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Cardiovascular disease is a major cause of morbidity and mortality, with increasing prevalence worldwide.

Identification of risk markers may enable improved prevention by targeting high-risk individuals, earlier disease diagnosis and treatment, as well as stratification of disease subtypes with different treatment options, thereby minimizing side effects while increasing success rates.

The overall aim of this thesis was to investigate associations between proteomic and metabolomic biomarkers, and the development of heart failure and ischemic stroke. Specific objectives were to examine potential causal pathways, and the added value in risk prediction of the identified risk markers.

In Studies I–II, we performed proximity extension assay based proteomic profiling of ≥80 circulating proteins in the Swedish cohorts Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS n=901, median age 70), and the Uppsala Longitudinal Study of Adult Men (ULSAM, n=685, median age 77). In Study I, we identified nine proteins involved in apoptosis, inflammation, matrix remodeling, and fibrinolysis associated with incident heart failure, including growth differentiation factor-15 (GDF-15). In Study II, we identified several proteins associated with incident ischemic stroke, including GDF-15. Both studies revealed potential to improve disease risk prediction by using proteomic data.

In Study III, we performed mass spectrometry-based metabolomic profiling in plasma or serum samples from PIVUS, ULSAM, and TwinGene (total n=3,924). The metabolites urobilin and sphingomyelin (30:1) were associated with incident heart failure.

In Study IV, we followed up on the results of Studies I–II, performing Mendelian randomization analyses (a framework for causal analysis using genetic variants) in 1,053,527 individuals, with 88,448 coronary artery disease cases, 70,305 ischemic stroke cases, and 1,420 heart failure cases. This study supports a causal role of genetically elevated GDF-15 levels in heart failure development, but not in coronary artery disease or ischemic stroke.

In conclusion, we identified multiple biomarkers associated with incident heart failure and ischemic stroke, potentially involved in early disease development. We also saw potential to improve disease risk prediction for incident heart failure and ischemic stroke using proteomics data.

Our findings encourage further large-scale proteomic, metabolomic, and genetic studies to give new insights into heart failure and stroke pathogenesis.

Aims: We aimed to investigate whether metabolomic profiling of blood can lead to novel insights into heart failure pathogenesis or improved risk prediction.

Methods: Mass spectrometry-based metabolomic profiling was performed in plasma or serum samples from three community-based cohorts without heart failure at baseline (total n=3,924; 341 incident heart failure events, median follow-up ranging from 4.6 to 13.9 years). Cox proportional hazards models were applied to assess the association of each of the 206 identified metabolites with incident heart failure in the discovery cohorts Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS, n=920) and Uppsala Longitudinal Study of Adult Men (ULSAM, n=1,121). Replication was undertaken in the independent cohort TwinGene (n=1,797). We also assessed whether metabolites could improve the prediction of heart failure beyond established risk factors (age, sex, body mass index, low-density lipoprotein- and high-density lipoprotein-cholesterol, triglycerides, lipid medication, diabetes, systolic and diastolic blood pressure, blood pressure medication, glomerular filtration rate, smoking status, and myocardial infarction prior to or during follow-up).

Results: Higher circulating urobilin and lower sphingomyelin (30:1) were associated with incident heart failure in age- and sex-adjusted models in the discovery and replication sample. The hazard ratio (HR) for urobilin in the replication cohort was estimated to 1.29 per SD unit, 95% confidence interval (CI) 1.03-1.63) and for sphingomyelin (30:1) to 0.72 (95% CI 0.58-0.89). Results remained similar after further adjustment for established heart failure risk factors in meta-analyses of all three cohorts. Urobilin concentrations were inversely associated with left ventricular ejection fraction at baseline in the PIVUS cohort (β= -0.70 (95% CI -1.03-(-0.38)). No improvement in risk prediction was observed when adding the two top metabolites (C-index 0.787 (95% CI 0.752-0.823)) or nine Lasso-selected metabolites (0.790 (95% CI 0.754-0.826)) to a modified Atherosclerosis Risk in Communities (ARIC) heart failure risk score model (0.780 (95% CI 0.745-0.816)).

Conclusions: Our metabolomics study identified associations of circulating levels of the heme breakdown product urobilin, and sphingomyelin (30:1), a cell membrane component involved in signal transduction and apoptosis, with incident heart failure.

Aims

To identify novel risk markers for incident heart failure using proteomic profiling of 80 proteins previously associated with cardiovascular pathology.

