miR-132-3p and KLF7 as novel regulators of aortic stiffening-associated EndMT in type 2 diabetes mellitus

Background: The prevalence of diabetes mellitus has risen considerably and currently affects more than 422 million people worldwide. Cardiovascular diseases including myocardial infarction and heart failure represent the major cause of death in type 2 diabetes (T2D). Diabetes patients exhibit accelerated aortic stiffening which is an independent predictor of cardiovascular disease and mortality. We recently showed that aortic stiffness precedes hypertension in a mouse model of diabetes (db/db mice), making aortic stiffness an early contributor to cardiovascular disease development. Elucidating how aortic stiffening develops is a pressing need in order to halt the pathophysiological process at an early time point. Methods: To assess EndMT occurrence, we performed co-immunofluorescence staining of an endothelial marker (CD31) with mesenchymal markers (α-SMA/S100A4) in aortic sections from db/db mice. Moreover, we performed qRT-PCR to analyze mRNA expression of EndMT transcription factors in aortic sections of db/db mice and diabetic patients. To identify the underlying mechanism by which EndMT contributes to aortic stiffening, we used aortas from db/db mice and diabetic patients in combination with high glucose-treated human umbilical vein endothelial cells (HUVECs) as an in vitro model of diabetes-associated EndMT. Results: We demonstrate robust CD31/α-SMA and CD31/S100A4 co-localization in aortic sections of db/db mice which was almost absent in control mice. Moreover, we demonstrate a significant upregulation of EndMT transcription factors in aortic sections of db/db mice and diabetic patients. As underlying regulator, we identified miR-132-3p as the most significantly downregulated miR in the micronome of db/db mice and high glucose-treated HUVECs. Indeed, miR-132-3p was also significantly downregulated in aortic tissue from diabetic patients. We identified Kruppel-like factor 7 (KLF7) as a target of miR-132-3p and show a significant upregulation of KLF7 in aortic sections of db/db mice and diabetic patients as well as in high glucose-treated HUVECs. We further demonstrate that miR-132-3p overexpression and KLF7 downregulation ameliorates EndMT in high glucose-treated HUVECs. Conclusions: We demonstrate for the first time that EndMT contributes to aortic stiffening in T2D. We identified miR-132-3p and KLF7 as novel EndMT regulators in this context. Altogether, this gives us new insights in the development of aortic stiffening in T2D.</p

Specific methanogenic activity of halophilic and mixed cultures in saline wastewater

Wastewater containing high concentrations of salt, are difficult to treat using biological treatment processes, especially anaerobic processes. Limited information is available on methanogenic activity in saline environments. The objective of this research was to investigate the activity of halophilic methanogens, digester sludge and a mixed culture of halophilic and methanogenic bacteria, at various levels of salinity, in terms of lag period and specific methanogenic activity (SMA) at two temperatures. For the halophilic bacteria at 35 °C, the initial SMA ranged from 0.46 to 0.90 g acetate/g VSS.d, but decreased at higher salt concentrations. The maximum SMA varied from 1.2 to 2.08 g acetate/g VSS.d. High sodium chloride concentrations had a significant adverse effect on digester sludge. At 25°C, at salt concentrations of 30 g/l and above, the digester sludge could not acclimate even in 50 days. Little difference was observed in the maximum SMA of mixed culture and halophilic bacteria at high salt concentrations of 40 -50 g/l

Impact of Endoscopic Ultrasonography on (18)F-FDG-PET/CT Upfront Towards Patient Specific Esophageal Cancer Treatment

