VSNL1 Co-Expression Networks in Aging Include Calcium Signaling, Synaptic Plasticity, and Alzheimer's Disease Pathways

Aging induces region-specific dysregulation of hormone synthesis in the primate adrenal gland

Adrenal glands, vital for steroid secretion and the regulation of metabolism, stress responses and immune activation, experience age-related decline, impacting systemic health. However, the regulatory mechanisms underlying adrenal aging remain largely uninvestigated. Here we established a single-nucleus transcriptomic atlas of both young and aged primate suprarenal glands, identifying lipid metabolism and steroidogenic pathways as core processes impacted by aging. We found dysregulation in centripetal adrenocortical differentiation in aged adrenal tissues and cells in the zona reticularis region, responsible for producing dehydroepiandrosterone sulfate (DHEA-S), were highly susceptible to aging, reflected by senescence, exhaustion and disturbed hormone production. Remarkably, LDLR was downregulated in all cell types of the outer cortex, and its targeted inactivation in human adrenal cells compromised cholesterol uptake and secretion of dehydroepiandrosterone sulfate, as observed in aged primate adrenal glands. Our study provides crucial insights into endocrine physiology, holding therapeutic promise for addressing aging-related adrenal insufficiency and delaying systemic aging.

A Meta-Atlas of the Developing Human Cortex Identifies Modules Driving Cell Subtype Specification

Human brain development requires the generation of hundreds of diverse cell types, a process targeted by recent single-cell transcriptomic profiling efforts. Through a meta-analysis of seven of these published datasets, we have generated 225 meta-modules - gene co-expression networks that can describe mechanisms underlying cortical development. Several meta-modules have potential roles in both establishing and refining cortical cell type identities, and we validated their spatiotemporal expression in primary human cortical tissues. These include meta-module 20, associated with FEZF2+ deep layer neurons. Half of meta-module 20 genes are putative FEZF2 targets, including TSHZ3, a transcription factor associated with neurodevelopmental disorders. Human cortical organoid experiments validated that both factors are necessary for deep layer neuron specification. Importantly, subtle manipulations of these factors drive slight changes in meta-module activity that cascade into strong differences in cell fate - demonstrating how of our meta-atlas can engender further mechanistic analyses of cortical fate specification.

Pathophysiology of Ischemic Stroke: Noncoding RNA Role in Oxidative Stress

Stroke is a neurological disease that causes significant disability and death worldwide. Ischemic stroke accounts for 75% of all strokes. The pathophysiological processes underlying ischemic stroke include oxidative stress, the toxicity of excitatory amino acids, ion disorder, enhanced apoptosis, and inflammation. Noncoding RNAs (ncRNAs) may have a vital role in regulating the pathophysiological processes of ischemic stroke, as confirmed by the altered expression of ncRNAs in blood samples from acute ischemic stroke patients, animal models, and oxygen-glucose-deprived (OGD) cell models. Due to specific changes in expression, ncRNAs can potentially be biomarkers for the diagnosis, treatment, and prognosis of ischemic stroke. As an important brain cell component, glial cells mediate the occurrence and progression of oxidative stress after ischemic stroke, and ncRNAs are an irreplaceable part of this mechanism. This review highlights the impact of ncRNAs in the oxidative stress process of ischemic stroke. It focuses on specific ncRNAs that underlie the pathophysiology of ischemic stroke and have potential as diagnostic biomarkers and therapeutic targets.

New Approach for Untangling the Role of Uncommon Calcium-Binding Proteins in the Central Nervous System

Although Ca²⁺ ion plays an essential role in cellular physiology, calcium-binding proteins (CaBPs) were long used for mainly as immunohistochemical markers of specific cell types in different regions of the central nervous system. They are a heterogeneous and wide-ranging group of proteins. Their function was studied intensively in the last two decades and a tremendous amount of information was gathered about them. Girard et al. compiled a comprehensive list of the gene-expression profiles of the entire EF-hand gene superfamily in the murine brain. We selected from this database those CaBPs which are related to information processing and/or neuronal signalling, have a Ca²⁺-buffer activity, Ca²⁺-sensor activity, modulator of Ca²⁺-channel activity, or a yet unknown function. In this way we created a gene function-based selection of the CaBPs. We cross-referenced these findings with publicly available, high-quality RNA-sequencing and in situ hybridization databases (Human Protein Atlas (HPA), Brain RNA-seq database and Allen Brain Atlas integrated into the HPA) and created gene expression heat maps of the regional and cell type-specific expression levels of the selected CaBPs. This represents a useful tool to predict and investigate different expression patterns and functions of the less-known CaBPs of the central nervous system.

New Approach for Untangling the Role of Uncommon Calcium-Binding Proteins in the Central Nervous System

Although Ca²⁺ ion plays an essential role in cellular physiology, calcium-binding proteins (CaBPs) were long used for mainly as immunohistochemical markers of specific cell types in different regions of the central nervous system. They are a heterogeneous and wide-ranging group of proteins. Their function was studied intensively in the last two decades and a tremendous amount of information was gathered about them. Girard et al. compiled a comprehensive list of the gene-expression profiles of the entire EF-hand gene superfamily in the murine brain. We selected from this database those CaBPs which are related to information processing and/or neuronal signalling, have a Ca²⁺-buffer activity, Ca²⁺-sensor activity, modulator of Ca²⁺-channel activity, or a yet unknown function. In this way we created a gene function-based selection of the CaBPs. We cross-referenced these findings with publicly available, high-quality RNA-sequencing and in situ hybridization databases (Human Protein Atlas (HPA), Brain RNA-seq database and Allen Brain Atlas integrated into the HPA) and created gene expression heat maps of the regional and cell type-specific expression levels of the selected CaBPs. This represents a useful tool to predict and investigate different expression patterns and functions of the less-known CaBPs of the central nervous system.

Cellular and molecular landscape of mammalian sinoatrial node revealed by single-cell RNA sequencing

Bioelectrical impulses intrinsically generated within the sinoatrial node (SAN) trigger the contraction of the heart in mammals. Though discovered over a century ago, the molecular and cellular features of the SAN that underpin its critical function in the heart are uncharted territory. Here, we identify four distinct transcriptional clusters by single-cell RNA sequencing in the mouse SAN. Functional analysis of differentially expressed genes identifies a core cell cluster enriched in the electrogenic genes. The similar cellular features are also observed in the SAN from both rabbit and cynomolgus monkey. Notably, Vsnl1, a core cell cluster marker in mouse, is abundantly expressed in SAN, but is barely detectable in atrium or ventricle, suggesting that Vsnl1 is a potential SAN marker. Importantly, deficiency of Vsnl1 not only reduces the beating rate of human induced pluripotent stem cell - derived cardiomyocytes (hiPSC-CMs) but also the heart rate of mice. Furthermore, weighted gene co-expression network analysis (WGCNA) unveiled the core gene regulation network governing the function of the SAN in mice. Overall, these findings reveal the whole transcriptome profiling of the SAN at single-cell resolution, representing an advance toward understanding of both the biology and the pathology of SAN.

The spontaneous bioelectrical activity of pacemaker cells in sinoatrial node (SAN) triggers the heartbeats. Here, the authors perform single-cell RNA sequencing in the mouse SAN and identify molecular and cellular features of the SAN conserved in rabbit and cynomolgus monkey, identifying a new potential SAN marker.

Transcriptional profiling of medulloblastoma with extensive nodularity (MBEN) reveals two clinically relevant tumor subsets with VSNL1 as potent prognostic marker

Medulloblastoma with extensive nodularity (MBEN) is one of the few central nervous system (CNS) tumor entities occurring in infants which is traditionally associated with good to excellent prognosis. Some MBEN, however, have been reported with an unfavorable clinical course. We performed an integrated DNA/RNA-based molecular analysis of a multi-institutional MBEN cohort (n = 41) to identify molecular events which might be responsible for variability in patients' clinical outcomes. RNA sequencing analysis of this MBEN cohort disclosed two clear transcriptome clusters (TCL) of these CNS tumors: "TCL1 MBEN" and "TCL2 MBEN" which were associated with various gene expression signatures, mutational landscapes and, importantly, prognosis. Thus, the clinically unfavorable "TCL1 MBEN" subset revealed transcriptome signatures composed of cancer-associated signaling pathways and disclosed a high frequency of clinically relevant germline PTCH1/SUFU alterations. In contrast, gene expression profiles of tumors from the clinically favorable "TCL2 MBEN" subgroup were associated with activation of various neurometabolic and neurotransmission signaling pathways, and germline SHH-pathway gene mutations were extremely rare in this transcriptome cluster. "TCL2 MBEN" also revealed strong and ubiquitous expression of VSNL1 (visinin-like protein 1) both at the mRNA and protein level, which was correlated with a favorable clinical course. Thus, combining mutational and epigenetic profiling with transcriptome analysis including VSNL1 immunohistochemistry, MBEN patients could be stratified into clinical risk groups of potential value for subsequent treatment planning.

miRNA dysregulation in ischaemic stroke: Focus on diagnosis, prognosis, therapeutic and protective biomarkers

Stroke is one of the leading causes of death and disability in both developing and developed countries. Biomarkers for stroke and its outcome can greatly facilitate early detection and management of the disease. miRNAs have been explored for their potential as biomarkers for diagnosis, prognosis and brain injury in ischaemic stroke. A substantial body of evidence suggests that miRNAs play key roles in numerous cellular changes following ischaemic stroke including mitochondrial dysfunction, energy failure, cytokine-mediated cytotoxicity, oxidative stress, activation of glial cells, increased intracellular calcium levels inflammatory responses and disruption of the blood-brain barrier (BBB). In addition, targeting specific miRNAs, therapeutic modulation of brain injury and apoptosis can also be achieved. Therefore, the current review has been compiled within an aim to give an overview of the developments exploiting miRNAs at different stages of stroke as prognostic, diagnostic, protective and therapeutic biomarkers.

A meta-analysis of cerebrospinal fluid visinin-like protein-1 in alzheimers disease patients relative to healthy controls and mild cognitive impairment patients

Objective:

To compare cerebrospinal fluid visinin-like protein-1 (CSF VLP-1) in alzheimer’s disease (AD) with that in healthy controls and mild cognitive impairment (MCI) patients and find out possible sources of heterogeneity.

Method:

“Visinin-like protein-1” and “alzheimer’s disease” were employed to search “PubMed”, “Springer” and “Medline” databases until July 2016 and standard mean difference (Std.MD) was calculated. Besides, subgroup analysis and meta-regression were performed to explore the possible heterogeneity sources.

Results:

Seven studies involved 1151 participants were pooled. The CSF VLP-1 in AD patients was higher than that in healthy controls and MCI patients (pooled Std.MD=0.81, 95% CI: [0.47, 1.16], p<0.00001). As shown by subgroup analysis, population variations were one of heterogeneity sources. Meta-regression revealed that Hedges’s g of CSF VLP-1 was correlated with Std.MD of t-tau (r=0.560, p=0.006) and Ab42 (r=-0.386, p=0.013).

Conclusion:

The CSF VLP-1 in AD patients is higher than that in healthy controls and MCI patients. The changes of VLP-1 in AD patients relative to healthy controls and MCI patients is less pronounced than that of core biomarkers, such as Ab42, t-tau and p-tau. Population variations, increasing t-tau and decreasing Ab42 in AD patients relative to healthy controls and MCI patients were the main sources of heterogeneity.

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be useful to predict treatment outcomes. A sample of 186 MDD patients received treatment with duloxetine for up to 8 weeks were categorized as "responders" based on a MADRS change >50% from baseline; or "remitters" based on a MADRS score ≤10 at end point. The initial dataset (N = 186) was randomly divided into training and test sets in a nested 5-fold cross-validation, where 80% was used as a training set and 20% made up five independent test sets. We performed genome-wide logistic regression to identify potentially significant variants related to duloxetine response/remission and extracted the most promising predictors using LASSO regression. Subsequently, classification-regression trees (CRT) and support vector machines (SVM) were applied to construct models, using ten-fold cross-validation. With regards to response, none of the pairs performed significantly better than chance (accuracy p > .1). For remission, SVM achieved moderate performance with an accuracy = 0.52, a sensitivity = 0.58, and a specificity = 0.46, and 0.51 for all coefficients for CRT. The best performing SVM fold was characterized by an accuracy = 0.66 (p = .071), sensitivity = 0.70 and a sensitivity = 0.61. In this study, the potential of using GWAS data to predict duloxetine outcomes was examined using ML models. The models were characterized by a promising sensitivity, but specificity remained moderate at best. The inclusion of additional non-genetic variables to create integrated models may improve prediction.

Genetic risk for schizophrenia and psychosis in Alzheimer disease

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD), affecting ~40 to 60% of individuals with AD (AD with psychosis (AD+P)). In comparison with AD subjects without psychosis, AD+P subjects have more rapid cognitive decline and poor outcomes. Prior studies have estimated the heritability of psychosis in AD at 61%, but the underlying genetic sources of this risk are not known. We evaluated a Discovery Cohort of 2876 AD subjects with (N=1761) or without psychosis (N=1115). All subjects were genotyped using a custom genotyping array designed to evaluate single-nucleotide polymorphisms (SNPs) with evidence of genetic association with AD+P and include SNPs affecting or putatively affecting risk for schizophrenia and AD. Results were replicated in an independent cohort of 2194 AD subjects with (N=734) or without psychosis (N=1460). We found that AD+P is associated with polygenic risk for a set of novel loci and inversely associated with polygenic risk for schizophrenia. Among the biologic pathways identified by the associations of schizophrenia SNPs with AD+P are endosomal trafficking, autophagy and calcium channel signaling. To the best of our knowledge, these findings provide the first clear demonstration that AD+P is associated with common genetic variation. In addition, they provide an unbiased link between polygenic risk for schizophrenia and a lower risk of psychosis in AD. This provides an opportunity to leverage progress made in identifying the biologic effects of schizophrenia alleles to identify novel mechanisms protecting against more rapid cognitive decline and psychosis risk in AD.

Age-Related Gene Expression in the Frontal Cortex Suggests Synaptic Function Changes in Specific Inhibitory Neuron Subtypes

Genome-wide expression profiling of the human brain has revealed genes that are differentially expressed across the lifespan. Characterizing these genes adds to our understanding of both normal functions and pathological conditions. Additionally, the specific cell-types that contribute to the motor, sensory and cognitive declines during aging are unclear. Here we test if age-related genes show higher expression in specific neural cell types. Our study leverages data from two sources of murine single-cell expression data and two sources of age-associations from large gene expression studies of postmortem human brain. We used nonparametric gene set analysis to test for age-related enrichment of genes associated with specific cell-types; we also restricted our analyses to specific gene ontology groups. Our analyses focused on a primary pair of single-cell expression data from the mouse visual cortex and age-related human post-mortem gene expression information from the orbitofrontal cortex. Additional pairings that used data from the hippocampus, prefrontal cortex, somatosensory cortex and blood were used to validate and test specificity of our findings. We found robust age-related up-regulation of genes that are highly expressed in oligodendrocytes and astrocytes, while genes highly expressed in layer 2/3 glutamatergic neurons were down-regulated across age. Genes not specific to any neural cell type were also down-regulated, possibly due to the bulk tissue source of the age-related genes. A gene ontology-driven dissection of the cell-type enriched genes highlighted the strong down-regulation of genes involved in synaptic transmission and cell-cell signaling in the Somatostatin (Sst) neuron subtype that expresses the cyclin dependent kinase 6 (Cdk6) and in the vasoactive intestinal peptide (Vip) neuron subtype expressing myosin binding protein C, slow type (Mybpc1). These findings provide new insights into cell specific susceptibility to normal aging, and suggest age-related synaptic changes in specific inhibitory neuron subtypes.

Altered Levels of Visinin-Like Protein 1 Correspond to Regional Neuronal Loss in Alzheimer Disease and Frontotemporal Lobar Degeneration

Recent studies have implicated the neuronal calcium-sensing protein visinin-like 1 protein (Vilip-1) as a peripheral biomarker in Alzheimer disease (AD), but little is known about expression of Vilip-1 in the brains of patients with AD. We used targeted and quantitative mass spectrometry to measure Vilip-1 peptide levels in the entorhinal cortex (ERC) and the superior frontal gyrus (SF) from cases with early to moderate stage AD, frontotemporal lobar degeneration (FTLD), and cognitively and neuropathologically normal elderly controls. We found that Vilip-1 levels were significantly lower in the ERC, but not in SF, of AD subjects compared to normal controls. In FTLD cases, Vilip-1 levels in the SF were significantly lower than in normal controls. These findings suggest a unique role for cerebrospinal fluid Vilip-1 as a biomarker of ERC neuron loss in AD.

Exploiting single-cell expression to characterize co-expression replicability

Background

Co-expression networks have been a useful tool for functional genomics, providing important clues about the cellular and biochemical mechanisms that are active in normal and disease processes. However, co-expression analysis is often treated as a black box with results being hard to trace to their basis in the data. Here, we use both published and novel single-cell RNA sequencing (RNA-seq) data to understand fundamental drivers of gene-gene connectivity and replicability in co-expression networks.

Results

We perform the first major analysis of single-cell co-expression, sampling from 31 individual studies. Using neighbor voting in cross-validation, we find that single-cell network connectivity is less likely to overlap with known functions than co-expression derived from bulk data, with functional variation within cell types strongly resembling that also occurring across cell types. To identify features and analysis practices that contribute to this connectivity, we perform our own single-cell RNA-seq experiment of 126 cortical interneurons in an experimental design targeted to co-expression. By assessing network replicability, semantic similarity and overall functional connectivity, we identify technical factors influencing co-expression and suggest how they can be controlled for. Many of the technical effects we identify are expression-level dependent, making expression level itself highly predictive of network topology. We show this occurs generally through re-analysis of the BrainSpan RNA-seq data.

Conclusions

Technical properties of single-cell RNA-seq data create confounds in co-expression networks which can be identified and explicitly controlled for in any supervised analysis. This is useful both in improving co-expression performance and in characterizing single-cell data in generally applicable terms, permitting cross-laboratory comparison within a common framework.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0964-6) contains supplementary material, which is available to authorized users.

Transcriptome study and identification of potential marker genes related to the stable expression of recombinant proteins in CHO clones

BACKGROUND

Chinese hamster ovary (CHO) cells have become the host of choice for the production of recombinant proteins, due to their capacity for correct protein folding, assembly, and posttranslational modifications. The most widely used system for recombinant proteins is the gene amplification procedure that uses the CHO-Dhfr expression system. However, CHO cells are known to have a very unstable karyotype. This is due to chromosome rearrangements that can arise from translocations and homologous recombination, especially when cells with the CHO-Dhfr expression system are treated with methotrexate hydrate. The present method used in the industry for testing clones for their long-term stability of recombinant protein production is empirical, and it involves their cultivation over extended periods of time prior to the selection of the most suitable clone for further bioprocess development. The aim of the present study was the identification of marker genes that can predict stable expression of recombinant genes in particular clones early in the development stage.

RESULTS

The transcriptome profiles of CHO clones with stable and unstable recombinant protein production were investigated over 10-weeks of cultivation, using a DNA microarray. We identified 14 genes that were differentially expressed between the stable and unstable clones already at 2 weeks from the beginning of the cultivation. Their expression was validated by reverse-transcription quantitative real-time PCR (RT-qPCR). Furthermore, the k-nearest neighbour algorithm approach shows that the combination of the gene expression patterns of only five of these 14 genes is sufficient to predict stable recombinant protein production in clones in the early phases of cell-line development.

CONCLUSIONS

The exact molecular mechanisms that cause unstable recombinant protein production are not fully understood. However, the expression profiles of some genes in clones with stable and unstable recombinant protein production allow prediction of such instability early in the cell-line development stage. We have thus developed a proof-of-concept for a novel approach to eliminate unstable clones in the CHO-Dhfr expression system, which saves time and labour-intensive work in cell-line development.