Ecoclimber
Senior Member
- Messages
- 1,011
In Autoimmune Diseases Affecting Millions, Researchers Pinpoint Genetic Risks, Cellular Culprits
New Software Tool Helps Makes Sense of Previous Genetic Data on Multiple Sclerosis, Type 1 Diabetes, Other Diseases
By Jeffrey Norris on October 29, 201
Scores of autoimmune diseases afflicting one in 12 Americans — ranging from type 1 diabetes, to multiple sclerosis (MS), to rheumatoid arthritis, to asthma — mysteriously cause the immune system to harm tissues within our own bodies. Now, a new study pinpoints the complex genetic origins for many of these diseases, a discovery that may lead to better diagnosis and ultimately to improved treatments.
A team of scientists from UC San Francisco, the Broad Institute of MIT and Harvard, and Yale School of Medicine developed a new mathematical tool to more deeply probe existing DNA databases. In so doing they discovered how certain DNA variations, when inherited, are likely to contribute to disease.
By applying their method to analyzing data from previous studies of 21 different autoimmune diseases, the research team has deepened scientific understanding of the genetic underpinnings of a wide range of these disorders. They also found the specific immune cells most responsible for the diseases. Their study is published online on October 29, 2014 in Nature.
Continue reading here.
NATURE
Genetic and epigenetic fine mapping of causal autoimmune disease variants
Kyle Kai-How Farh, Alexander Marson, Jiang Zhu, Markus Kleinewietfeld, William J. Housley, Samantha Beik, Noam Shoresh, Holly Whitton, Russell J. H. Ryan, Alexander A. Shishkin, Meital Hatan, Marlene J. Carrasco-Alfonso, Dita Mayer, C. John Luckey, Nikolaos A. Patsopoulos, Philip L. De Jager, Vijay K. Kuchroo, Charles B. Epstein, Mark J. Daly, David A. Hafler & Bradley E. Bernstein
Nature (2014) doi:10.1038/nature13835
Abstract:
Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown.
Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4+ T-cell subsets, regulatory T cells, CD8+ T cells, B cells, and monocytes.
We find that ~90% of causal variants are non-coding, with ~60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10–20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models.
Last edited by a moderator: