The Association of 9 Amino Acids With Cardiovascular Events in Finnish Men in a 12-Year Follow-up Study.

BACKGROUND AND AIMS: To investigate the significance of 9 amino acids as risk factors for incident cardiovascular disease events in 9584 Finnish men. MATERIALS AND METHODS: A total of 9584 men (age 57.4 ± 7.0 years, body mass index 27.2 ± 4.2 kg/m2) from the Metabolic Syndrome in Men study without cardiovascular disease and type 1 diabetes at baseline were included in this study. A total of 662 coronary artery disease (CAD) events, 394 ischemic stroke events, and 966 cardiovascular disease (CVD; CAD and stroke combined) events were recorded in a 12.3-year follow-up. Amino acids were measured using nuclear magnetic resonance platform. RESULTS: In Cox regression analysis, phenylalanine and tyrosine were significantly associated with increased risk of CAD and CVD events, and phenylalanine with increased risk of ischemic stroke after the adjustment for confounding factors. Glutamine was significantly associated with decreased risk of stroke and CVD events and nominally with CAD events. Alanine was nominally associated with CAD events. CONCLUSION: We identified alanine as a new amino acid associated with increased risk of CAD and glutamine as a new amino acid associated with decreased risk of ischemic stroke. We also confirmed that phenylalanine and tyrosine were associated with CAD, ischemic stroke, and CVD events.

Novel biomarkers associated with incident heart failure in 10 106 Finnish men.

AIMS: There are only a few studies on novel biomarkers for incident heart failure (HF). We investigated the association of multiple circulating biomarkers with incident HF in a large prospective population-based study. METHODS AND RESULTS: Conventional risk factors and inflammatory biomarkers were measured, and systemic metabolic measures determined by a high-throughput serum nuclear magnetic resonance platform in a population-based Metabolic Syndrome in Men study including 10 106 Finnish men without HF at baseline. During an 8.8 year follow-up, 172 (1.7%) participants developed HF. Adiponectin, high-sensitivity C-reactive protein (hs-CRP), glycoprotein acetyls, alanine, phenylalanine, glycerol, and pyruvate were associated with incident HF in unadjusted Cox regression analyses, in addition to age, systolic blood pressure, body mass index (BMI), waist circumference, fasting plasma glucose and insulin, haemoglobin A1c (HbA1c), and urinary albumin excretion rate (UAER). After adjustment for age, BMI, diabetes, and statin medication, only adiponectin [hazard ratio (HR) 1.18 (1.10-1.26, P = 4.1E-08)], pyruvate [HR 1.38 (1.28-1.50, P = 8.2E-05)], and UAER [HR 1.15 (1.11-1.18, P = 7.8E-06)] remained statistically significant. In principal component analysis of biomarkers associated with HF in univariate Cox regression analysis, we identified six components, explaining 61.7% of total variance. Four principal components, one with significant loadings on waist, BMI, fasting plasma insulin, interleukin 1 receptor antagonist, and hs-CRP; another on pyruvate, glycoprotein acetyls, alanine, glycerol and HbA1c; third on age and glomerular filtration rate; and fourth on systolic blood pressure, UAER, and adiponectin, significantly associated with incident HF. CONCLUSIONS: Several novel metabolic and inflammatory biomarkers were associated with incident HF, suggesting early activation of respective pathways in the pathogenesis of HF.

Systems Genetics Approach to Biomarker Discovery: GPNMB and Heart Failure in Mice and Humans.

We describe a simple bioinformatics method for biomarker discovery that is based on the analysis of global transcript levels in a population of inbred mouse strains showing variation for disease-related traits. This method has advantages such as controlled environment and accessibility to heart and plasma tissue in the preclinical selection stage. We illustrate the approach by identifying candidate heart failure (HF) biomarkers by overlaying mouse transcriptome and clinical traits from 91 Hybrid Mouse Diversity Panel (HMDP) inbred strains and human HF transcriptome from the Myocardial Applied Genomics Network (MAGNet) consortium. We found that some of the top differentially expressed genes correlated with known human HF biomarkers, such as galectin-3 and tissue inhibitor of metalloproteinase 1. Using ELISA assays, we investigated one novel candidate, Glycoprotein NMB, in a mouse model of chronic ß-adrenergic stimulation by isoproterenol (ISO) induced HF. We observed significantly lower GPNMB plasma levels in the ISO model compared to the control group (p-value = 0.007). In addition, we assessed GPNMB plasma levels among 389 HF cases and controls from the METabolic Syndrome In Men (METSIM) study. Lower levels of GPNMB were also observed in patients with HF from the METSIM study compared to non-HF controls (p-value < 0.0001). In summary, we have identified several candidate biomarkers for HF using the cardiac transcriptome data in a population of mice that may be directly relevant and applicable to human populations.

Short Adult Stature Predicts Impaired ß-Cell Function, Insulin Resistance, Glycemia, and Type 2 Diabetes in Finnish Men.

CONTEXT: Recent studies have highlighted the role of height in complex diseases, but conflicting information has been reported on height as a predictor of changes in glycemia and risk of type 2 diabetes. OBJECTIVE: Our aim was to investigate the association of height with insulin sensitivity, insulin secretion, glycemia, type 2 diabetes, and cardiovascular disease (CVD) in a large prospective population-based study. DESIGN: The study included 8746 Finnish men (mean ± standard deviation, age 57.2 ± 7.1 years, body mass index, 26.8 ± 3.8 kg/m2) selected from a population-based Metabolic Syndrome in Men (METSIM) study. SETTING: The study was conducted at Kuopio University Hospital and University of Eastern Finland. PARTICIPANTS: The participants were nondiabetic at the recruitment, and 5401 subjects have participated in the follow-up study. During the follow-up, a total of 693 subjects converted to type 2 diabetes and 351 were diagnosed with a new CVD event during the follow-up. MAIN OUTCOME MEASURES: The main outcome measures were incidence of type 2 diabetes and CVD. RESULTS: Height measured at baseline was significantly associated with lower levels of 2-hour glucose in an oral glucose tolerance test, an increase in insulin secretion, a decrease in the risk of type 2 diabetes [hazard ratio (HR) = 0.83(confidence interval [CI] 0.77 to 0.90)] and CVD [HR = 0.75(CI 0.67 to 0.83)] during the follow-up. CONCLUSION: Short stature is associated with unfavorable changes in glucose metabolism and predicts an increase in the risk of type 2 diabetes and cardiovascular events.

Differential Associations of Inflammatory Markers With Insulin Sensitivity and Secretion: The Prospective METSIM Study.

Context: Low-grade inflammation is involved in the development of type 2 diabetes and cardiovascular disease (CVD); however, prospective studies evaluating inflammatory markers as predictors of changes in insulin secretion and insulin sensitivity are lacking. Objective: We investigated the associations of glycoprotein acetyls (GlycA), interleukin-1 receptor antagonist (IL-1RA), and high-sensitivity C-reactive protein (hs-CRP) with insulin secretion, insulin sensitivity, incident type 2 diabetes, hypertension, CVD events, and total mortality in the prospective Metabolic Syndrome in Men (METSIM) study. Design: A prospective study. Participants: The cross-sectional METSIM study included 8749 nondiabetic Finnish men aged 45 to 73 years, who had been randomly selected from the population register of Kuopio, Finland. A total of 5401 men participated in the 6.8-year follow-up study. Main Outcome Measures: Changes in insulin secretion, insulin sensitivity, and cardiometabolic traits during the follow-up period and the incidence of type 2 diabetes, hypertension, CVD events, and total mortality. Results: During the follow-up period, GlycA was associated with impaired insulin secretion, hyperglycemia, incident type 2 diabetes (hazard ratio, 1.37; 95% confidence interval, 1.29 to 1.46) and CVD (hazard ratio, 1.21; 95% confidence interval, 1.12 to 1.32). IL-1RA and hs-CRP were associated with adverse changes in insulin sensitivity and obesity-related traits and with total mortality (hazard ratio, 1.13; 95% confidence interval, 1.07 to 1.20; and hazard ratio, 1.08; 95% confidence interval, 1.04 to 1.11, respectively). Conclusions: Inflammatory markers differentially predicted changes in insulin secretion and insulin sensitivity. GlycA predicted impaired insulin secretion, and IL-1RA and hs-CRP predicted changes in insulin sensitivity. Combining the three markers improved the prediction of disease outcomes, suggesting that they capture different aspects of low-grade inflammation.

Finnish Diabetes Risk Score Is Associated with Impaired Insulin Secretion and Insulin Sensitivity, Drug-Treated Hypertension and Cardiovascular Disease: A Follow-Up Study of the METSIM Cohort.

We investigated the association of the Finnish Diabetes Risk Score (FINDRISC) with insulin secretion, insulin sensitivity, and risk of type 2 diabetes, drug-treated hypertension, cardiovascular (CVD) events and total mortality in a follow-up study of the Metabolic Syndrome in Men (METSIM) cohort. The METSIM study includes 10,197 Finnish men, aged 45-73 years, and examined in 2005-2010. Of 8,749 non-diabetic participants of the METSIM study 693 developed incident type 2 diabetes, 225 started antihypertensive medication, 351 had a CVD event, and 392 died during a 8.2-year follow-up. The FINDRISC was significantly associated with decreases in insulin secretion and insulin sensitivity (P<0.0001), and with a 4.14-fold increased risk of incident type 2 diabetes, 2.43-fold increased risk of drug-treated hypertension, 1.61-fold increased risk of CVD, and 1.55-increased risk of total mortality (the FINDRISC ≥12 vs. < 12 points). In conclusion, the FINDRISC predicts impairment in insulin secretion and insulin sensitivity, the conversion to type 2 diabetes, drug-treated hypertension, CVD events and total mortality.

Markers of tissue-specific insulin resistance predict the worsening of hyperglycemia, incident type 2 diabetes and cardiovascular disease.

We investigated the ability of surrogate markers of tissue-specific insulin resistance (IR, Matsuda IR, Adipocyte IR, Liver IR) to predict deterioration of hyperglycemia, incident type 2 diabetes and cardiovascular events in the Metabolic Syndrome in Men (METSIM) Study. The METSIM Study includes 10,197 Finnish men, aged 45-73 years, and examined in 2005-2010. A total of 558 of 8,749 non-diabetic participants at baseline were diagnosed with new-onset diabetes and 239 with a new CVD event during a 5.9-year follow-up of this cohort (2010-2013). Compared to fasting plasma insulin level, Matsuda IR (IR in skeletal muscle) and Adipocyte IR were significantly better predictors of 2-hour plasma glucose and glucose area under the curve after adjustment for confounding factors. Liver IR was the strongest predictor of both incident type 2 diabetes (hazard ratio = 1.83, 95% confidence interval: 1.68-1.98) and cardiovascular events (hazard ratio = 1.31, 95% confidence interval: 1.15-1.48). Hazard ratios for fasting insulin were 1.37 (95% confidence interval: 1.32-1.42) and 1.11 (95% confidence interval: 1.00-1.24), respectively. Tissue-specific markers of IR, Matsuda IR and Adipocyte IR, were superior to fasting plasma insulin level in predicting worsening of hyperglycemia, and Liver IR was superior to fasting insulin level in predicting incident type 2 diabetes and cardiovascular events.