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Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases

Kiiskinen, Tuomo ; Helkkula, Pyry ; Krebs, Kristi ; Karjalainen, Juha ; Saarentaus, Elmo ; Mars, Nina ; Lehisto, Arto ; Zhou, Wei ; Cordioli, Mattia and Jukarainen, Sakari , et al. (2023) In Nature Medicine 29(1). p.209-218
Abstract

Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10–9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment... (More)

Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10–9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.

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Contribution to journal
publication status
published
subject
in
Nature Medicine
volume
29
issue
1
pages
10 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85146470442
  • pmid:36653479
ISSN
1078-8956
DOI
10.1038/s41591-022-02122-5
language
English
LU publication?
yes
id
e8c2f5a4-2725-4c7f-9e89-ea8af981811d
date added to LUP
2024-01-12 11:45:29
date last changed
2024-04-27 07:09:08
@article{e8c2f5a4-2725-4c7f-9e89-ea8af981811d,
  abstract     = {{<p>Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P &lt; 5 × 10<sup>–9</sup>) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.</p>}},
  author       = {{Kiiskinen, Tuomo and Helkkula, Pyry and Krebs, Kristi and Karjalainen, Juha and Saarentaus, Elmo and Mars, Nina and Lehisto, Arto and Zhou, Wei and Cordioli, Mattia and Jukarainen, Sakari and Rämö, Joel T. and Mehtonen, Juha and Veerapen, Kumar and Räsänen, Markus and Ruotsalainen, Sanni and Maasha, Mutaamba and Niiranen, Teemu and Tuomi, Tiinamaija and Salomaa, Veikko and Kurki, Mitja and Pirinen, Matti and Palotie, Aarno and Daly, Mark and Ganna, Andrea and Havulinna, Aki S. and Milani, Lili and Ripatti, Samuli}},
  issn         = {{1078-8956}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{209--218}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Medicine}},
  title        = {{Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases}},
  url          = {{http://dx.doi.org/10.1038/s41591-022-02122-5}},
  doi          = {{10.1038/s41591-022-02122-5}},
  volume       = {{29}},
  year         = {{2023}},
}