Although genome-wide association studies have revealed numerous risk loci associated with diverse diseases, they have also been tantalizingly short on detail. For example, association loci don’t necessarily pinpoint the variants, much less give any indication of the disease-causing mechanisms the variants may trigger.
Such details, however, may soon become more readily available, thanks to a new approach developed by researchers at the Harvard Medical School-affiliated Institute for Aging Research at Hebrew Senior Life. These researchers have found a way to track patterns within regulatory regions in a number of species close or distant to humans. The researchers proceeded on the assumption that variant patterns conserved across species are likely to serve important functions.
According to institute fellow Melina Claussnitzer, Ph.D., “It has become clear that the bulk of disease-associated variants are located in the noncoding part of the DNA, where the function of the DNA is largely unknown. Noncoding variants are known to contribute to disease through dysregulation of gene expression. But pinpointing the noncoding variants, which confer this dysregulation, remains a major challenge.”
Dr. Claussnitzer and her colleagues applied their approach to genetic variants associated with type 2 diabetes, one of the most prevalent human diseases. Claussnitzer’s team, in an article published January 17 in Cell, indicated that by using “integrative computational analysis of phylogenetic conservation with a complexity assessment of co-occurring transcription factor binding sites (TFBSs),” they were able to identify “cis-regulatory variants and elucidate their mechanistic role in disease.”
Although this particular study addressed the underlying genetic causes of type 2 diabetes, it describes a methodology that could, in principle, be applied to any common disease including osteoporosis, Alzheimer’s disease, and cancer.
The study, entitled “Leveraging Cross-Species Transcription Factor Binding Site Patterns: From Diabetes Risk Loci to Disease Mechanisms,” describes how the researchers sought conserved patterns of certain sequences that make up transcription factor binding sites (TFBSs). To find these conserved TFBS patterns, data about a given region around a gene variant in the human genome was analyzed to guide the search for comparable regions in other vertebrate species. The TFBS pattern conservation of the regions was then scored based on the similarity of TFBS arrangement across species. A high score indicated a high probability that this variant affects the regulation of genes, thereby pointing to the underlying mechanism of a disease.
In their paper, the authors wrote that analysis of established type 2 diabetes risk loci revealed a striking clustering of distinct homeobox TFBSs: “We identified the PRRX1 homeobox factor as a repressor of PPARG2 expression in adipose cells and demonstrate its adverse effect on lipid metabolism and systemic insulin sensitivity, dependent on the rs4684847 risk allele that triggers PRRX1 binding.”