Identification of evolutionarily conserved gene networks mediating neurodegenerative dementia

Glial reactivity and T cell infiltration in frontotemporal lobar degeneration with tau pathology

Frontotemporal lobar degeneration with tau (FTLD-tau) is a group of tauopathies that underlie ∼50% of FTLD cases. Identification of genetic risk variants related to innate/adaptive immunity have highlighted a role for neuroinflammation and neuroimmune interactions in FTLD. Studies have shown microglial and astrocyte activation together with T cell infiltration in the brain of THY-Tau22 tauopathy mice. However, this remains to be confirmed in FTLD-tau patients. We conducted a detailed post-mortem study of FTLD-tau cases including 45 progressive supranuclear palsy with clinical frontotemporal dementia, 33 Pick's disease, 12 FTLD-MAPT and 52 control brains to characterize the link between phosphorylated tau (pTau) epitopes and the innate and adaptive immunity. Tau pathology was assessed in the cerebral cortex using antibodies directed against: Tau-2 (phosphorylated and unphosphorylated tau), AT8 (pSer202/pThr205), AT100 (pThr212/pSer214), CP13 (pSer202), PHF1 (pSer396/pSer404), pThr181 and pSer356. The immunophenotypes of microglia and astrocytes were assessed with phenotypic markers (Iba1, CD68, HLA-DR, CD64, CD32a, CD16 for microglia and GFAP, EAAT2, glutamine synthetase and ALDH1L1 for astrocytes). The adaptive immune response was explored via CD4+ and CD8+ T cell quantification and the neuroinflammatory environment was investigated via the expression of 30 inflammatory-related proteins using V-Plex Meso Scale Discovery. As expected, all pTau markers were increased in FTLD-tau cases compared to controls. pSer356 expression was greatest in FTLD-MAPT cases versus controls (P < 0.0001), whereas the expression of other markers was highest in Pick's disease. Progressive supranuclear palsy with frontotemporal dementia consistently had a lower pTau protein load compared to Pick's disease across tau epitopes. The only microglial marker increased in FTLD-tau was CD16 (P = 0.0292) and specifically in FTLD-MAPT cases (P = 0.0150). However, several associations were detected between pTau epitopes and microglia, supporting an interplay between them. GFAP expression was increased in FTLD-tau (P = 0.0345) with the highest expression in Pick's disease (P = 0.0019), while ALDH1L1 was unchanged. Markers of astrocyte glutamate cycling function were reduced in FTLD-tau (P = 0.0075; Pick's disease: P < 0.0400) implying astrocyte reactivity associated with a decreased glutamate cycling activity, which was further associated with pTau expression. Of the inflammatory proteins assessed in the brain, five chemokines were upregulated in Pick's disease cases (P < 0.0400), consistent with the recruitment of CD4+ (P = 0.0109) and CD8+ (P = 0.0014) T cells. Of note, the CD8+ T cell infiltration was associated with pTau epitopes and microglial and astrocytic markers. Our results highlight that FTLD-tau is associated with astrocyte reactivity, remarkably little activation of microglia, but involvement of adaptive immunity in the form of chemokine-driven recruitment of T lymphocytes.

Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy

Background

Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).

Method

In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.

Results

Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP.

Conclusions

Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Cell States and Interactions of CD8 T Cells and Disease-Enriched Microglia in Human Brains with Alzheimer's Disease

Alzheimer's disease (AD) is a multi-stage neurodegenerative disorder characterized by beta-amyloid accumulation, hyperphosphorylated Tau deposits, neurodegeneration, neuroinflammation, and cognitive impairment. Recent studies implicate CD8 T cells as neuroimmune responders to the accumulation of AD pathology in the brain and potential contributors to toxic neuroinflammation. However, more evidence is needed to understand lymphocytes in disease, including their functional states, molecular mediators, and interacting cell types in diseased brain tissue. The scarcity of lymphocytes in brain tissue samples has limited the unbiased profiling of disease-associated cell types, cell states, drug targets, and relationships to common AD genetic risk variants based on transcriptomic analyses. However, using recent large-scale, high-quality single-nuclear sequencing datasets from over 84 Alzheimer's disease and control cases, we leverage single-nuclear RNAseq data from 800 lymphocytes collected from 70 individuals to complete unbiased molecular profiling. We demonstrate that effector memory CD8 T cells are the major lymphocyte subclass enriched in the brain tissues of individuals with AD dementia. We define disease-enriched interactions involving CD8 T cells and multiple brain cell subclasses including two distinct microglial disease states that correlate, respectively, to beta-amyloid and tau pathology. We find that beta-amyloid-associated microglia are a major hub of multicellular cross-talk gained in disease, including interactions involving both vulnerable neuronal subtypes and CD8 T cells. We reproduce prior reports that amyloid-response microglia are depleted in APOE4 carriers. Overall, these human-based studies provide additional support for the potential relevance of effector memory CD8 T cells as a lymphocyte population of interest in AD dementia and provide new candidate interacting partners and drug targets for further functional study.

A fluorescent splice-switching mouse model enables high-throughput, sensitive quantification of antisense oligonucleotide delivery and activity

While antisense oligonucleotides (ASOs) are used in the clinic, therapeutic development is hindered by the inability to assay ASO delivery and activity in vivo. Accordingly, we developed a dual-fluorescence, knockin mouse model that constitutively expresses mKate2 and an engineered EGFP that is alternatively spliced in the presence of ASO to induce expression. We first examined free ASO activity in the brain following intracerebroventricular injection revealing EGFP splice-switching is both ASO concentration and time dependent in major central nervous system cell types. We then assayed the impact of lipid nanoparticle delivery on ASO activity after intravenous administration. Robust EGFP fluorescence was observed in the liver and EGFP+ cells were successfully isolated using fluorescence-activated cell sorting. Together, these results show the utility of this animal model in quantifying both cell-type- and organ-specific ASO delivery, which can be used to advance ASO therapeutics for many disease indications.

