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Meta-Analysis
. 2025 Jun 20;15(1):207.
doi: 10.1038/s41398-025-03418-z.

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

Amy R Bentley #  1 Michael R Brown #  2 Solomon K Musani  3 Karen L Schwander  4 Thomas W Winkler  5 Mario Sims  6 Tuomas O Kilpeläinen  7   8 Hugues Aschard  9   10 Traci M Bartz  11 Lawrence F Bielak  12 Jin-Fang Chai  13 Kumaraswamy Naidu Chitrala  14 Nora Franceschini  15 Mariaelisa Graff  15 Xiuqing Guo  16 Fernando P Hartwig  17 Andrea R V R Horimoto  11   18 Elise Lim  19 Yongmei Liu  20 Alisa K Manning  21   22 Ilja M Nolte  23 Raymond Noordam  24 Melissa A Richard  25   26 Albert V Smith  27 Yun Ju Sung  28 Dina Vojinovic  29   30   31 Rujia Wang  32 Yujie Wang  15 Mary F Feitosa  4 Sarah E Harris  33 Leo-Pekka Lyytikäinen  34   35 Giorgio Pistis  36 Rainer Rauramaa  37 Peter J van der Most  23 Erin Ware  38 Stefan Weiss  39   40 Wanqing Wen  41 Lisa R Yanek  42 Dan E Arking  43 Donna K Arnett  44 Christie Ballantyne  45   46 Eric Boerwinkle  2   47 Yii-Der Ida Chen  16 Martha L Daviglus  48 Lisa de Las Fuentes  49   50 Paul S de Vries  2 Joseph A C Delaney  51   52   53   54 Amanda M Fretts  51   53 Lynette Ekunwe  55 Jessica D Faul  38 Linda C Gallo  56 Sami Heikkinen  57 Georg Homuth  39 M Arfan Ikram  29 Carmen R Isasi  58 Jost Bruno Jonas  59   60 Liisa Keltikangas-Järvinen  61 Pirjo Komulainen  37 Aldi T Kraja  62 Jose E Krieger  18 Lenore Launer  63 Lifelines Cohort StudyJianjun Liu  64 Kurt Lohman  65 Annemarie I Luik  29 Ani W Manichaikul  66   67   68 Pedro Marques-Vidal  69 Yuri Milaneschi  70 Stanford E Mwasongwe  71 Jeffrey R O'Connell  72 Kenneth Rice  11 Stephen S Rich  66   67   68 Pamela J Schreiner  73 Lars Schwettmann  74   75 James M Shikany  76 Xiao-Ou Shu  41 Jennifer A Smith  12   38 Harold Snieder  23 Nona Sotoodehnia  77 E Shyong Tai  78 Kent D Taylor  79 Lesley Tinker  80 Michael Y Tsai  81 André G Uitterlinden  82 Cornelia M van Duijn  29   83 Diana van Heemst  24 Melanie Waldenberger  84 Robert B Wallace  85 Hwee-Lin Wee  13 David R Weir  38 Wen-Bin Wei  86 Ko Willems van Dijk  87   88 Gregory Wilson  89 Jie Yao  16 Kristin L Young  15 Xiaoyu Zhang  19 Wei Zhao  12   38 Xiaofeng Zhu  90 Alan B Zonderman  63 Ian J Deary  33 Christian Gieger  84   91   92 Hans Jörgen Grabe  93   94 Timo A Lakka  37   57   95 Terho Lehtimäki  34   35 Albertine J Oldehinkel  96 Martin Preisig  36 Ya-Xing Wang  60 Wei Zheng  41 Michele K Evans  63 Michael Province  4 James Gauderman  97 Vilmundur Gudnason  98   99 Catharina A Hartman  96 Bernardo L Horta  100 Sharon L R Kardia  12 Charles Kooperberg  80 Ching-Ti Liu  19 Dennis O Mook-Kanamori  101   102 Brenda Wjh Penninx  70 Alexandre C Pereira  18 Patricia A Peyser  12 Bruce M Psaty  103 Jerome I Rotter  16 Xueling Sim  13 Kari E North  15 Dabeeru C Rao  49 Laura Bierut  104 Clint L Miller  66   67   68 Alanna C Morrison  2 Charles N Rotimi #  105 Myriam Fornage #  25 Ervin R Fox #  55
Collaborators, Affiliations
Meta-Analysis

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

Amy R Bentley et al. Transl Psychiatry. .

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.

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Conflict of interest statement

Competing interests: The authors declare the following competing interests: BMP serves on the Data and Safety Monitoring Board of a clinical trial funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson; CMvD was sponsored by GlaxoSmithKline; HJG received travel grants and speakers honoraria from Fresenius Medical Care, Neuraxpharm and Janssen Cilag as well as research funding from Fresenius Medical Care; JBJ serves in the Advisory Board Novartis; Patent holder with Biocompatibles UK Ltd. (Franham, Surrey, UK) (Title: Treatment of eye diseases using encapsulated cells encoding and secreting neuroprotective factor and / or anti-angiogenic factor; Patent number: 20120263794), and Europäische Patentanmeldung 16 720 043.5 and Patent application US 2019 0085065 A1 (Agents for use in the therapeutic or prophylactic treatment of myopia or hyperopia). Ethics Approval and Consent to Participate: For all participating cohorts, the appropriate institutional review boards approved research activities and informed consent was obtained from each participant. Further details on all participating cohorts is given in the Supplementary Note.

Figures

Fig. 1
Fig. 1. Study design.
African ancestry (AFR), Asian ancestry (ASN), Brazilian (BRZ), European ancestry (EUR), Hispanic (HISP), cross-population meta-analysis (CPMA)1 Brazilian samples were only available in Stage 1, so a Stage 1+2 meta-analysis of BRZ was not possible. These samples are include in the cross-population Stage 1+2 meta-analysis; 2 As the 2df results joinly measure the variant's main and interaction effects, our main results only include those 2df findings that are also more than 500 kb from known lipids loci.
Fig. 2
Fig. 2. Forest Plots of Key Findings.
Forest plot showing all studies contributing data on an interaction of A. rs11949029 × social support (SOCS) on LDLC using a 1df test of the interaction term (this interaction was also statistically significant using the 2df joint test of the main effect and interaction, shown in Supplementary Figure 4D); and B. rs59808825 × anxiety symptoms (ANXT) on LDLC. Box size represents the precision of the estimate, with larger boxes shown for results with lower variance. Abbreviations: African ancestry (AFR), Brazilian (BRZ), Effect Allele Frequency (EAF), European Ancestry (EUR), Hispanic (HISP), cross-population meta-analysis (CPMA).

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