Polygenic risk score incorporating rare variants does not improve fracture prediction
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Key takeaways:
- A polygenic risk score that includes rare variants did not substantially improve osteoporosis or fracture risk prediction.
- More data are needed for people of non-European ancestry.
The identification of rare genetic variants that influence bone mineral density did not significantly improve fracture risk screening among a large group of adults, according to data published in Journal of Bone and Mineral Research.
Using data from the UK Biobank, researchers performed whole-exome sequencing to identify 12 rare genetic variants that influence BMD. However, when those rare variants were incorporated into a common variant-based polygenic risk score, researchers did not see a large improvement compared with a polygenic risk score using common variants only.
“Rare variant screening and rare variant-informed risk prediction may not be efficient in an unselected population, considering the high cost of sequencing and low prevalence of influential rare variants,” Tianyuan Lu, PhD, a Schmidt AI in Science postdoctoral fellow at the University of Toronto, told Healio. “Triaging patients, such as those with a family history of osteoporosis or fracture, may increase the yield of such sequencing-based genetic testing and may help to utilize the improved capacity of the genetic risk score in predicting individual risk, although the cost-effectiveness remains to be evaluated.”
Lu and colleagues collected data from 392,259 participants in the UK Biobank who underwent whole-exome sequencing from 2006 to 2010. Adults had BMD measured at the heel. Osteoporosis cases were identified through ICD codes, and fracture cases were determined at recruitment or follow-up through March 2020. Rare genetic variants were defined as those with a minor allele frequency of 0.1% or less that were predicted to have a high impact on BMD, may cause loss of protein function or were missense variants. The rare variants were incorporated into a common variant polygenic risk score. The risk score with the rare variants included was assessed in a test group of participants to examine whether it could better predict risks for osteoporosis, major osteoporotic fracture and low-trauma fracture than the risk score with only common variants.
Fracture prediction similar between scores
Of the study population, 317,434 were included in the training data and the remaining 74,825 comprised the test data set. Among the training data set, researchers identified 12 rare genetic variants. The variants were observed among 5.3% of the training data set and 5.4% of those in the test data set using a stringent inclusion strategy.
Among adults in the test data set, each 1 standard deviation (SD) decrease in the polygenic risk score that included the rare variants was associated with a higher risk for osteoporosis (OR = 1.46; 95% CI, 1.21-1.77), a major osteoporotic fracture (HR = 1.35; 95% CI, 1.16-1.57) and a low-trauma fracture (HR = 1.26; 95% CI, 1.12-1.42). In comparison, each 1 SD decrease in polygenic risk score with only common variants included was linked to similar increases in risk for osteoporosis (OR = 1.39; 95% CI, 1.15-1.69), major osteoporotic fracture (HR = 1.32; 95% CI, 1.14-1.54) and low-trauma fracture (HR = 1.24; 95% CI, 1.11-1.4). There was no difference in C-index between the polygenic risk score with the rare variants included and the risk score without the rare variants. Results were similar using a more lenient inclusion strategy.
More research on rare variants needed
Researchers also tested the rare variant polygenic risk score among people of non-white British European ancestry, those of African ancestry, people of East Asian ancestry, a group of adults of South Asian ancestry and adults from other admixed ancestries.
“A critical drawback of polygenic risk prediction is the limited cross-ancestry portability,” Lu said. “Although adding influential rare variants improved prediction accuracy of the genetic risk score in the non-white British European, African and East Asian ancestry populations, it did not mitigate the performance discrepancies of the polygenic risk score between these populations and the white British ancestry population. This imposes a crucial challenge for research in osteoporosis genetics and necessitates investments into equitable use of risk prediction tools, possibly through enriching sequencing data resources in non-European ancestry populations.”
Lu said more research is needed to look at how rare genetic variants affect BMD and osteoporosis and to confirm the study’s findings in other cohorts. Lu also said more sequencing data in non-European ancestry populations is needed to better profile the genetic architecture of complex traits and diseases.
For more information:
Tianyuan Lu, PhD, can be reached at tianyuan.lu@mail.mcgill.ca.
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