Imaging of Nitric Oxide in Nitrergic Neuromuscular Neurotransmission in the Gut

Background: Numerous functional studies have shown that nitrergic neurotransmission plays a central role in peristalsis and sphincter relaxation throughout the gut and impaired nitrergic neurotransmission has been implicated in clinical disorders of all parts of the gut. However, the role of nitric oxide (NO) as a neurotransmitter continues to be controversial because: 1) the cellular site of production during neurotransmission is not well established; 2) NO may interacts with other inhibitory neurotransmitter candidates, making it difficult to understand its precise role. Methodology/Principal Findings: Imaging NO can help resolve many of the controversies regarding the role of NO in nitrergic neurotransmission. Imaging of NO and its cellular site of production is now possible. NO forms quantifiable fluorescent compound with diaminofluorescein (DAF) and allows imaging of NO with good specificity and sensitivity in living cells. In this report we describe visualization and regulation of NO and calcium ($Ca^{2+}$) in the myenteric nerve varicosities during neurotransmission using multiphoton microscopy. Our results in mice gastric muscle strips provide visual proof that NO is produced de novo in the nitrergic nerve varicosities upon nonadrenergic noncholinergic (NANC) nerve stimulation. These studies show that NO is a neurotransmitter rather than a mediator. Changes in NO production in response to various pharmacological treatments correlated well with changes in slow inhibitory junction potential of smooth muscles. Conclusions/Significance: Dual imaging and electrophysiologic studies provide visual proof that during nitrergic neurotransmission NO is produced in the nerve terminals. Such studies may help define whether NO production or its signaling pathway is responsible for impaired nitrergic neurotransmission in pathological states

The Brain Atlas Concordance Problem: Quantitative Comparison of Anatomical Parcellations

Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info

Psip1/p52 regulates posterior Hoxa genes through activation of lncRNA Hottip

Long noncoding RNAs (lncRNAs) have been implicated in various biological functions including the regulation of gene expression, however, the functionality of lncRNAs is not clearly understood and conflicting conclusions have often been reached when comparing different methods to investigate them. Moreover, little is known about the upstream regulation of lncRNAs. Here we show that the short isoform (p52) of a transcriptional co-activator—PC4 and SF2 interacting protein (Psip1), which is known to be involved in linking transcription to RNA processing, specifically regulates the expression of the lncRNA Hottip–located at the 5’ end of the Hoxa locus. Using both knockdown and knockout approaches we show that Hottip expression is required for activation of the 5’ Hoxa genes (Hoxa13 and Hoxa10/11) and for retaining Mll1 at the 5’ end of Hoxa. Moreover, we demonstrate that artificially inducing Hottip expression is sufficient to activate the 5’ Hoxa genes and that Hottip RNA binds to the 5’ end of Hoxa. By engineering premature transcription termination, we show that it is the Hottip lncRNA molecule itself, not just Hottip transcription that is required to maintains active expression of posterior Hox genes. Our data show a direct role for a lncRNA molecule in regulating the expression of developmentally-regulated mRNA genes in cis

Genome-Wide Detection of Allele Specific Copy Number Variation Associated with Insulin Resistance in African Americans from the HyperGEN Study

African Americans have been understudied in genome wide association studies of diabetes and related traits. In the current study, we examined the joint association of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with fasting insulin and an index of insulin resistance (HOMA-IR) in the HyperGEN study, a family based study with proband ascertainment for hypertension. This analysis is restricted to 1,040 African Americans without diabetes. We generated allele specific CNV genotypes at 872,243 autosomal loci using Birdsuite, a freely available multi-stage program. Joint tests of association for SNPs and CNVs were performed using linear mixed models adjusting for covariates and familial relationships. Our results highlight SNPs associated with fasting insulin and HOMA-IR (rs6576507 and rs8026527, 3.7*10−7≤P≤1.1*10−5) near ATPase, class V, type 10A (ATP10A), and the L Type voltage dependent calcium channel (CACNA1D, rs1401492, P≤5.2*10−6). ATP10A belongs to a family of aminophospholipid-transporting ATPases and has been associated with type 2 diabetes in mice. CACNA1D has been linked to pancreatic beta cell generation in mice. The two most significant copy variable markers (rs10277702 and rs361367; P<2.0*10−4) were in the beta variable region of the T-cell receptor gene (TCRVB). Human and mouse TCR has been shown to mimic insulin and its receptor and could contribute to insulin resistance. Our findings differ from genome wide association studies of fasting insulin and other diabetes related traits in European populations, highlighting the continued need to investigate unique genetic influences for understudied populations such as African Americans

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p