The results of the largest international study to date into the
genetic basis of rheumatoid arthritis shed light on the biology of the disease
and provide evidence that large-scale genetic studies can assist in the
identification of new drugs for complex disorders such as rheumatoid arthritis.
The study, conducted by Dr. Robert M. Plenge from the
Harvard Medical School and the Broad Institute in the USA and Dr. Yukinori
Okada from the RIKEN Center for Integrative Medical Sciences in Japan,
collaborating with colleagues from 70 institutions worldwide, is published in
the journal Nature.
Genome-wide association studies are a method employed
by scientists to identify the genes contributing to human disease. The current
Nature study is the first to demonstrate that integrating the information
provided by genome-wide association studies with existing datasets of genomic
and biological information, such as drug targets, can assist in the discovery
of drugs to cure human disease.
Rheumatoid arthritis is an autoimmune disease leading
to inflammation of the joints and affecting 0.5-1% of adults in the developed
world. The disease is thought to be caused by a complex combination of genetic
and environmental factors and several genes have been shown to be associated
with the disease. However, most of the findings were based on single population
studies, and no large-scale trans-ethnic study had been carried out to date.
Figure a) Showing RA |
Figure b) Showing Bioinformatics Process for Drug Discovery of RA |
The international team performed a genome-wide
association study meta-analysis on a total of over 100,000 subjects of European
and Asian descent -- 29,880 rheumatoid arthritis patients and 73,758 controls
-- by analysing around 10 million genetic variants called single nucleotide
polymorphism (SNPs). They identified 42 new regions in the genome (loci) that
are associated with rheumatoid arthritis, bringing the total number of known
rheumatoid arthritis loci to 101.
By conducting bioinformatics studies integrating
existing datasets with this new information, the researchers were able to
pinpoint 98 genes in these 101 loci that could potentially contribute to the
onset of rheumatoid arthritis. By integrating their findings with existing drug
databases they demonstrate that these genes indeed possess many overlapping
regions with the genes targeted by approved rheumatoid arthritis drugs --
although this wasn't known when the drugs were developed. The team identifies
existing drugs used to treat cancer that also target rheumatoid arthritis genes
and could potentially be used as therapy for the disease, such as CDK4/6
inhibitors.
The bioinformatics study also reveals that there is
significant overlap between the genes involved in rheumatoid arthritis, human
primary immunodeficiency disorders and blood cancers.
"This study sheds light on the fundamental genes,
pathways and cell types that contribute to the onset of rheumatoid arthritis
and provides evidence that the genetics of rheumatoid arthritis can provide
important information for drug discovery," conclude the authors.
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