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Use of proteomics to identify biomarkers associated with chronic kidney disease and long-term outcomes in patients with myocardial infarction

Edfors, R. (author)
Karolinska Institute,Bayer AB,Danderyd Hospital
Lindhagen, Lars (author)
Uppsala University,Uppsala universitet,Uppsala kliniska forskningscentrum (UCR),Uppsala University Hospital
Spaak, J. (author)
Karolinska Institutet,Uppsala University,Karolinska Institute,Danderyd Hospital
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Evans, M. (author)
Karolinska Institutet,Karolinska Institute
Andell, P. (author)
Karolinska Institutet,Karolinska Institute
Baron, Tomasz (author)
Uppsala University,Uppsala universitet,Uppsala kliniska forskningscentrum (UCR)
Mortberg, J. (author)
Karolinska Institutet,Karolinska Institute,Danderyd Hospital
Rezeli, M. (author)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Clinical Protein Science and Imaging,Forskargrupper vid Lunds universitet,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,Lund University Research Groups
Salzinger, B. (author)
Karolinska Institutet,Karolinska Institute,Danderyd Hospital
Lundman, P. (author)
Karolinska Institutet,Karolinska Institute,Danderyd Hospital
Szummer, K. (author)
Karolinska Institutet,Karolinska Institute
Tornvall, P. (author)
Karolinska Institutet,Karolinska Institute,Stockholm South General Hospital
Wallen, H. N. (author)
Karolinska Institutet,Karolinska Institute,Danderyd Hospital
Jacobson, S. H. (author)
Karolinska Inst, Danderyd Hosp, Div Renal Med, Dept Clin Sci, Stockholm, Sweden.
Kahan, T. (author)
Karolinska Institutet,Karolinska Institute,Danderyd Hospital
Marko-Varga, G. (author)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Clinical Protein Science and Imaging,Forskargrupper vid Lunds universitet,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,Lund University Research Groups
Erlinge, D. (author)
Lund University,Lunds universitet,Molekylär kardiologi,Forskargrupper vid Lunds universitet,Molecular Cardiology,Lund University Research Groups
James, Stefan, 1964- (author)
Uppsala universitet,Uppsala kliniska forskningscentrum (UCR)
Lindahl, Bertil, 1957- (author)
Uppsala University,Uppsala universitet,Uppsala kliniska forskningscentrum (UCR)
Jernberg, T. (author)
Karolinska Inst, Danderyd Hosp, Div Cardiovasc Med, Dept Clin Sci, 182 57 Danderyd, Stockholm, Sweden.
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 (creator_code:org_t)
2020-07-08
2020
English.
In: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 288:5, s. 581-592
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Background Patients with chronic kidney disease (CKD) have poor outcomes following myocardial infarction (MI). We performed an untargeted examination of 175 biomarkers to identify those with the strongest association with CKD and to examine the association of those biomarkers with long-term outcomes. Methods A total of 175 different biomarkers from MI patients enrolled in the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry were analysed either by a multiple reaction monitoring mass spectrometry assay or by a multiplex assay (proximity extension assay). Random forests statistical models were used to assess the predictor importance of biomarkers, CKD and outcomes. Results A total of 1098 MI patients with a median estimated glomerular filtration rate of 85 mL min(-1)/1.73 m(2)were followed for a median of 3.2 years. The random forests analyses, without and with adjustment for differences in demography, comorbidities and severity of disease, identified six biomarkers (adrenomedullin, TNF receptor-1, adipocyte fatty acid-binding protein-4, TNF-related apoptosis-inducing ligand receptor 2, growth differentiation factor-15 and TNF receptor-2) to be strongly associated with CKD. All six biomarkers were also amongst the 15 strongest predictors for death, and four of them were amongst the strongest predictors of subsequent MI and heart failure hospitalization. Conclusion In patients with MI, a proteomic approach could identify six biomarkers that best predicted CKD. These biomarkers were also amongst the most important predictors of long-term outcomes. Thus, these biomarkers indicate underlying mechanisms that may contribute to the poor prognosis seen in patients with MI and CKD.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Urologi och njurmedicin (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Urology and Nephrology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kardiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)

Keyword

acute coronary syndrome and myocardial infarction
biomarkers
chronic kidney disease
proteomics
renal dysfunction
renal failure
acute coronary syndrome and myocardial infarction
biomarkers
chronic kidney disease
proteomics
renal dysfunction
renal failure

Publication and Content Type

ref (subject category)
art (subject category)

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