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Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions.
Major depression is a common and severe psychiatric disorder with a highly polygenic genetic architecture. Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with major depression, but the exact causal genes and biological mechanisms are largely unknown. Tissue-specific network approaches may identify molecular mechanisms underlying major depression and provide a biological substrate for integrative analyses. We provide a framework for the identification of individual risk genes and gene co-expression networks using genome-wide association summary statistics and gene expression information across multiple human brain tissues and whole blood. We developed a novel gene-based method called eMAGMA that leverages tissue-specific eQTL information to identify 99 biologically plausible risk genes associated with major depression, of which 58 are novel. Among these novel associations is Complement Factor 4A (C4A), recently implicated in schizophrenia through its role in synaptic pruning during postnatal development. Major depression risk genes were enriched in gene co-expression modules in multiple brain tissues and the implicated gene modules contained genes involved in synaptic signalling, neuronal development, and cell transport pathways. Modules enriched with major depression signals were strongly preserved across brain tissues, but were weakly preserved in whole blood, highlighting the importance of using disease-relevant tissues in genetic studies of psychiatric traits. We identified tissue-specific genes and gene co-expression networks associated with major depression. Our novel analytical framework can be used to gain fundamental insights into the functioning of the nervous system in major depression and other brain-related traits.
Because the white matter of the cerebral cortex contains axons that connect distant neurons in the cortical gray matter, the relationship between the volumes of the 2 cortical compartments is key for information transmission in the brain. It has been suggested that the volume of the white matter scales universally as a function of the volume of the gray matter across mammalian species, as would be expected if a global principle of wiring minimization applied. Using a systematic analysis across several mammalian clades, here we show that the volume of the white matter does not scale universally with the volume of the gray matter across mammals and is not optimized for wiring minimization. Instead, the ratio between volumes of gray and white matter is universally predicted by the same equation that predicts the degree of folding of the cerebral cortex, given the clade-specific scaling of cortical thickness, such that the volume of the gray matter (or the ratio of gray to total cortical volumes) divided by the square root of cortical thickness is a universal function of total cortical volume, regardless of the number of cortical neurons. Thus, the very mechanism that we propose to generate cortical folding also results in compactness of the white matter to a predictable degree across a wide variety of mammalian species.
Evolutionary changes in enhancers are widely associated with variation in human traits and diseases. However, studies comprehensively quantifying levels of selection on enhancers at multiple evolutionary periods during recent human evolution and how enhancer evolution varies across human tissues are lacking. To address these questions, we integrated a dataset of 41,561 transcribed enhancers active in 41 different human tissues (FANTOM Consortium) with whole genome sequences of 1,668 individuals from the African, Asian, and European populations (1000 Genomes Project). Our analyses based on four different metrics (Tajima's , , H12, ) showed that ∼5.90% of enhancers showed evidence of recent positive selection and that genes associated with enhancers under very recent positive selection are enriched for diverse immune-related functions. The distributions of these metrics for brain and testis enhancers were often statistically significantly different and in the direction suggestive of less positive selection compared to those of other tissues; the same was true for brain and testis enhancers that are tissue-specific compared to those that are tissue-broad and for testis enhancers associated with tissue-enriched and non-tissue-enriched genes. These differences varied considerably across metrics and tissues and were generally in the form of changes in distributions' shapes rather than shifts in their values. Collectively, these results suggest that many human enhancers experienced recent positive selection throughout multiple time periods in human evolutionary history, that this selection occurred in a tissue-dependent and immune-related functional context, and that much like the evolution of their protein-coding gene counterparts, the evolution of brain and testis enhancers has been markedly different from that of enhancers in other tissues.
Copyright © 2019 Moon et al.
The genetic architecture of psychiatric disorders is characterized by a large number of small-effect variants located primarily in non-coding regions, suggesting that the underlying causal effects may influence disease risk by modulating gene expression. We provide comprehensive analyses using transcriptome data from an unprecedented collection of tissues to gain pathophysiological insights into the role of the brain, neuroendocrine factors (adrenal gland) and gastrointestinal systems (colon) in psychiatric disorders. In each tissue, we perform PrediXcan analysis and identify trait-associated genes for schizophrenia (n associations = 499; n unique genes = 275), bipolar disorder (n associations = 17; n unique genes = 13), attention deficit hyperactivity disorder (n associations = 19; n unique genes = 12) and broad depression (n associations = 41; n unique genes = 31). Importantly, both PrediXcan and summary-data-based Mendelian randomization/heterogeneity in dependent instruments analyses suggest potentially causal genes in non-brain tissues, showing the utility of these tissues for mapping psychiatric disease genetic predisposition. Our analyses further highlight the importance of joint tissue approaches as 76% of the genes were detected only in difficult-to-acquire tissues.
Annexin proteins function as Ca-dependent regulators of membrane trafficking and repair that may also modulate membrane curvature. Here, using high-resolution confocal imaging, we report that the intestine-specific annexin A13 (ANX A13) localizes to the tips of intestinal microvilli and determined the crystal structure of the ANX A13a isoform to 2.6 Å resolution. The structure revealed that the N terminus exhibits an alternative fold that converts the first two helices and the associated helix-loop-helix motif into a continuous α-helix, as stabilized by a domain-swapped dimer. We also found that the dimer is present in solution and partially occludes the membrane-binding surfaces of annexin, suggesting that dimerization may function as a means for regulating membrane binding. Accordingly, as revealed by binding and cellular localization assays, ANX A13a variants that favor a monomeric state exhibited increased membrane association relative to variants that favor the dimeric form. Together, our findings support a mechanism for how the association of the ANX A13a isoform with the membrane is regulated.
© 2019 McCulloch et al.
OBJECTIVE - Glucose is the major energy substrate of the brain and crucial for normal brain function. In diabetes, the brain is subject to episodes of hypo- and hyperglycemia resulting in acute outcomes ranging from confusion to seizures, while chronic metabolic dysregulation puts patients at increased risk for depression and Alzheimer's disease. In the present study, we aimed to determine how glucose is metabolized in different regions of the brain using imaging mass spectrometry (IMS).
METHODS - To examine the relative abundance of glucose and other metabolites in the brain, mouse brain sections were subjected to imaging mass spectrometry at a resolution of 100 μm. This was correlated with immunohistochemistry, qPCR, western blotting and enzyme assays of dissected brain regions to determine the relative contributions of the glycolytic and pentose phosphate pathways to regional glucose metabolism.
RESULTS - In brain, there are significant regional differences in glucose metabolism, with low levels of hexose bisphosphate (a glycolytic intermediate) and high levels of the pentose phosphate pathway (PPP) enzyme glucose-6-phosphate dehydrogenase (G6PD) and PPP metabolite hexose phosphate in thalamus compared to cortex. The ratio of ATP to ADP is significantly higher in white matter tracts, such as corpus callosum, compared to less myelinated areas. While the brain is able to maintain normal ratios of hexose phosphate, hexose bisphosphate, ATP, and ADP during fasting, fasting causes a large increase in cortical and hippocampal lactate.
CONCLUSION - These data demonstrate the importance of direct measurement of metabolic intermediates to determine regional differences in brain glucose metabolism and illustrate the strength of imaging mass spectrometry for investigating the impact of changing metabolic states on brain function at a regional level with high resolution.
Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.
We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.
Copyright © 2018 Elsevier Inc. All rights reserved.
We have previously reported that the dispersion of spin-lattice relaxation rates in the rotating frame (R ) of tissue water protons at high field can be dominated by chemical exchange contributions. Ischemia in brain causes changes in tissue pH, which in turn may affect proton exchange rates. Amide proton transfer (APT, a form of chemical exchange saturation transfer) has been shown to be sensitive to chemical exchange rates and able to detect pH changes non-invasively following ischemic stroke. However, the specificity of APT to pH changes is decreased because of the influence of several other factors that affect magnetization transfer. R is less influenced by such confounding factors and thus may be more specific for detecting variations in pH. Here, we applied a spin-locking sequence to detect ischemic stroke in animal models. Although R images acquired with a single spin-locking amplitude (ω ) have previously been used to assess stroke, here we use ΔR , which is the difference in R values acquired with two different locking fields to emphasize selectively the contribution of chemical exchange effects. Numerical simulations with different exchange rates and measurements of tissue homogenates with different pH were performed to evaluate the specificity of ΔR to detect tissue acidosis. Spin-lock and APT data were acquired on five rat brains after ischemic strokes induced via middle cerebral artery occlusions. Correlations between these data were analyzed at different time points after the onset of stroke. The results show that ΔR (but not R acquired with a single ω ) was significantly correlated with APT metrics consistent with ΔR varying with pH.
Copyright © 2018 John Wiley & Sons, Ltd.
BACKGROUND - Genome-phenome studies have identified thousands of variants that are statistically associated with disease or traits; however, their functional roles are largely unclear. A comprehensive investigation of regulatory mechanisms and the gene regulatory networks between phenome-wide association study (PheWAS) and genome-wide association study (GWAS) is needed to identify novel regulatory variants contributing to risk for human diseases.
METHODS - In this study, we developed an integrative functional genomics framework that maps 215,107 significant single nucleotide polymorphism (SNP) traits generated from the PheWAS Catalog and 28,870 genome-wide significant SNP traits collected from the GWAS Catalog into a global human genome regulatory map via incorporating various functional annotation data, including transcription factor (TF)-based motifs, promoters, enhancers, and expression quantitative trait loci (eQTLs) generated from four major functional genomics databases: FANTOM5, ENCODE, NIH Roadmap, and Genotype-Tissue Expression (GTEx). In addition, we performed a tissue-specific regulatory circuit analysis through the integration of the identified regulatory variants and tissue-specific gene expression profiles in 7051 samples across 32 tissues from GTEx.
RESULTS - We found that the disease-associated loci in both the PheWAS and GWAS Catalogs were significantly enriched with functional SNPs. The integration of functional annotations significantly improved the power of detecting novel associations in PheWAS, through which we found a number of functional associations with strong regulatory evidence in the PheWAS Catalog. Finally, we constructed tissue-specific regulatory circuits for several complex traits: mental diseases, autoimmune diseases, and cancer, via exploring tissue-specific TF-promoter/enhancer-target gene interaction networks. We uncovered several promising tissue-specific regulatory TFs or genes for Alzheimer's disease (e.g. ZIC1 and STX1B) and asthma (e.g. CSF3 and IL1RL1).
CONCLUSIONS - This study offers powerful tools for exploring the functional consequences of variants generated from genome-phenome association studies in terms of their mechanisms on affecting multiple complex diseases and traits.