# Multi-ancestry genome-wide association analyses incorporating SNP-by-psychosocial interactions identify novel loci for serum lipids

**Authors:** Amy R. Bentley, Michael R. Brown, Solomon K. Musani, Karen L. Schwander, Thomas W. Winkler, Mario Sims, Tuomas O. Kilpeläinen, Hugues Aschard, Traci M. Bartz, Lawrence F. Bielak, Jin-Fang Chai, Kumaraswamy Naidu Chitrala, Nora Franceschini, Mariaelisa Graff, Xiuqing Guo, Fernando P. Hartwig, Andrea R.V.R. Horimoto, Elise Lim, Yongmei Liu, Alisa K. Manning, Ilja M. Nolte, Raymond Noordam, Melissa A. Richard, Albert V. Smith, Yun Ju Sung, Dina Vojinovic, Rujia Wang, Yujie Wang, Mary F. Feitosa, Sarah E. Harris, Leo-Pekka Lyytikäinen, Giorgio Pistis, Rainer Rauramaa, Peter J. van der Most, Erin Ware, Stefan Weiss, Wanqing Wen, Lisa R. Yanek, Dan E. Arking, Donna K. Arnett, Christie Ballantyne, Eric Boerwinkle, Yii-Der Ida Chen, Martha L. Daviglus, Lisa de las Fuentes, Paul S. de Vries, Joseph A. C. Delaney, Amanda M. Fretts, Lynette Ekunwe, Jessica D. Faul, Linda C. Gallo, Sami Heikkinen, Georg Homuth, M. Arfan Ikram, Carmen R. Isasi, Jost Bruno Jonas, Liisa Keltikangas-Järvinen, Pirjo Komulainen, Aldi T. Kraja, Jose E. Krieger, Lenore Launer, Raul Aguirre-Gamboa, Raul Aguirre-Gamboa, Patrick Deelen, Lude Franke, Jan A. Kuivenhoven, Esteban A. Lopera Maya, Ilja M. Nolte, Serena Sanna, Harold Snieder, Morris A. Swertz, Peter M. Visscher, Judith M. Vonk, Cisca Wijmenga, Naomi Wray, Jianjun Liu, Kurt Lohman, Annemarie I. Luik, Ani W. Manichaikul, Pedro Marques-Vidal, Yuri Milaneschi, Stanford E. Mwasongwe, Jeffrey R. O’Connell, Kenneth Rice, Stephen S. Rich, Pamela J. Schreiner, Lars Schwettmann, James M. Shikany, Xiao-ou Shu, Jennifer A. Smith, Harold Snieder, Nona Sotoodehnia, E. Shyong Tai, Kent D. Taylor, Lesley Tinker, Michael Y. Tsai, André G. Uitterlinden, Cornelia M. van Duijn, Diana van Heemst, Melanie Waldenberger, Robert B. Wallace, Hwee-Lin Wee, David R. Weir, Wen-Bin Wei, Ko Willems van Dijk, Gregory Wilson, Jie Yao, Kristin L. Young, Xiaoyu Zhang, Wei Zhao, Xiaofeng Zhu, Alan B. Zonderman, Ian J. Deary, Christian Gieger, Hans Jörgen Grabe, Timo A. Lakka, Terho Lehtimäki, Albertine J. Oldehinkel, Martin Preisig, Ya-Xing Wang, Wei Zheng, Michele K. Evans, Michael Province, James Gauderman, Vilmundur Gudnason, Catharina A. Hartman, Bernardo L. Horta, Sharon L. R. Kardia, Charles Kooperberg, Ching-Ti Liu, Dennis O. Mook-Kanamori, Brenda WJH Penninx, Alexandre C. Pereira, Patricia A. Peyser, Bruce M. Psaty, Jerome I. Rotter, Xueling Sim, Kari E. North, Dabeeru C. Rao, Laura Bierut, Clint L. Miller, Alanna C. Morrison, Charles N. Rotimi, Myriam Fornage, Ervin R. Fox

PMC · DOI: 10.1038/s41398-025-03418-z · 2025-06-20

## TL;DR

This study finds new genetic loci linked to serum lipids by considering interactions between genes and psychosocial factors in a diverse population.

## Contribution

The study introduces a novel approach by incorporating gene-by-psychosocial interactions in multi-ancestry GWAS for serum lipids.

## Key findings

- Nine novel loci were identified, seven of which required interaction modeling for detection.
- Four lead variants showed very low frequency in European ancestry populations.
- RRP1B, a gene linked to a known drug target, was identified as a potential candidate for drug repurposing.

## Abstract

Serum lipid levels, which are influenced by both genetic and environmental factors, are key determinants of cardiometabolic health and are influenced by both genetic and environmental factors. Improving our understanding of their underlying biological mechanisms can have important public health and therapeutic implications. Although psychosocial factors, including depression, anxiety, and perceived social support, are associated with serum lipid levels, it is unknown if they modify the effect of genetic loci that influence lipids. We conducted a genome-wide gene-by-psychosocial factor interaction (G×Psy) study in up to 133,157 individuals to evaluate if G×Psy influences serum lipid levels. We conducted a two-stage meta-analysis of G×Psy using both a one-degree of freedom (1df) interaction test and a joint 2df test of the main and interaction effects. In Stage 1, we performed G×Psy analyses on up to 77,413 individuals and promising associations (P < 10−5) were evaluated in up to 55,744 independent samples in Stage 2. Significant findings (P < 5 × 10−8) were identified based on meta-analyses of the two stages. There were 10,230 variants from 120 loci significantly associated with serum lipids. We identified novel associations for variants in four loci using the 1df test of interaction, and five additional loci using the 2df joint test that were independent of known lipid loci. Of these 9 loci, 7 could not have been detected without modeling the interaction as there was no evidence of association in a standard GWAS model. The genetic diversity of included samples was key in identifying these novel loci: four of the lead variants displayed very low frequency in European ancestry populations. Functional annotation highlighted promising loci for further experimental follow-up, particularly rs73597733 (MACROD2), rs59808825 (GRAMD1B), and rs11702544 (RRP1B). Notably, one of the genes in identified loci (RRP1B) was found to be a target of the approved drug Atenolol suggesting potential for drug repurposing. Overall, our findings suggest that taking interaction between genetic variants and psychosocial factors into account and including genetically diverse populations can lead to novel discoveries for serum lipids.

## Linked entities

- **Genes:** MACROD2 (mono-ADP ribosylhydrolase 2) [NCBI Gene 140733], GRAMD1B (GRAM domain containing 1B) [NCBI Gene 57476], RRP1B (ribosomal RNA processing 1B) [NCBI Gene 23076]
- **Chemicals:** Atenolol (PubChem CID 2249)

## Full-text entities

- **Genes:** GRAMD1B (GRAM domain containing 1B) [NCBI Gene 57476] {aka LAMb, LINC01059}, MACROD2 (mono-ADP ribosylhydrolase 2) [NCBI Gene 140733] {aka C20orf133, C2orf133}, RRP1B (ribosomal RNA processing 1B) [NCBI Gene 23076] {aka KIAA0179, NNP1L, Nnp1, PPP1R136, RRP1}
- **Diseases:** anxiety (MESH:D001007), depression (MESH:D003866)
- **Chemicals:** Atenolol (MESH:D001262), lipid (MESH:D008055)
- **Mutations:** rs59808825, rs11702544, rs73597733

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12179276/full.md

---
Source: https://tomesphere.com/paper/PMC12179276