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The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites (n = 284) obtained by mass spectrometry among a subsample (n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites (n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.
For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In this paper, we propose a definition for individualization and a corresponding statistical operationalization, delivering thereby a statistical framework in which the usefulness of a variable in the meaningful differentiation of individuals with the same phenotype can be assessed. Based on this framework, we develop a statistical workflow to derive individualized phenotypes, demonstrating that under specific statistical constraints the prediction error of prediction scores contains information about hidden biological traits not represented in the modeled phenotype of interest, allowing thereby internal differentiation of individuals with the same assigned phenotypic manifestation. We applied our procedure to data of the population-based Study of Health in Pomerania to construct a refined definition of obesity, demonstrating the utility of the definition in prospective survival analyses. Summarizing, we propose a framework for the individualization of phenotypes aiding personalized medicine by shifting the focus in the assessment of prediction models from the model fit to the informational content of the prediction error.
Our goal was to provide a comprehensive overview of the antibody response to Staphylococcus aureus antigens in the general population as a basis for defining disease-specific profiles and diagnostic signatures. We tested the specific IgG and IgA responses to 79 staphylococcal antigens in 996 individuals from the population-based Study of Health in Pomerania. Using a dilution-based multiplex suspension array, we extended the dynamic range of specific antibody detection to seven orders of magnitude, allowing the precise quantification of high and low abundant antibody specificities in the same sample. The observed IgG and IgA antibody responses were highly heterogeneous with differences between individuals as well as between bacterial antigens that spanned several orders of magnitude. Some antigens elicited significantly more IgG than IgA and vice versa. We confirmed a strong influence of colonization on the antibody response and quantified the influence of sex, smoking, age, body mass index, and serum glucose on anti-staphylococcal IgG and IgA. However, all host parameters tested explain only a small part of the extensive variability in individual response to the different antigens of S. aureus.
Abstract
Study Objective
Long‐term intake of proton pump inhibitors (PPIs) might increase the risk of cardiovascular events. One suggested mechanism is that PPIs inhibit the enzyme dimethylarginine dimethylaminohydrolase (DDAH) and thereby block the degradation of endothelial asymmetrical dimethylarginine (ADMA). Excess ADMA in turn leads to impaired endothelial nitric oxide (NO) generation. So far, this mechanism has only been established in human cell cultures. Previous studies that examined this pathway in human populations measured circulating ADMA and found no association with PPI use and excess plasma ADMA. But in a recent study, plasma ADMA was not correlated with intracellular ADMA. We therefore focused on changes in plasma citrulline as an indicator for potential DDAH inhibition.
Design
We analyzed the association between regular daily PPI intake and flow‐mediated dilation (FMD) of the brachial artery as well as plasma concentrations of citrulline, arginine, ADMA, and symmetric dimethylarginine using inverse probability weighting to adjust for confounding and censoring.
Data Source
Data of 1298 participants from two independent cohorts of the population‐based Study of Health in Pomerania were used.
Participants
Participants of the population‐based Study of Health in Pomerania are a stratified random sample of the study region.
Exposure
Regular daily intake of PPIs.
Measurements
FMD of the brachial artery and plasma concentrations of citrulline, arginine, ADMA, and symmetric dimethylarginine.
Main Results
Eighty‐seven participants (57.5% female) were regular daily users of PPIs. In the fully adjusted models, associations were identified for FMD and plasma citrulline concentrations. PPI users revealed a 0.99% (95% CI: −1.96 to −0.02) lower FMD and 3.03 µmol/L (95% CI: −4.96 to −1.10) lower plasma citrulline levels as compared to non‐users.
Conclusion
Our data provide evidence that long‐term intake of PPIs might inhibit human DDAH activity, resulting in impaired endothelial NO production and reduced vascular function. In the long run, this might explain an increased risk for cardiovascular diseases associated with long‐term PPI use.
Objective
This study provides a comprehensive overview of the associations of five adipokines (adiponectin, chemerin, galectin‐3, leptin, and resistin) with fat deposits, behavioral risk factors, and metabolic phenotypes.
Methods
Using multivariable linear and logistic regression models, cross‐sectional data from 4,116 participants of the population‐based Study of Health in Pomerania were analyzed.
