IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0232735.html
   My bibliography  Save this article

Genetic risk scores for coronary artery disease and its traditional risk factors: Their role in the progression of coronary artery calcification—Results of the Heinz Nixdorf Recall study

Author

Listed:
  • Sonali Pechlivanis
  • Susanne Moebus
  • Nils Lehmann
  • Raimund Erbel
  • Amir A Mahabadi
  • Per Hoffmann
  • Karl-Heinz Jöckel
  • Markus M Nöthen
  • Hagen S Bachmann
  • on behalf of the Heinz Nixdorf Recall Study Investigative Group

Abstract

Background: Atherosclerosis is the primary cause of coronary artery disease (CAD). Several observational studies have examined the association of traditional CAD risk factors with the progression of coronary artery calcification (CAC). In our study we investigated the effect of 11 different genetic risk scores associated with CAD and CAD risk factors on the progression of CAC. Methods and results: We included 3097 participants from the Heinz Nixdorf Recall study who had available CAC measurements at baseline (CACb) and at the 5-year follow-up (CAC5y). A weighted genetic risk score for CAD and each of the CAD-associated risk factors was constructed. Multiple regression analyses were applied to i) the difference between the observed log(CAC5y+1) (log(obs)) and expected log(CAC5y+1) (log(exp)) at the 5-year follow-up following the individual’s log(CACb+1) percentile for the time between scans (log(obs)–log(exp)) and ii) the 5-year CAC progression, defined as 5*(log(CAC5y+1)–log(CACb+1))/time between the scans, adjusted for age, sex, and log(CACb+1) as well as for risk factors. The median percent deviation from the expected (CAC5y+1) and the 5-year progression of (CAC+1) in our study were 0 (first quartile: Q1; third quartile: Q3: -0.32; 0.48) and 45.4% (0%; 171.0%) respectively. In the age-, sex- and log(CACb+1)-adjusted model, the per-standard deviation (SD) increase in CAD genetic risk score was associated with the percent deviation from the expected (CAC5y+1) (9.7% (95% confidence interval: 5.2%; 14.5%), p = 1.6x10-5) and the 5-year progression of CAC (7.1% (3.0%; 11.4%), p = 0.0005). The CAD genetic risk score explains an additional 0.6% of the observed phenotypic variance for “log(obs)–log(exp)” and 0.4% for 5-year progression of CAC. Additionally, the per-SD increase in the CAC genetic risk score was associated with the percent deviation from the expected (CAC5y+1) (6.2% (1.9%; 10.8%, p = 0.005)) explaining an additional 0.2% of the observed phenotypic variance. However, the per-SD increase in the CAC genetic risk score was not associated with the 5-year progression of CAC (4.4% (0.4%; 8.5%), p = 0.03) after multiple testing. Adjusting for risk factors did not change the results. None of the other genetic risk scores showed an association with the percent deviation from the expected (CAC5y+1) or with the 5-year progression of CAC. Conclusions: The association of the CAC genetic risk score and the CAD genetic risk score provides evidence that genetic determinants for CAC and CAD influence the progression of CAC.

