The Effect of Family Structure on the Still-Missing Heritability and Genomic Prediction Accuracy of Type 2 Diabetes Publisher Pubmed



Amiri Roudbar M¹ ; Vahedi SM³ ; Jin J⁴ ; Jahangiri M⁵ ; Lanjanian H⁶ ; Habibi D^{6, 17} ; Masjoudi S⁶ ; Riahi P⁶ ; Fateh ST⁷ ; Neshati F⁶ ; Zahedi AS⁶ ; Moazzamjazi M⁶ ; Najdhassanbonab L⁶ ; Mousavi SF⁸ Show All Authors
Source: Human Genomics Published:2024

Abstract

This study aims to assess the effect of familial structures on the still-missing heritability estimate and prediction accuracy of Type 2 Diabetes (T2D) using pedigree estimated risk values (ERV) and genomic ERV. We used 11,818 individuals (T2D cases: 2,210) with genotype (649,932 SNPs) and pedigree information from the ongoing periodic cohort study of the Iranian population project. We considered three different familial structure scenarios, including (i) all families, (ii) all families with ≥ 1 generation, and (iii) families with ≥ 1 generation in which both case and control individuals are presented. Comprehensive simulation strategies were implemented to quantify the difference between estimates of and. A proportion of still-missing heritability in T2D could be explained by overestimation of pedigree-based heritability due to the presence of families with individuals having only one of the two disease statuses. Our research findings underscore the significance of including families with only case/control individuals in cohort studies. The presence of such family structures (as observed in scenarios i and ii) contributes to a more accurate estimation of disease heritability, addressing the underestimation that was previously overlooked in prior research. However, when predicting disease risk, the absence of these families (as seen in scenario iii) can yield the highest prediction accuracy and the strongest correlation with Polygenic Risk Scores. Our findings represent the first evidence of the important contribution of familial structure for heritability estimations and genomic prediction studies in T2D. © The Author(s) 2024.