CKD prevalence estimation is central to CKD management and prevention planning at the population level. This study estimated CKD prevalence in the European adult general population and investigated ...international variation in CKD prevalence by age, sex, and presence of diabetes, hypertension, and obesity. We collected data from 19 general-population studies from 13 European countries. CKD stages 1-5 was defined as eGFR<60 ml/min per 1.73 m(2), as calculated by the CKD-Epidemiology Collaboration equation, or albuminuria >30 mg/g, and CKD stages 3-5 was defined as eGFR<60 ml/min per 1.73 m(2) CKD prevalence was age- and sex-standardized to the population of the 27 Member States of the European Union (EU27). We found considerable differences in both CKD stages 1-5 and CKD stages 3-5 prevalence across European study populations. The adjusted CKD stages 1-5 prevalence varied between 3.31% (95% confidence interval 95% CI, 3.30% to 3.33%) in Norway and 17.3% (95% CI, 16.5% to 18.1%) in northeast Germany. The adjusted CKD stages 3-5 prevalence varied between 1.0% (95% CI, 0.7% to 1.3%) in central Italy and 5.9% (95% CI, 5.2% to 6.6%) in northeast Germany. The variation in CKD prevalence stratified by diabetes, hypertension, and obesity status followed the same pattern as the overall prevalence. In conclusion, this large-scale attempt to carefully characterize CKD prevalence in Europe identified substantial variation in CKD prevalence that appears to be due to factors other than the prevalence of diabetes, hypertension, and obesity.
To analyse the prevalence, incidence and clinical relevance of pancreatic cysts detected as incidental finding in a population-based longitudinal study.
A total of 1077 participants (521 men, mean ...age 55.8±12.8 years) of 2333 participants from the population-based Study of Health in Pomerania (SHIP) underwent magnetic resonance cholangiopancreaticography (MRCP) at baseline (2008-2012). MRCP was analysed for pancreatic cysts with a diameter ≥2 mm. 676/1077 subjects received a 5-year follow-up (2014-2016). The prevalence and incidence of pancreatic cysts (weighted for study participation) were assessed in association to age, gender and suspected epidemiological risk factors. Mortality follow-up was performed in 2015 for all SHIP participants (mean follow-up period 5.9 years, range 3.2-7.5 years).
At baseline pancreatic cysts had a weighted prevalence of 49.1%, with an average number of 3.9 (95% CI 3.2 to 4.5) cysts per subject in the subgroup harbouring cysts. Cyst size ranged from 2 to 29 mm. Prevalence (p<0.001), number (p=0.001) and maximum size (p<0.001) increased significantly with age. The 5-year follow-up revealed a weighted incidence of 12.9% newly detected pancreatic cysts. 57.1% of the subjects initially harbouring pancreatic cysts showed an increase in number and/or maximum cyst size. Of all subjects undergoing MRCP, no participant died of pancreatic diseases within mortality follow-up.
The prevalence of pancreatic cysts in the general population is unexpectedly high, and their number and size increase with age. Overall, no pancreatic cancer was observed in this collective during a 5-year follow-up. Nevertheless, prospective follow-up imaging showed minimal progress in more than 50%. Only about 6% of cysts and 2.5% of the study group initially presented with cysts of more than 1 cm and thus might be clinically meaningful.
Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In ...particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing individuals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer's disease, have also been identified using machine learning. Prior efforts to derive these indices have been hampered by the need for sophisticated and not easily reproducible processing steps, by insufficiently powered or diversified samples from which typical brain ageing trajectories were derived, and by limited reproducibility across populations and MRI scanners. Herein, we develop and test a sophisticated deep brain network (DeepBrainNet) using a large (n = 11 729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages and geographic locations around the world. Tests using both cross-validation and a separate replication cohort of 2739 individuals indicate that DeepBrainNet obtains robust brain-age estimates from these diverse datasets without the need for specialized image data preparation and processing. Furthermore, we show evidence that moderately fit brain ageing models may provide brain age estimates that are most discriminant of individuals with pathologies. This is not unexpected as tightly-fitting brain age models naturally produce brain-age estimates that offer little information beyond age, and loosely fitting models may contain a lot of noise. Our results offer some experimental evidence against commonly pursued tightly-fitting models. We show that the moderately fitting brain age models obtain significantly higher differentiation compared to tightly-fitting models in two of the four disease groups tested. Critically, we demonstrate that leveraging DeepBrainNet, along with transfer learning, allows us to construct more accurate classifiers of several brain diseases, compared to directly training classifiers on patient versus healthy control datasets or using common imaging databases such as ImageNet. We, therefore, derive a domain-specific deep network likely to reduce the need for application-specific adaptation and tuning of generic deep learning networks. We made the DeepBrainNet model freely available to the community for MRI-based evaluation of brain health in the general population and over the lifespan.
As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying ...acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3–96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease.
