Researchers hunt through gene chip data for Parkinson’s clue

August 04, 2014 − by Suzanne Elvidge − in Big data, Big data in research, Data analytics, Data mining, Healthcare big data analysis − No Comments

A team of researchers funded by the National Institutes of Health (NIH) has used data from over 18,000 patients to find more than two dozen genetic risk factors involved in Parkinson’s disease, including six that had not been previously reported.

Parkinson’s disease affects millions of people worldwide, and can lead to difficulties in walking, talking, and completing other simple tasks. Although nine genes have been shown to cause rare forms of Parkinson’s disease, scientists continue to search for genetic risk factors to provide a complete genetic picture of the disorder.

“Unravelling the genetic underpinnings of Parkinson’s is vital to understanding the multiple mechanisms involved in this complex disease, and hopefully, may one day lead to effective therapies,” said Andrew Singleton of the NIH’s National Institute on Aging (NIA).

The team carried out a meta-analysis of existing Parkinson’s disease genome-wide association studies (GWAS), looking at 13,708 cases and 95,282 controls from across Europe to find risk variants that increase an individual’s chance of developing Parkinson’s disease. The data came from collaborations with public and private organizations, including the U.S. Department of Defense, the Michael J. Fox Foundation, 23andMe and many international investigators.

“The study brought together a large international group of investigators from both public and private institutions who were interested in sharing data to accelerate the discovery of genetic risk factors for Parkinson’s disease,” said Margaret Sutherland of the National Institute of Neurological Disorders and Stroke (NINDS), part of NIH. “The advantage of this collaborative approach is highlighted in the identification of pathways and gene networks that may significantly increase our understanding of Parkinson’s disease.”

The NIH researchers found 32 single nucleotide polymorphisms (SNPs) with genome-wide significant association, including six newly identified loci. Their results suggested that the more variants a person has, the greater the risk, up to three times higher, for developing the disorder in some cases.

The results were then confirmed in another sample of subjects, including 5,353 patients and 5,551 controls. Using a state-of-the-art gene chip that contains the details of approximately 24,000 common genetic variants, the researchers confirmed that 24 of the variants represented genetic risk factors for Parkinson’s disease, including six variants that had not been previously identified.

Some of the newly identified genetic risk factors are thought to be involved with Gaucher’s disease, regulating inflammation and the nerve cell chemical messenger dopamine as well as alpha-synuclein, a protein that has been shown to accumulate in the brains of some cases of Parkinson’s disease. Further research is needed to determine the roles of the variants identified in this study.

GenoKey’s data mining technology has been used to analyse GWAS, finding statistically significant connections between the clusters of SNPs and the symptoms of bipolar disorder.





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