Type 2 diabetes is a serious and costly disease that impacts at least 20 million people in the United States, with chronic complications including accelerated development of cardiovascular and microvascular disease. Genome wide association studies (GWAS) have revolutionized the field of complex disease genetics in recent years, where intense efforts have been successful in discovering key genetic variants robustly associated with type 2 diabetes. However, GWAS only reports genomic signals associated with a given trait and not necessarily the precise localization of culprit genes. As such, over the past ten years, GWAS did not strictly represent a decade of gene target discovery, rather it was simply a decade of signal discovery. One clear example of this is highlighted by the recent progress in characterizing the FTO locus in the related trait of obesity. The GWAS signal that resides within an intronic region of FTO has in fact been recently shown to primarily influence the expression of the IRX3 and IRX5 genes nearby rather than the ?host? gene itself, suggesting that this variant is in an enhancer embedded in one gene but influencing the expression of others. So a key question is: how often is this the case with type 2 diabetes association signals? Indeed, we have already addressed the most significant GWAS finding in type 2 diabetes reported to date, namely genetic variation within the transcription factor 7?like 2 (TCF7L2) gene, which the P.I. on this application first described in 2006. Given that the type 2 diabetes genetics community widely consider the T allele of the intronic single nucleotide polymorphism (SNP), rs7903146, within TCF7L2 to be the causal variant at this locus, we utilized chromatin conformation capture and CRISPR/Cas9 genome editing techniques to target this specific genomic region. As a consequence, we have compelling evidence that the actual culprit gene at this locus is in fact ?acyl-CoA synthetase long chain family, member 5? (ACSL5). Given we already have a dedicated infrastructure in place funded by the Children?s Hospital of Philadelphia to conduct such ?variant to gene mapping? efforts, our team is poised to determine how additional recently uncovered type 2 diabetes GWAS-implicated loci affect the expression and function of specific genes through the use key cutting-edge molecular biology approaches. The application of ?3D Genomics? based techniques will aid in the pinpointing of the causal gene(s) at ten of the type 2 diabetes GWAS signals, where the ?credible set? of SNPs is no more than ten variants i.e. a number of loci have already been distilled down through extensive genetic mapping efforts to a manageable shortlist of candidate variants, of which one must be causal. As such, these recently published lists of SNPs represent a workable number of variants in order to both determine the causal gene(s) at each locus and to demonstrate the generalizability of our approach. Only by uncovering the correct functional context of these genetic variants and understanding how they operate can we truly translate these high value GWAS reports in to meaningful benefits for patient care.
Genome wide association studies (GWAS) have clearly revolutionized the field of complex disease genetics, where intense efforts by numerous research groups have been successful in discovering key genetic variants robustly associated with type 2 diabetes. However, GWAS only reports genomic signals associated with a given trait and not necessarily the precise localization of culprit genes. Given the need for ?variant to gene mapping?, we already have a dedicated infrastructure in place and a team poised to shed further light on the genomics of type 2 diabetes through the application of ?3D Genomics? based techniques to pinpoint the causal gene at each key GWAS-implicated locus.
| Manduchi, Elisabetta; Williams, Scott M; Chesi, Alessandra et al. (2018) Leveraging epigenomics and contactomics data to investigate SNP pairs in GWAS. Hum Genet 137:413-425 |
