1.48 to 1.63; P=1.5×10). Hand grip strength was inversely associated with fracture risk, but this result was not significant after multiple testing correction. The remaining clinical risk factors (including vitamin D levels) showed no evidence for an effect on fracture. CONCLUSIONS: This large scale GWAS meta-analysis for fracture identified 15 genetic determinants of fracture, all of which also influenced bone mineral density. Among the clinical risk factors for fracture assessed, only bone mineral density showed a major causal effect on fracture. Genetic predisposition to lower levels of vitamin D and estimated calcium intake from dairy sources were not associated with fracture risk.

Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease. - Young, William J; Haessler, Jeffrey; Benjamins, Jan-Walter; Repetto, Linda; Yao, Jie; Isaacs, Aaron; Harper, Andrew R; Ramirez, Julia; Garnier, Sophie; Van Duijvenboden, Stefan; Baldassari, Antoine R; Concas, Maria Pina; et al. (Nat Commun, 2023)
The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
Keywords: Arrhythmias, Cardiac; Atrioventricular Block; Biomarkers; Cardiovascular Diseases; Electrocardiography; Genome-Wide Association Study; Humans; Risk Factors