•Multi-site harmonization method that pools volumetric data from 18 studies, controlling for nonlinear age effects.•Resulting dataset covers ages 3 to 96 and used to derive age trends of brain structure through the lifespan.•Interactive visualization tool provided for exploring age trends and comparing new data.
Irisin is a myokine, which is mainly inversely associated with the risk for non-communicable diseases. Irisin improves cellular energy metabolism by uncoupling the mitochondrial respiratory chain ...resulting in increased energy expenditure using lipids. To date potential associations between irisin concentration and lipid profile are poorly understood. Therefore, this investigation aimed to evaluate potential associations between irisin and lipid levels in the general population.
Data of 430 men and 537 women from the population-based Study of Health in Pomerania (SHIP-TREND) with available irisin and lipid concentrations were used. Analyses of variance, linear and logistic regression models adjusted for age, HBA1c, waist circumference, physical activity, smoking, alcohol consumption, systolic blood pressure, ALAT were calculated.
We detected significantly inverse associations between irisin and circulating levels of total beta coefficient 0.21 (standard error 0.08), p = 0.01, low-density cholesterol -0.16 (0.07), p = 0.03 and triglycerides -0.17 (0.08), p = 0.02 for men. Females without lipid lowering medication had an inverse association between irisin and total cholesterol -0.12 (0.06), p = 0.05. Further, male subjects with irisin concentrations in the third tertile had an increased odds for elevated low-density cholesterol odds ratio 1.96 (95% confidence interval 1.07-3.48), p = 0.03) and triglyceride 1.95 (1.09-3.47), p = 0.02 levels, even after exclusion of subjects with lipid lowering medication. In addition, our data revealed an annual rhythm of serum irisin levels with peak levels arise in winter and summer months.
This is the first investigation to report a significant association between circulating irisin and a favourable lipid profile in the general population. This may infer that higher irisin concentrations are associated with a reduced risk for non-communicable diseases.
Context: To date, it is unclear which measure of obesity is the most appropriate for risk stratification.
Objective: The aim of the study was to compare the associations of various measures of ...obesity with incident cardiovascular events and mortality.
Design and Setting: We analyzed two German cohort studies, the DETECT study and SHIP, including primary care and general population.
Participants: A total of 6355 (mean follow-up, 3.3 yr) and 4297 (mean follow-up, 8.5 yr) individuals participated in DETECT and SHIP, respectively.
Interventions: We measured body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR) and assessed cardiovascular and all-cause mortality and the composite endpoint of incident stroke, myocardial infarction, or cardiovascular death.
Results: In both studies, we found a positive association of the composite endpoint with WHtR but not with BMI. There was no heterogeneity among studies. The relative risks in the highest versus the lowest sex- and age-specific quartile of WHtR, WC, WHR, and BMI after adjustment for multiple confounders were as follows in the pooled data: cardiovascular mortality, 2.75 (95% confidence interval, 1.31–5.77), 1.74 (0.84–3.6), 1.71 (0.91–3.22), and 0.74 (0.35–1.57), respectively; all-cause mortality, 1.86 (1.25–2.76), 1.62 (1.22–2.38), 1.36 (0.93–1.69), and 0.77 (0.53–1.13), respectively; and composite endpoint, 2.16 (1.39–3.35), 1.59 (1.04–2.44), 1.49 (1.07–2.07), and 0.57 (0.37–0.89), respectively. Separate analyses of sex and age groups yielded comparable results. Receiver operating characteristics analysis yielded the highest areas under the curve for WHtR for predicting these endpoints.
Conclusions: WHtR represents the best predictor of cardiovascular risk and mortality, followed by WC and WHR. Our results discourage the use of the BMI.
Measures of abdominal obesity but not body mass index predict cardiovascular risk and mortality.
Metabolic syndrome (MetS) remains a controversial entity. Specific clusters of MetS components - rather than MetS per se - are associated with accelerated arterial ageing and with cardiovascular (CV) ...events. To investigate whether the distribution of clusters of MetS components differed cross-culturally, we studied 34,821 subjects from 12 cohorts from 10 European countries and one cohort from the USA in the MARE (Metabolic syndrome and Arteries REsearch) Consortium.
In accordance with the ATP III criteria, MetS was defined as an alteration three or more of the following five components: elevated glucose (G), fasting glucose ≥110 mg/dl; low HDL cholesterol, < 40mg/dl for men or <50 mg/dl for women; high triglycerides (T), ≥150 mg/dl; elevated blood pressure (B), ≥130/≥85 mmHg; abdominal obesity (W), waist circumference >102 cm for men or >88 cm for women.
MetS had a 24.3% prevalence (8468 subjects: 23.9% in men vs. 24.6% in women, p < 0.001) with an age-associated increase in its prevalence in all the cohorts. The age-adjusted prevalence of the clusters of MetS components previously associated with greater arterial and CV burden differed across countries (p < 0.0001) and in men and women (p < 0.0001). In details, the cluster TBW was observed in 12% of the subjects with MetS, but was far more common in the cohorts from the UK (32.3%), Sardinia in Italy (19.6%), and Germany (18.5%) and less prevalent in the cohorts from Sweden (1.2%), Spain (2.6%), and the USA (2.5%). The cluster GBW accounted for 12.7% of subjects with MetS with higher occurrence in Southern Europe (Italy, Spain, and Portugal: 31.4, 18.4, and 17.1% respectively) and in Belgium (20.4%), than in Northern Europe (Germany, Sweden, and Lithuania: 7.6, 9.4, and 9.6% respectively).
The analysis of the distribution of MetS suggested that what follows under the common definition of MetS is not a unique entity rather a constellation of cluster of MetS components, likely selectively risky for CV disease, whose occurrence differs across countries.
We analyzed the putative association between abdominal obesity (measured in waist circumference) and gray matter volume (Study of Health in Pomerania: SHIP-2, N=758) adjusted for age and gender by ...applying volumetric analysis and voxel-based morphometry (VBM) with VBM8 to brain magnetic resonance (MR) imaging.
We sought replication in a second, independent population sample (SHIP-TREND, N=1586). In a combined analysis (SHIP-2 and SHIP-TREND) we investigated the impact of hypertension, type II diabetes and blood lipids on the association between waist circumference and gray matter. Volumetric analysis revealed a significant inverse association between waist circumference and gray matter volume. VBM in SHIP-2 indicated distinct inverse associations in the following structures for both hemispheres: frontal lobe, temporal lobes, pre- and postcentral gyrus, supplementary motor area, supramarginal gyrus, insula, cingulate gyrus, caudate nucleus, olfactory sulcus, para-/hippocampus, gyrus rectus, amygdala, globus pallidus, putamen, cerebellum, fusiform and lingual gyrus, (pre-) cuneus and thalamus. These areas were replicated in SHIP-TREND. More than 76% of the voxels with significant gray matter volume reduction in SHIP-2 were also distinct in TREND. These brain areas are involved in cognition, attention to interoceptive signals as satiety or reward and control food intake. Due to our cross-sectional design we cannot clarify the causal direction of the association. However, previous studies described an association between subjects with higher waist circumference and future cognitive decline suggesting a progressive brain alteration in obese subjects. Pathomechanisms may involve chronic inflammation, increased oxidative stress or cellular autophagy associated with obesity.
•Highly significant associations between abdominal obesity and reduced gray matter volume•76% of the areas with gray matter volume differences were replicated in an independent sample.•Adjustment for metabolic factors did not change results.
Chronological age is one of the most important risk factors for adverse clinical outcome. Still, two individuals at the same chronological age could have different biological aging states, leading to ...different individual risk profiles. Capturing this individual variance could constitute an even more powerful predictor enhancing prediction in age-related morbidity. Applying a nonlinear regression technique, we constructed a metabonomic measurement for biological age, the metabolic age score, based on urine data measured via 1H NMR spectroscopy. We validated the score in two large independent population-based samples by revealing its significant associations with chronological age and age-related clinical phenotypes as well as its independent predictive value for survival over approximately 13 years of follow-up. Furthermore, the metabolic age score was prognostic for weight loss in a sample of individuals who underwent bariatric surgery. We conclude that the metabolic age score is an informative measurement of biological age with possible applications in personalized medicine.
To analyze the association between cardiorespiratory fitness (CRF) and global and local brain volumes.
We studied 2103 adults (21-84 years old) from 2 independent population-based cohorts (Study of ...Health in Pomerania, examinations from June 25, 2008, through September 30, 2012). Cardiorespiratory fitness was measured using peak oxygen uptake (VO
peak), oxygen uptake at the anaerobic threshold (VO
@AT), and maximal power output from cardiopulmonary exercise testing on a bicycle ergometer. Magnetic resonance imaging brain data were analyzed by voxel-based morphometry using regression models with adjustment for age, sex, education, smoking, body weight, systolic blood pressure, glycated hemoglobin level, and intracranial volume.
Volumetric analyses revealed associations of CRF with gray matter (GM) volume and total brain volume. After multivariable adjustment, a 1-standard deviation increase in VO
peak was related to a 5.31 cm³ (95% CI, 3.27 to 7.35 cm³) higher GM volume. Whole-brain voxel-based morphometry analyses revealed significant positive relations between CRF and local GM volumes. The VO
peak was strongly associated with GM volume of the left middle temporal gyrus (228 voxels), the right hippocampal gyrus (146 voxels), the left orbitofrontal cortex (348 voxels), and the bilateral cingulate cortex (68 and 43 voxels).
Cardiorespiratory fitness was positively associated with GM volume, total brain volume, and specific GM and white matter clusters in brain areas not primarily involved in movement processing. These results, from a representative population sample, suggest that CRF might contribute to improved brain health and might, therefore, decelerate pathology-specific GM decrease.
PDF
