Interactive exploration of adverse events and multimorbidity in CKD.

BACKGROUND AND HYPOTHESIS: Persons with chronic kidney disease (CKD) are at increased risk of adverse events, early mortality, and multimorbidity. A detailed overview of adverse event types and rates from a large CKD cohort under regular nephrological care is missing. We generated an interactive tool to enable exploration of adverse events and their combinations in the prospective, observational German CKD (GCKD) study. METHODS: The GCKD study enrolled 5217 participants under regular nephrological care with an estimated glomerular filtration rate of 30-60 or >60 mL/min/1.73m2 and an overt proteinuria. Cardio-, cerebro- and peripheral vascular, kidney, infection, and cancer events, as well as deaths were adjudicated following a standard operation procedure. We summarized these time-to-event data points for exploration in interactive graphs within an R shiny app. Multivariable adjusted Cox models for time to first event were fitted. Cumulative incidence functions, Kaplan-Meier curves and intersection plots were used to display main adverse events and their combinations by sex and CKD etiology. RESULTS: Over a median of 6.5 years, 10 271 events occurred in total and 680 participants (13.0%) died while 2947 participants (56.5%) experienced any event. The new publicly available interactive platform enables readers to scrutinize adverse events and their combinations as well as mortality trends as a gateway to better understand multimorbidity in CKD: incident rates per 1000 patient-years varied by event type, CKD etiology, and baseline characteristics. Incidence rates for the most frequent events and their recurrence were 113.6 (cardiovascular), 75.0 (kidney), and 66.0 (infection). Participants with diabetic kidney disease and men were more prone to experiencing events. CONCLUSION: This comprehensive explorative tool to visualize adverse events (https://gckd.diz.uk-erlangen.de/), their combination, mortality, and multimorbidity among persons with CKD may manifest as a valuable resource for patient care, identification of high-risk groups, health services, and public health policy planning.

Imaging Markers Derived From MRI-Based Automated Kidney Segmentation­an Analysis of Data From the German National Cohort (NAKO Gesundheitsstudie)

BACKGROUND: Population-wide research on potential new imaging biomarkers of the kidney depends on accurate automated segmentation of the kidney and its compartments (cortex, medulla, and sinus). METHODS: We developed a robust deep-learning framework for kidney (sub-)segmentation based on a hierarchical, three-dimensional convolutional neural network (CNN) that was optimized for multi-scale problems of combined localization and segmentation. We applied the CNN to abdominal magnetic resonance images from the population-based German National Cohort (NAKO) study. RESULTS: There was good to excellent agreement between the model predictions and manual segmentations. The median values for the body-surface normalized total kidney, cortex, medulla, and sinus volumes of 9934 persons were 158, 115, 43, and 24 mL/m2. Distributions of these markers are provided both for the overall study population and for a subgroup of persons without kidney disease or any associated conditions. Multivariable adjusted regression analyses revealed that diabetes, male sex, and a higher estimated glomerular filtration rate (eGFR) are important predictors of higher total and cortical volumes. Each increase of eGFR by one unit (i.e., 1 mL/min per 1.73 m2 body surface area) was associated with a 0.98 mL/m2 increase in total kidney volume, and this association was significant. Volumes were lower in persons with eGFR-defined chronic kidney disease. CONCLUSION: The extraction of image-based biomarkers through CNN-based renal sub-segmentation using data from a population-based study yields reliable results, forming a solid foundation for future investigations.

Epigenome-wide DNA methylation in obsessive-compulsive disorder.

In adult patients with obsessive-compulsive disorder (OCD), altered DNA methylation has been discerned in several candidate genes, while DNA methylation on an epigenome-wide level has been investigated in only one Chinese study so far. Here, an epigenome-wide association study (EWAS) was performed in a sample of 76 OCD patients of European ancestry (37 women, age ± SD: 33.51 ± 10.92 years) and 76 sex- and age-matched healthy controls for the first time using the Illumina MethylationEPIC BeadChip. After quality control, nine epigenome-wide significant quantitative trait methylation sites (QTMs) and 21 suggestive hits were discerned in the final sample of 68 patients and 68 controls. The top hit (cg24159721) and four other significant QTMs (cg11894324, cg01070250, cg11330075, cg15174812) map to the region of the microRNA 12136 gene (MIR12136). Two additional significant CpG sites (cg05740793, cg20450977) are located in the flanking region of the MT-RNR2 (humanin) like 8 gene (MT-RNRL8), while two further QTMs (cg16267121, cg15890734) map to the regions of the MT-RNR2 (humanin) like 3 (MT-RNRL3) and MT-RNR2 (humanin) like 2 (MT-RNRL2) genes. Provided replication of the present findings in larger samples, the identified QTMs might provide more biological insight into the pathogenesis of OCD and thereby could in the future serve as peripheral epigenetic markers of OCD risk with the potential to inform targeted preventive and therapeutic efforts.

Association of the metabolic syndrome with mortality and major adverse cardiac events: A large chronic kidney disease cohort.

BACKGROUND: Metabolic syndrome with its key components insulin resistance, central obesity, dyslipidaemia, and hypertension is associated with a high risk for cardiovascular events and all-cause mortality in the general population. However, evidence that these findings apply to patients with chronic kidney disease (CKD) with moderately reduced estimated glomerular filtration rate and/or albuminuria is limited. OBJECTIVES: We aimed to investigate the association between metabolic syndrome and its components with all-cause mortality and cardiovascular outcomes in CKD patients. METHODS: Prospective observation of a cohort of 5110 CKD patients from the German Chronic Kidney Disease study with 3284 (64.3%) of them having a metabolic syndrome at baseline. RESULTS: During the follow-up of 6.5 years, 605 patients died and 650 patients experienced major cardiovascular events. After extended data adjustment, patients with a metabolic syndrome had a higher risk for all-cause mortality (hazard ratio [HR] = 1.26, 95% confidence interval [CI]: 1.04-1.54) and cardiovascular events (HR = 1.48, 95% CI: 1.22-1.79). The risk increased steadily with a growing number of metabolic syndrome components (increased waist circumference, glucose, triglycerides, hypertension and decreased HDL cholesterol): HR per component = 1.09 (95% CI: 1.02-1.17) for all-cause mortality and 1.23 (95% CI: 1.15-1.32) for cardiovascular events. This resulted in hazard ratios between 1.50 and 2.50 in the case when four or five components are present. An analysis of individual components of metabolic syndrome showed that the glucose component led to the highest increase in risk for all-cause mortality (HR = 1.68, 95% CI: 1.38-2.03) and cardiovascular events (HR = 1.81, 95% CI: 1.51-2.18), followed by the HDL cholesterol and triglyceride components. CONCLUSIONS: We observed a high prevalence of metabolic syndrome among patients with moderate CKD. Metabolic syndrome increases the risk for all-cause mortality and cardiovascular events. The glucose and lipid components seem to be the main drivers for the association with outcomes.