Methods and results

Proteomic profiling (proximity extension assay) was performed in two community‐based prospective cohorts of elderly individuals without heart failure at baseline: the Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS, n = 901, median age 70.2 (interquartile range 70.0–70.3) years, 80 events]; and the Uppsala Longitudinal Study of Adult Men [ULSAM, n = 685, median age 77.8 (interquartile range 76.9–78.1) years, 90 events]. Twenty‐nine proteins were associated with incident heart failure in the discovery cohort PIVUS after adjustment for age and sex, and correction for multiple testing. Eighteen associations replicated in ULSAM. In pooled analysis of both cohorts, higher levels of nine proteins were associated with incident heart failure after adjustment for established risk factors: growth differentiation factor 15 (GDF‐15), T‐cell immunoglobulin and mucin domain 1 (TIM‐1), tumour necrosis factor‐related apoptosis‐inducing ligand receptor 2 (TRAIL‐R2), spondin‐1 (SPON1), matrix metalloproteinase‐12 (MMP‐12), follistatin (FS), urokinase‐type plasminogen activator surface receptor (U‐PAR), osteoprotegerin (OPG), and suppression of tumorigenicity 2 (ST2). Of these, GDF‐15, U‐PAR, MMP‐12, TRAIL‐R2, SPON1 and FS were associated with worsened echocardiographic left ventricular systolic function at baseline, while only TIM‐1 was positively associated with worsened diastolic function (P < 0.02 for all).

Conclusion

Proteomic profiling identified several novel associations between proteins involved in apoptosis, inflammation, matrix remodelling, and fibrinolysis with incident heart failure in elderly individuals. Our results encourage additional studies investigating the underlying mechanisms and the clinical utility of our findings.

Background Apart from several established clinical risk factors for atrial fibrillation (AF), a number of biomarkers have also been identified as potential risk factors for AF. None of these have so far been adopted in clinical practice. Objective To use a novel custom-made proteomics chip to discover new prognostic biomarkers for AF risk. Methods In two independent community-based cohorts (Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study (978 participants without AF, mean age 70.1 years, 50% women, median followup 10.0 years) and Uppsala Longitudinal Study of Adult Men (ULSAM) (n= 725, mean age 77.5 years, median follow-up 7.9 years)), ninety-two plasma proteins were assessed at baseline by a proximity extension assay (PEA) chip. Of those, 85 proteins showed a call rate > 70% in both cohorts. Results Thirteen proteins were related to incident AF in PIVUS (148 events) using a false discovery rate of 5%. Of those, five were replicated in ULSAM at nominal multivariable p value (123 events, N-terminal pro-B-type natriuretic peptide (NT-pro-BNP), fibroblast growth factor 23 (FGF-23), fatty acid-binding protein 4 (FABP4), growth differentiation factor 15 (GDF-15) and interleukin-6 (IL-6)). Of those, NT-pro-BNP and FGF-23 were also associated with AF after adjusting for established AF risk factors. In a prespecified secondary analysis pooling the two data sets, T-cell immunoglobulin and mucin domain 1 (TIM-1) and adrenomedullin (AM) were also significantly related to incident AF in addition to the aforementioned five proteins (Bonferroni-adjustment). The addition of NT-proBNP to a model with established risk factors increased the C-statistic from 0.605 to 0.676 (p< 0.0001). Conclusions Using a novel proteomics approach, we confirmed the previously reported association between NT-pro-BNP, FGF-23, GDF-15 and incident AF, and also discovered four proteins (FABP4, IL-6, TIM-1 and AM) that could be of importance in the development of AF.

BACKGROUND: The underlying mechanisms for the development of albuminuria and the increased cardiovascular risk in patients with elevated albuminuria levels are incompletely understood. We therefore investigated the associations between 80 cardiovascular proteins and the urinary albumin to creatinine ratio (ACR).

METHODS: We used a discovery/replication approach in two independent community-based cohorts of elderly patients: the Uppsala Longitudinal Study of Adult Men (n = 662; mean age 78 years) and the Prospective Investigation of the Vasculature in Uppsala Seniors (n = 757; mean age 75 years; 51% women). A proteomic chip with a panel of 80 plasma proteins associated with different aspects of cardiovascular disease was analysed. In the discovery cohort, we used a false discovery rate of 5% to take into account the multiple statistical testing. Nominal p values were used in the replication.

RESULTS: Higher levels of T-cell immunoglobulin mucin-1, placenta growth factor, growth/differentiation factor-15, urokinase plasminogen activator surface receptor and kallikrein-11 were robustly associated with a higher ACR in both cohorts in multivariable linear regression models adjusted for sex, established cardiovascular risk factors, antihypertensive treatment, prevalent cardiovascular disease and glomerular filtration rate (p < 0.02 for all). All associations were also significant in separate analyses of patients without diabetes.

CONCLUSIONS: We discovered and replicated associations between ACR and five cardiovascular proteins involved in tubular injury, atherosclerosis, endothelial function, heart failure, inflammation, glomerulosclerosis and podocyte injury. Our findings put forward multiplex proteomics as a promising approach to explore novel aspects of the complex detrimental interplay between kidney function and the cardiovascular system.

