GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium

Decline in muscle strength with aging is an important predictor of health trajectory in the elderly. Several factors, including genetics, are proposed contributors to variability in muscle strength. To identify genetic contributors to muscle strength, a meta-analysis of genomewide association studies of handgrip was conducted. Grip strength was measured using a handheld dynamometer in 27 581 individuals of European descent over 65 years of age from 14 cohort studies. Genomewide association analysis was conducted on ~2.7 million imputed and genotyped variants (SNPs). Replication of the most significant findings was conducted using data from 6393 individuals from three cohorts. GWAS of lower body strength was also characterized in a subset of cohorts. Two genomewide significant (P-value< 5 × 10−8) and 39 suggestive (P-value< 5 × 10−5) associations were observed from meta-analysis of the discovery cohorts. After meta-analysis with replication cohorts, genomewide significant association was observed for rs752045 on chromosome 8 (β = 0.47, SE = 0.08, P-value = 5.20 × 10−10). This SNP is mapped to an intergenic region and is located within an accessible chromatin region (DNase hypersensitivity site) in skeletal muscle myotubes differentiated from the human skeletal muscle myoblasts cell line. This locus alters a binding motif of the CCAAT/enhancer-binding protein-β (CEBPB) that is implicated in muscle repair mechanisms. GWAS of lower body strength did not yield significant results. A common genetic variant in a chromosomal region that regulates myotube differentiation and muscle repair may contribute to variability in grip strength in the elderly. Further studies are needed to uncover the mechanisms that link this genetic variant with muscle strength

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

Low muscle strength is an important heritable indicator of poor health linked to morbidity and mortality in older people. In a genome-wide association study meta-analysis of 256,523 Europeans aged 60 years and over from 22 cohorts we identify 15 loci associated with muscle weakness (European Working Group on Sarcopenia in Older People definition: n = 48,596 cases, 18.9% of total), including 12 loci not implicated in previous analyses of continuous measures of grip strength. Loci include genes reportedly involved in autoimmune disease (HLA-DQA1p = 4 × 10−17), arthritis (GDF5p = 4 × 10−13), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing

GWAS of longevity in CHARGE consortium confirms APOE and FOXO3 candidacy

Background. The genetic contribution to longevity in humans has been estimated to range from 15% to 25%. Only two genes, APOE and FOXO3, have shown association with longevity in multiple independent studies. Methods. We conducted a meta-analysis of genome-wide association studies including 6,036 longevity cases, age90 years, and 3,757 controls that died between ages 55 and 80 years. We additionally attempted to replicate earlier identified single nucleotide polymorphism (SNP) associations with longevity. Results. In our meta-analysis, we found suggestive evidence for the association of SNPs near CADM2 (odds ratio [OR] = 0.81; p value = 9.66 × 10-7) and GRIK2 (odds ratio = 1.24; p value = 5.09 × 10-8) with longevity. When attempting to replicate findings earlier identified in genome-wide association studies, only the APOE locus consistently replicated. In an additional look-up of the candidate gene FOXO3, we found that an earlier identified variant shows a highly significant association with longevity when including published data with our meta-analysis (odds ratio = 1.17; p value = 1.85×10-10). Conclusions. We did not identify new genome-wide significant associations with longevity and did not replicate earlier findings except for APOE and FOXO3. Our inability to find new associations with survival to ages90 years because longevity represents multiple complex traits with heterogeneous genetic underpinnings, or alternatively, that longevity may be regulated by rare variants that are not captured by standard genome-wide genotyping and imputation of common variants

A genome-wide association study of aging

Human longevity and healthy aging show moderate heritability (20%-50%). We conducted a meta-analysis of genome-wide association studies from 9 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium for 2 outcomes: (1) all-cause mortality, and (2) survival free of major disease or death. No single nucleotide polymorphism (SNP) was a genome-wide significant predictor of either outcome (p < 5 × 10-8). We found 14 independent SNPs that predicted risk of death, and 8 SNPs that predicted event-free survival (p < 10-5). These SNPs are in or near genes that are highly expressed in the brain (HECW2, HIP1, BIN2, GRIA1), genes involved in neural development and function (KCNQ4, LMO4, GRIA1, NETO1) and autophagy (ATG4C), and genes that are associated with risk of various diseases including cancer and Alzheimer's disease. In addition to considerable overlap between the traits, pathway and network analysis corroborated these findings. These findings indicate that variation in genes involved in neurological processes may be an important factor in regulating aging free of major disease and achieving longevity

Correction: The complex genetics of gait speed: Genome-wide metaanalysis approach [Aging, (Albany NY), 9, 1, (2017), (209-246)]doi 10.18632/aging.101151

Applying HaploReg v4.1 analysis to the 536 variants resulted in 9 categories (Supplementary Table 8): miscRNA (1 variant); snoRNA (2 variants); microRNA (4 variants); snRNA (9 variants); pseudogenes (14 variants); sequencing in progress (43 variants); LINC RNA (86 variants); and 372 variants within protein coding genes. In addition, some variants annotate to the same gene resulting in a total of 139 genes (protein-coding or non-coding). Of those genes, 6 are exceptionally long, containing over a million base-pairs, the longest of which is PTPRT coded by 1117219bp. The shortest genes are the ones coding for micro (MIR3143) or small nuclear (U7) RNAs at 63bp each. There is only partial information regarding the chromatin state of each variant. However, from the information gathered in the analysis we observed 14 transcription start sites and 245 enhancers (Supplementary Table 8)