Suggested Citation

  • Sonali Pechlivanis & Susanne Moebus & Nils Lehmann & Raimund Erbel & Amir A Mahabadi & Per Hoffmann & Karl-Heinz Jöckel & Markus M Nöthen & Hagen S Bachmann & on behalf of the Heinz Nixdorf Recall Stu, 2020. "Genetic risk scores for coronary artery disease and its traditional risk factors: Their role in the progression of coronary artery calcification—Results of the Heinz Nixdorf Recall study," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.
    • Handle: RePEc:plo:pone00:0232735
    DOI: 10.1371/journal.pone.0232735
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0232735
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0232735&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0232735?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mirjam Frank & Nico Dragano & Marina Arendt & Andreas J Forstner & Markus M Nöthen & Susanne Moebus & Raimund Erbel & Karl-Heinz Jöckel & Börge Schmidt, 2019. "A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-14, August.
    2. Tanya M. Teslovich & Kiran Musunuru & Albert V. Smith & Andrew C. Edmondson & Ioannis M. Stylianou & Masahiro Koseki & James P. Pirruccello & Samuli Ripatti & Daniel I. Chasman & Cristen J. Willer & C, 2010. "Biological, clinical and population relevance of 95 loci for blood lipids," Nature, Nature, vol. 466(7307), pages 707-713, August.
    3. Adam E. Locke & Bratati Kahali & Sonja I. Berndt & Anne E. Justice & Tune H. Pers & Felix R. Day & Corey Powell & Sailaja Vedantam & Martin L. Buchkovich & Jian Yang & Damien C. Croteau-Chonka & Tonu , 2015. "Genetic studies of body mass index yield new insights for obesity biology," Nature, Nature, vol. 518(7538), pages 197-206, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jordi Manuello & Joosung Min & Paul McCarthy & Fidel Alfaro-Almagro & Soojin Lee & Stephen Smith & Lloyd T. Elliott & Anderson M. Winkler & Gwenaëlle Douaud, 2024. "The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Yang, Chiao-Yu & Lei, Lihua & Ho, Nhat & Fithian, William, 2022. "BONuS: Multiple Multivariate Testing with a Data-Adaptive Test Statistic," Research Papers 4031, Stanford University, Graduate School of Business.
    3. Jacob Joseph & Chang Liu & Qin Hui & Krishna Aragam & Zeyuan Wang & Brian Charest & Jennifer E. Huffman & Jacob M. Keaton & Todd L. Edwards & Serkalem Demissie & Luc Djousse & Juan P. Casas & J. Micha, 2022. "Genetic architecture of heart failure with preserved versus reduced ejection fraction," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Vikesh Amin & Jere R. Behrman & Jason M. Fletcher & Carlos A. Flores & Alfonso Flores‐Lagunes & Hans‐Peter Kohler, 2021. "Genetic risks, adolescent health, and schooling attainment," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2905-2920, November.
    5. Lili Liu & Atlas Khan & Elena Sanchez-Rodriguez & Francesca Zanoni & Yifu Li & Nicholas Steers & Olivia Balderes & Junying Zhang & Priya Krithivasan & Robert A. LeDesma & Clara Fischman & Scott J. Heb, 2022. "Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    6. Shaan Khurshid & Julieta Lazarte & James P. Pirruccello & Lu-Chen Weng & Seung Hoan Choi & Amelia W. Hall & Xin Wang & Samuel F. Friedman & Victor Nauffal & Kiran J. Biddinger & Krishna G. Aragam & Pu, 2023. "Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Dixon, Padraig & Hollingworth, William & Harrison, Sean & Davies, Neil M. & Davey Smith, George, 2020. "Mendelian Randomization analysis of the causal effect of adiposity on hospital costs," Journal of Health Economics, Elsevier, vol. 70(C).
    8. Cecilia Pessoa Rodrigues & Aindrila Chatterjee & Meike Wiese & Thomas Stehle & Witold Szymanski & Maria Shvedunova & Asifa Akhtar, 2021. "Histone H4 lysine 16 acetylation controls central carbon metabolism and diet-induced obesity in mice," Nature Communications, Nature, vol. 12(1), pages 1-21, December.
    9. Adrienne Tin & Pascal Schlosser & Pamela R. Matias-Garcia & Chris H. L. Thio & Roby Joehanes & Hongbo Liu & Zhi Yu & Antoine Weihs & Anselm Hoppmann & Franziska Grundner-Culemann & Josine L. Min & Vic, 2021. "Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
    10. Yi Huang & Anyongqi Wang & Wenjiang Zhou & Baoguo Li & Linshan Zhang & Agata M. Rudolf & Zengguang Jin & Catherine Hambly & Guanlin Wang & John R. Speakman, 2024. "Maternal dietary fat during lactation shapes single nucleus transcriptomic profile of postnatal offspring hypothalamus in a sexually dimorphic manner in mice," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    11. Sang Hong Lee & Naomi R Wray, 2013. "Novel Genetic Analysis for Case-Control Genome-Wide Association Studies: Quantification of Power and Genomic Prediction Accuracy," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-7, August.
    12. Wei Zhao & Erin B. Ware & Zihuai He & Sharon L. R. Kardia & Jessica D. Faul & Jennifer A. Smith, 2017. "Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting," IJERPH, MDPI, vol. 14(10), pages 1-17, September.
    13. Jie Huang & Jennifer E. Huffman & Yunfeng Huang & Ítalo Valle & Themistocles L. Assimes & Sridharan Raghavan & Benjamin F. Voight & Chang Liu & Albert-László Barabási & Rose D. L. Huang & Qin Hui & Xu, 2022. "Genomics and phenomics of body mass index reveals a complex disease network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    14. Kristina M. Garske & Asha Kar & Caroline Comenho & Brunilda Balliu & David Z. Pan & Yash V. Bhagat & Gregory Rosenberg & Amogha Koka & Sankha Subhra Das & Zong Miao & Janet S. Sinsheimer & Jaakko Kapr, 2023. "Increased body mass index is linked to systemic inflammation through altered chromatin co-accessibility in human preadipocytes," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    15. Sheng Wang & Hyunseung Kang, 2022. "Weak‐instrument robust tests in two‐sample summary‐data Mendelian randomization," Biometrics, The International Biometric Society, vol. 78(4), pages 1699-1713, December.
    16. Samuel Baker & Pietro Biroli & Hans van Kippersluis & Stephanie von Hinke, 2022. "Beyond Barker: Infant Mortality at Birth and Ischaemic Heart Disease in Older Age," Bristol Economics Discussion Papers 22/765, School of Economics, University of Bristol, UK.
    17. Parsa Akbari & Olukayode A. Sosina & Jonas Bovijn & Karl Landheer & Jonas B. Nielsen & Minhee Kim & Senem Aykul & Tanima De & Mary E. Haas & George Hindy & Nan Lin & Ian R. Dinsmore & Jonathan Z. Luo , 2022. "Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    18. Viinikainen, Jutta & Bryson, Alex & Böckerman, Petri & Kari, Jaana T. & Lehtimäki, Terho & Raitakari, Olli & Viikari, Jorma & Pehkonen, Jaakko, 2022. "Does better education mitigate risky health behavior? A mendelian randomization study," Economics & Human Biology, Elsevier, vol. 46(C).
    19. Sarah Meulebrouck & Judith Merrheim & Gurvan Queniat & Cyril Bourouh & Mehdi Derhourhi & Mathilde Boissel & Xiaoyan Yi & Alaa Badreddine & Raphaël Boutry & Audrey Leloire & Bénédicte Toussaint & Souhi, 2024. "Functional genetics reveals the contribution of delta opioid receptor to type 2 diabetes and beta-cell function," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    20. Groero, Jaroslav, 2024. "The role of gene–environment interaction in the formation of risk attitudes," Economics & Human Biology, Elsevier, vol. 55(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0232735. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.