The Long Noncoding RNA FEDORA is a Cell-Type- and Sex-Specific Regulator of Depression

Women suffer from depression at twice the rate of men, but the underlying molecular mechanisms are poorly understood. Here, we identify dramatic baseline sex differences in expression of long noncoding RNAs (lncRNAs) in human postmortem brain tissue that are profoundly lost in depression. One such lncRNA, RP11-298D21.1 (which we termed FEDORA), is enriched in oligodendrocytes and neurons and upregulated in several cortical regions of depressed females but not males. We found that virally-expressing FEDORA selectively either in neurons or in oligodendrocytes of prefrontal cortex promoted depression-like behavioral abnormalities in female mice only, changes associated with cell-type-specific regulation of synaptic properties, myelin thickness, and gene expression. We also found that blood FEDORA levels have diagnostic significance for depressed women. These findings demonstrate the important role played by lncRNAs, and FEDORA in particular, in shaping the sex-specific landscape of the brain and contributing to sex differences in depression.

MGEnrichment: A web application for microglia gene list enrichment analysis

Gene expression analysis is becoming increasingly utilized in neuro-immunology research, and there is a growing need for non-programming scientists to be able to analyze their own genomic data. MGEnrichment is a web application developed both to disseminate to the community our curated database of microglia-relevant gene lists, and to allow non-programming scientists to easily conduct statistical enrichment analysis on their gene expression data. Users can upload their own gene IDs to assess the relevance of their expression data against gene lists from other studies. We include example datasets of differentially expressed genes (DEGs) from human postmortem brain samples from Autism Spectrum Disorder (ASD) and matched controls. We demonstrate how MGEnrichment can be used to expand the interpretations of these DEG lists in terms of regulation of microglial gene expression and provide novel insights into how ASD DEGs may be implicated specifically in microglial development, microbiome responses and relationships to other neuropsychiatric disorders. This tool will be particularly useful for those working in microglia, autism spectrum disorders, and neuro-immune activation research. MGEnrichment is available at https://ciernialab.shinyapps.io/MGEnrichmentApp/ and further online documentation and datasets can be found at https://github.com/ciernialab/MGEnrichmentApp. The app is released under the GNU GPLv3 open source license.

Genome-wide sequencing-based identification of methylation quantitative trait loci and their role in schizophrenia risk

DNA methylation (DNAm) is an epigenetic regulator of gene expression and a hallmark of gene-environment interaction. Using whole-genome bisulfite sequencing, we have surveyed DNAm in 344 samples of human postmortem brain tissue from neurotypical subjects and individuals with schizophrenia. We identify genetic influence on local methylation levels throughout the genome, both at CpG sites and CpH sites, with 86% of SNPs and 55% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting the genes and regions with which these loci are epigenetically associated. These findings can be used to better characterize schizophrenia GWAS-identified variants as epigenetic risk variants. Regions differentially methylated by schizophrenia risk-SNPs explain much of the heritability associated with risk loci, despite covering only a fraction of the genomic space. We provide a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain.

A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs

Currently, the detection of the allele asymmetry of gene expression from RNA-seq data or the transcription factor binding from ChIP-seq data is one of the approaches used to identify the functional genetic variants that can affect gene expression (regulatory SNPs or rSNPs). In this study, we searched for rSNPs using the data for human pulmonary arterial endothelial cells (PAECs) available from the Sequence Read Archive (SRA). Allele-asymmetric binding and expression events are analyzed in paired ChIP-seq data for H3K4me3 mark and RNA-seq data obtained for 19 individuals. Two statistical approaches, weighted z-scores and predicted probabilities, were used to improve the efficiency of finding rSNPs. In total, we identified 14,266 rSNPs associated with both allele-specific binding and expression. Among them, 645 rSNPs were associated with GWAS phenotypes; 4746 rSNPs were reported as eQTLs by GTEx, and 11,536 rSNPs were located in 374 candidate transcription factor binding motifs. Additionally, we searched for the rSNPs associated with gene expression using an SRA RNA-seq dataset for 281 clinically annotated human postmortem brain samples and detected eQTLs for 2505 rSNPs. Based on these results, we conducted Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and constructed the protein–protein interaction networks to represent the top-ranked biological processes with a possible contribution to the phenotypic outcome.

Correction to: Coronaviruses: a challenge of today and a call for extended human postmortem brain analyses

A correction to this paper has been published: https://doi.org/10.1007/s00702-021-02356-6

MGEnrichment: a web application for microglia gene list enrichment analysis

Gene expression analysis is becoming increasingly utilized in neuro-immunology research, and there is a growing need for non-programming scientists to be able to analyze their own genomic data. MGEnrichment is a web application developed both to disseminate to the community our curated database of microglia-relevant gene lists, and to allow non-programming scientists to easily conduct statistical enrichment analysis on their gene expression data. Users can upload their own gene IDs to assess the relevance of their expression data against gene lists from other studies. We include example datasets of differentially expressed genes (DEGs) from human postmortem brain samples from Autism Spectrum Disorder (ASD) and matched controls. We demonstrate how MGEnrichment can be used to expand the interpretations of these DEG lists in terms of regulation of microglial gene expression and provide novel insights into how ASD DEGs may be implicated specifically in microglial development, microbiome responses and relationships to other neuropsychiatric disorders. This tool will be particularly useful for those working in microglia, autism spectrum disorders, and neuro-immune activation research. MGEnrichment is available at https://ciernialab.shinyapps.io/MGEnrichmentApp/ and further online documentation and datasets can be found at https://github.com/ciernialab/MGEnrichmentApp . The app is released under the GNU GPLv3 open source license.

TOMM40 RNA Transcription in Alzheimer’s Disease Brain and Its Implication in Mitochondrial Dysfunction

Increasing evidence suggests that the Translocase of Outer Mitochondria Membrane 40 (TOMM40) gene may contribute to the risk of Alzheimer’s disease (AD). Currently, there is no consensus as to whether TOMM40 expression is up- or down-regulated in AD brains, hindering a clear interpretation of TOMM40’s role in this disease. The aim of this study was to determine if TOMM40 RNA levels differ between AD and control brains. We applied RT-qPCR to study TOMM40 transcription in human postmortem brain (PMB) and assessed associations of these RNA levels with genetic variants in APOE and TOMM40. We also compared TOMM40 RNA levels with mitochondrial functions in human cell lines. Initially, we found that the human genome carries multiple TOMM40 pseudogenes capable of producing highly homologous RNAs that can obscure precise TOMM40 RNA measurements. To circumvent this obstacle, we developed a novel RNA expression assay targeting the primary transcript of TOMM40. Using this assay, we showed that TOMM40 RNA was upregulated in AD PMB. Additionally, elevated TOMM40 RNA levels were associated with decreases in mitochondrial DNA copy number and mitochondrial membrane potential in oxidative stress-challenged cells. Overall, differential transcription of TOMM40 RNA in the brain is associated with AD and could be an indicator of mitochondrial dysfunction.

PAC1 receptor–mediated clearance of tau in postsynaptic compartments attenuates tau pathology in mouse brain

Accumulation of pathological tau in synapses has been identified as an early event in Alzheimer’s disease (AD) and correlates with cognitive decline in patients with AD. Tau is a cytosolic axonal protein, but under disease conditions, tau accumulates in postsynaptic compartments and presynaptic terminals, due to missorting within neurons, transsynaptic transfer between neurons, or a failure of clearance pathways. Using subcellular fractionation of brain tissue from rTg4510 tau transgenic mice with tauopathy and human postmortem brain tissue from patients with AD, we found accumulation of seed-competent tau predominantly in postsynaptic compartments. Tau-mediated toxicity in postsynaptic compartments was exacerbated by impaired proteasome activity detected by measuring lysine-48 polyubiquitination of proteins targeted for proteasomal degradation. To combat the accumulation of tau and proteasome impairment in the postsynaptic compartments of rTg4510 mouse brain, we stimulated the pituitary adenylate cyclase–activating polypeptide (PACAP) type 1 receptor (PAC1R) with its ligand PACAP administered intracerebroventricularly to rTg4510 mice. We observed enhanced synaptic proteasome activity and reduced total tau in postsynaptic compartments in mouse brain after PACAP treatment. The clearance of tau from postsynaptic compartments correlated with attenuated tauopathy and improved cognitive performance of rTg4510 transgenic mice on two behavioral tests. These results suggest that activating PAC1R could prevent accumulation of aggregate-prone tau and indicate a potential therapeutic approach for AD and other tauopathies.

A Practical Guide to Sparse Clustering for Studying Molecular Development of the Human Brain

Studying the molecular development of the human brain presents unique challenges for selecting the best data analysis approach. The rare and valuable nature of human postmortem brain samples, especially for studies examining development, means that those studies have small sample sizes (n) but often include measurements (p) for a large number of genes or proteins for every sample. Thus, most of those data sets have a structure that is p >> n, which introduces the problem of sparsity. Here we present a guide to analyzing human brain development data by focusing on sparsity-based clustering methods developed for small sample sizes. We test different methods and identify an application of sparse K-means clustering called Robust Sparse K-means Clustering (RSKC) that does a good job revealing clusters of samples that reflect lifespan stages from birth to aging. The algorithm adaptively selects a subset of the genes or proteins that contributes to generating clusters of samples that are spread across the lifespan. This approach addresses a problem in current studies that were unable to identify postnatal clusters. The guide illustrates that careful selection of the clustering method is essential to reveal meaningful aspects of human brain development.