Molecular reductions in glucokinase activity increase counter-regulatory responses to hypoglycemia in mice and humans with diabetes.

OBJECTIVE: Appropriate glucose levels are essential for survival; thus, the detection and correction of low blood glucose is of paramount importance. Hypoglycemia prompts an integrated response involving reduction in insulin release and secretion of key counter-regulatory hormones glucagon and epinephrine that together promote endogenous glucose production to restore normoglycemia. However, specifically how this response is orchestrated remains to be fully clarified. The low affinity hexokinase glucokinase is found in glucose-sensing cells involved in glucose homeostasis including pancreatic β-cells and in certain brain areas. Here, we aimed to examine the role of glucokinase in triggering counter-regulatory hormonal responses to hypoglycemia, hypothesizing that reduced glucokinase activity would lead to increased and/or earlier triggering of responses. METHODS: Hyperinsulinemic glucose clamps were performed to examine counter-regulatory responses to controlled hypoglycemic challenges created in humans with monogenic diabetes resulting from heterozygous glucokinase mutations (GCK-MODY). To examine the relative importance of glucokinase in different sensing areas, we then examined responses to clamped hypoglycemia in mice with molecularly defined disruption of whole body and/or brain glucokinase. RESULTS: GCK-MODY patients displayed increased and earlier glucagon responses during hypoglycemia compared with a group of glycemia-matched patients with type 2 diabetes. Consistent with this, glucagon responses to hypoglycemia were also increased in I366F mice with mutated glucokinase and in streptozotocin-treated β-cell ablated diabetic I366F mice. Glucagon responses were normal in conditional brain glucokinase-knockout mice, suggesting that glucagon release during hypoglycemia is controlled by glucokinase-mediated glucose sensing outside the brain but not in β-cells. For epinephrine, we found increased responses in GCK-MODY patients, in β-cell ablated diabetic I366F mice and in conditional (nestin lineage) brain glucokinase-knockout mice, supporting a role for brain glucokinase in triggering epinephrine release. CONCLUSIONS: Our data suggest that glucokinase in brain and other non β-cell peripheral hypoglycemia sensors is important in glucose homeostasis, allowing the body to detect and respond to a falling blood glucose.Yousef Jameel Fund Sir Jukes Thorn Trust Elmore Fund Chang Gung University College of Medicin

Impulsivity is a heritable trait in rodents and associated with a novel quantitative trait locus on chromosome 1

Abstract: Impulsivity describes the tendency to act prematurely without appropriate foresight and is symptomatic of a number of neuropsychiatric disorders. Although a number of genes for impulsivity have been identified, no study to date has carried out an unbiased, genome-wide approach to identify genetic markers associated with impulsivity in experimental animals. Herein we report a linkage study of a six-generational pedigree of adult rats phenotyped for one dimension of impulsivity, namely premature responding on the five-choice serial reaction time task, combined with genome wide sequencing and transcriptome analysis to identify candidate genes associated with the expression of the impulsivity trait. Premature responding was found to be heritable (h2 = 13–16%), with significant linkage (LOD 5.2) identified on chromosome 1. Fine mapping of this locus identified a number of polymorphic candidate genes, however only one, beta haemoglobin, was differentially expressed in both the founder strain and F6 generation. These findings provide novel insights into the genetic substrates and putative neurobiological mechanisms of impulsivity with broader translational relevance for impulsivity-related disorders in humans

Transcriptional Landscape of the Prenatal Human Brain

Summary The anatomical and functional architecture of the human brain is largely determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and postmitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and human-expanded outer subventricular zones. Both germinal and postmitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in frontal lobe. Finally, many neurodevelopmental disorder and human evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

Differential predictors for alcohol use in adolescents as a function of familial risk

Abstract: Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties