Dhayana Dallmeier

Metabolic syndrome and inflammatory biomarkers: a community-based cross-sectional study at the Framingham Heart Study

BackgroundPrior studies reported conflicting findings on the association between metabolic syndrome and inflammatory biomarkers. We tested the cross-sectional associations between metabolic syndrome and nine inflammatory markers.MethodsWe measured C-reactive protein, CD40 ligand, interleukin-6, intercellular adhesion molecule-1, monocyte chemoattractant protein-1, osteoprotegerin, P-selectin, tumor necrosis factor-alpha, and tumor necrosis factor receptor-2 in 2570 Framingham Offspring Study participants free of diabetes and cardiovascular disease at examination 7. Metabolic syndrome was defined by National Cholesterol Education Program criteria. We performed multivariable linear regressions for each biomarker with metabolic syndrome as the exposure adjusting for age, sex, smoking, aspirin use, and hormone replacement. We subsequently added to the models components of the metabolic syndrome as continuous traits plus lipid lowering and hypertension treatments. We considered P < 0.05 as statistically significant.ResultsMetabolic syndrome was present in 984 (38%) participants and was statistically significantly associated with each biomarker (all P < 0.02) except osteoprotegerin. After adjusting for its component variables, the metabolic syndrome was associated only with P-selectin (1.06 fold higher in metabolic syndrome, 95% CI 1.02, 1.10, p = 0.005).ConclusionsMetabolic syndrome was associated with multiple inflammatory biomarkers. However, adjusting for each of its components eliminated the association with most inflammatory markers, except P-selectin. Our results suggest that the relation between metabolic syndrome and inflammation is largely accounted for by its components.

Insulin resistance and atrial fibrillation (from the Framingham Heart Study)

Diabetes mellitus and obesity are increasing in prevalence and are associated with an elevated risk of atrial fibrillation (AF). Given the aging of the United States population, AF is projected to concomitantly increase in prevalence in the upcoming decades. Both diabetes and obesity are associated with insulin resistance. Whether insulin resistance is an intermediate step for the development of AF is uncertain. We hypothesized that insulin resistance is associated with an increased risk of incident AF. We examined the association of insulin resistance with incident AF using multivariate Cox proportional hazards regression analysis adjusting for the established AF risk factors (i.e., age, gender, systolic blood pressure, hypertension treatment, PR interval, significant heart murmur, heart failure, and body mass index). Of the 3,023 eligible participants (55% women; mean age 59 years) representing 4,583 person-examinations (Framingham Offspring fifth and seventh examination cycles), 279 participants developed AF (9.3%) within ≤10 years of follow-up. With multivariate modeling, insulin resistance was not significantly associated with incident AF (hazard ratio comparing top quartile to other 3 quartiles of homeostatic model assessment index 1.18, 95% confidence interval 0.84 to 1.65, p = 0.34). In a community-based cohort with ≤10 years of follow-up, no significant association was observed between insulin resistance and incident AF.

Clinical correlates of change in inflammatory biomarkers: The Framingham Heart Study

OBJECTIVES Traditional clinical risk factors are associated with inflammation cross-sectionally, but associations of longitudinal variation in inflammatory biomarkers with corresponding changes in clinical risk factors are incompletely described. We sought to analyze clinical factors associated with change in inflammation in the community. METHODS We studied 3013 Framingham Offspring (n = 2735) and Omni Cohort (n = 278) participants (mean age 59 years, 55% women, 9% ethnic/racial minority) who attended two consecutive examination cycles (mean 6.7 years apart). We selected ten inflammatory biomarkers representing distinctive biological functions: C-reactive protein (CRP), intercellular adhesion molecule-1, interleukin-6, isoprostanes, lipoprotein-associated phospholipase-2 (Lp-PLA2) activity, Lp-PLA2-mass, monocyte chemoattractant protein-1, osteoprotegerin, P-selectin, and tumor necrosis factor receptor II (TNFRII). We constructed multivariable-adjusted regression models to assess the relations of baseline, follow-up and change in clinical risk factors with change in biomarker concentrations over time. RESULTS Baseline, follow-up and change in clinical risk factors explain a moderate amount of the variation in biomarker concentrations across 2 consecutive examinations (ranging from r(2) = 0.28 [TNFRII] up to 0.52 [Lp-PLA2-mass]). In multivariable models, increasing body-mass index, smoking initiation, worsening lipid profile, and increasing waist size were associated with increasing concentrations of several biomarkers. Conversely, hypercholesterolemia therapy and hormone replacement cessation were associated with decreasing concentrations of biomarkers such as CRP, Lp-PLA2-mass and activity. CONCLUSION Cardiovascular risk factors have different patterns of association with longitudinal change in inflammatory biomarkers and explain modest amounts of variability in biomarker concentrations. Nevertheless, a substantial proportion of longitudinal change in inflammatory markers is not explained by traditional risk factors.

