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The hypothalamus–pituitary–adrenal axis is the main physiological stress response system and regulating the release of cortisol. The two corticoid receptors encoded by the genes NR3C1 and NR3C2 are the main players in regulating the physiological response to cortisol. This biological system has been linked to neurocognitive processes and memory, yet the mechanisms remain largely unclear. In two independent general population studies (SHIP, total sample size > 5500), we aim to diseantangle the effects of genetic variation, gene expression and cortisol on verbal memory and memory associated brain volume. Especially for NR3C1 results exhibited a consistent pattern of direct an interactive effects. All three biological layers, genetic variation (rs56149945), gene expression for NR3C1 and cortisol levels, were directly associated with verbal memory. Interactions between these components showed significant effects on verbal memory as well as hippocampal volume. For NR3C2 such a complex association pattern could not be observed. Our analyses revealed that different components of the stress response system are acting together on different aspects of cognition. Complex phenotypes, such as cognition and memory function are regulated by a complex interplay between different genetic and epigenetic features. We promote the glucocorticoid receptor NR3C1 as a main target to focus in the context of verbal memory and provided a mechanistic concept of the interaction between various biological layers spanning NR3C1 function and its effects on memory. Especially the NR3C1 transcript seemed to be a key element in this complex system.
Introduction
Supplementation with spermidine may support healthy aging, but elevated spermidine tissue levels were shown to be an indicator of Alzheimer's disease (AD).
Methods
Data from 659 participants (age range: 21–81 years) of the population-based Study of Health in Pomerania TREND were included. We investigated the association between spermidine plasma levels and markers of brain aging (hippocampal volume, AD score, global cortical thickness [CT], and white matter hyperintensities [WMH]).
Results
Higher spermidine levels were significantly associated with lower hippocampal volume (ß = −0.076; 95% confidence interval [CI]: −0.13 to −0.02; q = 0.026), higher AD score (ß = 0.118; 95% CI: 0.05 to 0.19; q = 0.006), lower global CT (ß = −0.104; 95% CI: −0.17 to −0.04; q = 0.014), but not WMH volume. Sensitivity analysis revealed no substantial changes after excluding participants with cancer, depression, or hemolysis.
Discussion
Elevated spermidine plasma levels are associated with advanced brain aging and might serve as potential early biomarker for AD and vascular brain pathology.
Aims
Sphingosine-1-phosphate (S1P) is a signaling lipid, which is involved in several cellular processes including cell growth, proliferation, migration and apoptosis. The associations of serum S1P levels with cardiac geometry and function are still not clear. We investigated the associations of S1P with cardiac structure and systolic function in a population-based sample.
Methods and results
We performed cross-sectional analyses of 858 subjects (467 men; 54.4%), aged 22 to 81 years, from a sub-sample of the population-based Study of Health in Pomerania (SHIP-TREND-0). We analyzed the associations of serum S1P with structural and systolic function left ventricular (LV) and left atrial (LA) parameters as determined by magnetic resonance imaging (MRI) using sex-stratified multivariable-adjusted linear regression models. In men, MRI data showed that a 1 µmol/L lower S1P concentration was associated with an 18.1 mL (95% confidence interval [CI] 3.66–32.6; p = 0.014) larger LV end-diastolic volume (LVEDV), a 0.46 mm (95% CI 0.04–0.89; p = 0.034) greater LV wall thickness (LVWT) and a 16.3 g (95% CI 6.55–26.1; p = 0.001) higher LV mass (LVM). S1P was also associated with a 13.3 mL/beat (95% CI 4.49–22.1; p = 0.003) greater LV stroke volume (LVSV), an 18.7 cJ (95% CI 6.43–30.9; p = 0.003) greater LV stroke work (LVSW) and a 12.6 mL (95% CI 1.03–24.3; p = 0.033) larger LA end-diastolic volume (LAEDV). We did not find any significant associations in women.
Conclusions
In this population-based sample, lower levels of S1P were associated with higher LV wall thickness and mass, larger LV and LA chamber sizes and greater stroke volume and work of the LV in men, but not in women. Our results indicate that lower levels of S1P were associated with parameters related with cardiac geometry and systolic function in men, but not in women.
Introduction: It has been shown that Alzheimer’s disease (AD) is accompanied by marked structural brain changes that can be detected several years before clinical diagnosis via structural magnetic resonance (MR) imaging. In this study, we developed a structural MR-based biomarker for in vivo detection of AD using a supervised machine learning approach. Based on an individual’s pattern of brain atrophy a continuous AD score is assigned which measures the similarity with brain atrophy patterns seen in clinical cases of AD.
Methods: The underlying statistical model was trained with MR scans of patients and healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI-1 screening). Validation was performed within ADNI-1 and in an independent patient sample from the Open Access Series of Imaging Studies (OASIS-1). In addition, our analyses included data from a large general population sample of the Study of Health in Pomerania (SHIP-Trend).
Results: Based on the proposed AD score we were able to differentiate patients from healthy controls in ADNI-1 and OASIS-1 with an accuracy of 89% (AUC = 95%) and 87% (AUC = 93%), respectively. Moreover, we found the AD score to be significantly associated with cognitive functioning as assessed by the Mini-Mental State Examination in the OASIS-1 sample after correcting for diagnosis, age, sex, age·sex, and total intracranial volume (Cohen’s f2 = 0.13). Additional analyses showed that the prediction accuracy of AD status based on both the AD score and the MMSE score is significantly higher than when using just one of them. In SHIP-Trend we found the AD score to be weakly but significantly associated with a test of verbal memory consisting of an immediate and a delayed word list recall (again after correcting for age, sex, age·sex, and total intracranial volume, Cohen’s f2 = 0.009). This association was mainly driven by the immediate recall performance.
Discussion: In summary, our proposed biomarker well differentiated between patients and healthy controls in an independent test sample. It was associated with measures of cognitive functioning both in a patient sample and a general population sample. Our approach might be useful for defining robust MR-based biomarkers for other neurodegenerative diseases, too.
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.
Deteriorations in slow wave sleep (SWS) have been linked to brain aging and Alzheimer’s disease (AD), possibly due to its key role in clearance of amyloid-beta and tau (Aß/tau), two pathogenic hallmarks of AD. Spermidine administration has been shown to improve sleep quality in animal models. So far, the association between spermidine levels in humans and parameters of SWS physiology are unknown but may be valuable for therapeutic strategies. Data from 216 participants (age range 50–81 years) of the population-based Study of Health in Pomerania TREND were included in our analysis. We investigated associations between spermidine plasma levels, key parameters of sleep macroarchitecture and microarchitecture that were previously associated with AD pathology, and brain health measured via a marker of structural brain atrophy (AD score). Higher spermidine levels were significantly associated with lower coupling between slow oscillations and spindle activity. No association was evident for SWS, slow oscillatory, and spindle activity throughout non-rapid eye movement sleep. Furthermore, elevated spermidine blood levels were significantly associated with a higher AD score, while sleep markers revealed no association with AD score. The association between higher spermidine levels and brain health was not mediated by coupling between slow oscillations and spindle activity. We report that higher spermidine blood levels are associated not only with deteriorated brain health but also with less advantageous markers of sleep quality in older adults. Future studies need to evaluate whether sleep, spermidine, and Aß/tau deposition are interrelated and whether sleep may play a mediating role.
Background
We investigated the association between low cardiorespiratory fitness and liver fat content (LFC) in the general population.
Materials and Methods
We evaluated data from 2151 adults (51.1% women) from two population-based cohorts of the Study of Health in Pomerania (SHIP-2 and SHIP-TREND-0). We analysed the cross-sectional associations of peak oxygen uptake (VO2peak) with LFC, assessed by magnetic resonance imaging proton density fat fraction, as well as serum gamma-glutamyltransferase (GGT) and aminotransferase concentrations by multivariable regression models.
Results
We observed significant inverse associations of VO2peak with LFC and serum GGT, but not with serum aminotransferase levels. Specifically, a 1 L/min lower VO2peak was associated with a 1.09% (95% confidence interval [CI]: 0.45-1.73; P = .002) higher LFC and a 0.18 μkatal/L (95% CI: 0.09-0.26; P < .001) higher GGT levels. The adjusted odds ratio (OR) for the risk of prevalent hepatic steatosis (HS) by a 1 L/min decrease in VO2peak was 1.61 (95% CI: 1.22-2.13; P = .001). Compared to subjects with high VO2peak, obese and overweight individuals with low VO2peak had 1.78% (95% CI: 0.32-3.25; P = .017) and 0.94% (95% CI: 0.15-1.74; P = .021) higher mean LFC, respectively. Compared to those with high VO2peak, low VO2peak was independently associated with a higher risk of prevalent HS in the obese (adjusted-OR 2.29, 95% CI=1.48-3.56; P < .001) and overweight (adjusted OR 1.57, 95% CI=1.16-2.14; P = .04) groups.
Conclusions
Lower VO2peak was significantly associated with greater LFC and higher serum GGT levels in a population-based cohort of adult individuals. Our results suggest that low VO2peak might be a risk factor for HS.
Background: The aim of our study was to investigate associations of spleen volume with blood count markers and lipid profile in the general population.
Materials & methods: Cross-sectional data from 1,106 individuals aged 30–90 years from the population-based Study of Health in Pomerania (SHIP-START-2) were analyzed. Blood count markers included red blood cell (RBC) counts, hemoglobin, platelet count, and white blood cell (WBC) counts. Lipid profile included total-cholesterol, high-density lipoprotein-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C) as well as triglycerides. Linear regression models adjusted for age, sex, body height, and weight were used to associate standardized spleen volume with blood counts and lipid profile markers.
Results: Spleen volume was positively associated with RBC (β = 0.05; 95% confidence interval [CI] = 0.03 to 0.08) and hemoglobin (β = 0.05; 95% CI = 0.01 to 0.09) but inversely with platelet count (β = −16.3; 95% CI = –20.5 to −12.1) and WBC (β = −0.25; 95% CI = −0.37 to −0.14). Furthermore, spleen volume showed inverse associations with total cholesterol (β = −0.17; 95% CI = −0.24 to −0.09), HDL-C (β = −0.08; 95% CI = −0.10 to −0.05), and LDL-C (β = −0.12; 95% CI = −0.17 to −0.06). There was no significant association of spleen volume with triglycerides.
Conclusion: Our study showed that the spleen volume is associated with markers of the blood count and lipid profile in the general population.
Background
In acute pancreatitis, secondary infection of pancreatic necrosis is a complication that mostly necessitates interventional therapy. A reliable prediction of infected necrotizing pancreatitis would enable an early identification of patients at risk, which however, is not possible yet.
Methods
This study aims to identify parameters that are useful for the prediction of infected necrosis and to develop a prediction model for early detection. We conducted a retrospective analysis from the hospital information and reimbursement data system and screened 705 patients hospitalized with diagnosis of acute pancreatitis who underwent contrast-enhanced computed tomography and additional diagnostic puncture or drainage of necrotic collections. Both clinical and laboratory parameters were analyzed for an association with a microbiologically confirmed infected pancreatic necrosis. A prediction model was developed using a logistic regression analysis with stepwise inclusion of significant variables. The model quality was tested by receiver operating characteristics analysis and compared to single parameters and APACHE II score.
Results
We identified a total of 89 patients with necrotizing pancreatitis, diagnosed by computed tomography, who additionally received biopsy or drainage. Out of these, 59 individuals had an infected necrosis. Eleven parameters showed a significant association with an infection including C-reactive protein, albumin, creatinine, and alcoholic etiology, which were independent variables in a predictive model. This model showed an area under the curve of 0.819, a sensitivity of 0.692 (95%-CI [0.547–0.809]), and a specificity of 0.840 (95%-CI [0.631–0.947]), outperforming single laboratory markers and APACHE II score. Even in cases of missing values predictability was reliable.
Conclusion
A model consisting of a few single blood parameters and etiology of pancreatitis might help for differentiation between infected and non-infected pancreatic necrosis and assist medical therapy in acute necrotizing pancreatitis.