Large-scale gene expression changes in APP/PSEN1 and GFAP mutation models exhibit high congruence with Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder with both genetic and non-genetic causes. Animal research models are available for a multitude of diseases and conditions affecting the central nervous system (CNS), and large-scale CNS gene expression data exist for many of these. Although there are several models specifically for AD, each recapitulates different aspects of the human disease. In this study we evaluate over 500 animal models to identify those with CNS gene expression patterns matching human AD datasets. Approaches included a hypergeometric based scoring system that rewards congruent gene expression patterns but penalizes discordant gene expression patterns. The top two models identified were APP/PS1 transgenic mice expressing mutant APP and PSEN1, and mice carrying a GFAP mutation that is causative of Alexander disease, a primary disorder of astrocytes in the CNS. The APP/PS1 and GFAP models both matched over 500 genes moving in the same direction as in human AD, and both had elevated GFAP expression and were highly congruent with one another. Also scoring highly were the 5XFAD model (with five mutations in APP and PSEN1) and mice carrying CK-p25, APP, and MAPT mutations. Animals with the APOE3 and 4 mutations combined with traumatic brain injury ranked highly. Bulbectomized rats scored high, suggesting anosmia could be causative of AD-like gene expression. Other matching models included the SOD1G93A strain and knockouts for SNORD116 (Prader-Willi mutation), GRID2, INSM1, XBP1, and CSTB. Many top models demonstrated increased expression of GFAP, and results were similar across multiple human AD datasets. Heatmap and Uniform Manifold Approximation Plot results were consistent with hypergeometric ranking. Finally, some gene manipulation models, including for TYROBP and ATG7, were identified with reversed AD patterns, suggesting possible neuroprotective effects. This study provides insight for the pathobiology of AD and the potential utility of available animal models.

Curbing Rhes Actions: Mechanism-based Molecular Target for Huntington's Disease and Tauopathies

A highly interconnected network of diverse brain regions is necessary for the precise execution of human behaviors, including cognitive, psychiatric, and motor functions. Unfortunately, degeneration of specific brain regions causes several neurodegenerative disorders, but the mechanisms that elicit selective neuronal vulnerability remain unclear. This knowledge gap greatly hinders the development of effective mechanism-based therapies, despite the desperate need for new treatments. Here, we emphasize the importance of the Rhes (Ras homolog-enriched in the striatum) protein as an emerging therapeutic target. Rhes, an atypical small GTPase with a SUMO (small ubiquitin-like modifier) E3-ligase activity, modulates biological processes such as dopaminergic transmission, alters gene expression, and acts as an inhibitor of motor stimuli in the brain striatum. Mutations in the Rhes gene have also been identified in selected patients with autism and schizophrenia. Moreover, Rhes SUMOylates pathogenic form of mutant huntingtin (mHTT) and tau, enhancing their solubility and cell toxicity in Huntington's disease and tauopathy models. Notably, Rhes uses membrane projections resembling tunneling nanotubes to transport mHTT between cells and Rhes deletion diminishes mHTT spread in the brain. Thus, we predict that effective strategies aimed at diminishing brain Rhes levels will prevent or minimize the abnormalities that occur in HD and tauopathies and potentially in other brain disorders. We review the emerging technologies that enable specific targeting of Rhes in the brain to develop effective disease-modifying therapeutics.

FUS-dependent microRNA deregulations identify TRIB2 as a druggable target for ALS motor neurons

MicroRNAs (miRNAs) modulate mRNA expression, and their deregulation contributes to various diseases including amyotrophic lateral sclerosis (ALS). As fused in sarcoma (FUS) is a causal gene for ALS and regulates biogenesis of miRNAs, we systematically analyzed the miRNA repertoires in spinal cords and hippocampi from ALS-FUS mice to understand how FUS-dependent miRNA deregulation contributes to ALS. miRNA profiling identified differentially expressed miRNAs between different central nervous system (CNS) regions as well as disease states. Among the up-regulated miRNAs, miR-1197 targets the pro-survival pseudokinase Trib2. A reduced TRIB2 expression was observed in iPSC-derived motor neurons from ALS patients. Pharmacological stabilization of TRIB2 protein with a clinically approved cancer drug rescues the survival of iPSC-derived human motor neurons, including those from a sporadic ALS patient. Collectively, our data indicate that miRNA profiling can be used to probe the molecular mechanisms underlying selective vulnerability, and TRIB2 is a potential therapeutic target for ALS.

Longitudinal characterization of behavioral, morphological and transcriptomic changes in a tauopathy mouse model

Neurodegenerative disorders, such as Alzheimer's disease (AD), have the gradual onset of neurobiological changes preceding clinical diagnosis by decades. To elucidate how brain dysfunction proceeds in neurodegenerative disorders, we performed longitudinal characterization of behavioral, morphological, and transcriptomic changes in a tauopathy mouse model, P301S transgenic mice. P301S mice exhibited cognitive deficits as early as 3 months old, and deficits in social preference and social cognition at 5-6 months. They had a significant decrease of arborization in basal dendrites of hippocampal pyramidal neurons from 3 months and apical dendrites of PFC pyramidal neurons at 9 months. Transcriptomic analysis of genome-wide changes revealed the enrichment of synaptic gene upregulation at 3 months of age, while most of these synaptic genes were downregulated in PFC and hippocampus of P301S mice at 9 months. These time-dependent changes in gene expression may lead to progressive alterations of neuronal structure and function, resulting in the manifestation of behavioral symptoms in tauopathies.

Neurodevelopmental deficits and cell-type-specific transcriptomic perturbations in a mouse model of HNRNPU haploinsufficiency

Heterozygous de novo loss-of-function mutations in the gene expression regulator HNRNPU cause an early-onset developmental and epileptic encephalopathy. To gain insight into pathological mechanisms and lay the potential groundwork for developing targeted therapies, we characterized the neurophysiologic and cell-type-specific transcriptomic consequences of a mouse model of HNRNPU haploinsufficiency. Heterozygous mutants demonstrated global developmental delay, impaired ultrasonic vocalizations, cognitive dysfunction and increased seizure susceptibility, thus modeling aspects of the human disease. Single-cell RNA-sequencing of hippocampal and neocortical cells revealed widespread, yet modest, dysregulation of gene expression across mutant neuronal subtypes. We observed an increased burden of differentially-expressed genes in mutant excitatory neurons of the subiculum-a region of the hippocampus implicated in temporal lobe epilepsy. Evaluation of transcriptomic signature reversal as a therapeutic strategy highlights the potential importance of generating cell-type-specific signatures. Overall, this work provides insight into HNRNPU-mediated disease mechanisms and provides a framework for using single-cell RNA-sequencing to study transcriptional regulators implicated in disease.

Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease - specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.

Non-Coding RNA in Microglia Activation and Neuroinflammation in Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by complex pathophysiological features. Amyloid plaques resulting from extracellular amyloid deposition and neurofibrillary tangles formed by intracellular hyperphosphorylated tau accumulation serve as primary neuropathological criteria for AD diagnosis. The activation of microglia has been closely associated with these pathological manifestations. Non-coding RNA (ncRNA), a versatile molecule involved in various cellular functions such as genetic information storage and transport, as well as catalysis of biochemical reactions, plays a crucial role in microglial activation. This review aims to investigate the regulatory role of ncRNAs in protein expression by directly targeting genes, proteins, and interactions. Furthermore, it explores the ability of ncRNAs to modulate inflammatory pathways, influence the expression of inflammatory factors, and regulate microglia activation, all of which contribute to neuroinflammation and AD. However, there are still significant controversies surrounding microglial activation and polarization. The categorization into M1 and M2 phenotypes may oversimplify the intricate and multifaceted regulatory processes in microglial response to neuroinflammation. Limited research has been conducted on the role of ncRNAs in regulating microglial activation and inducing distinct polarization states in the context of neuroinflammation. Moreover, the regulatory mechanisms through which ncRNAs govern microglial function continue to be refined. The current understanding of ncRNA regulatory pathways involved in microglial activation remains incomplete and may be influenced by spatial, temporal, and tissue-specific factors. Therefore, further in-depth investigations are warranted. In conclusion, there are ongoing debates and uncertainties regarding the activation and polarization of microglial cells, particularly concerning the categorization into M1 and M2 phenotypes. The study of ncRNA regulation in microglial activation and polarization, as well as its mechanisms, is still in its early stages and requires further investigation. However, this review offers new insights and opportunities for therapeutic approaches in AD. The development of ncRNA-based drugs may hold promise as a new direction in AD treatment.

Suberoylanilide Hydroxamic Acid (SAHA) Is a Driver Molecule of Neuroplasticity: Implication for Neurological Diseases

Neuroplasticity is a crucial property of the central nervous system to change its activity in response to intrinsic or extrinsic stimuli. This is mainly achieved through the promotion of changes in the epigenome. One of the epi-drivers priming this process is suberoylanilide hydroxamic acid (SAHA or Vorinostat), a pan-histone deacetylase inhibitor that modulates and promotes neuroplasticity in healthy and disease conditions. Knowledge of the specific molecular changes induced by this epidrug is an important area of neuro-epigenetics for the identification of new compounds to treat cognition impairment and/or epilepsy. In this review, we summarize the findings obtained in cellular and animal models of various brain disorders, highlighting the multiple mechanisms activated by SAHA, such as improvement of memory, learning and behavior, and correction of faulty neuronal functioning. Supporting this evidence, in vitro and in vivo data underline how SAHA positively regulates the expression of neuronal genes and microtubule dynamics, induces neurite outgrowth and spine density, and enhances synaptic transmission and potentiation. In particular, we outline studies regarding neurodevelopmental disorders with pharmaco-resistant seizures and/or severe cognitive impairment that to date lack effective drug treatments in which SAHA could ameliorate defective neuroplasticity.

Frontotemporal lobar degeneration

Frontotemporal lobar degeneration (FTLD) is one of the most common causes of early-onset dementia and presents with early social-emotional-behavioural and/or language changes that can be accompanied by a pyramidal or extrapyramidal motor disorder. About 20-25% of individuals with FTLD are estimated to carry a mutation associated with a specific FTLD pathology. The discovery of these mutations has led to important advances in potentially disease-modifying treatments that aim to slow progression or delay disease onset and has improved understanding of brain functioning. In both mutation carriers and those with sporadic disease, the most common underlying diagnoses are linked to neuronal and glial inclusions containing tau (FTLD-tau) or TDP-43 (FTLD-TDP), although 5-10% of patients may have inclusions containing proteins from the FUS-Ewing sarcoma-TAF15 family (FTLD-FET). Biomarkers definitively identifying specific pathological entities in sporadic disease have been elusive, which has impeded development of disease-modifying treatments. Nevertheless, disease-monitoring biofluid and imaging biomarkers are becoming increasingly sophisticated and are likely to serve as useful measures of treatment response during trials of disease-modifying treatments. Symptomatic trials using novel approaches such as transcranial direct current stimulation are also beginning to show promise.

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) depends on environmental and heritable factors, with remarkable differences evident between individuals at the molecular level. Here we present a transcriptomic survey of AD using spatial transcriptomics (ST) and single-nucleus RNA-seq in cortical samples from early-stage AD, late-stage AD, and AD in Down Syndrome (AD in DS) donors. Studying AD in DS provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. Our analysis revealed spatial and cell-type specific changes in disease, with broad similarities in these changes between sAD and AD in DS. We performed additional ST experiments in a disease timecourse of 5xFAD and wildtype mice to facilitate cross-species comparisons. Finally, amyloid plaque and fibril imaging in the same tissue samples used for ST enabled us to directly link changes in gene expression with accumulation and spread of pathology.

microRNA-132 regulates gene expression programs involved in microglial homeostasis

microRNA-132 (miR-132), a known neuronal regulator, is one of the most robustly downregulated microRNAs (miRNAs) in the brain of Alzheimer's disease (AD) patients. Increasing miR-132 in AD mouse brain ameliorates amyloid and Tau pathologies, and also restores adult hippocampal neurogenesis and memory deficits. However, the functional pleiotropy of miRNAs requires in-depth analysis of the effects of miR-132 supplementation before it can be moved forward for AD therapy. We employ here miR-132 loss- and gain-of-function approaches using single-cell transcriptomics, proteomics, and in silico AGO-CLIP datasets to identify molecular pathways targeted by miR-132 in mouse hippocampus. We find that miR-132 modulation significantly affects the transition of microglia from a disease-associated to a homeostatic cell state. We confirm the regulatory role of miR-132 in shifting microglial cell states using human microglial cultures derived from induced pluripotent stem cells.

Lipid nanoparticle delivery limits antisense oligonucleotide activity and cellular distribution in the brain after intracerebroventricular injection

Antisense oligonucleotide (ASO) therapeutics are being investigated for a broad range of neurological diseases. While ASOs have been effective in the clinic, improving productive ASO internalization into target cells remains a key area of focus in the field. Here, we investigated how the delivery of ASO-loaded lipid nanoparticles (LNPs) affects ASO activity, subcellular trafficking, and distribution in the brain. We show that ASO-LNPs increase ASO activity up to 100-fold in cultured primary brain cells as compared to non-encapsulated ASO. However, in contrast to the widespread ASO uptake and activity observed following free ASO delivery in vivo, LNP-delivered ASOs did not downregulate mRNA levels throughout the brain after intracerebroventricular injection. This lack of activity was likely due to ASO accumulation in cells lining the ventricles and blood vessels. Furthermore, we reveal a formulation-dependent activation of the immune system post dosing, suggesting that LNP encapsulation cannot mask cellular ASO backbone-mediated toxicities. Together, these data provide insights into how LNP encapsulation affects ASO distribution as well as activity in the brain, and a foundation that enables future optimization of brain-targeting ASO-LNPs.

Tau activation of microglial cGAS-IFN reduces MEF2C-mediated cognitive resilience

Pathological hallmarks of Alzheimer's disease (AD) precede clinical symptoms by years, indicating a period of cognitive resilience before the onset of dementia. Here, we report that activation of cyclic GMP-AMP synthase (cGAS) diminishes cognitive resilience by decreasing the neuronal transcriptional network of myocyte enhancer factor 2c (MEF2C) through type I interferon (IFN-I) signaling. Pathogenic tau activates cGAS and IFN-I responses in microglia, in part mediated by cytosolic leakage of mitochondrial DNA. Genetic ablation of Cgas in mice with tauopathy diminished the microglial IFN-I response, preserved synapse integrity and plasticity and protected against cognitive impairment without affecting the pathogenic tau load. cGAS ablation increased, while activation of IFN-I decreased, the neuronal MEF2C expression network linked to cognitive resilience in AD. Pharmacological inhibition of cGAS in mice with tauopathy enhanced the neuronal MEF2C transcriptional network and restored synaptic integrity, plasticity and memory, supporting the therapeutic potential of targeting the cGAS-IFN-MEF2C axis to improve resilience against AD-related pathological insults.

Identification of gene networks mediating regional resistance to tauopathy in late-onset Alzheimer’s disease

Neurofibrillary lesions composed of tau protein aggregates are defining hallmarks of Alzheimer’s Disease. Despite tau filaments appearing to spread between networked brain regions in a prion-like manner, certain areas including cerebellum resist trans-synaptic spread of tauopathy and degeneration of their constituent neuronal cell bodies. To identify molecular correlates of resistance, we derived and implemented a ratio of ratios approach for disaggregating gene expression data on the basis of regional vulnerability to tauopathic neurodegeneration. When applied to vulnerable pre-frontal cortex as an internal reference for resistant cerebellum, the approach segregated adaptive changes in expression into two components. The first was enriched for neuron-derived transcripts associated with proteostasis including specific members of the molecular chaperone family and was unique to resistant cerebellum. When produced as purified proteins, each of the identified chaperones depressed aggregation of 2N4R tau in vitro at sub-stoichiometric concentrations, consistent with the expression polarity deduced from ratio of ratios testing. In contrast, the second component enriched for glia- and microglia-derived transcripts associated with neuroinflammation, segregating these pathways from susceptibility to tauopathy. These data support the utility of ratio of ratios testing for establishing the polarity of gene expression changes with respect to selective vulnerability. The approach has the potential to identify new targets for drug discovery predicated on their ability to promote resistance to disease in vulnerable neuron populations.

Astroglial toxicity promotes synaptic degeneration in the thalamocortical circuit in frontotemporal dementia with GRN mutations

Mutations in the human progranulin (GRN) gene are a leading cause of frontotemporal lobar degeneration (FTLD). While previous studies implicate aberrant microglial activation as a disease-driving factor in neurodegeneration in the thalamocortical circuit in Grn-/- mice, the exact mechanism for neurodegeneration in FTLD-GRN remains unclear. By performing comparative single-cell transcriptomics in the thalamus and frontal cortex of Grn-/- mice and patients with FTLD-GRN, we have uncovered a highly conserved astroglial pathology characterized by upregulation of gap junction protein GJA1, water channel AQP4, and lipid-binding protein APOE, and downregulation of glutamate transporter SLC1A2 that promoted profound synaptic degeneration across the two species. This astroglial toxicity could be recapitulated in mouse astrocyte-neuron cocultures and by transplanting induced pluripotent stem cell-derived astrocytes to cortical organoids, where progranulin-deficient astrocytes promoted synaptic degeneration, neuronal stress, and TDP-43 proteinopathy. Together, these results reveal a previously unappreciated astroglial pathology as a potential key mechanism in neurodegeneration in FTLD-GRN.

Rate of tau propagation is a heritable disease trait in genetically diverse mouse strains

The speed and scope of cognitive deterioration in Alzheimer's disease is highly associated with the advancement of tau neurofibrillary lesions across brain networks. We tested whether the rate of tau propagation is a heritable disease trait in a large, well-characterized cohort of genetically divergent mouse strains. Using an AAV-based model system, P301L-mutant human tau (hTau) was introduced into the entorhinal cortex of mice derived from 18 distinct lines. The extent of tau propagation was measured by distinguishing hTau-producing cells from neurons that were recipients of tau transfer. Heritability calculation revealed that 43% of the variability in tau spread was due to genetic variants segregating across background strains. Strain differences in glial markers were also observed, but did not correlate with tau propagation. Identifying unique genetic variants that influence the progression of pathological tau may uncover novel molecular targets to prevent or slow the pace of tau spread and cognitive decline.

A wheat integrative regulatory network from large-scale complementary functional datasets enables trait-associated gene discovery for crop improvement

Gene regulation is central to all aspects of organism growth, and understanding it using large-scale functional datasets can provide a whole view of biological processes controlling complex phenotypic traits in crops. However, the connection between massive functional datasets and trait-associated gene discovery for crop improvement is still lacking. In this study, we constructed a wheat integrative gene regulatory network (wGRN) by combining an updated genome annotation and diverse complementary functional datasets, including gene expression, sequence motif, transcription factor (TF) binding, chromatin accessibility, and evolutionarily conserved regulation. wGRN contains 7.2 million genome-wide interactions covering 5947 TFs and 127 439 target genes, which were further verified using known regulatory relationships, condition-specific expression, gene functional information, and experiments. We used wGRN to assign genome-wide genes to 3891 specific biological pathways and accurately prioritize candidate genes associated with complex phenotypic traits in genome-wide association studies. In addition, wGRN was used to enhance the interpretation of a spike temporal transcriptome dataset to construct high-resolution networks. We further unveiled novel regulators that enhance the power of spike phenotypic trait prediction using machine learning and contribute to the spike phenotypic differences among modern wheat accessions. Finally, we developed an interactive webserver, wGRN (http://wheat.cau.edu.cn/wGRN), for the community to explore gene regulation and discover trait-associated genes. Collectively, this community resource establishes the foundation for using large-scale functional datasets to guide trait-associated gene discovery for crop improvement.

Investigation of early molecular alterations in tauopathy with generative adversarial networks

The recent advances in deep learning-based approaches hold great promise for unravelling biological mechanisms, discovering biomarkers, and predicting gene function. Here, we deployed a deep generative model for simulating the molecular progression of tauopathy and dissecting its early features. We applied generative adversarial networks (GANs) for bulk RNA-seq analysis in a mouse model of tauopathy (TPR50-P301S). The union set of differentially expressed genes from four comparisons (two phenotypes with two time points) was used as input training data. We devised four-way transition curves for a virtual simulation of disease progression, clustered and grouped the curves by patterns, and identified eight distinct pattern groups showing different biological features from Gene Ontology enrichment analyses. Genes that were upregulated in early tauopathy were associated with vasculature development, and these changes preceded immune responses. We confirmed significant disease-associated differences in the public human data for the genes of the different pattern groups. Validation with weighted gene co-expression network analysis suggested that our GAN-based approach can be used to detect distinct patterns of early molecular changes during disease progression, which may be extremely difficult in in vivo experiments. The generative model is a valid systematic approach for exploring the sequential cascades of mechanisms and targeting early molecular events related to dementia.

Leveraging genetic diversity in mice to inform individual differences in brain microstructure and memory

In human Alzheimer's disease (AD) patients and AD mouse models, both differential pre-disease brain features and differential disease-associated memory decline are observed, suggesting that certain neurological features may protect against AD-related cognitive decline. The combination of these features is known as brain reserve, and understanding the genetic underpinnings of brain reserve may advance AD treatment in genetically diverse human populations. One potential source of brain reserve is brain microstructure, which is genetically influenced and can be measured with diffusion MRI (dMRI). To investigate variation of dMRI metrics in pre-disease-onset, genetically diverse AD mouse models, we utilized a population of genetically distinct AD mice produced by crossing the 5XFAD transgenic mouse model of AD to 3 inbred strains (C57BL/6J, DBA/2J, FVB/NJ) and two wild-derived strains (CAST/EiJ, WSB/EiJ). At 3 months of age, these mice underwent diffusion magnetic resonance imaging (dMRI) to probe neural microanatomy in 83 regions of interest (ROIs). At 5 months of age, these mice underwent contextual fear conditioning (CFC). Strain had a significant effect on dMRI measures in most ROIs tested, while far fewer effects of sex, sex*strain interactions, or strain*sex*5XFAD genotype interactions were observed. A main effect of 5XFAD genotype was observed in only 1 ROI, suggesting that the 5XFAD transgene does not strongly disrupt neural development or microstructure of mice in early adulthood. Strain also explained the most variance in mouse baseline motor activity and long-term fear memory. Additionally, significant effects of sex and strain*sex interaction were observed on baseline motor activity, and significant strain*sex and sex*5XFAD genotype interactions were observed on long-term memory. We are the first to study the genetic influences of brain microanatomy in genetically diverse AD mice. Thus, we demonstrated that strain is the primary factor influencing brain microstructure in young adult AD mice and that neural development and early adult microstructure are not strongly altered by the 5XFAD transgene. We also demonstrated that strain, sex, and 5XFAD genotype interact to influence memory in genetically diverse adult mice. Our results support the usefulness of the 5XFAD mouse model and convey strong relationships between natural genetic variation, brain microstructure, and memory.

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome. Via NETTAG, we identified 156 AD-risk genes enriched in druggable targets. Combining network-based prediction and retrospective case-control observations with 10 million individuals, we identified that usage of four drugs (ibuprofen, gemfibrozil, cholecalciferol, and ceftriaxone) is associated with reduced likelihood of AD incidence. Gemfibrozil (an approved lipid regulator) is significantly associated with 43% reduced risk of AD compared with simvastatin using an active-comparator design (95% confidence interval 0.51-0.63, p < 0.0001). In summary, NETTAG offers a deep learning methodology that utilizes GWAS and multi-genomic findings to identify pathobiology and drug repurposing in AD.

Upregulation of miR-664a-3p Ameliorates Calcific Aortic Valve Disease by Inhibiting the BMP2 Signaling Pathway

The development of calcific aortic valve disease (CAVD) is a complex process of ectopic calcification involving various factors that lead to aortic valve stenosis, hemodynamic changes, and, in severe cases, even sudden death. Currently, aortic valve replacement is the only effective method. The osteogenic differentiation of aortic valve interstitial cells (AVICs) is one of the key factors of valve calcification. Emerging evidence suggests that bone morphogenetic protein 2 (BMP2) can induce the proosteogenic activation of AVICs. However, the regulatory mechanism underlying this activation in AVICs is unclear. In the present study, we elucidated through high-throughput RNA sequencing and RT-qPCR that miR-664a-3p was evidently downregulated in the calcific aortic valve. We also proved that miR-664a-3p was involved in regulating osteogenic differentiation in AVICs. Target prediction analysis and dual-luciferase reporter gene assay confirmed that miR-664a-3p is preferentially bound to BMP2. Furthermore, the effect of the miR-664a-3p/BMP2 axis on osteogenic differentiation in AVICs was examined using the gain- and loss-of-function approach. Finally, we constructed a mouse CAVD model and verified the effect of the miR-664a-3p/BMP2 axis on the aortic valve calcification leaflets in vivo. In conclusion, miR-664a-3p regulates osteogenic differentiation in AVICs through negative regulation of BMP2, highlighting that miR-664a-3p may be a potential therapeutic target for CAVD.

Functional regulatory variants implicate distinct transcriptional networks in dementia

Predicting the function of noncoding variation is a major challenge in modern genetics. In this study, we used massively parallel reporter assays to screen 5706 variants identified from genome-wide association studies for both Alzheimer's disease (AD) and progressive supranuclear palsy (PSP), identifying 320 functional regulatory variants (frVars) across 27 loci, including the complex 17q21.31 region. We identified and validated multiple risk loci using CRISPR interference or excision, including complement 4 (C4A) and APOC1 in AD and PLEKHM1 and KANSL1 in PSP. Functional variants disrupt transcription factor binding sites converging on enhancers with cell type-specific activity in PSP and AD, implicating a neuronal SP1-driven regulatory network in PSP pathogenesis. These analyses suggest that noncoding genetic risk is driven by common genetic variants through their aggregate activity on specific transcriptional programs.

MiR-203 is an anti-obese miRNA by targeting ASBT

Obesity is characterized by excessive fat deposition within the body. Bile acids (BA) are important regulators for controlling the absorption of lipid. Here we show that miR-203 exerts weight-loss and lipid-lowering effects by increasing total BA excretion in obese rodents. miR-203 overexpression transgenic mice are resistant to high-fat diet (HFD)-induced obesity and dyslipidemia. Moreover, the knockdown of miR-203 deteriorates metabolic disorders. ASBT plays important role in regulating BA homeostasis and is a direct target of miR-203. In human intestinal epithelial cells, overexpression of miR-203 decreases the cellular uptake of BA by inhibiting ASBT. Furthermore, TCF7L2 is downregulated in obese mice and acts as a transcription factor of miR-203. The ASBT mRNA level was positively correlated with the body mass index (BMI) of population, while the miR-203 level was negatively associated with BMI. Taken together, these data suggest miR-203 could be a new therapeutic BA regulator for obesity and dyslipidemia.

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miR-203 is downregulated in obese rodents and overweight/obese population

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ASBT is a direct target of miR-203 in obesity

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TCF7L2 acts as an upstream activator of miR-203 in obesity

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miR-203 ameliorates obesity and dyslipidemia by increasing TBAs and lipids excretion

Combined analyses of RNA-sequence and Hi-C along with GWAS loci—A novel approach to dissect keloid disorder genetic mechanism

Keloid disorder is a tumour-like disease with invasive growth and a high recurrence rate. Genetic contribution is well expected due to the presence of autosomal dominant inheritance and various genetic mutations in keloid lesions. However, GWAS failed to reveal functional variants in exon regions but single nucleotide polymorphisms in the non-coding regions, suggesting the necessity of innovative genetic investigation. This study employed combined GWAS, RNA-sequence and Hi-C analyses to dissect keloid disorder genetic mechanisms using paired keloid tissues and normal skins. Differentially expressed genes, miRNAs and lncRNAs mined by RNA-sequence were identified to construct a network. From which, 8 significant pathways involved in keloid disorder pathogenesis were enriched and 6 of them were verified. Furthermore, topologically associated domains at susceptible loci were located via the Hi-C database and ten differentially expressed RNAs were identified. Among them, the functions of six molecules for cell proliferation, cell cycle and apoptosis were particularly examined and confirmed by overexpressing and knocking-down assays. This study firstly revealed unknown key biomarkers and pathways in keloid lesions using RNA-sequence and previously reported mutation loci, indicating a feasible approach to reveal the genetic contribution to keloid disorder and possibly to other diseases that are failed by GWAS analysis alone.

Keloid disorder is a benign skin tumour characterized by uncontrolled fibroproliferative tissue growth, which only occurs in human beings with severe reoccurrence post-therapy. It affects several hundred million people with difficulty to control its growth and relapse. It has been long thought that exonic gene mutations must play an important role, but large-scaled GWAS analyses only revealed 3 single nucleotide polymorphisms in the non-coding regions as previously reported. For the first time, this study demonstrated that the true genetic mechanism is likely to be the dysfunctional epigenetic regulation caused by mutations in regulatory elements at the non-coding region as revealed by the combined analyses of GWAS, RNA-sequence and Hi-C data. This approach may lead to the breakthrough of keloid disorder genetic/epigenetic mechanism, if further large-scaled analyses are performed along with human keloid tissue Hi-C data.

LRcell: detecting the source of differential expression at the sub-cell-type level from bulk RNA-seq data

Given most tissues are consist of abundant and diverse (sub-)cell types, an important yet unaddressed problem in bulk RNA-seq analysis is to identify at which (sub-)cell type(s) the differential expression occurs. Single-cell RNA-sequencing (scRNA-seq) technologies can answer the question, but they are often labor-intensive and cost-prohibitive. Here, we present LRcell, a computational method aiming to identify specific (sub-)cell type(s) that drives the changes observed in a bulk RNA-seq experiment. In addition, LRcell provides pre-embedded marker genes computed from putative scRNA-seq experiments as options to execute the analyses. We conduct a simulation study to demonstrate the effectiveness and reliability of LRcell. Using three different real datasets, we show that LRcell successfully identifies known cell types involved in psychiatric disorders. Applying LRcell to bulk RNA-seq results can produce a hypothesis on which (sub-)cell type(s) contributes to the differential expression. LRcell is complementary to cell type deconvolution methods.

Predictive high-throughput screening of PEGylated lipids in oligonucleotide-loaded lipid nanoparticles for neuronal gene silencing

Lipid nanoparticles (LNPs) are gaining traction in the field of nucleic acid delivery following the success of two mRNA vaccines against COVID-19. As one of the constituent lipids on LNP surfaces, PEGylated lipids (PEG-lipids) play an important role in defining LNP physicochemical properties and biological interactions. Previous studies indicate that LNP performance is modulated by tuning PEG-lipid parameters including PEG size and architecture, carbon tail type and length, as well as the PEG-lipid molar ratio in LNPs. Owing to these numerous degrees of freedom, a high-throughput approach is necessary to fully understand LNP behavioral trends over a broad range of PEG-lipid variables. To this end, we report a low-volume, automated, high-throughput screening (HTS) workflow for the preparation, characterization, and in vitro assessment of LNPs loaded with a therapeutic antisense oligonucleotide (ASO). A library of 54 ASO-LNP formulations with distinct PEG-lipid compositions was prepared using a liquid handling robot and assessed for their physiochemical properties as well as gene silencing efficacy in murine cortical neurons. Our results show that the molar ratio of anionic PEG-lipid in LNPs regulates particle size and PEG-lipid carbon tail length controls ASO-LNP gene silencing activity. ASO-LNPs formulated using PEG-lipids with optimal carbon tail lengths achieved up to 5-fold lower mRNA expression in neurons as compared to naked ASO. Representative ASO-LNP formulations were further characterized using dose-response curves and small-angle X-ray scattering to understand structure-activity relationships. Identified hits were also tested for efficacy in primary murine microglia and were scaled-up using a microfluidic formulation technique, demonstrating a smooth translation of ASO-LNP properties and in vitro efficacy. The reported HTS workflow can be used to screen additional multivariate parameters of LNPs with significant time and material savings, therefore guiding the selection and scale-up of optimal formulations for nucleic acid delivery to a variety of cellular targets.

MicroRNA-Based Diagnosis and Therapeutics for Vascular Cognitive Impairment and Dementia

Vascular cognitive impairment and dementia (VCID) is a neurodegenerative disease that is recognized as the second leading cause of dementia after Alzheimer's disease (AD). The underlying pathological mechanism of VCID include crebromicrovascular dysfunction, blood-brain barrier (BBB) disruption, neuroinflammation, capillary rarefaction, and microhemorrhages, etc. Despite the high incidence of VCID, no effective therapies are currently available for preventing or delaying its progression. Recently, pathophysiological microRNAs (miRNAs) in VCID have shown promise as novel diagnostic biomarkers and therapeutic targets. Studies have revealed that miRNAs can regulate the function of the BBB, affect apoptosis and oxidative stress (OS) in the central nervous system, and modulate neuroinflammation and neurodifferentiation. Thus, this review summarizes recent findings on VCID and miRNAs, focusing on their correlation and contribution to the development of VCID pathology.

Translational approaches to understanding resilience to Alzheimer's disease

Individuals who maintain cognitive function despite high levels of Alzheimer's disease (AD)-associated pathology are said to be 'resilient' to AD. Identifying mechanisms underlying resilience represents an exciting therapeutic opportunity. Human studies have identified a number of molecular and genetic factors associated with resilience, but the complexity of these cohorts prohibits a complete understanding of which factors are causal or simply correlated with resilience. Genetically and phenotypically diverse mouse models of AD provide new and translationally relevant opportunities to identify and prioritize new resilience mechanisms for further cross-species investigation. This review will discuss insights into resilience gained from both human and animal studies and highlight future approaches that may help translate these insights into therapeutics designed to prevent or delay AD-related dementia.

Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer's disease

The roles of brain regions activities and gene expressions in the development of Alzheimer's disease (AD) remain unclear. Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region-gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.

