Thomas W Winkler, Simon Wiegrebe, Janina M Herold, Klaus J Stark, Helmut Küchenhoff, Iris M Heid
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引用次数: 0
Abstract
Background: Genome-wide association studies (GWAS) have identified thousands of loci for disease-related human traits in cross-sectional data. However, the impact of age on genetic effects is underacknowledged. Also, identifying genetic effects on longitudinal trait change has been hampered by small sample sizes for longitudinal data. Such effects on deteriorating trait levels over time or disease progression can be clinically relevant.
Results: Under certain assumptions, we demonstrate analytically that genetic-by-age interaction observed in cross-sectional data can be indicative of genetic association on longitudinal trait change. We propose a 2-stage approach with genome-wide pre-screening for genetic-by-age interaction in cross-sectional data and testing identified variants for longitudinal change in independent longitudinal data. Within UK Biobank cross-sectional data, we analyze 8 complex traits (up to 370,000 individuals). We identify 44 genetic-by-age interactions (7 loci for obesity traits, 26 for pulse pressure, few to none for lipids). Our cross-trait view reveals trait-specificity regarding the proportion of loci with age-modulated effects, which is particularly high for pulse pressure. Testing the 44 variants in longitudinal data (up to 50,000 individuals), we observe significant effects on change for obesity traits (near APOE, TMEM18, TFAP2B) and pulse pressure (near FBN1, IGFBP3; known for implication in arterial stiffness processes).
Conclusions: We provide analytical and empirical evidence that cross-sectional genetic-by-age interaction can help pinpoint longitudinal-change effects, when cross-sectional data surpasses longitudinal sample size. Our findings shed light on the distinction between traits that are impacted by age-dependent genetic effects and those that are not.
期刊介绍：
Genome Biology is a leading research journal that focuses on the study of biology and biomedicine from a genomic and post-genomic standpoint. The journal consistently publishes outstanding research across various areas within these fields.
With an impressive impact factor of 12.3 (2022), Genome Biology has earned its place as the 3rd highest-ranked research journal in the Genetics and Heredity category, according to Thomson Reuters. Additionally, it is ranked 2nd among research journals in the Biotechnology and Applied Microbiology category. It is important to note that Genome Biology is the top-ranking open access journal in this category.
In summary, Genome Biology sets a high standard for scientific publications in the field, showcasing cutting-edge research and earning recognition among its peers.
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