Genome-wide association study identified copy number variants important for appendicular lean mass

Pleiotropic effects on Sarcopenia subphenotypes point to potential molecular markers for the disease

Sarcopenia is a progressive age-related muscle disease characterized by low muscle strength, quantity and quality, and low physical performance. The clinical overlap between these subphenotypes (reduction in muscle strength, quantity and quality, and physical performance) was evidenced, but the genetic overlap is still poorly investigated. Herein, we investigated whether there is a genetic overlap amongst sarcopenia subphenotypes in the search for more effective molecular markers for this disease. For that, a Bioinformatics approach was used to identify and characterize pleiotropic effects at the genome, loci and gene levels using Genome-wide association study results. As a result, a high genetic correlation was identified between gait speed and muscle strength (rG=0.5358, p=3.39 × 10-8). Using a Pleiotropy-informed conditional and conjunctional false discovery rate method we identified two pleiotropic loci for muscle strength and gait speed, one of them was nearby the gene PHACTR1. Moreover, 11 pleiotropic loci and 25 genes were identified for muscle mass and muscle strength. Lastly, using a gene-based GWAS approach three candidate genes were identified in the overlap of the three Sarcopenia subphenotypes: FTO, RPS10 and CALCR. The current study provides evidence of genetic overlap and pleiotropy among sarcopenia subphenotypes and highlights novel candidate genes and molecular markers associated with the risk of sarcopenia.

Genome-wide methylation analysis of post-mortem cerebellum samples supports the role of peroxisomes in autism spectrum disorder

Aim: We tested the hypothesis that a subset of patients with autism spectrum disorder (ASD) contains candidate genes with high DNA methylation differences (effective values) that potentially affect one of the two alleles. Materials & methods: Genome-wide DNA methylation comparisons were made on cerebellum samples from 30 patients and 45 controls. Results: 12 genes with high effective values, including GSDMD, MMACHC, SLC6A5 and NKX6-2, implicated in ASD and other neuropsychiatric disorders were identified. Monoallelic promoter methylation and downregulation were observed for SERHL (serine hydrolase-like) and CAT (catalase) genes associated with peroxisome function. Conclusion: These data are consistent with the hypothesis implicating impaired peroxisome function/biogenesis for ASD. A similar approach holds promise for identifying rare epimutations in ASD and other complex disorders.

Unveiling genetic variants for age-related sarcopenia by conducting a genome-wide association study on Korean cohorts

Sarcopenia is an age-related disorder characterised by a progressive decrease in skeletal muscle mass. As the genetic biomarkers for sarcopenia are not yet well characterised, this study aimed to investigate the genetic variations related to sarcopenia in a relatively aged cohort, using genome-wide association study (GWAS) meta-analyses of lean body mass (LBM) in 6961 subjects. Two Korean cohorts were analysed, and subgroup GWAS was conducted for appendicular skeletal muscle mass (ASM) and skeletal muscle index. The effects of significant single nucleotide polymorphisms (SNPs) on gene expression were also investigated using multiple expression quantitative trait loci datasets, differentially expressed gene analysis, and gene ontology analyses. Novel genetic biomarkers were identified for LBM (rs1187118; rs3768582) and ASM (rs6772958). Their related genes, including RPS10, NUDT3, NCF2, SMG7, and ARPC5, were differently expressed in skeletal muscle tissue, while GPD1L was not. Furthermore, the 'mRNA destabilisation' biological process was enriched for sarcopenia. Our study identified RPS10, NUDT3, and GPD1L as significant genetic biomarkers for sarcopenia. These genetic loci were related to lipid and energy metabolism, suggesting that genes involved in metabolic dysregulation may lead to the pathogenesis of age-related sarcopenia.

A molecular marker of milk composition traits in NCAM2 gene of Chinese Holstein

The aim of this study was to detect the novel copy number variation (CNV) locus of NCAM2 gene in Chinese Holstein, and to analyze the effect of the novel CNV locus in NCAM2 gene on milk composition traits. The novel CNV locus of NCAM2 gene in 310 Chinese Holstein was detected by real-time quantitative fluorescent PCR (qPCR) and association analysis was performed between the novel CNV locus in NCAM2 gene and milk composition traits in Chinese Holstein. There are three CNV types of NCAM2 gene in Chinese Holstein: gain (increased copy number), median (normal copy number) and loss (deleted copy number). Statistical analysis revealed that there was a significant association between CNV types and milk fat rate (p < 0.05). Moreover, we also discovered that the milk production and milk protein rate of gain type is higher than that of loss type, but that of mediate type is lower than that of loss type. However, in terms of somatic cell score, loss type is higher than that of gain type, but that of mediate type is lower than that of gain type. These observations suggested that gain type can be used as a candidate molecular genetic marker of milk fat rate.HighlightsThe CNVs of the NCAM2 gene were detected and validated in Chinese Holstein.The type of CNV was successfully implemented using qPCR.The statistical analysis indicated that the CNV of the NCAM2 gene are significantly associated with milk fat rate.

Replication of FTO Gene associated with lean mass in a Meta-Analysis of Genome-Wide Association Studies

Sarcopenia is characterized by low skeletal muscle, a complex trait with high heritability. With the dramatically increasing prevalence of obesity, obesity and sarcopenia occur simultaneously, a condition known as sarcopenic obesity. Fat mass and obesity-associated (FTO) gene is a candidate gene of obesity. To identify associations between lean mass and FTO gene, we performed a genome-wide association study (GWAS) of lean mass index (LMI) in 2207 unrelated Caucasian subjects and replicated major findings in two replication samples including 6,004 unrelated Caucasian and 38,292 unrelated Caucasian. We found 29 single nucleotide polymorphisms (SNPs) in FTO significantly associated with sarcopenia (combined p-values ranging from 5.92 × 10⁻¹² to 1.69 × 10⁻⁹). Potential biological functions of SNPs were analyzed by HaploReg v4.1, RegulomeDB, GTEx, IMPC and STRING. Our results provide suggestive evidence that FTO gene is associated with lean mass.

Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2

Muscle bulk in adult healthy humans is highly variable even after height, age, and sex are accounted for. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-aged (aged 38-49 years) individuals from the UK Biobank (UKB), we found 182 loci associated with ALM (p < 5 × 10-8). We replicated associations for 78% of these loci (p < 5 × 10-8) with ALM in a population of 181,862 elderly (aged 60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J); this GWAS identified 23 quantitative trait loci. Thirty-eight positional candidates distributed across five loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.

Functional genomics applications and therapeutic implications in sarcopenia

The human genome contains around 20,000-25,000 genes coding for 30,000 proteins. Some proteins and genes represent therapeutic targets for human diseases. RNA and protein expression profiling tools allow the study of the molecular basis of aging and drug discovery validation. Throughout the life, there is an age-related and disease-related muscle decline. Sarcopenia is defined as a loss of muscle mass and a decrease in functional properties such as muscle strength and physical performance. Yet, there is still no consensus on the evaluation methods of sarcopenia prognosis. The main challenge of this complex biological phenomena is its multifactorial etiology. Thus, functional genomics methods attempt to shape the related scientific approaches via an innovative in-depth view on sarcopenia. Gene and drug high throughput screening combined with functional genomics allow the generation and the interpretation of a large amount of data related to sarcopenia and therapeutic progress. This review focuses on the application of selected functional genomics techniques such as RNA interference, RNA silencing, proteomics, transgenic mice, metabolomics, genomics, and epigenomics to better understand sarcopenia mechanisms.

Genomics and metabolomics of muscular mass in a community-based sample of UK females

The contribution of specific molecular-genetic factors to muscle mass variation and sarcopenia remains largely unknown. To identify endogenous molecules and specific genetic factors associated with appendicular lean mass (APLM) in the general population, cross-sectional data from the TwinsUK Adult Twin Registry were used. Non-targeted mass spec-based metabolomic profiling was performed on plasma of 3953 females (mostly dizygotic and monozygotic twins). APLM was measured using dual-energy X-ray absorptiometry (DXA) and genotyping was genome-wide (GWAS). Specific metabolites were used as intermediate phenotypes in the identification of single-nucleotide polymorphisms associated with APLM using GWAS. In all, 162 metabolites were found significantly correlated with APLM, and explained 17.4% of its variation. However, the top three of them (unidentified substance X12063, urate, and mannose) explained 11.1% (P ≤ 9.25 × 10(-26)) so each was subjected to GWAS. Each metabolite showed highly significant (P ≤ 9.28 × 10(-46)) associations with genetic variants in the corresponding genomic regions. Mendelian randomization using these SNPs found no evidence for a direct causal effect of these metabolites on APLM. However, using a new software platform for bivariate analysis we showed that shared genetic factors contribute significantly (P ≤ 4.31 × 10(-43)) to variance in both the metabolites and APLM--independent of the effect of the associated SNPs. There are several metabolites, having a clear pattern of genetic inheritance, which are highly significantly associated with APLM and may provide a cheap and readily accessible biomarker of muscle mass. However, the mechanism by which the genetic factor influences muscle mass remains to be discovered.

Recent genetic discoveries in osteoporosis, sarcopenia and obesity

Osteoporosis is a skeletal disorder characterized by low bone mineral density (BMD) and an increased susceptibility to fractures. Evidence from genetic studies indicates that BMD, a complex quantitative trait with a normal distribution, is genetically controlled. Genome-wide association studies (GWAS) as well as studies using candidate gene approaches have identified single-nucleotide polymorphisms (SNPs) that are associated with BMD, osteoporosis and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding WNT/β-catenin signaling proteins. Understanding the genetics of osteoporosis will help to identify novel candidates for diagnostic and therapeutic targets. Genetic factors are also important for the development of sarcopenia, which is characterized by a loss of lean body mass, and obesity, which is characterized by high fat mass. Hence, in this review, we discuss the genetic factors, identified by genetic studies, which regulate the body components related to osteoporosis, sarcopenia, and obesity.