BACKGROUND Sarcopenia is a skeletal muscle disease of clinical importance that occurs commonly in old age and in various disease sub-categories. Widening the scope of knowledge of the genetics of muscle mass and strength is important because it may allow to identify patients with an increased risk to develop a specific musculoskeletal disease or condition such as sarcopenia based on genetic markers. METHODS We used bioinformatics tools to identify gene loci responsible for regulating muscle strength and lean mass, which can then be a target for downstream lab experimentation validation. Single nuclear polymorphisms (SNPs) associated with various disease traits of muscles and specific genes were chosen according to their muscle phenotype association p-value, as traditionally done in Genome Wide Association Studies, GWAS. We've developed and applied a combination of expression quantitative trait loci (eQTLs) and GWAS summary information, to prioritize causative SNP and point out the unique genes associated in the tissues of interest (muscle). RESULTS We found NUDT3 and KLF5 for lean mass and HLA-DQB1-AS1 for hand grip strength as candidate genes to target for these phenotypes. The associated regulatory SNPs are rs464553, rs1028883 and rs3129753 respectively. CONCLUSION Transcriptome Wide Association Studies, TWAS, approaches of combining GWAS and eQTL summary statistics proved helpful in statistically prioritizing genes and their associated SNPs for the disease phenotype of study, in this case, Sarcopenia. Potentially regulatory SNPs associated with these genes, and the genes further prioritized by a scoring system, can be then wet lab verified, depending on the phenotype it is hypothesized to affect.

中文翻译：

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解开肌肉减少症的遗传学：将NUDT3和KLF5优先考虑为瘦体重基因，并将HLA-DQB1-AS1优先用于手握力以及相关的增强SNP和评分系统。

背景技术肌肉减少症是一种具有临床重要性的骨骼肌疾病，通常发生在老年和各种疾病亚类中。扩大肌肉质量和力量遗传学知识的范围很重要，因为它可以允许根据遗传标记物识别出罹患特定肌肉骨骼疾病或病症（例如肌肉减少症）的风险增加的患者。方法我们使用生物信息学工具确定负责调节肌肉力量和瘦体重的基因位点，然后将其作为下游实验室实验验证的目标。如在GWAS的“基因组广泛关联研究”中所做的那样，根据其肌肉表型关联p值选择与肌肉和特定基因的各种疾病特征相关的单核多态性（SNP）。我们' 我们已经开发并应用了表达数量性状基因座（eQTL）和GWAS摘要信息的组合，以区分引起SNP的优先顺序并指出与目标组织（肌肉）相关的独特基因。结果我们发现瘦体重的NUDT3和KLF5和手握强度的HLA-DQB1-AS1是这些表型的候选基因。相关的调节性SNP分别为rs464553，rs1028883和rs3129753。结论转录组广泛关联研究，TWAS，结合GWAS和eQTL摘要统计的方法被证明有助于对疾病及其研究表型（本例为少见症）的基因及其相关SNPs进行统计学优先排序。然后可以对这些基因相关的潜在调节性SNP以及通过评分系统进一步确定优先级的基因进行湿实验室验证，