Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis.
Eleni ZenginiKonstantinos HatzikotoulasIoanna TachmazidouJulia SteinbergFernando Pires HartwigLorraine SouthamSophie HackingerCindy Germaine BoerUnnur StyrkársdóttirArthur GillyDaniel SuvegesBritt KillianThorvaldur IngvarssonHelgi JonssonGeorge C BabisAndrew McCaskieAndre G UitterlindenJoyce B J van MeursUnnur ThorsteinsdottirKari StefanssonGeorge Davey SmithJeremy Mark WilkinsonEleftheria ZegginiPublished in: Nature genetics (2018)
Osteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes.
Keyphrases
- genome wide
- rheumatoid arthritis
- genome wide association study
- knee osteoarthritis
- type diabetes
- public health
- dna methylation
- body mass index
- copy number
- electronic health record
- cardiovascular disease
- metabolic syndrome
- physical activity
- gene expression
- cross sectional
- big data
- risk factors
- adipose tissue
- insulin resistance
- artificial intelligence