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

Contributors

• Isabela Drumond Fonseca 💻 🔬 🚧 - Lattes: http://lattes.cnpq.br/3971412171428758
• Izinara Rosse da Cruz 📆 🤔 - Lattes: http://lattes.cnpq.br/4671130343607854
• Lauro Ângelo Gonçalves de Moraes - Lattes: http://lattes.cnpq.br/7273329679145458

Project abstract

The increase in human life expectancy results in the increasing incidence and prevalence of musculoskeletal diseases, such as sarcopenia. Sarcopenia (from the Greek 'Saex' flesh and 'penia' loss) is a progressive muscle disease related to age, characterized by low muscle strength, quantity and quality and by low physical performance. It is a disease that results in several personal burdens, since a person affected by sarcopenia has difficulty performing common everyday tasks, making them dependent on others. It is a pathology that has a multifactorial etiology, influenced by several external factors, such as nutritional, genetic and hormonal factors, and also by lifestyle. Thus, the disease is associated with higher mortality, morbidity and physical disability, making it a public health problem. Based on the algorithm proposed by the 2019 European Working Group on Sarcopenia in Older People (EWGSOP), the clinical overlap between phenotypes (muscle strength, muscle quality and quantity, and physical performance) was evidenced, inferring that there is a possibility of a genetic overlap, too. Therefore, investigating whether there is genetic overlap between the phenotypes of sarcopenia may show the occurrence of pleiotropic effects for this disease and, thus, point to an effective molecular marker. For that reason, the objectives of this study were to investigate whether there is genetic overlap between sarcopenia phenotypes. For this, we performed an analysis of the pleiotropic effect between sarcopenia phenotypes, using bioinformatics tools at genome, loci and gene levels. We applied LD score regression to verify the existence of genetic correlation between sarcopenia phenotypes. Subsequently, we applied a Pleiotropy-informed conditional and conjunctional false discovery rate method to identify shared loci with pleiotropic effect between pairs of phenotype. Lastly, to identify overlapping genes between pairs of phenotypes, we used a gene-based GWAS approach. Then, was used listcompare.py to compare candidate gene lists. A strong genetic correlation was observed between gait speed and muscle strength (rG=0.5358, p=3.39x10-8). Two shared loci were identified between the muscle strength and speed phenotypes, with 18 associated SNPs, nearby the PHACTR1 gene, 11 loci containing 146 SNPs in 26 genes for the pair of muscle mass and muscle strength phenotypes. Through the gene-based approach, it was possible to identify the FTO, RPS10 and CALCR genes associated with the three phenotypes. molecular methods for the prevention, diagnosis and prognosis of sarcopenia.

Info

listcompare.py is a Python script that aims to compare two lists of genes, resulting in a common gene list.

Project status

Under development.

Copyright

This project is licensed under the terms of the MIT license and protected by Udacity Honor Code and Community Code of Conduct. See license and disclaimer.