New targets for a wide range of conditions have been unveiled by a large, multicenter genomic study led by researchers at Children’s Hospital of Philadelphia (CHOP). The team compared the sequence data of more than 100,000 people of European ancestry and found copy number variant (CNV) associations in four major disease categories: autoimmune, cardio-metabolic, oncologic, and neurological/psychiatric diseases. Some of these CNVs represent “potential drug targets for future validation,” they write. This study also identified several drug-repurposing opportunities.The team’s findings were published this week in the journal Nature Communications.
“This analysis provides us with a dense map of the impact of rare recurrent copy number variations, which represent an important source of genetic variation in our genome, often predisposing us to, and sometimes causing, complex diseases,” said senior author Hakon Hakonarson, MD, PhD, Director of the Center for Applied Genomics at CHOP. “Our study showed that previous methods are likely not capturing the accurate incidence or prevalence of rare copy number variation regions that directly impact human health.”
Thestudy samples were derived from two cohorts. The first included 52,321 samples from the genomics biorepository at CHOP. The second set comprised 29,085 samples from subjects with neurological disease and 19,584 matching controls, which were run on a CGH array at The University of Washington in Seattle, WA.It’s increasingly recognized that such large datasets are necessary to power meaningful genomic studies, and the number of these has swelled over the years. As of last summer, at least ten countries were building sequence databanks of 100,000 or more.
The researchers analyzed the CNV genomic landscape of 100,028 unrelated individuals of European ancestry, using SNP and CGH array datasets. They observed an average CNV burden of ~650 kb, and found a total of 11,314 deletion, 5625 duplication, and 2746 homozygous deletion CNV regions (CNVRs). In all, 13.7% of these are unreported, 58.6% overlap with at least one gene, and 32.8% interrupt coding exons. The copy number variant regions (CNVRs) they identified are significantly more likely to overlap OMIM genes, GWAS loci, and non-coding RNAs, compared with random distribution.
CNV associations were found in four major disease categories, including autoimmune, cardio-metabolic, oncologic, and neurological/psychiatric diseases, and pointed to several drug-repurposing opportunities. The vast majority (more than 99%) of the CNV regions uncovered, while individually rare, were recurrent, meaning that they occurred in at least two individuals.Among these regions that are most clinically relevant are those with homozygous deletions. The study team identified 375 previously unreported regions like this. In addition to confirming disease-associated CNV regions from previous studies, the researchers discovered several previously unreported regions that match genes that are already of clinical interest, in some cases because drugs that target relevant pathways may already exist.
Some specific regions of interest identified in this study include the chr7p15.3 deletion associated with autoimmune diseases, since it overlaps with the gene that encodes for ITGB8a, a well-established drug target for ovarian cancer; a homozygous deletion region associated with autoimmunity at chr2q34 that that interrupts the coding region of the gene ERBB4, a key oncogene that can be targeted by multiple FDA-approved small molecule inhibitors; and the locus chr19p13.3, which encodes the gene HCN2 and could be a potential target for therapies to treat both epilepsy and pain.
“The number of gene candidates found in our study that warrant further studies establishes the strong correlation between regions of copy number variations and what we already know about the genome,” Hakonarson said. “While ongoing, large scale studies focusing on new discoveries are important, we believe that further investigating these newly identified regions in parallel will continue to yield even more clinically relevant information and accelerate precision medicine.”