BACKGROUND AND OBJECTIVES: Using a discovery/replication approach, we investigated associations between a multiplex panel of 80 circulating proteins associated with cardiovascular pathology or inflammation, and eGFR decline per year and CKD incidence.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We used two cohorts, the Prospective Investigation of the Vasculature in Uppsala Seniors Study (PIVUS; n=687, mean age of 70 years, 51% women) and the Uppsala Longitudinal Study of Adult Men (ULSAM; n=360 men, mean age of 78 years), with 5-year follow-up data on eGFR. There were 231 and 206 incident cases of CKD during follow-up in the PIVUS and ULSAM studies, respectively. Proteomic profiling of 80 proteins was assessed by a multiplex assay (proximity extension assay). The assay uses two antibodies for each protein and a PCR step to achieve a high-specific binding and the possibility to measure multiple proteins in parallel, but gives no absolute concentrations.

RESULTS: In the discovery cohort from the PIVUS Study, 28 plasma proteins were significantly associated with eGFR decline per year, taking into account the multiple testing. Twenty of these proteins were significantly associated with eGFR decline per year in the replication cohort from the ULSAM Study after adjustment for age, sex, cardiovascular risk factors, medications, and urinary albumin-to-creatinine ratio (in order of significance: TNF-related apoptosis-inducing ligand receptor 2*, CD40L receptor, TNF receptor 1*, placenta growth factor*, thrombomodulin*, urokinase plasminogen activator surface receptor*, growth/differentiation factor 15*, macrophage colony-stimulating factor 1, fatty acid-binding protein*, cathepsin D, resistin, kallikrein 11*, C-C motif chemokine 3, proteinase-activated receptor 1*, cathepsin L, chitinase 3-like protein 1, TNF receptor 2*, fibroblast growth factor 23*, monocyte chemotactic protein 1, and kallikrein 6). Moreover, 11 of the proteins predicted CKD incidence (marked with * above). No protein consistently predicted eGFR decline per year independently of baseline eGFR in both cohorts.

CONCLUSIONS: Several circulating proteins involved in phosphate homeostasis, inflammation, apoptosis, extracellular matrix remodeling, angiogenesis, and endothelial dysfunction were associated with worsening kidney function. Multiplex proteomics appears to be a promising way of discovering novel aspects of kidney disease pathology.

Non-targeted metabolomic profiling is used to simultaneously assess a large part of the metabolome in a biological sample. Here, we describe both the analytical and computational methods used to analyze a large UPLC–Q-TOF MS-based metabolomic profiling effort using plasma and serum samples from participants in three Swedish population-based studies of middle-aged and older human subjects: TwinGene, ULSAM and PIVUS. At present, more than 200 metabolites have been manually annotated in more than 3600 participants using an in-house library of standards and publically available spectral databases. Data available at the metabolights repository include individual raw unprocessed data, processed data, basic demographic variables and spectra of annotated metabolites. Additional phenotypical and genetic data is available upon request to cohort steering committees. These studies represent a unique resource to explore and evaluate how metabolic variability across individuals affects human diseases.

Background and Purpose-Emerging technologies have made it possible to simultaneously evaluate a large number of circulating proteins as potential new stroke risk markers. Methods-We explored associations between 85 cardiovascular proteins, assessed by a proteomics chip, and incident ischemic stroke in 2 independent cohorts of elderly (Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS]: n=977; 50% women, mean age=70.1 years, 71 fatal/nonfatal ischemic stroke events during 10.0 years; and Uppsala Longitudinal Study in Adult Men [ULSAM]: n=720, mean age=77.5 years, 75 ischemic stroke events during 9.5 years). The proteomics chip uses 2 antibodies for each protein and a polymerase chain reaction step to achieve a high-specific binding and the possibility to measure multiple proteins in parallel, but gives no absolute concentrations. Results-In PIVUS, 16 proteins were related to incident ischemic stroke using a false discovery rate of 5%. Of these, N-terminal pro-B-type natriuretic peptide (P=0.0032), adrenomedullin (P=0.018), and eosinophil cationic protein (P=0.0071) were replicated in ULSAM after adjustment for established stroke risk factors. In predefined secondary meta-analyses of individual data, interleukin-27 subunit , growth/differentiation factor 15, urokinase plasminogen activator surface receptor, tumor necrosis factor receptor superfamily member 6, macrophage colony-stimulating factor 1, and matrix metalloproteinase-7 were also potential risk markers for ischemic stroke after adjustment for multiple comparisons (P<0.0006). The addition of N-terminal pro-B-type natriuretic peptide, adrenomedullin, and eosinophil cationic protein to a model with established risk factors increased the C-statistic from 0.629 to 0.689 (P=0.001). Conclusions-Our data suggest that large-scale proteomics analysis is a promising way of discovering novel biomarkers that could substantially improve the prediction of ischemic stroke.