Screening of biomarkers for prediction of multisite artery disease in patients with recent myocardial infarction.


Journal

Scandinavian journal of clinical and laboratory investigation
ISSN: 1502-7686
Titre abrégé: Scand J Clin Lab Invest
Pays: England
ID NLM: 0404375

Informations de publication

Date de publication:
Sep 2021
Historique:
pubmed: 5 8 2021
medline: 8 3 2022
entrez: 4 8 2021
Statut: ppublish

Résumé

A few studies have examined biomarkers in patients with myocardial infarction (MI) and peripheral artery disease (PAD), i.e. multisite artery disease (MSAD). The aim of the study was firstly, to associate biomarkers with the occurrence of PAD/MSAD and secondly, if those can, in addition to clinical characteristics, identify MI patients with MSAD.In two prospectively observational studies including unselected patients with recent MI, PAD was defined as an abnormal ankle-brachial index (ABI) score (<0.9 or >1.4). The proximity extension assay (PEA) technique was used, simultaneously analyzing 92 biomarkers with association to cardiovascular disease. Biomarkers were tested for univariate associations with PAD. Random forest was used to identify biomarkers with a higher association to PAD. The additional discriminatory accuracy of adding biomarkers to clinical characteristics was analyzed by the c-statistics. Nine biomarkers were identified as significantly associated with MSAD/PAD in the primary patient cohort, analyzed early after the MI. In the prediction analysis, six biomarkers were identified associated with PAD. Three of these; Tumor necrosis factor receptor (TNFR-1), Tumor necrosis factor receptor 2 (TNFR-2) and Growth Differentiation Factor 15 (GDF-15) improved c-statistics when added to clinical characteristics from 0.683 (95% CI 0.610-0.756) to 0.715 (95% CI 0.645-0.784) in the primary patient cohort with a similar result, 0.729 (95% CI 0.687-0.770) to 0.752 (95% CI 0.771-0.792) in the secondary patient cohort. Biomarkers associated with inflammatory pathways are associated with MSAD in MI patients. Three biomarkers of 92; TNFR-1, TNFR-2 and GDF-15, in this exploratory added information in the prediction of MSAD and emphasis the importance of further studies.

Identifiants

pubmed: 34346268
doi: 10.1080/00365513.2021.1921839
doi:

Substances chimiques

Biomarkers 0
GDF15 protein, human 0
Growth Differentiation Factor 15 0
Receptors, Tumor Necrosis Factor, Type I 0
Receptors, Tumor Necrosis Factor, Type II 0
TNFRSF1A protein, human 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

353-360

Auteurs

Birgitta Jönelid (B)

Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.

Christina Christersson (C)

Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.

Pär Hedberg (P)

Department of Clinical Physiology, Uppsala University, Västmanland County Hospital, Västerås, Sweden.

Jerzy Leppert (J)

Centre for Clinical Research, Uppsala University, Västmanland County Hospital, Västerås, Sweden.

Bertil Lindahl (B)

Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.
Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.

Lars Lindhagen (L)

Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.

Jonas Oldgren (J)

Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.
Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.

Agneta Siegbahn (A)

Department of Medical Sciences, Clinical Chemistry, Uppsala, Sweden.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH