Transcriptomic profiling of the human brain reveals that altered synaptic gene expression is associated with chronological aging

Cell-type-specific effects of age and sex on human cortical neurons

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

Characterizing a complex CT-rich haplotype in intron 4 of SNCA using large-scale targeted amplicon long-read sequencing

Parkinson's disease (PD) is a common neurodegenerative disorder with a significant risk proportion driven by genetics. While much progress has been made, most of the heritability remains unknown. This is in-part because previous genetic studies have focused on the contribution of single nucleotide variants. More complex forms of variation, such as structural variants and tandem repeats, are already associated with several synucleinopathies. However, because more sophisticated sequencing methods are usually required to detect these regions, little is understood regarding their contribution to PD. One example is a polymorphic CT-rich region in intron 4 of the SNCA gene. This haplotype has been suggested to be associated with risk of Lewy Body (LB) pathology in Alzheimer's Disease and SNCA gene expression, but is yet to be investigated in PD. Here, we attempt to resolve this CT-rich haplotype and investigate its role in PD. We performed targeted PacBio HiFi sequencing of the region in 1375 PD cases and 959 controls. We replicate the previously reported associations and a novel association between two PD risk SNVs (rs356182 and rs5019538) and haplotype 4, the largest haplotype. Through quantitative trait locus analyzes we identify a significant haplotype 4 association with alternative CAGE transcriptional start site usage, not leading to significant differential SNCA gene expression in post-mortem frontal cortex brain tissue. Therefore, disease association in this locus might not be biologically driven by this CT-rich repeat region. Our data demonstrates the complexity of this SNCA region and highlights that further follow up functional studies are warranted.

Molecular Signatures of Neurodegenerative Diseases Identified by Proteomic and Phosphoproteomic Analyses in Aging Mouse Brain

A central hallmark of neurodegenerative diseases is the irreversible accumulation of misfolded proteins in the brain by aberrant phosphorylation. Understanding the mechanisms underlying protein phosphorylation and its role in pathological protein aggregation within the context of aging is crucial for developing therapeutic strategies aimed at preventing or reversing such diseases. Here, we applied multi-protease digestion and quantitative mass spectrometry to compare and characterize dysregulated proteins and phosphosites in the mouse brain proteome using three different age groups: young-adult (3-4 months), middle-age (10 months), and old mice (19-21 months). Proteins associated with senescence, neurodegeneration, inflammation, cell cycle regulation, the p53 hallmark pathway, and cytokine signaling showed significant age-dependent changes in abundances and level of phosphorylation. Several proteins implicated in Alzheimer's disease (AD) and Parkinson's disease (PD) including tau (Mapt), Nefh, and Dpysl2 (also known as Crmp2) were hyperphosphorylated in old mice brain suggesting their susceptibility to the diseases. Cdk5 and Gsk3b, which are known to phosphorylate Dpysl2 at multiple specific sites, had also increased phosphorylation levels in old mice suggesting a potential crosstalk between them to contribute to AD. Hapln2, which promotes α-synuclein aggregation in patients with PD, was one of the proteins with highest abundance in old mice. CD9, which regulates senescence through the PI3K-AKT-mTOR-p53 signaling was upregulated in old mice and its regulation was correlated with the activation of phosphorylated AKT1. Overall, the findings identify a significant association between aging and the dysregulation of proteins involved in various pathways linked to neurodegenerative diseases with potential therapeutic implications.

Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity

Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.

A concerted neuron-astrocyte program declines in ageing and schizophrenia

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.

Concerted neuron-astrocyte gene expression declines in aging and schizophrenia

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron-and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer's disease brains

BACKGROUND

The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.

METHODS

Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs).

RESULTS

Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes.

CONCLUSIONS

To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia

The effect of schizophrenia (SCZ) genetic risk on gene expression in brain remains elusive. A popular approach to this problem has been the application of gene co-expression network algorithms (e.g., WGCNA). To improve reliability with this method it is critical to remove unwanted sources of variance while also preserving biological signals of interest. In this WCGNA study of RNA-Seq data from postmortem prefrontal cortex (78 neurotypical donors, EUR ancestry), we tested the effects of SCZ genetic risk on co-expression networks. Specifically, we implemented a novel design in which gene expression was adjusted by linear regression models to preserve or remove variance explained by biological signal of interest (GWAS genomic scores for SCZ risk-(GS-SCZ), and genomic scores- GS of height (GS-Ht) as a negative control), while removing variance explained by covariates of non-interest. We calculated co-expression networks from adjusted expression (GS-SCZ and GS-Ht preserved or removed), and consensus between them (representative of a "background" network free of genomic scores effects). We then tested the overlap between GS-SCZ preserved modules and background networks reasoning that modules with reduced overlap would be most affected by GS-SCZ biology. Additionally, we tested these modules for convergence of SCZ risk (i.e., enrichment in PGC3 SCZ GWAS priority genes, enrichment in SCZ risk heritability and relevant biological ontologies. Our results highlight key aspects of GS-SCZ effects on brain co-expression networks, specifically: 1) preserving/removing SCZ genetic risk alters the co-expression modules; 2) biological pathways enriched in modules affected by GS-SCZ implicate processes of transcription, translation and metabolism that converge to influence synaptic transmission; 3) priority PGC3 SCZ GWAS genes and SCZ risk heritability are enriched in modules associated with GS-SCZ effects. Overall, our results indicate that gene co-expression networks that selectively integrate information about genetic risk can reveal novel combinations of biological pathways involved in schizophrenia.

Divergent patterns of healthy aging across human brain regions at single-cell resolution reveal links to neurodegenerative disease

Age is a major common risk factor underlying neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Previous studies reported that chronological age correlates with differential gene expression across different brain regions. However, prior datasets have not disambiguated whether expression associations with age are due to changes in cell numbers and/or gene expression per cell. In this study, we leveraged single nucleus RNA-sequencing (snRNAseq) to examine changes in cell proportions and transcriptomes in four different brain regions, each from 12 donors aged 20-30 years (young) or 60-85 years (old). We sampled 155,192 nuclei from two cortical regions (entorhinal cortex and middle temporal gyrus) and two subcortical regions (putamen and subventricular zone) relevant to neurodegenerative diseases or the proliferative niche. We found no changes in cellular composition of different brain regions with healthy aging. Surprisingly, we did find that each brain region has a distinct aging signature, with only minor overlap in differentially associated genes across regions. Moreover, each cell type shows distinct age-associated expression changes, including loss of protein synthesis genes in cortical inhibitory neurons, axonogenesis genes in excitatory neurons and oligodendrocyte precursor cells, enhanced gliosis markers in astrocytes and disease-associated markers in microglia, and genes critical for neuron-glia communication. Importantly, we find cell type-specific enrichments of age associations with genes nominated by Alzheimer's disease and Parkinson's disease genome-wide association studies (GWAS), such as apolipoprotein E (APOE), and leucine-rich repeat kinase 2 (LRRK2) in microglia that are independent of overall expression levels across cell types. We present this data as a new resource which highlights, first, region- and cell type-specific transcriptomic changes in healthy aging that may contribute to selective vulnerability and, second, provide context for testing GWAS-nominated disease risk genes in relevant subtypes and developing more targeted therapeutic strategies. The data is readily accessible without requirement for extensive computational support in a public website, https://brainexp-hykyffa56a-uc.a.run.app/.

Axonal energy metabolism, and the effects in aging and neurodegenerative diseases

Human studies consistently identify bioenergetic maladaptations in brains upon aging and neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Glucose is the major brain fuel and glucose hypometabolism has been observed in brain regions vulnerable to aging and NDAs. Many neurodegenerative susceptible regions are in the topological central hub of the brain connectome, linked by densely interconnected long-range axons. Axons, key components of the connectome, have high metabolic needs to support neurotransmission and other essential activities. Long-range axons are particularly vulnerable to injury, neurotoxin exposure, protein stress, lysosomal dysfunction, etc. Axonopathy is often an early sign of neurodegeneration. Recent studies ascribe axonal maintenance failures to local bioenergetic dysregulation. With this review, we aim to stimulate research in exploring metabolically oriented neuroprotection strategies to enhance or normalize bioenergetics in NDA models. Here we start by summarizing evidence from human patients and animal models to reveal the correlation between glucose hypometabolism and connectomic disintegration upon aging/NDAs. To encourage mechanistic investigations on how axonal bioenergetic dysregulation occurs during aging/NDAs, we first review the current literature on axonal bioenergetics in distinct axonal subdomains: axon initial segments, myelinated axonal segments, and axonal arbors harboring pre-synaptic boutons. In each subdomain, we focus on the organization, activity-dependent regulation of the bioenergetic system, and external glial support. Second, we review the mechanisms regulating axonal nicotinamide adenine dinucleotide (NAD+) homeostasis, an essential molecule for energy metabolism processes, including NAD+ biosynthetic, recycling, and consuming pathways. Third, we highlight the innate metabolic vulnerability of the brain connectome and discuss its perturbation during aging and NDAs. As axonal bioenergetic deficits are developing into NDAs, especially in asymptomatic phase, they are likely exaggerated further by impaired NAD+ homeostasis, the high energetic cost of neural network hyperactivity, and glial pathology. Future research in interrogating the causal relationship between metabolic vulnerability, axonopathy, amyloid/tau pathology, and cognitive decline will provide fundamental knowledge for developing therapeutic interventions.

Molecular differences in brain regional vulnerability to aging between males and females

Background

Aging-related cognitive decline is associated with brain structural changes and synaptic loss. However, the molecular mechanisms of cognitive decline during normal aging remain elusive.

Results

Using the GTEx transcriptomic data from 13 brain regions, we identified aging-associated molecular alterations and cell-type compositions in males and females. We further constructed gene co-expression networks and identified aging-associated modules and key regulators shared by both sexes or specific to males or females. A few brain regions such as the hippocampus and the hypothalamus show specific vulnerability in males, while the cerebellar hemisphere and the anterior cingulate cortex regions manifest greater vulnerability in females than in males. Immune response genes are positively correlated with age, whereas those involved in neurogenesis are negatively correlated with age. Aging-associated genes identified in the hippocampus and the frontal cortex are significantly enriched for gene signatures implicated in Alzheimer's disease (AD) pathogenesis. In the hippocampus, a male-specific co-expression module is driven by key synaptic signaling regulators including VSNL1, INA, CHN1 and KCNH1; while in the cortex, a female-specific module is associated with neuron projection morphogenesis, which is driven by key regulators including SRPK2, REPS2 and FXYD1. In the cerebellar hemisphere, a myelination-associated module shared by males and females is driven by key regulators such as MOG, ENPP2, MYRF, ANLN, MAG and PLP1, which have been implicated in the development of AD and other neurodegenerative diseases.

Conclusions

This integrative network biology study systematically identifies molecular signatures and networks underlying brain regional vulnerability to aging in males and females. The findings pave the way for understanding the molecular mechanisms of gender differences in developing neurodegenerative diseases such as AD.

The reverse transcriptase inhibitor 3TC protects against age-related cognitive dysfunction

Aging is the primary risk factor for most neurodegenerative diseases, including Alzheimer's disease. Major hallmarks of brain aging include neuroinflammation/immune activation and reduced neuronal health/function. These processes contribute to cognitive dysfunction (a key risk factor for Alzheimer's disease), but their upstream causes are incompletely understood. Age-related increases in transposable element (TE) transcripts might contribute to reduced cognitive function with brain aging, as the reverse transcriptase inhibitor 3TC reduces inflammation in peripheral tissues and TE transcripts have been linked with tau pathology in Alzheimer's disease. However, the effects of 3TC on cognitive function with aging have not been investigated. Here, in support of a role for TE transcripts in brain aging/cognitive decline, we show that 3TC: (a) improves cognitive function and reduces neuroinflammation in old wild-type mice; (b) preserves neuronal health with aging in mice and Caenorhabditis elegans; and (c) enhances cognitive function in a mouse model of tauopathy. We also provide insight on potential underlying mechanisms, as well as evidence of translational relevance for these observations by showing that TE transcripts accumulate with brain aging in humans, and that these age-related increases intersect with those observed in Alzheimer's disease. Collectively, our results suggest that TE transcript accumulation during aging may contribute to cognitive decline and neurodegeneration, and that targeting these events with reverse transcriptase inhibitors like 3TC could be a viable therapeutic strategy.

Decoding the role of transcriptomic clocks in the human prefrontal cortex

Aging is a complex process with interindividual variability, which can be measured by aging biological clocks. Aging clocks are machine-learning algorithms guided by biological information and associated with mortality risk and a wide range of health outcomes. One of these aging clocks are transcriptomic clocks, which uses gene expression data to predict biological age; however, their functional role is unknown. Here, we profiled two transcriptomic clocks (RNAAgeCalc and knowledge-based deep neural network clock) in a large dataset of human postmortem prefrontal cortex (PFC) samples. We identified that deep-learning transcriptomic clock outperforms RNAAgeCalc to predict transcriptomic age in the human PFC. We identified associations of transcriptomic clocks with psychiatric-related traits. Further, we applied system biology algorithms to identify common gene networks among both clocks and performed pathways enrichment analyses to assess its functionality and prioritize genes involved in the aging processes. Identified gene networks showed enrichment for diseases of signal transduction by growth factor receptors and second messenger pathways. We also observed enrichment of genome-wide signals of mental and physical health outcomes and identified genes previously associated with human brain aging. Our findings suggest a link between transcriptomic aging and health disorders, including psychiatric traits. Further, it reveals functional genes within the human PFC that may play an important role in aging and health risk.

Cellular mechanisms in brain aging: Focus on physiological and pathological aging

Aging is a natural phenomenon characterized by accumulation of cellular damage and debris. Oxidative stress, cellular senescence, sustained inflammation, and DNA damage are the main cellular processes characteristic of aging associated with morphological and functional decline. These effects tend to be more pronounced in tissues with high metabolic rates such as the brain, mainly in regions such as the prefrontal cortex, hippocampus, and amygdala. These regions are highly related to cognitive behavior, and therefore their atrophy usually leads to decline in processes such as memory and learning. These cognitive declines can occur in physiological aging and are exacerbated in pathological aging. In this article, we review the cellular processes that underlie the triggers of aging and how they relate to one another, causing the atrophy of nerve tissue that is typical of aging. The main topic of this review to determine the central factor that triggers all the cellular processes that lead to cellular aging and discriminate between normal and pathological aging. Finally, we review how the use of supplements with antioxidant and anti-inflammatory properties reduces the cognitive decline typical of aging, which reinforces the hypothesis of oxidative stress and cellular damage as contributors of physiological atrophy of aging. Moreover, cumulative evidence suggests their possible use as therapies, which improve the aging population's quality of life.

Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies

Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.

Functional connectivity signatures of NMDAR dysfunction in schizophrenia-integrating findings from imaging genetics and pharmaco-fMRI

Both, pharmacological and genome-wide association studies suggest N-methyl-D-aspartate receptor (NMDAR) dysfunction and excitatory/inhibitory (E/I)-imbalance as a major pathophysiological mechanism of schizophrenia. The identification of shared fMRI brain signatures of genetically and pharmacologically induced NMDAR dysfunction may help to define biomarkers for patient stratification. NMDAR-related genetic and pharmacological effects on functional connectivity were investigated by integrating three different datasets: (A) resting state fMRI data from 146 patients with schizophrenia genotyped for the disease-associated genetic variant rs7191183 of GRIN2A (encoding the NMDAR 2 A subunit) as well as 142 healthy controls. (B) Pharmacological effects of the NMDAR antagonist ketamine and the GABA-A receptor agonist midazolam were obtained from a double-blind, crossover pharmaco-fMRI study in 28 healthy participants. (C) Regional gene expression profiles were estimated using a postmortem whole-brain microarray dataset from six healthy donors. A strong resemblance was observed between the effect of the genetic variant in schizophrenia and the ketamine versus midazolam contrast of connectivity suggestive for an associated E/I-imbalance. This similarity became more pronounced for regions with high density of NMDARs, glutamatergic neurons, and parvalbumin-positive interneurons. From a functional perspective, increased connectivity emerged between striato-pallido-thalamic regions and cortical regions of the auditory-sensory-motor network, while decreased connectivity was observed between auditory (superior temporal gyrus) and visual processing regions (lateral occipital cortex, fusiform gyrus, cuneus). Importantly, these imaging phenotypes were associated with the genetic variant, the differential effect of ketamine versus midazolam and schizophrenia (as compared to healthy controls). Moreover, the genetic variant was associated with language-related negative symptomatology which correlated with disturbed connectivity between the left posterior superior temporal gyrus and the superior lateral occipital cortex. Shared genetic and pharmacological functional connectivity profiles were suggestive of E/I-imbalance and associated with schizophrenia. The identified brain signatures may help to stratify patients with a common molecular disease pathway providing a basis for personalized psychiatry.

Prediction of Synaptically Localized RNAs in Human Neurons Using Developmental Brain Gene Expression Data

In the nervous system, synapses are special and pervasive structures between axonal and dendritic terminals, which facilitate electrical and chemical communications among neurons. Extensive studies have been conducted in mice and rats to explore the RNA pool at synapses and investigate RNA transport, local protein synthesis, and synaptic plasticity. However, owing to the experimental difficulties of studying human synaptic transcriptomes, the full pool of human synaptic RNAs remains largely unclear. We developed a new machine learning method, called PredSynRNA, to predict the synaptic localization of human RNAs. Training instances of dendritically localized RNAs were compiled from previous rodent studies, overcoming the shortage of empirical instances of human synaptic RNAs. Using RNA sequence and gene expression data as features, various models with different learning algorithms were constructed and evaluated. Strikingly, the models using the developmental brain gene expression features achieved superior performance for predicting synaptically localized RNAs. We examined the relevant expression features learned by PredSynRNA and used an independent test dataset to further validate the model performance. PredSynRNA models were then applied to the prediction and prioritization of candidate RNAs localized to human synapses, providing valuable targets for experimental investigations into neuronal mechanisms and brain disorders.

Multiomics technologies: role in disease biomarker discoveries and therapeutics

 

Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.

SUMMARY POINTS

A Novel and Selective Dopamine Transporter Inhibitor, (S)-MK-26, Promotes Hippocampal Synaptic Plasticity and Restores Effort-Related Motivational Dysfunctions

Dopamine (DA), the most abundant human brain catecholaminergic neurotransmitter, modulates key behavioral and neurological processes in young and senescent brains, including motricity, sleep, attention, emotion, learning and memory, and social and reward-seeking behaviors. The DA transporter (DAT) regulates transsynaptic DA levels, influencing all these processes. Compounds targeting DAT (e.g., cocaine and amphetamines) were historically used to shape mood and cognition, but these substances typically lead to severe negative side effects (tolerance, abuse, addiction, and dependence). DA/DAT signaling dysfunctions are associated with neuropsychiatric and progressive brain disorders, including Parkinson’s and Alzheimer diseases, drug addiction and dementia, resulting in devastating personal and familial concerns and high socioeconomic costs worldwide. The development of low-side-effect, new/selective medicaments with reduced abuse-liability and which ameliorate DA/DAT-related dysfunctions is therefore crucial in the fields of medicine and healthcare. Using the rat as experimental animal model, the present work describes the synthesis and pharmacological profile of (S)-MK-26, a new modafinil analogue with markedly improved potency and selectivity for DAT over parent drug. Ex vivo electrophysiology revealed significantly augmented hippocampal long-term synaptic potentiation upon acute, intraperitoneally delivered (S)-MK-26 treatment, whereas in vivo experiments in the hole-board test showed only lesser effects on reference memory performance in aged rats. However, in effort-related FR5/chow and PROG/chow feeding choice experiments, (S)-MK-26 treatment reversed the depression-like behavior induced by the dopamine-depleting drug tetrabenazine (TBZ) and increased the selection of high-effort alternatives. Moreover, in in vivo microdialysis experiments, (S)-MK-26 significantly increased extracellular DA levels in the prefrontal cortex and in nucleus accumbens core and shell. These studies highlight (S)-MK-26 as a potent enhancer of transsynaptic DA and promoter of synaptic plasticity, with predominant beneficial effects on effort-related behaviors, thus proposing therapeutic potentials for (S)-MK-26 in the treatment of low-effort exertion and motivational dysfunctions characteristic of depression and aging-related disorders.

Integrative epigenomic and transcriptomic analyses reveal metabolic switching by intermittent fasting in brain

Intermittent fasting (IF) remains the most effective intervention to achieve robust anti-aging effects and attenuation of age-related diseases in various species. Epigenetic modifications mediate the biological effects of several environmental factors on gene expression; however, no information is available on the effects of IF on the epigenome. Here, we first found that IF for 3 months caused modulation of H3K9 trimethylation (H3K9me₃) in the cerebellum, which in turn orchestrated a plethora of transcriptomic changes involved in robust metabolic switching processes commonly observed during IF. Second, a portion of both the epigenomic and transcriptomic modulations induced by IF was remarkably preserved for at least 3 months post-IF refeeding, indicating that memory of IF-induced epigenetic changes was maintained. Notably, though, we found that termination of IF resulted in a loss of H3K9me₃ regulation of the transcriptome. Collectively, our study characterizes the novel effects of IF on the epigenetic-transcriptomic axis, which controls myriad metabolic processes. The comprehensive analyses undertaken in this study reveal a molecular framework for understanding how IF impacts the metabolo-epigenetic axis of the brain and will serve as a valuable resource for future research.

Poly(A) RNA sequencing reveals age-related differences in the prefrontal cortex of dogs

Dogs may possess a unique translational potential to investigate neural aging and dementia because they are prone to age-related cognitive decline, including an Alzheimer’s disease–like pathological condition. Yet very little is known about the molecular mechanisms underlying canine cognitive decline. The goal of the current study was to explore the transcriptomic differences between young and old dogs’ frontal cortex, which is a brain region often affected by various forms of age-related dementia in humans. RNA isolates from the frontal cortical brain area of 13 pet dogs, which represented 7 different breeds and crossbreds, were analyzed. The dogs were euthanized for medical reasons, and their bodies had been donated by their owners for scientific purposes. The poly(A) tail RNA subfraction of the total transcriptome was targeted in the sequencing analysis. Cluster analyses, differential gene expression analyses, and gene ontology analyses were carried out to assess which genes and genetic regulatory mechanisms were mostly affected by aging. Age was the most prominent factor in the clustering of the animals, indicating the presence of distinct gene expression patterns related to aging in a genetically variable population. A total of 3436 genes were found to be differentially expressed between the age groups, many of which were linked to neural function, immune system, and protein synthesis. These findings are in accordance with previous human brain aging RNA sequencing studies. Some genes were found to behave more similarly to humans than to rodents, further supporting the applicability of dogs in translational aging research.

Reinstatement of synaptic plasticity in the aging brain through specific dopamine transporter inhibition

Aging-related neurological deficits negatively impact mental health, productivity, and social interactions leading to a pronounced socioeconomic burden. Since declining brain dopamine signaling during aging is associated with the onset of neurological impairments, we produced a selective dopamine transporter (DAT) inhibitor to restore endogenous dopamine levels and improve cognitive function. We describe the synthesis and pharmacological profile of (S,S)-CE-158, a highly specific DAT inhibitor, which increases dopamine levels in brain regions associated with cognition. We find both a potentiation of neurotransmission and coincident restoration of dendritic spines in the dorsal hippocampus, indicative of reinstatement of dopamine-induced synaptic plasticity in aging rodents. Treatment with (S,S)-CE-158 significantly improved behavioral flexibility in scopolamine-compromised animals and increased the number of spontaneously active prefrontal cortical neurons, both in young and aging rodents. In addition, (S,S)-CE-158 restored learning and memory recall in aging rats comparable to their young performance in a hippocampus-dependent hole board test. In sum, we present a well-tolerated, highly selective DAT inhibitor that normalizes the age-related decline in cognitive function at a synaptic level through increased dopamine signaling.

Identifying biomarkers for prenatal diagnosis of neural tube defects based on "omics"

Neural tube defects (NTDs) are the most severe birth defects and the main cause of newborn death; posing a great challenge to the affected children, families, and societies. Presently, the clinical diagnosis of NTDs mainly relies on ultrasound images combined with certain indices, such as alpha-fetoprotein levels in the maternal serum and amniotic fluid. Recently, the discovery of additional biomarkers in maternal tissue has presented new possibilities for prenatal diagnosis. Over the past 20 years, "omics" techniques have provided the premise for the study of biomarkers. This review summarizes recent advances in candidate biomarkers for the prenatal diagnosis of fetal NTDs based on omics techniques using maternal biological specimens of different origins, including amniotic fluid, blood, and urine, which may provide a foundation for the early prenatal diagnosis of NTDs.

Omics sciences for systems biology in Alzheimer's disease: State-of-the-art of the evidence

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-β and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences - genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics - embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data - i.e., neuroimaging-omics - will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level.

Transcriptome analysis of human dorsal striatum implicates attenuated canonical WNT signaling in neuroinflammation and in age-related impairment of striatal neurogenesis and synaptic plasticity

BACKGROUND

Motor and cognitive decline as part of the normal aging process is linked to alterations in synaptic plasticity and reduction of adult neurogenesis in the dorsal striatum. Neuroinflammation, particularly in the form of microglial activation, is suggested to contribute to these age-associated changes.

OBJECTIVE AND METHODS

To explore the molecular basis of alterations in striatal function during aging we analyzed RNA-Seq data for 117 postmortem human dorsal caudate samples and 97 putamen samples acquired through GTEx.

RESULTS

Increased expression of neuroinflammatory transcripts including TREM2, MHC II molecules HLA-DMB, HLA-DQA2, HLA-DPA1, HLA-DPB1, HLA-DMA and HLA-DRA, complement genes C1QA, C1QB, CIQC and C3AR1, and MHCI molecules HLA-B and HLA-F was identified. We also identified down-regulation of transcripts involved in neurogenesis, synaptogenesis, and synaptic pruning, including DCX, CX3CL1, and CD200, and the canonical WNTs WNT7A, WNT7B, and WNT8A. The canonical WNT signaling pathway has previously been shown to mediate adult neurogenesis and synapse formation and growth. Recent findings also highlight the link between WNT/β-catenin signaling and inflammation pathways.

CONCLUSIONS

These findings suggest that age-dependent attenuation of canonical WNT signaling plays a pivotal role in regulating striatal plasticity during aging. Dysregulation of WNT/β-catenin signaling via astrocyte-microglial interactions is suggested to be a novel mechanism that drives the decline of striatal neurogenesis and altered synaptic connectivity and plasticity, leading to a subsequent decrease in motor and cognitive performance with age. These findings may aid in the development of therapies targeting WNT/β-catenin signaling to combat cognitive and motor impairments associated with aging.

Accelerated aging of the brain transcriptome by the common chemotherapeutic doxorubicin

Cancer is one of the most common age-related diseases, and over one-third of cancer patients will receive chemotherapy. One frequently reported side effect of chemotherapeutic agents like doxorubicin (Doxo) is impaired cognitive function, commonly known as "chemotherapy-induced cognitive impairment (CICI)", which may mimic accelerated brain aging. The biological mechanisms underlying the adverse effects of Doxo on the brain are unclear but could involve mitochondrial dysfunction. Here, we characterized brain (hippocampal) transcriptome and cognitive/behavioral changes in young mice treated with Doxo +/- the mitochondrial therapeutic MitoQ. We found that Doxo altered transcriptome/biological processes related to synaptic transmission and neurotransmitter function, neuronal health and behavior, and that these gene expression changes were: 1) similar to key differences observed in transcriptome data on brain aging; and 2) associated with related, aging-like behavioral differences, such as decreased exploration time and impaired novel object recognition test (NOR, an index of learning/memory) performance. Interestingly, MitoQ partially prevented Doxo-induced transcriptome changes in the brain, but it had no effect on behavior or cognitive function. Collectively, our findings are consistent with the idea that chemotherapeutic agents could induce neuronal/gene expression and behavioral changes similar to those that occur during brain aging. In this context, mitochondrial therapeutics may have potential as treatments for CICI at the biological level, but their effects on behavior/cognitive function require further investigation.

Integrated transcriptomic and neuroimaging brain model decodes biological mechanisms in aging and Alzheimer's disease

Both healthy aging and Alzheimer's disease (AD) are characterized by concurrent alterations in several biological factors. However, generative brain models of aging and AD are limited in incorporating the measures of these biological factors at different spatial resolutions. Here, we propose a personalized bottom-up spatiotemporal brain model that accounts for the direct interplay between hundreds of RNA transcripts and multiple macroscopic neuroimaging modalities (PET, MRI). In normal elderly and AD participants, the model identifies top genes modulating tau and amyloid-β burdens, vascular flow, glucose metabolism, functional activity, and atrophy to drive cognitive decline. The results also revealed that AD and healthy aging share specific biological mechanisms, even though AD is a separate entity with considerably more altered pathways. Overall, this personalized model offers novel insights into the multiscale alterations in the elderly brain, with important implications for identifying effective genetic targets for extending healthy aging and treating AD progression.

CoExp: A Web Tool for the Exploitation of Co-expression Networks

Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner.

Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

Advances in transcriptome analysis of human brain aging

Aging is associated with gradual deterioration of physiological and biochemical functions, including cognitive decline. Transcriptome profiling of brain samples from individuals of varying ages has identified the whole-transcriptome changes that underlie age-associated cognitive declines. In this review, we discuss transcriptome-based research on human brain aging performed by using microarray and RNA sequencing analyses. Overall, decreased synaptic function and increased immune function are prevalent in most regions of the aged brain. Age-associated gene expression changes are also cell dependent and region dependent and are affected by genotype. In addition, the transcriptome changes that occur during brain aging include different splicing events, intersample heterogeneity, and altered levels of various types of noncoding RNAs. Establishing transcriptome-based hallmarks of human brain aging will improve the understanding of cognitive aging and neurodegenerative diseases and eventually lead to interventions that delay or prevent brain aging.

Effect of ladostigil treatment of aging rats on gene expression in four brain areas associated with regulation of memory

Episodic and spatial memory decline in aging and are controlled by the hippocampus, perirhinal, frontal and parietal cortices and the connections between them. Ladostigil, a drug with antioxidant and anti-inflammatory activity, was shown to prevent the loss of episodic and spatial memory in aging rats. To better understand the molecular effects of aging and ladostigil on these brain regions we characterized the changes in gene expression using RNA-sequencing technology in rats aged 6 and 22 months. We found that the changes induced by aging and chronic ladostigil treatment were brain region specific. In the hippocampus, frontal and perirhinal cortex, ladostigil decreased the overexpression of genes regulating calcium homeostasis, ion channels and those adversely affecting synaptic function. In the parietal cortex, ladostigil increased the expression of several genes that provide neurotrophic support, while reducing that of pro-apoptotic genes and those encoding pro-inflammatory cytokines and their receptors. Ladostigil also decreased the expression of axonal growth inhibitors and those impairing mitochondrial function. Together, these actions could explain the protection by ladostigil against age-related memory decline.

