Petra Belcredi

Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting.

Background Metabolomics is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in a biological fluid. However, no single analytic technique covers the entire spectrum of the human metabolome. Here we present results from a multiplatform study, in which we investigate what kind of results can presently be obtained in the field of diabetes research when combining metabolomics data collected on a complementary set of analytical platforms in the framework of an epidemiological study. Methodology/Principal Findings 40 individuals with self-reported diabetes and 60 controls (male, over 54 years) were randomly selected from the participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) study, representing an extensively phenotyped sample of the general German population. Concentrations of over 420 unique small molecules were determined in overnight-fasting blood using three different techniques, covering nuclear magnetic resonance and tandem mass spectrometry. Known biomarkers of diabetes could be replicated by this multiple metabolomic platform approach, including sugar metabolites (1,5-anhydroglucoitol), ketone bodies (3-hydroxybutyrate), and branched chain amino acids. In some cases, diabetes-related medication can be detected (pioglitazone, salicylic acid). Conclusions/Significance Our study depicts the promising potential of metabolomics in diabetes research by identification of a series of known and also novel, deregulated metabolites that associate with diabetes. Key observations include perturbations of metabolic pathways linked to kidney dysfunction (3-indoxyl sulfate), lipid metabolism (glycerophospholipids, free fatty acids), and interaction with the gut microflora (bile acids). Our study suggests that metabolic markers hold the potential to detect diabetes-related complications already under sub-clinical conditions in the general population.

Differences between Human Plasma and Serum Metabolite Profiles

Background Human plasma and serum are widely used matrices in clinical and biological studies. However, different collecting procedures and the coagulation cascade influence concentrations of both proteins and metabolites in these matrices. The effects on metabolite concentration profiles have not been fully characterized. Methodology/Principal Findings We analyzed the concentrations of 163 metabolites in plasma and serum samples collected simultaneously from 377 fasting individuals. To ensure data quality, 41 metabolites with low measurement stability were excluded from further analysis. In addition, plasma and corresponding serum samples from 83 individuals were re-measured in the same plates and mean correlation coefficients (r) of all metabolites between the duplicates were 0.83 and 0.80 in plasma and serum, respectively, indicating significantly better stability of plasma compared to serum (p = 0.01). Metabolite profiles from plasma and serum were clearly distinct with 104 metabolites showing significantly higher concentrations in serum. In particular, 9 metabolites showed relative concentration differences larger than 20%. Despite differences in absolute concentration between the two matrices, for most metabolites the overall correlation was high (mean r = 0.81±0.10), which reflects a proportional change in concentration. Furthermore, when two groups of individuals with different phenotypes were compared with each other using both matrices, more metabolites with significantly different concentrations could be identified in serum than in plasma. For example, when 51 type 2 diabetes (T2D) patients were compared with 326 non-T2D individuals, 15 more significantly different metabolites were found in serum, in addition to the 25 common to both matrices. Conclusions/Significance Our study shows that reproducibility was good in both plasma and serum, and better in plasma. Furthermore, as long as the same blood preparation procedure is used, either matrix should generate similar results in clinical and biological studies. The higher metabolite concentrations in serum, however, make it possible to provide more sensitive results in biomarker detection.

Individual Daytime Noise Exposure during Routine Activities and Heart Rate Variability in Adults: A Repeated Measures Study

Background: Epidemiological studies have demonstrated associations between noise exposure and cardiovascular events. However, there have been few studies of possible underlying mechanisms. Objectives: We examined the association between individual daytime noise exposure and heart rate variability (HRV). Methods: In a prospective panel study in Augsburg, Germany (March 2007–December 2008), 110 individuals participated in 326 electrocardiogram recordings with a mean duration of 6 hr. Five-minute averages of heart rate (HR) and HRV parameters were determined. Individual noise exposure was measured as A-weighted equivalent continuous sound pressure levels (Leq). Effects were estimated using additive mixed models adjusted for long- and short-term time trends and physical activity. Due to nonlinear exposure–response functions, we performed piecewise linear analyses with a cut-off point at 65 dB(A). Results: Concurrent increases of 5dB(A) in Leq < 65dB(A) were associated with increases in HR (percent change of mean value: 1.48%; 95% CI: 1.37, 1.60%) and the ratio of low-frequency (LF) to high-frequency (HF) power (4.89%; 95% CI: 3.48, 6.32%), and with decreases in LF (–3.77%; 95% CI: –5.49, –2.02%) and HF (–8.56%; 95% CI: –10.31, –6.78%) power. Standard deviation of normal-to-normal intervals (SDNN) was positively associated with concurrent noise < 65dB(A) (5.74%; 95% CI: 5.13, 6.36) but negatively associated with noise lagged by 5–15 min (–0.53% to –0.69%). Associations with cardiac function were less pronounced for noise ≥ 65dB(A), with some in opposite directions from associations with noise < 65dB(A). Concurrent associations were modified by sex and age. Conclusions: Individual daytime noise exposure was associated with immediate changes in HRV, suggesting a possible mechanism linking noise to cardiovascular risk. Noise at lower levels may have health consequences beyond those resulting from “fight-or-flight” responses to high levels of noise.

