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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.
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.
Microbial metabolites measured using NMR may serve as markers for physiological or pathological host–microbe interactions and possibly mediate the beneficial effects of microbiome diversity. Yet, comprehensive analyses of gut microbiome data and the urine NMR metabolome from large general population cohorts are missing. Here, we report the associations between gut microbiota abundances or metrics of alpha diversity, quantified from stool samples using 16S rRNA gene sequencing, with targeted urine NMR metabolites measures from 951 participants of the Study of Health in Pomerania (SHIP). We detected significant genus–metabolite associations for hippurate, succinate, indoxyl sulfate, and formate. Moreover, while replicating the previously reported association between hippurate and measures of alpha diversity, we identified formate and 4-hydroxyphenylacetate as novel markers of gut microbiome alpha diversity. Next, we predicted the urinary concentrations of each metabolite using genus abundances via an elastic net regression methodology. We found profound associations of the microbiome-based hippurate prediction score with markers of liver injury, inflammation, and metabolic health. Moreover, the microbiome-based prediction score for hippurate completely mediated the clinical association pattern of microbial diversity, hinting at a role of benzoate metabolism underlying the positive associations between high alpha diversity and healthy states. In conclusion, large-scale NMR urine metabolomics delivered novel insights into metabolic host–microbiome interactions, identifying pathways of benzoate metabolism as relevant candidates mediating the beneficial health effects of high microbial alpha diversity.
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.
Aim
To investigate the medium-term associations of serum protein subfractions derived from proton nuclear magnetic resonance (1H-NMR) spectroscopy with periodontitis and tooth loss.
Materials and Methods
A total of 3031 participants of the cohort Study of Health in Pomerania (SHIP-TREND) were included. In addition to conventional serum testing, serum lipoprotein contents and subfractions were analysed by 1H-NMR spectroscopy. Confounder-adjusted associations of lipoprotein variables with periodontitis and the number of missing teeth variables were analysed using mixed-effects models with random intercepts for time across individuals, accounting for multiple testing.
Results
While only spurious associations between lipoprotein levels from conventional blood tests were found—that is, triglycerides were associated with mean clinical attachment level (CAL) and low-density lipoprotein cholesterol/high-density lipoprotein cholesterol (LDL-C/HDL-C) ratio with the number of missing teeth - several associations emerged from serum lipoprotein subfractions derived from 1H-NMR analysis. Specifically, elevated LDL triglycerides were associated with higher levels of mean probing depth (PD), mean CALs, and increased odds of having <20 teeth. HDL-4 cholesterol levels were inversely associated with mean PD. Systemic inflammation (C-reactive protein) might mediate the effects of LDL and HDL triglyceride contents on periodontitis severity.
Conclusions
Several associations between serum lipoprotein subfractions and periodontitis were observed. As the underlying biochemical mechanisms remain unclear, further research is needed.
Background
Lower cortisol concentrations in adulthood were repeatedly associated with more severe childhood maltreatment. Additionally, childhood maltreatment was reported to promote health risk behavior, such as smoking or alcohol consumption, and to increase the risk of mental and somatic diseases during adulthood, such as major depressive disorders or obesity. The present study investigated if health risk behavior and disease symptoms in adults mediate the associations between past childhood maltreatment and present basal serum cortisol concentrations.
Methods
Data from two independent adult cohorts of the general population-based Study of Health in Pomerania (SHIP-TREND-0: N = 3,517; SHIP-START-2: N = 1,640) was used. Childhood maltreatment was assessed via the Childhood Trauma Questionnaire (CTQ). Cortisol concentrations were measured in single-point serum samples. Health risk behavior and mental and physical symptoms were used as mediators. Mediation analyses were calculated separately for both cohorts; results were integrated via meta-analyses.
Results
In mediator-separated analyses, associations between childhood maltreatment and basal serum cortisol concentrations were partly mediated by depressive symptoms (BDI-II: βindirect effect = -.011, pFDR = .017, 21.0% mediated) and subjective somatic health complaints (somatic complaints: βindirect effect = -.010, pFDR = .005, 19.4% mediated). In the second step, both mediators were simultaneously integrated into one mediation model. The model replicated the mediation effects of the subjective somatic health complaints (whole model: βindirect effect = -.014, p = .001, 27.6% mediated; BDI-II: βindirect effect = -.006, p = .163, 11.4% mediated, somatic complaints: βindirect effect = -.020, p = .020, 15.5% mediated).
Conclusion
The results support the hypothesis that the long-lasting effects of childhood maltreatment on the stress response system are partly mediated through self-perceived disease symptoms. However, no mediation was found for health risk behavior or physically measured mediators. Mediation models with multiple simultaneous mediators pointed to a relevant overlap between the potential mediators. This overlap should be focused on in future studies.
Background: The global obesity epidemic is a major public health concern, and accurate diagnosis is essential for identifying at-risk individuals. Three-dimensional (3D) body scanning technology offers several advantages over the standard practice of tape measurements for diagnosing obesity. This study was conducted to validate body scan data from a German population-based cohort and explore clinical implications of this technology in the context of metabolic syndrome. Methods: We performed a cross-sectional analysis of 354 participants from the Study of Health in Pomerania that completed a 3D body scanning examination. The agreement of anthropometric data obtained from 3D body scanning with manual tape measurements was analyzed using correlation analysis and Bland–Altman plots. Classification agreement regarding abdominal obesity based on IDF guidelines was assessed using Cohen’s kappa. The association of body scan measures with metabolic syndrome components was explored using correlation analysis. Results: Three-dimensional body scanning showed excellent validity with slightly larger values that presumably reflect the true circumferences more accurately. Metabolic syndrome was highly prevalent in the sample (31%) and showed strong associations with central obesity. Using body scan vs. tape measurements of waist circumference for classification resulted in a 16% relative increase in the prevalence of abdominal obesity (61.3% vs. 52.8%). Conclusions: These results suggest that the prevalence of obesity may be underestimated using the standard method of tape measurements, highlighting the need for more accurate approaches.