Translational control in aging and neurodegeneration

Protein metabolism plays central roles in age-related decline and neurodegeneration. While a large body of research has explored age-related changes in protein degradation, alterations in the efficiency and fidelity of protein synthesis with aging are less well understood. Age-associated changes occur in both the protein synthetic machinery (ribosomal proteins and rRNA) and within regulatory factors controlling translation. At the same time, many of the interventions that prolong lifespan do so in part by pre-emptively decreasing protein synthesis rates to allow better harmonization to age-related declines in protein catabolism. Here we review the roles of translation regulation in aging, with a specific focus on factors implicated in age-related neurodegeneration. We discuss how emerging technologies such as ribosome profiling and superior mass spectrometric approaches are illuminating age-dependent mRNA-specific changes in translation rates across tissues to reveal a critical interplay between catabolic and anabolic pathways that likely contribute to functional decline. These new findings point to nodes in posttranscriptional gene regulation that both contribute to aging and offer targets for therapy. This article is categorized under: Translation > Translation Regulation Translation > Ribosome Biogenesis Translation > Translation Mechanisms.

Blood-based systems biology biomarkers for next-generation clinical trials in Alzheimer's disease

Alzheimer's disease (AD)-a complex disease showing multiple pathomechanistic alterations-is triggered by nonlinear dynamic interactions of genetic/epigenetic and environmental risk factors, which, ultimately, converge into a biologically heterogeneous disease. To tackle the burden of AD during early preclinical stages, accessible blood-based biomarkers are currently being developed. Specifically, next-generation clinical trials are expected to integrate positive and negative predictive blood-based biomarkers into study designs to evaluate, at the individual level, target druggability and potential drug resistance mechanisms. In this scenario, systems biology holds promise to accelerate validation and qualification for clinical trial contexts of use-including proof-of-mechanism, patient selection, assessment of treatment efficacy and safety rates, and prognostic evaluation. Albeit in their infancy, systems biology-based approaches are poised to identify relevant AD "signatures" through multifactorial and interindividual variability, allowing us to decipher disease pathophysiology and etiology. Hopefully, innovative biomarker-drug codevelopment strategies will be the road ahead towards effective disease-modifying drugs.
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Transcriptomic and metabolomic profiling of long-lived growth hormone releasing hormone knock-out mice: evidence for altered mitochondrial function and amino acid metabolism

Numerous genetic manipulations that extend lifespan in mice have been discovered over the past two decades, the most robust of which has arguably been the down regulation of growth hormone (GH) signaling. However, while decreased GH signaling has been associated with improved health and lifespan, many of the underlying physiological changes and molecular mechanisms associated with GH signaling have yet to be elucidated. To this end, we have completed the first transcriptomic and metabolomic study on long-lived growth hormone releasing hormone knockout (GHRH-KO) and wild-type mice in brown adipose tissue (transcriptomics) and blood serum (metabolomics). We find that GHRH-KO mice have increased transcript levels of mitochondrial and amino acid genes with decreased levels of extracellular matrix genes. Concurrently, mitochondrial metabolites are differentially regulated in GHRH-KO. Furthermore, we find a strong signal of genotype-by-sex interactions, suggesting the sexes have differing physiological responses to GH deficiency. Overall, our results point towards a strong influence of mitochondrial metabolism in GHRH-KO mice which potentially is tightly intertwined with their extended lifespan phenotype.

When function follows form: Nuclear compartment structure and the epigenetic landscape of the aging neuron

The human brain is affected by cellular aging. Neurons are primarily generated during embryogenesis and early life with a limited capacity for renewal and replacement, making them some of the oldest cells in the human body. Our present understanding of neurodegenerative diseases points towards advanced neuronal age as a prerequisite for the development of these disorders. While significant progress has been made in understanding the relationship between aging and neurological disease, it will be essential to delve further into the molecular mechanisms of neuronal aging in order to develop therapeutic interventions targeting age-related brain dysfunction. In this mini review, we highlight recent findings on the relationship between the aging of nuclear structures and changes in the epigenetic landscape during neuronal aging and disease.

White Matter Abnormalities Linked to Interferon, Stress Response, and Energy Metabolism Gene Expression Changes in Older HIV-Positive Patients on Antiretroviral Therapy

Neurocognitive impairment (NCI) remains a significant cause of morbidity in human immunodeficiency virus (HIV)-positive individuals despite highly active antiretroviral therapy (HAART). White matter abnormalities have emerged as a key component of age-related neurodegeneration, and accumulating evidence suggests they play a role in HIV-associated neurocognitive disorders. Viral persistence in the brain induces chronic inflammation associated with lymphocytic infiltration, microglial proliferation, myelin loss, and cerebrovascular lesions. In this study, gene expression profiling was performed on frontal white matter from 34 older HIV+ individuals on HAART (18 with NCI) and 24 HIV-negative controls. We used the NanoString nCounter platform to evaluate 933 probes targeting inflammation, interferon and stress responses, energy metabolism, and central nervous system-related genes. Viral loads were measured using single-copy assays. Compared to HIV- controls, HIV+ individuals exhibited increased expression of genes related to interferon, MHC-1, and stress responses, myeloid cells, and T cells and decreased expression of genes associated with oligodendrocytes and energy metabolism in white matter. These findings correlated with increased white matter inflammation and myelin pallor, suggesting interferon (IRFs, IFITM1, ISG15, MX1, OAS3) and stress response (ATF4, XBP1, CHOP, CASP1, WARS) gene expression changes are associated with decreased energy metabolism (SREBF1, SREBF2, PARK2, TXNIP) and oligodendrocyte myelin production (MAG, MOG), leading to white matter dysfunction. Machine learning identified a 15-gene signature predictive of HIV status that was validated in an independent cohort. No specific gene expression patterns were associated with NCI. These findings suggest therapies that decrease chronic inflammation while protecting mitochondrial function may help to preserve white matter integrity in older HIV+ individuals.

Neuroserpin expression during human brain development and in adult brain revealed by immunohistochemistry and single cell RNA sequencing

Neuroserpin is a serine-protease inhibitor mainly expressed in the CNS and involved in the inhibition of the proteolytic cascade. Animal models confirmed its neuroprotective role in perinatal hypoxia-ischaemia and adult stroke. Although neuroserpin may be a potential therapeutic target in the treatment of the aforementioned conditions, there is still no information in the literature on its distribution during human brain development. The present study provides a detailed description of the changing spatiotemporal patterns of neuroserpin focusing on physiological human brain development. Five stages were distinguished within our examined age range which spanned from the 7th gestational week until adulthood. In particular, subplate and deep cortical plate neurons were identified as the main sources of neuroserpin production between the 25th gestational week and the first postnatal month. Our immunohistochemical findings were substantiated by single cell RNA sequencing data showing specific neuronal and glial cell types expressing neuroserpin. The characterization of neuroserpin expression during physiological human brain development is essential for forthcoming studies which will explore its involvement in pathological conditions, such as perinatal hypoxia-ischaemia and adult stroke in human.

Integrative Analysis of Global Gene Expression Identifies Opposite Patterns of Reactive Astrogliosis in Aged Human Prefrontal Cortex

The prefrontal cortex (PFC) is one of the brain regions with more prominent changes in human aging. The molecular processes related to the cognitive decline and mood changes during aging are not completely understood. To improve our knowledge, we integrated transcriptomic data of four studies of human PFC from elderly people (58–80 years old) compared with younger people (20–40 years old) using a meta-analytic approximation combined with molecular signature analysis. We identified 1817 differentially expressed genes, 561 up-regulated and 1256 down-regulated. Pathway analysis revealed down-regulation of synaptic genes with conservation of gene expression of other neuronal regions. Additionally, we identified up-regulation of markers of astrogliosis with transcriptomic signature compatible with A1 neurotoxic astrocytes and A2 neuroprotective astrocytes. Response to interferon is related to A1 astrocytes and the A2 phenotype is mediated in aging by activation of sonic hedgehog (SHH) pathway and up-regulation of metallothioneins I and genes of the family ERM (ezrin, radixin, and moesin). The main conclusions of our study are the confirmation of a global dysfunction of the synapses in the aged PFC and the evidence of opposite phenotypes of astrogliosis in the aging brain, which we report for the first time in the present article.

Questions concerning the role of amyloid-β in the definition, aetiology and diagnosis of Alzheimer's disease

The dominant hypothesis of Alzheimer’s disease (AD) aetiology, the neuropathological guidelines for diagnosing AD and the majority of high-profile therapeutic efforts, in both research and in clinical practice, have been built around one possible causal factor, amyloid-β (Aβ). However, the causal link between Aβ and AD remains unproven. Here, in the context of a detailed assessment of historical and contemporary studies, we raise critical questions regarding the role of Aβ in the definition, diagnosis and aetiology of AD. We illustrate that a holistic view of the available data does not support an unequivocal conclusion that Aβ has a central or unique role in AD. Instead, the data suggest alternative views of AD aetiology are potentially valid, at this time. We propose that an unbiased way forward for the field, beyond the current Aβ-centric approach, without excluding a role for Aβ, is required to come to an accurate understanding of AD dementia and, ultimately, an effective treatment.

Role of gamma-amino-butyric acid in the dorsal anterior cingulate in age-associated changes in cognition

GABAergic mechanisms have been shown to contribute to cognitive aging in animal models, but there is currently limited in vivo evidence to support this relationship in humans. It is also unclear whether aging is associated with changes in GABA levels measured with proton magnetic resonance spectroscopy (MRS). Spectral-editing MRS at 3 T was used to measure GABA in the dorsal anterior cingulate cortex (dACC) for a large sample of healthy volunteers (N = 229) aged 18-55. In a subset of 171 participants, age effects on several cognitive tasks were studied. We formally tested whether the MRS measures mediated the relationship between age and cognition. Robust associations of age with performance were found for the Wisconsin Card Sorting Test ([WCST], p < 0.0001). Age was also significantly associated with declining levels of GABA in the dACC (p < 0.001), and GABA levels significantly predicted WCST performance (p < 0.0004). Mediation analysis revealed that GABA in the dACC mediated the effect of age on WCST performance (p < 0.01). Other metabolites were similarly associated with age, but only GABA and creatine levels were significantly associated with WCST performance. No association with age or cognitive performance was found in a frontal white matter control region in a subset of participants. The association of GABA with WCST performance was not related to the amount of brain atrophy associated with aging as measured by the proportion of CSF, gray, and white matter in the MRS voxel. These results implicate GABAergic and possibly energetic metabolism in the dACC as mechanisms of age effects in executive function.