Association of plasma aldosterone with the metabolic syndrome in two German populations

OBJECTIVE The aim of this study was to analyze the potential association of the plasma aldosterone concentration (PAC) with the metabolic syndrome (MetS) and its components in two German population-based studies. METHODS We selected 2830 and 2901 participants (31-80 years) from the follow-ups of the Study of Health in Pomerania (SHIP)-1 and the Cooperative Health Research in the Region of Augsburg (KORA) F4 respectively. MetS was defined as the presence of at least three out of the following five criteria: waist circumference ≥94 cm (men (m)) and ≥80 cm (women (w)); high-density lipoprotein (HDL) cholesterol <1.0 mmol/l (m) and <1.3 mmol/l (w); blood pressure ≥130/85 mmHg or antihypertensive treatment; non-fasting glucose (SHIP-1) ≥8 mmol/l, fasting glucose (KORA F4) ≥5.55 mmol/l or antidiabetic treatment; non-fasting triglycerides (SHIP-1) ≥2.3 mmol/l, fasting triglycerides (KORA F4) ≥1.7 mmol/l, or lipid-lowering treatment. We calculated logistic regression models by comparing the highest study- and sex-specific PAC quintiles versus all lower quintiles. RESULTS MetS was common with 48.1% (m) and 34.8% (w) in SHIP-1 and 42.7% (m) and 27.5% (w) in KORA F4. Our logistic regression models revealed associations of PAC with MetS, elevated triglycerides, and decreased HDL cholesterol in SHIP-1 and KORA F4. CONCLUSIONS Our findings add to the increasing evidence supporting a relation between aldosterone and MetS and suggest that aldosterone may be involved in the pathophysiology of MetS and lipid metabolism disorders.

Short-term effects of air temperature on blood markers of coagulation and inflammation in potentially susceptible individuals

Objectives Changes in air temperature are associated with an increase in cardiovascular events, but the role of procoagulant and proinflammatory blood markers is still poorly understood. The authors investigated the association between air temperature and fibrinogen, plasminogen activator inhibitor type 1, interleukin-6 and high-sensitivity C reactive protein in two potentially susceptible groups. Methods This prospective panel study was conducted between March 2007 and December 2008 in Augsburg, Germany. The study population comprised 187 participants with type 2 diabetes mellitus or impaired glucose tolerance and 87 participants with genetic polymorphisms on the detoxification and inflammation pathways. Overall, 1766 repeated blood measurements were collected. Hourly meteorology data were available from a central measurement site. The association between temperature and blood markers was analysed with additive mixed models. Results For type 2 diabetes mellitus and impaired glucose tolerance participants, the authors observed immediate, lagged and cumulative increases in fibrinogen (range of percentage changes in geometric mean: 0.6%–0.8%) and plasminogen activator inhibitor type 1 (6.0%–10.1%) in association with a 5°C temperature decrement. Participants with a body mass index above 30 kg/m2 as well as females showed particularly strong fibrinogen effects. In participants with the special genetic background, 5°C decreases in the 5-day average of temperature led to a change of 8.0% (95% CI 0.5% to 16.2%) in interleukin-6 and of −8.4% (95% CI −15.8% to −0.3%) in high-sensitivity C reactive protein, the latter driven by physically active individuals. Conclusions The authors observed different temperature effects on blood markers in two potentially susceptible groups probably indicating varying underlying biological mechanisms. This study results might provide a link between temperature and cardiovascular events.

Acute air pollution effects on heart rate variability are modified by SNPs involved in cardiac rhythm in individuals with diabetes or impaired glucose tolerance.

BACKGROUND Epidemiological studies have shown associations between particulate matter (PM) and heart rate variability (HRV). OBJECTIVES We investigated the effects of air pollution on the root mean square of successive differences (RMSSD) and the standard deviation of normal-to-normal intervals (SDNN) and effect modifications by single nucleotide polymorphisms (SNP). METHODS Between March 2007 and December 2008 207 ECG recordings comprising 1153 1 h-intervals were measured in 61 individuals with type 2 diabetes or impaired glucose tolerance (IGT) from Augsburg, Germany. Associations between 1 h-averages of air pollutants (PM, sulphate, black carbon, and ultrafine particles) and ECG parameters were analyzed using additive mixed models. Genotypes of 139 SNPs supposed to be involved in cardiac rhythm were identified in the literature. Using regression trees for longitudinal data, SNPs associated with ECG parameters were determined and included as potential air pollution effect modifiers. RESULTS We observed concurrent and lagged decreases in SDNN by about 2-5% in association with all air pollutants, especially in participants with at least one minor allele of rs332229. Increases in PM<2.5 μm (PM(2.5)) were associated with 4 h-lagged decreases of -6.6% [95%-confidence interval:-10.6;-2.6%] and -13.0% [-20.7;-5.1%] in SDNN in individuals with one or two minor alleles. We observed a -7.2% [-12.2;-1.8%] reduction in RMSSD associated with concurrent increases in PM(2.5.) Individuals with at least one minor allele of rs2096767 or at most one minor allele of rs2745967 exhibited stronger PM(2.5) effects. CONCLUSIONS We identified a genetic predisposition in persons with diabetes or IGT making them potentially more susceptible to air pollutants with regard to changes in HRV.