Addition of Inflammatory Biomarkers Did Not Improve Diabetes Prediction in the Community: The Framingham Heart Study

Background Prior studies have reported conflicting findings with regard to the association of biomarkers in the prediction of incident type 2 diabetes. We evaluated 12 biomarkers as possible diabetes predictors in the Framingham Heart Study. Methods and Results Biomarkers representing inflammation (C-reactive protein, interleukin-6, monocyte chemoattractant protein-1, tumor necrosis factor receptor 2, osteoprotegerin, and fibrinogen), endothelial dysfunction (intercellular adhesion molecule-1), vascular damage (CD40-ligand, P-selectin, and lipoprotein-associated phospholipase A2 mass and activity), and oxidative stress (urinary isoprostanes) were measured in participants without diabetes attending the Offspring seventh (n=2499) or multiethnic Omni second (n=189) examination (1998–2001). Biomarkers were loge transformed and standardized. Multivariable logistic regression tested each biomarker in association with incident diabetes at a follow-up examination (the Offspring eighth and Omni third examination; mean 6.6 years later), with adjustment for age, sex, cohort, body mass index, fasting glucose, systolic blood pressure, high-density lipoprotein cholesterol, triglycerides, and smoking. C statistics were evaluated with and without inflammatory markers. In 2638 participants (56% women, mean age 59 years), 162 (6.1%) developed type 2 diabetes. All biomarkers, excluding osteoprotegerin, were associated with the outcome with adjustment for age, sex, and cohort; however, none remained significant after multivariable adjustment (all P>0.05). The c statistic from the model including only clinical covariates (0.89) did not statistically significantly improve after addition of biomarkers (all P>0.10). Conclusions Biomarkers representing different inflammatory pathways are associated with incident diabetes but do not remain statistically significant after adjustment for established clinical covariates. Inflammatory biomarkers might not be an effective resource to predict type 2 diabetes in community-based samples. (J Am Heart Assoc. 2012;1:e000737 doi: 10.1161/JAHA.112.000869.)

Sex-specific associations of established and emerging cardiac biomarkers with all-cause mortality in older adults: the ActiFE study.

BACKGROUND N-terminal pro B-type natriuretic peptide (NT-proBNP) has strong prognostic value for all-cause mortality in the general population. High-sensitivity assays now allow detection of cardiac troponins even in asymptomatic populations. We examined the association between NT-proBNP, high-sensitivity cardiac troponin T (hs-cTnT), and hs-cTnI and all-cause mortality in older adults. METHODS We conducted a longitudinal cohort study [Activity and Function in the Elderly in Ulm (ActiFE Ulm)] including 1506 community-dwelling adults ≥65 years old with NT-proBNP, hs-cTnT, and hs-cTnI measured at baseline. We evaluated the associations between log-transformed biomarker concentrations and 4-year total mortality, accounting for possible confounders, with Cox proportional hazards models. RESULTS We observed 125 deaths among 1422 participants (median follow-up 4 years). We detected effect modification by sex for all biomarkers (all P values <0.05) expressed as hazard ratio (HR) for death per 1-unit increment of ln(biomarker concentration) in women (n = 618, 37 deaths) compared with men (n = 804, 88 deaths): HR 2.97 (95% CI 2.04-4.33) vs 1.73 (1.40-2.13) for NT-proBNP; 3.67 (2.31-5.81) vs 2.15 (1.61-2.87) for hs-cTnT; and 3.32 (2.13-5.18) vs 1.92 (1.55-2.38) for hs-cTnI. Among 777 participants with undetectable hs-cTnT (<5 ng/L), hs-cTnI remained associated with all-cause mortality in age- and sex-adjusted analysis. CONCLUSIONS NT-proBNP, hs-cTnT, and hs-cTnI were independently associated with all-cause mortality in older adults. The strength of these associations varied between men and women, emphasizing the need for additional sex-specific research among older people.

A Variant In the Abo Gene Explains the Variation in Soluble E-Selectin Levels—Results from Dense Genotyping in Two Independent Populations

Background Elevated soluble (s) E-selectin levels have been associated with various cardiovascular diseases. Recently, genetic variants in the ABO blood group have been related to E-selectin levels in a small cohort of patients with type 1 diabetes. We evaluated whether this association is reproducible in two large samples of Caucasians. Methodology/ Principal Findings Data of the present study was drawn from the population-based MONICA/KORA Augsburg study (n = 1,482) and the patients-based LURIC study (n = 1,546). A high-density genotyping array (50K IBC Chip) containing single-nucleotide polymorphisms (SNPs) from E-selectin candidate genes selected on known biology of E-selectin metabolism, mouse genetic studies, and human genetic association studies, was used for genotyping. Linear regression analyses with adjustment for age and sex (and survey in KORA) were applied to assess associations between gene variants and sE-selectin concentrations. A number of 12 SNPs (in KORA) and 13 SNPs (in LURIC), all from the ABO blood group gene, were significantly associated with the log-transformed concentration of E-selectin. The strongest association was observed for rs651007 with a change of log-transformed sE-selectin per one copy of the minor allele of −0.37 ng/ml (p = 1.87×10−103) in KORA and −0.35 ng/ml (p = 5.11×10−84) in LURIC. Inclusion of rs651007 increased the explained sE-selectin variance by 0.256 in KORA and 0.213 in LURIC. All SNPs had minor allele frequencies above 20% showing a substantial gene variation. Conclusions/ Significance Our findings in two independent samples indicate that the genetic variants at the ABO locus affect sE-selectin levels. Since distinct genome-wide association studies linked the ABO gene with myocardial infarction (MI) in the presence of coronary atherosclerosis and with coronary artery disease, these findings may not only enhance our understanding of adhesion molecule biology, but may also provide a focus for several novel research avenues.

Biomarkers associated with sedentary behaviour in older adults: A systematic review

OBJECTIVE Pathomechanisms of sedentary behaviour (SB) are unclear. We conducted a systematic review to investigate the associations between SB and various biomarkers in older adults. METHODS Electronic databases were searched (MEDLINE, EMBASE, CINAHL, AMED) up to July 2015 to identify studies with objective or subjective measures of SB, sample size ≥50, mean age ≥60years and accelerometer wear time ≥3days. Methodological quality was appraised with the CASP tool. The protocol was pre-specified (PROSPERO CRD42015023731). RESULTS 12701 abstracts were retrieved, 275 full text articles further explored, from which 249 were excluded. In the final sample (26 articles) a total of 63 biomarkers were detected. Most investigated markers were: body mass index (BMI, n=15), waist circumference (WC, n=15), blood pressure (n=11), triglycerides (n=12) and high density lipoprotein (HDL, n=15). Some inflammation markers were identified such as interleukin-6, C-reactive protein or tumor necrosis factor alpha. There was a lack of renal, muscle or bone biomarkers. Randomized controlled trials found a positive correlation for SB with BMI, neck circumference, fat mass, HbA1C, cholesterol and insulin levels, cohort studies additionally for WC, leptin, C-peptide, ApoA1 and Low density lipoprotein and a negative correlation for HDL. CONCLUSION Most studied biomarkers associated with SB were of cardiovascular or metabolic origin. There is a suggestion of a negative impact of SB on biomarkers but still a paucity of high quality investigations exist. Longitudinal studies with objectively measured SB are needed to further elucidate the pathophysiological pathways and possible associations of unexplored biomarkers.

What works to prevent falls in older adults dwelling in long term care facilities and hospitals? An umbrella review of meta-analyses of randomised controlled trials

Preventing falls in long term care facilities (LTCF) and hospitals is an international priority. Many interventions have been investigated and summarised in meta-analyses (MA) and there is a need to synthesise the top of the hierarchy of evidence in one place. Therefore we conducted an umbrella review of MA of randomised controlled trials (RCTs) of falls prevention interventions LTCF and hospitals. Two independent reviewers searched major electronic databases from inception till October 2014 for MA containing ≥3 RCTs investigating any intervention to prevent falls in LTCF or hospitals in older adults aged ≥60 years. Methodological quality was assessed by the AMSTAR tool and data were narratively synthesised. The methodological quality of the MA was moderate to high across the 10 included MA. Nine MA provided data for LTCF and only two considered hospital settings. Only one MA defined a fall and two reported adverse events (although minor). Consistent evidence suggests that multifactorial interventions reduce falls (including the rate, risk and odds of falling) in LTCF and hospitals. Inconsistent evidence exists for exercise and vitamin D as single interventions in LTCF, whilst no MA has investigated this in hospitals. No evidence exists for hip protectors and medication review on falls in LTCF. In conclusion, multifactorial interventions appear to be the most effective interventions to prevent falls in LTCF and hospital settings. This is not without limitations and more high quality RCTs are needed in hospital settings in particular. Future RCTs and MA should clearly report adverse events.

Objectively Measured Walking Duration and Sedentary Behaviour and Four-Year Mortality in Older People

Background Physical activity is an important component of health. Recommendations based on sensor measurements are sparse in older people. The aim of this study was to analyse the effect of objectively measured walking and sedentary duration on four-year mortality in community-dwelling older people. Methods Between March 2009 and April 2010, physical activity of 1271 participants (≥65 years, 56.4% men) from Southern Germany was measured over one week using a thigh-worn uni-axial accelerometer (activPAL; PAL Technologies, Glasgow, Scotland). Mortality was assessed during a four-year follow-up. Cox-proportional-hazards models were used to estimate the associations between walking (including low to high intensity) and sedentary duration with mortality. Models were adjusted for age and sex, additional epidemiological variables, and selected biomarkers. Results An inverse relationship between walking duration and mortality with a minimum risk for the 3rd quartile (102.2 to128.4 minutes walking daily) was found even after multivariate adjustment with HRs for quartiles 2 to 4 compared to quartile 1 of 0.45 (95%-CI: 0.26; 0.76), 0.18 (95%-CI: 0.08; 0.41), 0.39 (95%-CI: 0.19; 0.78), respectively. For sedentary duration an age- and sex-adjusted increased mortality risk was observed for the 4th quartile (daily sedentary duration ≥1137.2 min.) (HR 2.05, 95%-CI: 1.13; 3.73), which diminished, however, after full adjustment (HR 1.63, 95%-CI: 0.88; 3.02). Furthermore, our results suggest effect modification between walking and sedentary duration, such that in people with low walking duration a high sedentary duration was noted as an independent factor for increased mortality. Conclusions In summary, walking duration was clearly associated with four-year overall mortality in community-dwelling older people.

Growth Differentiation Factor 15, Its 12-Month Relative Change, and Risk of Cardiovascular Events and Total Mortality in Patients with Stable Coronary Heart Disease: 10-Year Follow-up of the KAROLA Study

BACKGROUND This study considered whether baseline concentrations and 12-month changes of growth differentiation factor 15 (GDF-15) are associated with subsequent cardiovascular events (CVEs) and total mortality in patients with stable coronary heart disease. METHODS Baseline GDF-15 serum concentrations were measured in 1073 participants in a cardiac rehabilitation program (median follow-up 10 years). GDF-15 associations with subsequent CVE and total mortality were evaluated by Cox-proportional hazards models adjusting for well-established cardiovascular risk factors (Model 2), plus N-terminal probrain natriuretic peptide, high-sensitivity (hs) CRP, and hs cardiac troponin T (Model 3). RESULTS In our study population [84.7% men, mean age 59 years, median baseline GDF-15 1232 ng/L (interquartile range, 916, 1674)] we observed 190 CVE and 162 deaths. Compared to participants with GDF-15 <1200 ng/L, increased risk for death was found in participants with GDF-15 ≥1200 and ≤1800 ng/L [hazard ratio (HR) 1.68 (95% CI, 1.08-2.62)] and with GDF-15 >1800 ng/L [HR 1.73 (1.02-2.94)], even in Model 3. The 12-month relative median change was -16.7%. As compared to participants with 12-month relative changes between -20% and 20%, GDF-15 increments >20% were associated with: a) an HR of 1.84 (1.04-3.26) for CVE in Model 2, but found nonsignificant in Model 3; (b) an HR of 2.26 (1.32-3.86) for death even in Model 3. CONCLUSIONS GDF-15 at baseline is independently associated with subsequent CVE and 10-year total mortality. Twelve-month relative changes remained associated with subsequent CVE when adjusting for well-established cardiovascular risk factors, and with total mortality even after further adjustment for established cardiac biomarkers.