New York, Dec 26 (IANS): Rheumatoid arthritis, which afflicts nearly one crore people in India and affects the young and the old alike, is not merely a physical disability but also affects the human life span.

Here is a good news for such patients. Large-scale genetic studies can assist in identifying new drugs for complex disorders like rheumatoid arthritis, says an international study.

Rheumatoid arthritis is an auto-immune disease leading to inflammation and damage of the joints.

The study, conducted by Robert M. Plenge from Harvard Medical School and and Yukinori Okada from the RIKEN Center for Integrative Medical Sciences in Japan - along with colleagues from 70 institutions worldwide - says that integrating the information provided by genome-wide association studies with existing datasets of genomic and biological information can assist in the discovery of drugs to cure rheumatoid arthritis.

Genome-wide association studies are a method employed by scientists to identify the genes contributing to human disease.

The researchers performed a genome-wide association study meta-analysis on over 100,000 people 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).

By integrating existing datasets with this new information, the researchers were able to find 98 genes in these people that could potentially contribute to the onset of rheumatoid arthritis.

By integrating their findings with existing drug databases, the research noted that these genes indeed possess many overlapping regions with the genes targeted by approved rheumatoid arthritis drugs.

“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,” the authors said.

“Our study provides a systematic approach by which human genetic data can be efficiently integrated with other biological information to derive biological insights and drug discovery,” they added.