Polygenic and clinical risk scores and their impact on age at onset of cardiometabolic diseases and common cancers

Mars, N. J.; Koskela, J. T.; Ripatti, P.; Kiiskinen, T. T. J.; Havulinna, A. S.; Lindbohm, J. V.; Ahola-Olli, A.; Kurki, M.; Karjalainen, J.; Palta, P.; FinnGen,; Neale, B. M.; Daly, M.; Salomaa, V.; Palotie, A.; Widen, E.; Ripatti, S.

doi:10.1101/727057

bioRxiv · 10.1101/727057

Polygenic and clinical risk scores and their impact on age at onset of cardiometabolic diseases and common cancers

Mars, N. J.·Koskela, J. T.·Ripatti, P.·Kiiskinen, T. T. J.·Havulinna, A. S.·Lindbohm, J. V.·Ahola-Olli, A.·Kurki, M.·Karjalainen, J.·Palta, P.·FinnGen,·Neale, B. M.·Daly, M.·Salomaa, V.·Palotie, A.·Widen, E.·Ripatti, S.

View original source ↗Export metadata ↓

Abstract

BackgroundPolygenic risk scores (PRS) have shown promise in predicting susceptibility to common diseases. However, the extent to which PRS and clinical risk factors act jointly and identify high-risk individuals for early onset of disease is unknown.\n\nMethodsWe used large-scale biobank data (the FinnGen study; n=135,300), with up to 46 years of prospective follow-up, and the FINRISK study with standardized clinical risk factor measurements to build genome-wide PRSs with >6M variants for coronary heart disease (CHD), type 2 diabetes (T2D), atrial fibrillation (AF), and breast and prostate cancer. We evaluated their associations with first disease events, age at disease onset, and impact together with routinely used clinical risk scores for predicting future disease.\n\nResultsCompared to the 20-80th percentiles, a PRS in the top 2.5% translated into hazard ratios (HRs) for incident disease ranging from 2.03 to 4.28 (p-values 1.96x10-59 to <1.00x10-100) and the bottom 2.5% into HRs ranging from 0.20 to 0.61. The estimated difference in age at disease onset between top and bottom 2.5% of PRSs was 6 to 13 years. Among early-onset cases, 21.3-32.9% had a PRS in the highest decile and in CHD and AF.\n\nConclusionsThe properties of PRS were similar in all five diseases. PRS identified a considerable proportion early-onset cases, and for all ages the performance of PRS was comparable to established clinical risk scores. These findings warrant further clinical studies on application of polygenic risk information for stratified screening or for guiding lifestyle and preventive medical interventions.

Explore related subjects

genomics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Mars, N. J., Koskela, J. T., Ripatti, P., Kiiskinen, T. T. J., Havulinna, A. S., Lindbohm, J. V., Ahola-Olli, A., Kurki, M., Karjalainen, J., Palta, P., FinnGen,, Neale, B. M., Daly, M., Salomaa, V., Palotie, A., Widen, E., Ripatti, S.. 2019-08-06. Polygenic and clinical risk scores and their impact on age at onset of cardiometabolic diseases and common cancers. https://doi.org/10.1101/727057

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Long-read DNA sequencing reveals global hypomethylation and focal hypermethylation in SDHx-deficient pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGL) are highly heritable neuroendocrine tumors of the autonomic ganglia. Genomic DNA in most cancer cells is hypomethylated. However, DNA in PPGLs secondary to mutations in succinate dehydrogenase complex (SDHx) genes is reportedly hypermethylated due to succinate-mediated inhibition of DNA demethylases. We used nanopore long-read sequencing to characterize the methylome of tumor and white blood cell DNA from SDHx and non-SDHx PPGL patients, alongside normal adrenal medulla. We find that both SDHx and non-SDHx PPGLs are globally hypomethylated, particularly at centromeres. In normal adrenal medulla, CpG islands marked by H3K4 methylation are hypomethylated, whereas CpG islands lacking H3K4 methylation are hypermethylated. In SDHx-related PPGL, some H3K4me-marked CpG islands are hypermethylated, but most are not. We propose that DNA methylation in SDHx-related PPGL reflects the global hypomethylation generally observed in tumors, partly offset by succinate-mediated inhibition of TET DNA demethylases. Opposing effects of succinate may alter the balance between DNA methylation (indirect inhibition of the DNMT3A/B DNA methylases via inhibition of H3K4me demethylases) and DNA demethylation (inhibition of TET DNA demethylases) at active CpG islands.

genomics↗

bioRxiv2026

High piRNA abundance is a hallmark of evolutionarily persistent piRNA-producing loci.

PIWI-interacting RNAs (piRNAs) silence transposons in the germline, and the loci that produce them diverge rapidly between species. Yet, some loci retain both their genomic location and their piRNA production across large evolutionary distances, and the basis for this conservation is unclear. To identify the features that distinguish these persistent loci, we compared piRNA production at orthologous loci in three closely related mouse species, contrasting loci that produce piRNAs in all three species with those that do so in only one. Transposon content and UTR features, often linked to piRNA production, did not distinguish the two groups. Transcription extending beyond gene ends (readthrough) was more frequent at conserved loci, but did not explain conservation once the amount of piRNAs produced was taken into account. Instead, we found that the conserved loci are those that produce the most piRNAs. The same association holds true in human and two other primate species. We speculate that most piRNAs expressed in testis are tolerated molecular noise, and that only the highly expressed minority are likely to be functional.

genomics↗

bioRxiv2026

Epigenome-informed Polymer Modeling Reveals Chromosome Folding Landscapes across Distinct Genetic and Epigenetic Contexts

Three-dimensional (3D) genome organization is critical for gene regulation, enabling long-range interactions between genes and distal regulatory elements. Genomic structural variations and epigenetic differences can perturb this organization, contributing to phenotypic variation and tissue-specific gene regulation. Prior studies have assessed the impact of these genetic and epigenetic changes on 3D genome folding, primarily using population-averaged features such as topologically associating domains and loops. However, growing evidence from single-cell and live-imaging studies indicates that chromosomes are highly dynamic and exist as heterogeneous ensembles of conformations. Here, we applied an epigenetic-state-informed polymer modeling framework to generate chromosomal conformational ensembles directly from cell- and tissue-specific epigenomic data. The resulting ensembles reproduced experimental Hi-C maps across cell lines and tissue types. Comparison of these conformational ensembles revealed that, although polymer dynamics were conserved across cell lines, their folding landscapes diverged. These differences arose primarily from cell-line-specific chromatin-state interaction networks and were concentrated in rare, long-lived contacts. Furthermore, modeling a TAD-boundary-disrupting deletion without re-optimizing the model parameters indicated a shift in the chromatin conformational ensemble from predominantly insulated to predominantly fused states. The modeled deletion also selectively strengthened active chromatin contacts and differentially disrupted enhancer contacts involving neighboring genes. Finally, comparison of two tissue types from the same donor revealed epigenetically driven rewiring of chromatin-state interaction networks. These findings establish chromosomal conformational ensembles as a sensitive readout of genome reorganization across distinct genetic and epigenetic contexts.

genomics↗