INTRODUCTION: In patients with potentially resectable esophageal cancer (EC), the value of endoscopic ultrasonography (EUS) after fluorine-18 labeled fluorodeoxyglucose positron emission tomography with computed tomography ((18)F-FDG-PET/CT) is questionable. Retrospectively, we assessed the impact of EUS after PET/CT on the given treatment in EC patients. METHODS: During the period 2009-2015, 318 EC patients were staged as T1-4aN0-3M0 with hybrid (18)F-FDG-PET/CT or (18)F-FDG-PET with CT and EUS if applicable in a nonspecific order. We determined the impact of EUS on the given treatment in 279 patients who also were staged with EUS. EUS had clinical consequences if it changed curability, extent of radiation fields or lymph node resection (AJCC stations 2-5), and when the performed fine-needle aspiration (FNA) provided conclusive information of suspicious lymph node. RESULTS: EUS had an impact in 80 (28.7%) patients; it changed the radiation field in 63 (22.6%), curability in 5 (1.8%), lymphadenectomy in 48 (17.2%), and FNA was additional in 21 (7.5%). In patients treated with nCRT (n = 194), EUS influenced treatment in 53 (27.3%) patients; in 38 (19.6%) the radiation field changed, in 3 (1.5%) the curability, in 35 (18.0%) the lymphadenectomy, and in 17 (8.8%) FNA was additional. EUS influenced both the extent of radiation field and nodal resection in 31 (16.0%) nCRT patients. CONCLUSIONS: EUS had an impact on the given treatment in approximately 29%. In most patients, the magnitude of EUS found expression in the extent of radiotherapy target volume delineation to upper/high mediastinal lymph nodes

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia

We performed a systematic analysis of blood DNA methylation profiles from 4,483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1,048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia

White Matter Development in Early Puberty: A Longitudinal Volumetric and Diffusion Tensor Imaging Twin Study

White matter microstructure and volume show synchronous developmental patterns in children. White matter volume increases considerably during development. Fractional anisotropy, a measure for white matter microstructural directionality, also increases with age. Development of white matter volume and development of white matter microstructure seem to go hand in hand. The extent to which the same or different genetic and/or environmental factors drive these two aspects of white matter maturation is currently unknown. We mapped changes in white matter volume, surface area and diffusion parameters in mono- and dizygotic twins who were scanned at age 9 (203 individuals) and again at age 12 (126 individuals). Over the three-year interval, white matter volume (+6.0%) and surface area (+1.7%) increased, fiber bundles expanded (most pronounced in the left arcuate fasciculus and splenium), and fractional anisotropy increased (+3.0%). Genes influenced white matter volume (heritability ∼85%), surface area (∼85%), and fractional anisotropy (locally 7% to 50%) at both ages. Finally, volumetric white matter growth was negatively correlated with fractional anisotropy increase (r = –0.62) and this relationship was driven by environmental factors. In children who showed the most pronounced white matter growth, fractional anisotropy increased the least and vice-versa. Thus, white matter development in childhood may reflect a process of both expansion and fiber optimization

Differential Brain Development with Low and High IQ in Attention-Deficit/Hyperactivity Disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) and intelligence (IQ) are both heritable phenotypes. Overlapping genetic effects have been suggested to influence both, with neuroimaging work suggesting similar overlap in terms of morphometric properties of the brain. Together, this evidence suggests that the brain changes characteristic of ADHD may vary as a function of IQ. This study investigated this hypothesis in a sample of 108 children with ADHD and 106 typically developing controls, who participated in a cross-sectional anatomical MRI study. A subgroup of 64 children also participated in a diffusion tensor imaging scan. Brain volumes, local cortical thickness and average cerebral white matter microstructure were analyzed in relation to diagnostic group and IQ. Dimensional analyses investigated possible group differences in the relationship between anatomical measures and IQ. Second, the groups were split into above and below median IQ subgroups to investigate possible differences in the trajectories of cortical development. Dimensionally, cerebral gray matter volume and cerebral white matter microstructure were positively associated with IQ for controls, but not for ADHD. In the analyses of the below and above median IQ subgroups, we found no differences from controls in cerebral gray matter volume in ADHD with below-median IQ, but a delay of cortical development in a number of regions, including prefrontal areas. Conversely, in ADHD with above-median IQ, there were significant reductions from controls in cerebral gray matter volume, but no local differences in the trajectories of cortical development

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h2 = 0.53–0.90, p < 10− 5), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3–90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain