NEW YORK (GenomeWeb) – In a study published today in Nature Genetics, an international team led by investigators at the New York Genome Center and 23andMe described efforts to uncover genetic loci influencing multiple human conditions or characteristics.
By bringing together information from past large genome-wide association studies for dozens of traits or diseases, the researchers uncovered hundreds of sites in the genome that seemed to influence more than one human trait. Using these clues, they explored the spectrum of traits that were apparently affected by individual genomic loci, as well as conditions sharing the same genetic underpinnings.
"While genomic studies have been successful in identifying genetic variants that influence disease risk, it's important to understand the impact of genetic variants across many diseases," first author Joseph Pickrell, a biological sciences researcher affiliated with the NYGC and Columbia University, said in a statement.
With that in mind, Pickrell and his colleagues compiled data from 43 large GWAS focused on 42 different phenotypes — from risk of inherited or infectious disease to physical features, metabolic phenotypes, and blood-related traits. The set included 17 unpublished GWAS done by 23andMe, and the team also used 1000 Genomes Project data to do new variant imputation for a subset of GWAS without such imputation data.
"We were interested in using the individual variants found to affect multiple traits to identify biological relationships between traits, including potential relationships where one trait is causally upstream of the other," the study's authors wrote.
After using a statistical method to scan for variants associated with multiple human phenotypes, the researchers detected 341 genomic loci that appeared to influence at least two different traits.
The search also led to individual variants with potential ties to several different phenotypes. For example, the team saw non-synonymous SNPs in and around the SLC39A8 gene, which codes for a zinc transporter, that were linked to seven different human conditions — from schizophrenia and Parkinson disease risk to height.
Similarly, the analysis pointed to a variant in the vicinity of the ABO blood group gene that was apparently associated with 11 phenotypes, including coronary artery disease, blood traits, lipid features, and immune traits, as well as risk of having to undergo a tonsillectomy.
By starting from the phenotype side of the equation, meanwhile, researchers described particular traits that seemed to share ties to shared genetic variants. For example, they uncovered unexpected overlap between inflammatory bowel disease-associated variants and variants implicated in schizophrenia risk.
And within the set of variants associated with puberty and growth features, the team detected a subset of SNPs involved in age at menstruation that seemed to have a downstream impact traits height and other traits.
The team's results also recapitulated clusters of diseases that were already known to share some underlying features — for example, grouping together asthma, rheumatoid arthritis, Crohn's disease, and other autoimmune conditions with infectious disease susceptibility.
The available data also made it possible to start teasing apart causal relationships between certain conditions, including variants that appear to mediate an uptick in triglyceride levels in the wake of weight gain, as measured by body mass index.
The investigators predicted that genetic correlation patterns for various human phenotypes may eventually become easier to decipher than genetic overlap alone, particularly as more and more individuals are genotyped across broader sets of variants. And, they noted, it remains to be seen whether the genetic overlap identified using common variant data also exists for rarer disease- or trait-associated variants found through large exome or genome sequencing studies.