Results
Participants with obesity showed higher chemerin, galectin‐3, and leptin but showed lower adiponectin concentrations. Independently of other fat compounds, liver fat content, visceral adipose tissue, and subcutaneous adipose tissue (SAT) were inversely associated with adiponectin. Independent positive associations of liver fat content and SAT with chemerin as well as of SAT with galectin‐3 and leptin were observed. Physically inactive participants had higher chemerin and leptin concentrations. Smokers had higher chemerin and galectin‐3 as well as lower leptin. Alcohol consumption was associated with adiponectin (positive) and resistin (inverse). All adipokines were associated with at least one lipid marker. Associations with glucose metabolism were seen for adiponectin, chemerin, galectin‐3, and leptin.
Conclusions
High adiponectin concentrations were related to favorable metabolic conditions, whereas high chemerin, galectin‐3, and leptin were associated with an unfavorable metabolic profile. High leptin seems to be primarily indicative of obesity, whereas high adiponectin and chemerin are associated with a broader range of metabolic phenotypes.
Background: Chronic kidney disease (CKD) and low serum total testosterone (TT) concentrations are independent predictors of mortality risk in the general population, but their combined potential for improved mortality risk stratification is unknown. Methods: We used data of 1,822 men from the population-based Study of Health in Pomerania followed- up for 9.9 years (median). The direct effects of kidney dysfunction (estimated glomerular filtration rate <60 ml/min/ 1.73 m<sup>2</sup>), albuminuria (urinary albumin-creatinine ratio ≧2.5 mg/mmol) and their combination (CKD) on all-cause and cardiovascular mortality were analyzed using multivariable Cox regression models. Serum TT concentrations below the age-specific 10th percentile (by decades) were considered low and were used for further risk stratification. Results: Kidney dysfunction (hazard ratio, HR, 1.40; 95% confidence interval, CI, 1.02–1.92), albuminuria (HR, 1.38; 95% CI, 1.06–1.79), and CKD (HR, 1.42; 95% CI, 1.09–1.84) were associated with increased all-cause mortality risk, while only kidney dysfunction (HR, 2.01; 95% CI, 1.21–3.34) was associated with increased cardiovascular mortality risk after multivariable adjustment. Men with kidney dysfunction and low TT concentrations were identified as high-risk individuals showing a more than 2-fold increased all-cause mortality risk (HR, 2.52; 95% CI, 1.08–5.85). Added to multivariable models, nonsignificant interaction terms suggest that kidney dysfunction and low TT are primarily additive rather than synergistic mortality risk factors. Conclusion: In the case of early loss of kidney function, measured TT concentrations might help to detect high-risk individuals for potential therapeutic interventions and to improve mortality risk assessment and outcome.
Context: 3,5-Diiodo-<smlcap>L</smlcap>-thyronine (3,5-T<sub>2</sub>) is a thyroid hormone metabolite which exhibited versatile effects in rodent models, including the prevention of insulin resistance or hepatic steatosis typically forced by a high-fat diet. With respect to euthyroid humans, we recently observed a putative link between serum 3,5-T<sub>2</sub> and glucose but not lipid metabolism. Objective: The aim of the present study was to widely screen the urine metabolome for associations with serum 3,5-T<sub>2</sub> concentrations in healthy individuals. Study Design and Methods: Urine metabolites of 715 euthyroid participants of the population-based Study of Health in Pomerania (SHIP-TREND) were analyzed by <sup>1</sup>H-NMR spectroscopy. Multinomial logistic and multivariate linear regression models were used to detect associations between urine metabolites and serum 3,5-T<sub>2</sub> concentrations. Results: Serum 3,5-T<sub>2</sub> concentrations were positively associated with urinary levels of trigonelline, pyroglutamate, acetone and hippurate. In detail, the odds for intermediate or suppressed serum 3,5-T<sub>2</sub> concentrations doubled owing to a 1-standard deviation (SD) decrease in urine trigonelline levels, or increased by 29-50% in relation to a 1-SD decrease in urine pyroglutamate, acetone and hippurate levels. Conclusion: Our findings in humans confirmed the metabolic effects of circulating 3,5-T<sub>2</sub> on glucose and lipid metabolism, oxidative stress and enhanced drug metabolism as postulated before based on interventional pharmacological studies in rodents. Of note, 3,5-T<sub>2</sub> exhibited a unique urinary metabolic profile distinct from previously published results for the classical thyroid hormones.