Reproductive Factors and Serum Uric Acid Levels in Females from the General Population: The KORA F4 Study

Objective Hyperuricemia is associated with an increased risk of metabolic and cardiovascular diseases. There are pronounced sex differences in the levels of uric acid. It is largely unknown whether or not reproductive parameters which induce hormonal changes are responsible for this. We examined if there are associations between reproductive parameters and uric acid levels in a female population-based sample. Methods In this cross-sectional analysis, data of 1530 women aged 32 to 81 years participating in the KORA F4 study, conducted between 2006 and 2008 in Southern Germany were used. Reproductive parameters were obtained by standardized interviews. Uric acid levels were tested by the uricase method. The whole study sample and stratified in pre- and postmenopausal women was analyzed. Results Menopausal status and earlier age at menarche were associated with higher serum uric acid levels (age-adjusted: p-values 0.003, <0.001 respectively; after multivariable adjustment, including BMI: p-values 0.002, 0.036). A history of oral contraceptive use showed an association with uric acid levels only after multivariable adjustment (p-value 0.009). Hot flushes showed an association with uric acid levels only after age-adjustment (p-value 0.038), but lost significance after adding other confounders. Other reproductive factors, including parity, current or ever use of hormone replacement therapy, current use of oral contraceptives, hysterectomy, bilateral oophorectomy, or depressive mood related to menopausal transition were not associated with uric acid levels. Conclusions Postmenopausal status, earlier age at menarche and a history of oral contraceptive use were independently associated with higher serum uric acid concentrations in women from the general population. Further studies, especially longitudinal population-based studies investigating the relationship of female reproductive parameters with uric acid levels are necessary to confirm our findings.

Impact of personally measured pollutants on cardiac function

Epidemiological studies have shown associations between ambient air pollution and changes in heart rate variability (HRV). However, studies using personal air pollution measurements, especially with exposure averages <24h, are still rare. Between February and March 2008 HRV data as well as personal exposure to particulate matter <2.5μm (PM2.5), and particle number concentrations (PNC) were collected in five volunteers for up to 8.3h on a 5min resolution. Information about the participants whereabouts was also collected. Mixed models were used to analyze concurrent and up to 30min delayed effects of air pollutants as well as being in traffic on 5min-averages of heart rate (HR), high and low frequency power (HF and LF), standard deviation of all normal-to-normal intervals (SDNN), and the root mean square of successive interval differences (RMSSD). Results are presented as %-change from the mean per increase in interquartile range of air pollutant. In total, 474 5-min segments were available for analysis. We observed concurrent and delayed reductions in SDNN of about 0.8-1.0% in association with a 5.4μg/m(3) increase in PM2.5. However, being in traffic by car led to an increase of about 20% 10-14min and 15-19min later. An increase in PM2.5 or PNC was associated with lagged decreases for RMSSD and HF. We detected concurrent reductions in RMSSD (-17.6% [95%-confidence interval: 29.1; -4.3]) when being in traffic by bike/foot. Being in traffic by car was associated with an immediate reduction in LF while more delayed increases in LF were observed when being in traffic by bike/foot. Air pollution and traffic effects on HR were less consistent. These rapid changes in HRV within 30min might be mediated by the autonomic nervous system in response to direct reflexes from receptors in the lungs.

Are diabetes risk scores useful for the prediction of cardiovascular diseases? Assessment of seven diabetes risk scores in the KORA S4/F4 cohort study

AIM To evaluate the utility of diabetes prediction models for CVD prediction as stated in two earlier studies. METHODS 845 subjects from the population based German KORA (Cooperative Health Research in the Region of Augsburg) S4/F4 cohort study (aged 55 to 74 years, without diabetes, former stroke, and former myocardial infarction at baseline) were followed for up to ten years for incident stroke and myocardial infarction. Seven diabetes risk scores developed from four different studies were applied to the KORA cohort to assess their predictive ability for CVD. RESULTS Areas under the receiver-operating curve (AROCs) for the prediction of CVD ranged from 0.60 to 0.65 when diabetes risk scores were applied to the KORA cohort. When diabetes risk scores were used to predict CVD and type 2 diabetes, respectively, AROCs for the prediction of CVD were 0.09 to 0.24 lower than AROCs for the prediction of type 2 diabetes. Furthermore, we used KORA data to develop prediction models for either diabetes or CVD, and found that they differed widely in selected predictor variables. CONCLUSION In the older population, diabetes risk scores are not useful for the prediction of CVD, and prediction models for diabetes and CVD, respectively, require different parameters.