| Literature DB >> 32777102 |
Douglas P Kiel1,2,3,4, John P Kemp5,6, Fernando Rivadeneira7, Jennifer J Westendorf8, David Karasik1,9, Emma L Duncan10, Yuuki Imai11, Ralph Müller12, Jason Flannick3,13, Lynda Bonewald14, Noël Burtt4.
Abstract
The development of high-throughput genotyping technologies and large biobank collections, complemented with rapid methodological advances in statistical genetics, has enabled hypothesis-free genome-wide association studies (GWAS), which have identified hundreds of genetic variants across many loci associated with musculoskeletal conditions. Similarly, basic scientists have valuable molecular cellular and animal data based on musculoskeletal disease that would be enhanced by being able to determine the human translation of their findings. By integrating these large-scale human genomic musculoskeletal datasets with complementary evidence from model organisms, new and existing genetic loci can be statistically fine-mapped to plausibly causal variants, candidate genes, and biological pathways. Genes and pathways identified using this approach can be further prioritized as drug targets, including side-effect profiling and the potential for new indications. To bring together these big data, and to realize the vision of creating a knowledge portal, the International Federation of Musculoskeletal Research Societies (IFMRS) established a working group to collaborate with scientists from the Broad Institute to create the Musculoskeletal Knowledge Portal (MSK-KP)(http://mskkp.org/). The MSK consolidates omics datasets from humans, cellular experiments, and model organisms into a central repository that can be accessed by researchers. The vision of the MSK-KP is to enable better understanding of the biological mechanisms underlying musculoskeletal disease and apply this knowledge to identify and develop new disease interventions.Entities:
Keywords: DISEASES AND DISORDERS OF/RELATED TO BONE; EPIGENETICS; GENETIC RESEARCH; OSTEOARTHRITIS; OSTEOPOROSIS
Mesh:
Year: 2020 PMID: 32777102 PMCID: PMC8114232 DOI: 10.1002/jbmr.4147
Source DB: PubMed Journal: J Bone Miner Res ISSN: 0884-0431 Impact factor: 6.741