Skip to main content
Premium Trial:

Request an Annual Quote

Consanguinity Contributes to Common Disease Risk, Study Suggests

NEW YORK – An international team led by investigators at the Wellcome Sanger Institute, the University of Amsterdam, and VU Amsterdam has linked a dozen common diseases to the runs of homozygosity (ROH) that can arise from consanguineous unions between related individuals. The results were published in Cell on Tuesday.

"Our paper is the first to look at the effects of autozygosity on common diseases across the phenotypic spectrum, while dealing with confounding in a robust way," senior and corresponding author Hilary Martin, a researcher at the Wellcome Sanger Institute, said in an email.

For their study, Martin and her colleagues brought together array-based genotyping profiles and electronic health record data for nearly 397,200 UK Biobank (UKB) participants and 23,978 participants in the Genes and Health (G&H) study, a community-based effort involving British individuals with Bangladeshi or Pakistani ancestry.

"Given that G&H has high self-reported rates of consanguinity (9 percent in British Bangladeshi individuals and 36 percent in British Pakistani individuals), we first sought to genetically characterize consanguinity patterns in the cohort and compare them with the UKB," the authors explained, noting that parental relatedness was estimated using ROH distributions in individuals' genomes.

After teasing out parental relatedness in the participants, the team considered potential ties between common disease risk and fractions of the genome represented by ROH, focusing on individuals born to couples who were first cousins. The approach made it possible to distinguish between autozygosity-related associations and potential lifestyle or socioeconomic confounders such as alcohol or tobacco use, education history, or religiosity.

"A challenging problem in assessing the relationship between autozygosity and phenotypes is that associations may be confounded by both population structure and the social circumstances in which consanguinity and endogamy are practiced," the authors wrote. They noted that "subsetting association analyses to highly consanguineous individuals better controls for social and environmental confounding."

The search pointed to significant associations between the amount of ROH in the genome and 12 common diseases, ranging from asthma, type 2 diabetes (T2D) or dermatitis to infectious gastroenteritis, colitis, stress disorder, or anxiety disorder, the researchers reported.

The results prompted them to take a closer look at two of the conditions — T2D and post-traumatic stress disorder (PTSD) — in research-consented 23andMe customers. Together, the authors explained, their results suggested that "autozygosity impacts several common diseases spanning multiple organ systems, notably T2D and PTSD."

Based on the results so far, the team noted that consanguinity may have non-additive effects on common disease risk in populations where consanguineous relationships are relatively common. For example, they estimated that some 5 percent to 18 percent of the T2D cases diagnosed in British Pakistani individuals may be explained by the autozygosity-related risk detected in their analysis.

While more work will be needed to tease out the genetic contributors behind the associations identified, Martin noted that future searches will no doubt focus on recessive variants, which are more likely to be homozygous in individuals whose parents are related.

"Some of these may have been missed by standard additive association tests, and finding them may shed further light on the biology of these diseases, and potentially identify novel drug targets," she explained, adding that autozygosity may also provide an additional layer of information when attempting to determine disease risk using polygenic scores or conventional clinical factors.

"[I]t would be interesting to explore whether including genome-wide autozygosity in models can improve disease risk prediction," Martin said. "If so, this could be useful in the future if genetic risk prediction starts to be implemented in clinical care for complex diseases, even if we don’t know which specific genetic variants are driving the signals we found."