Use of Antihypertensive Agents and Association With Risk of Adverse Outcomes in Chronic Kidney Disease: Focus on Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers.

Background Our objective was to determine patterns of antihypertensive agent use by stage of chronic kidney disease (CKD) and to evaluate the association between different classes of antihypertensive agents with nonrenal outcomes, especially in advanced CKD . Methods and Results We studied 3939 participants of the CRIC (Chronic Renal Insufficiency Cohort) study. Predictors were time-dependent angiotensin-converting enzyme inhibitor or angiotensin receptor blocker , β-blocker, and calcium channel blocker use (versus nonuse of agents in each class). Outcomes were adjudicated heart failure events or death. Adjusted Cox models were used to determine the association between predictors and outcomes. We also examined whether the associations differed based on the severity of CKD (early [stage 2-3 CKD ] versus advanced disease [stage 4-5 CKD ]). During median follow-up of 7.5 years, renin-angiotensin-aldosterone system inhibitor use plateaued during CKD stage 3 (75%) and declined to 37% by stage 5, while β-blocker, calcium channel blocker, and diuretic use increased steadily with advancing CKD . Renin-angiotensin-aldosterone system inhibitor use was associated with lower risk of heart failure (hazard ratio, 0.79; 95% confidence interval, 0.67-0.97) and death (hazard ratio, 0.78; 95% confidence interval, 0.67-0.90), regardless of severity of CKD . Calcium channel blocker use was not associated with risk of heart failure or death, regardless of the severity of CKD . β-Blocker use was associated with higher risk of heart failure (hazard ratio, 1.62; 95% confidence interval, 1.29-2.04) and death (hazard ratio, 1.22; 95% confidence interval, 1.03-1.43), especially during early CKD ( P<0.05 for interaction). Conclusions Angiotensin-converting enzyme inhibitor and angiotensin receptor blocker use decreased, while use of other agents increased with advancing CKD . Use of agents besides angiotensin-converting enzyme inhibitors or angiotensin receptor blockers may be associated with suboptimal outcomes in patients with CKD

Novel Anemia Therapies in CKD: Conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Anemia is common in patients with chronic kidney disease (CKD) and is associated with a high burden of morbidity and adverse clinical outcomes. In 2012, Kidney Disease: Improving Global Outcomes (KDIGO) published a guideline for the diagnosis and management of anemia in CKD. Since then, new data from studies assessing established and emerging therapies for the treatment of anemia and iron deficiency have become available. Beginning in 2019, KDIGO planned two Controversies Conferences to review the new evidence and its potential impact on the management of anemia in clinical practice. Here we report on the second of these conferences held virtually in December 2021 which focused on a new class of agents, the hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHIs). This report provides a review of the consensus points and controversies from this second conference and highlights areas that warrant prioritization for future research

Lpd depletion reveals that SRF specifies radial versus tangential migration of pyramidal neurons

During corticogenesis, pyramidal neurons (~80% of cortical neurons) arise from the ventricular zone, pass through a multipolar stage to become bipolar and attach to radial glia[superscript 1, 2], and then migrate to their proper position within the cortex[superscript 1, 3]. As pyramidal neurons migrate radially, they remain attached to their glial substrate as they pass through the subventricular and intermediate zones, regions rich in tangentially migrating interneurons and axon fibre tracts. We examined the role of lamellipodin (Lpd), a homologue of a key regulator of neuronal migration and polarization in Caenorhabditis elegans, in corticogenesis. Lpd depletion caused bipolar pyramidal neurons to adopt a tangential, rather than radial-glial, migration mode without affecting cell fate. Mechanistically, Lpd depletion reduced the activity of SRF, a transcription factor regulated by changes in the ratio of polymerized to unpolymerized actin. Therefore, Lpd depletion exposes a role for SRF in directing pyramidal neurons to select a radial migration pathway along glia rather than a tangential migration mode.Ruth L. Kirschstein National Research Service Award (grant F32- GM074507)National Institutes of Health (U.S.) (grant # GM068678

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20\%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD. © 2013 Liu et al

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A consensus protocol for functional connectivity analysis in the rat brain

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience