Skip to main content
Premium Trial:

Request an Annual Quote

Loss-of-Function, Truncating Variants in UK Biobank Data Point to New Drug Targets

NEW YORK (GenomeWeb) –Researchers have delved into the potential functions and consequences of predicted loss-of-function (pLOF) or protein-truncating mutations found in hundreds of thousands of UK Biobank participants, tying them both to disease and to protection from illness.

The results, from two independent research teams, are appearing online today in two studies in Nature Communications.

For one of the papers, researchers from Massachusetts General Hospital, the Broad Institute, and elsewhere analyzed almost 3,800 pLOF variants in 335,660 UK Biobank participants of European ancestry and 69,909 non-European participants, looking for ties to two dozen conditions ranging from cardiovascular or metabolic disease to cancer or allergic conditions.

The 3,759 pLOF variants in question included early stop codons, frameshift changes, or essential splice site alterations found by comparing participant sequences with version hg19 of the human reference genome, they noted.

By folding in information on six cardiovascular conditions, six metabolic features, and 12 more conditions such as breast cancer, depression, and psoriasis, the team uncovered 18 rare or low-frequency pLOFs with ties to one or more of these phenotypes.

Among them are: LOFs that appeared to protect against conditions such as obesity, type 2 diabetes, asthma, autoimmune conditions, hypothyroidism, or coronary artery disease, highlighting genes that might ultimately yield new therapeutic targets.

"[W]e associated pLOF variants with a range of biomarker and disease phenotypes in a large, national biobank and identified several new genes in which pLOF variants protect against disease, prioritizing these genes for therapeutic targeting," corresponding author Sekar Kathiresan, a genomic medicine as well as medical and population genetic researcher affiliated with Mass General and the Broad Institute, and his colleagues wrote. 

For the other study, a team led by Stanford University biomedical data science researcher Manuel Rivas focused on 18,225 protein-truncating variants in relation to 135 phenotypes in 337,205 of the UK Biobank participants.

That search led to associations between 20 disease-related phenotypes and 27 protein-truncating variants in 17 genes outside immune-related sequences in the major histocompatibility complex (MHC). Another 47 protein-truncating variants with potential disease ties fell in or around the MHC.

The non-MHC variant set included protein-truncating variants that seemed to protect against conditions such as asthma, bronchitis, hypothyroidism, and hypertension, the researchers reported. A dozen other protein-truncating variants appeared to bump up disease risk, including variants in genes previously identified in genome-wide association studies of lung cancer, hypertension, and other conditions.

To take a closer look at these associations, the team subsequently used a GWAS approach to look for possible disease links for additional, missense variants in the genes implicated by the protein-truncating variants. In the process, it saw significant disease associations for more than a dozen missense variants in these genes, along with new associations for still other missense variants.

Hundreds more potentially informative protein-truncating variants turned up when the researchers imputed additional genotypes, leading to nine more variants with apparent disease ties.

The team's phenome-wide association study highlighted protein-truncating variants that corresponded to more than one condition, while an analysis of individuals with protein-truncating variants affecting both copies of a given gene provided a look at the consequences of several naturally occurring gene "knockouts."

"Naturally occurring human knockouts that protect against disease provide in vivo validation of safety and efficacy and may be relatively simple to target with drugs," the authors wrote, noting that the results so far "illustrate the value of deep population-scale health and genomic datasets for prioritizing genetic variants and genes with translational potential."

Drug companies have already taken note. Regeneron Pharmaceuticals, for example, has been sequencing the exomes of more than 250,000 individuals, including those from the UK Biobank, to find human knockouts that could lead to new therapeutics.