Analysis of modular gene co-expression networks reveals molecular pathways underlying Alzheimer’s disease and progressive supranuclear palsy

A comprehensive understanding of the pathological mechanisms involved at different stages of neurodegenerative diseases is key for the advance of preventive and disease-modifying treatments. Gene expression alterations in the diseased brain is a potential source of information about biological processes affected by pathology. In this work, we performed a systematic comparison of gene expression alterations in the brains of human patients diagnosed with Alzheimer’s disease (AD) or Progressive Supranuclear Palsy (PSP) and animal models of amyloidopathy and tauopathy. Using a systems biology approach to uncover biological processes associated with gene expression alterations, we could pinpoint processes more strongly associated with tauopathy/PSP and amyloidopathy/AD. We show that gene expression alterations related to immune-inflammatory responses preponderate in younger, whereas those associated to synaptic transmission are mainly observed in older AD patients. In PSP, however, changes associated with immune-inflammatory responses and synaptic transmission overlap. These two different patterns observed in AD and PSP brains are fairly recapitulated in animal models of amyloidopathy and tauopathy, respectively. Moreover, in AD, but not PSP or animal models, gene expression alterations related to RNA splicing are highly prevalent, whereas those associated with myelination are enriched both in AD and PSP, but not in animal models. Finally, we identify 12 AD and 4 PSP genetic risk factors in cell-type specific co-expression modules, thus contributing to unveil the possible role of these genes to pathogenesis. Altogether, this work contributes to unravel the potential biological processes affected by amyloid versus tau pathology and how they could contribute to the pathogenesis of AD and PSP.

miR-203, fine-tunning neuroinflammation by juggling different components of NF-κB signaling

BACKGROUND

miR-203 was first indicated in maintaining skin homeostasis and innate immunity. Aberrant expression of miR-203 was found associated with pathological progressions of immune disorders, cancers, as well as neurodegenerations. Recently, increasing data on miR-203 in regulating neuroinflammation and neuronal apoptosis has raised extensive concern about the biological function of this microRNA.

METHODS

Mouse model with ectopic miR-203 expression in the hippocampus was constructed by stereotactic injection of lentiviral expression vector of pre-miR-203. Association of miR-203 and mRNA of Akirin2, as well as the competition for miR-203 targeting between Akirin2 3'UTR and another recently characterized miR-203 target, 14-3-3θ, was verified using Dual-Luciferase Reporter Gene Assay and western blot. Microglia activation and pro-inflammatory cytokines expression in the hippocampus of mice overexpressing miR-203 was evaluated using immunohistochemistry analysis and western blot. Neuronal cell death was monitored using anti-caspase 8 in immunohistochemistry as well as TUNEL assay. Cognition of mice was assessed with a behavior test battery consisting of nesting behavior test, Barnes maze and fear conditioning test.

RESULTS

Akirin2, an activator of NF-κB signaling, was identified as a direct target of miR-203. By also targeting 14-3-3θ, a negative regulator of NF-κB signaling, miR-203 displayed an overall pro-inflammatory role both in vitro and in vivo. Promoted nuclear translocation of NF-κB and increased expression of proinflammatory cytokines were observed in cultured BV2 cells transfected with miR-203 mimics. Microglia activation and upregulation of NF-κB, IL-1β and IL-6 were observed in mouse hippocampus with overexpression of miR-203. In addition, promoted neuronal cell death in the hippocampus and impaired neuronal activities resulted in cognitive dysfunction of mice with ectopic miR-203 expression in the hippocampus.

CONCLUSION

A pro-inflammatory and neurodisruptive role of miR-203 was addressed based on our data in this study. Given the identification of Akirin2 as a direct target of miR-203 and the competition with 14-3-3θ for miR-203 targeting, together with the findings of other signaling molecules in NF-κB pathway as targets of miR-203, we proposed that miR-203 was a master modulator, fine-tunning neuroinflammation by juggling different components of NF-κB signaling.

A knowledge-driven network for fine-grained relationship detection between miRNA and disease

Increasing biological evidence indicated that microRNAs (miRNAs) play a vital role in exploring the pathogenesis of various human diseases (especially in tumors). Mining disease-related miRNAs is of great significance for the clinical diagnosis and treatment of diseases. Compared with the traditional experimental methods with the significant limitations of high cost, long cycle and small scale, the methods based on computing have the advantages of being cost-effective. However, although the current methods based on computational biology can accurately predict the correlation between miRNAs and disease, they can not predict the detailed association information at a fine level. We propose a knowledge-driven approach to the fine-grained prediction of disease-related miRNAs (KDFGMDA). Different from the previous methods, this method can finely predict the clear associations between miRNA and disease, such as upregulation, downregulation or dysregulation. Specifically, KDFGMDA extracts triple information from massive experimental data and existing datasets to construct a knowledge graph and then trains a depth graph representation learning model based on knowledge graph to complete fine-grained prediction tasks. Experimental results show that KDFGMDA can predict the relationship between miRNA and disease accurately, which is of far-reaching significance for medical clinical research and early diagnosis, prevention and treatment of diseases. Additionally, the results of case studies on three types of cancers, Kaplan-Meier survival analysis and expression difference analysis further provide the effectiveness and feasibility of KDFGMDA to detect potential candidate miRNAs. Availability: Our work can be downloaded from https://github.com/ShengPengYu/KDFGMDA.

A longitudinal study of alterations of circulating DJ-1 and miR203a-3p in association to olanzapine medication in a sample of first episode patients with schizophrenia

Among different proposed pathophysiological mechanisms, redox imbalance has been suggested to be a potential contributor in the pathogenesis of schizophrenia. DJ-1 is a redox-sensitive protein that has been shown to have neuroprotective function in the brain in Parkinson's disease and other neurodegenerative diseases. However, a role for DJ-1 in schizophrenia is unknown. Bioinformatic analysis suggested that microRNA (miR)-203a-3p could target the 3' untranslated region (UTR) of DJ-1. In whole blood and blood-derived exosomes of 11 first episode antipsychotic naïve schizophrenia patients, DJ-1 protein and mRNA demonstrated decreased DJ-1 mRNA and protein and increased miR203a-3p levels compared to healthy controls. In whole blood, antipsychotic monotherapy with olanzapine for 6 weeks increased DJ-1 and attenuated miR203a-3p levels, whereas in blood derived exosomes, olanzapine returned DJ-1 and miR203a-3p to levels seen healthy controls. Consistent with this finding, we showed that human umbilical vein endothelial cells (HUVACs) transfected with a DJ-1-3' UTR luciferase reporter construct displayed reduced gene expression when subjected to the oxidative stressor H₂O_2. Transfection of a miR203a-3p mimic into HUVACs reduced DJ-1-3 'UTR reporter gene expression, while transfection of an anti miR-203a-3p prevented the H₂O₂-induced downregulation of the reporter gene. We conclude that miR-203a-3p is an essential mediator of oxidative stress in schizophrenia via its ability to target the 3' UTR of DJ-1 and antipsychotic monotherapy restores DJ-1 antioxidant levels by regulating miR203a-3p expression. miR-203a-3p and DJ-1 might represent attractive targets for the treatment of pathologies such as schizophrenia that has underlying oxidative stress.

Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer's disease

BACKGROUND

Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer's disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful.

METHODS

To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein-protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein-protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells.

RESULTS

Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861-0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862-0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD.

CONCLUSIONS

In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD.

Small Molecule Drugs Targeting Non-Coding RNAs as Treatments for Alzheimer's Disease and Related Dementias

Despite the enormous burden of Alzheimer's disease and related dementias (ADRD) on patients, caregivers, and society, only a few treatments with limited efficacy are currently available. While drug development conventionally focuses on disease-associated proteins, RNA has recently been shown to be druggable for therapeutic purposes as well. Approximately 70% of the human genome is transcribed into non-protein-coding RNAs (ncRNAs) such as microRNAs, long ncRNAs, and circular RNAs, which can adopt diverse structures and cellular functions. Many ncRNAs are specifically enriched in the central nervous system, and their dysregulation is implicated in ADRD pathogenesis, making them attractive therapeutic targets. In this review, we first detail why targeting ncRNAs with small molecules is a promising therapeutic strategy for ADRD. We then outline the process from discovery to validation of small molecules targeting ncRNAs in preclinical studies, with special emphasis on primary high-throughput screens for identifying lead compounds. Screening strategies for specific ncRNAs will also be included as examples. Key challenges-including selecting appropriate ncRNA targets, lack of specificity of small molecules, and general low success rate of neurological drugs and how they may be overcome-will be discussed throughout the review.

Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer's disease

We developed an endophenotype disease module-based methodology for Alzheimer's disease (AD) drug repurposing and identified sildenafil as a potential disease risk modifier. Based on retrospective case-control pharmacoepidemiologic analyses of insurance claims data for 7.23 million individuals, we found that sildenafil usage was significantly associated with a 69% reduced risk of AD (hazard ratio = 0.31, 95% confidence interval 0.25-0.39, P<1.0×10^-8). Propensity score stratified analyses confirmed that sildenafil is significantly associated with a decreased risk of AD across all four drug cohorts we tested (diltiazem, glimepiride, losartan and metformin) after adjusting age, sex, race, and disease comorbidities. We also found that sildenafil increases neurite growth and decreases phospho-tau expression in AD patient-induced pluripotent stem cells-derived neuron models, supporting mechanistically its potential beneficial effect in Alzheimer's disease. The association between sildenafil use and decreased incidence of AD does not establish causality or its direction, which requires a randomized clinical trial approach.

Systems biology approaches to unravel the molecular and genetic architecture of Alzheimer's disease and related tauopathies

Over the years, genetic studies have identified multiple genetic risk variants associated with neurodegenerative disorders and helped reveal new biological pathways and genes of interest. However, genetic risk variants commonly reside in non-coding regions and may regulate distant genes rather than the nearest gene, as well as a gene's interaction partners in biological networks. Systems biology and functional genomics approaches provide the framework to unravel the functional significance of genetic risk variants in disease. In this review, we summarize the genetic and transcriptomic studies of Alzheimer's disease and related tauopathies and focus on the advantages of performing systems-level analyses to interrogate the biological pathways underlying neurodegeneration. Finally, we highlight new avenues of multi-omics analysis with single-cell approaches, which provide unparalleled opportunities to systematically explore cellular heterogeneity, and present an example of how to integrate publicly available single-cell datasets. Systems-level analysis has illuminated the function of many disease risk genes, but much work remains to study tauopathies and to understand spatiotemporal gene expression changes of specific cell types.

Network biology bridges the gaps between quantitative genetics and multi-omics to map complex diseases

With advances in high-throughput sequencing technologies, quantitative genetics approaches have provided insights into genetic basis of many complex diseases. Emerging in-depth multi-omics profiling technologies have created exciting opportunities for systematically investigating intricate interaction networks with different layers of biological molecules underlying disease etiology. Herein, we summarized two main categories of biological networks: evidence-based and statistically inferred. These different types of molecular networks complement each other at both bulk and single-cell levels. We also review three main strategies to incorporate quantitative genetics results with multi-omics data by network analysis: (a) network propagation, (b) functional module-based methods, (c) comparative/dynamic networks. These strategies not only aid in elucidating molecular mechanisms of complex diseases but can guide the search for therapeutic targets.

A microRNA signature that correlates with cognition and is a target against cognitive decline

While some individuals age without pathological memory impairments, others develop age-associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study, we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3-microRNA signature that reflects key processes linked to neural homeostasis and inform about cognitive status. We furthermore provide evidence that expression changes in this signature represent multiple mechanisms deregulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives

Multi-pathway approaches for the treatment of complex polygenic disorders are emerging as alternatives to classical monotarget therapies and microRNAs are of particular interest in that regard. MicroRNA research has come a long way from their initial discovery to the cumulative appreciation of their regulatory potential in healthy and diseased brain. However, systematic interrogation of putative therapeutic or toxic effects of microRNAs in (models of) Alzheimer's disease is currently missing and fundamental research findings are yet to be translated into clinical applications. Here, we review the literature to summarize the knowledge on microRNA regulation in Alzheimer's pathophysiology and to critically discuss whether and to what extent these increasing insights can be exploited for the development of microRNA-based therapeutics in the clinic.

microRNA-425 loss mediates amyloid plaque microenvironment heterogeneity and promotes neurodegenerative pathologies

Different cellular and molecular changes underlie the pathogenesis of Alzheimer's disease (AD). Among these, neuron‐specific dysregulation is a necessary event for accumulation of classic pathologies including amyloid plaques. Here, we show that AD‐associated pathophysiology including neuronal cell death, inflammatory signaling, and endolysosomal dysfunction is spatially colocalized to amyloid plaques in regions with abnormal microRNA‐425 (miR‐425) levels and this change leads to focal brain microenvironment heterogeneity, that is, an amyloid plaque‐associated microenvironment (APAM). APAM consists of multiple specific neurodegenerative signature pathologies associated with senile plaques that contribute to the heterogeneity and complexity of AD. Remarkably, miR‐425, a neuronal‐specific regulator decreased in AD brain, maintains a normal spatial transcriptome within brain neurons. We tested the hypothesis that miR‐425 loss correlates with enhanced levels of mRNA targets downstream, supporting APAM and AD progression. A miR‐425‐deficient mouse model has enhanced APP amyloidogenic processing, neuroinflammation, neuron loss, and cognitive impairment. In the APP/PS1 mouse model, intervening with miR‐425 supplementation ameliorated APAM changes and memory deficits. This study reveals a novel mechanism of dysregulation of spatial transcriptomic changes in AD brain, identifying a probable neuronal‐specific microRNA regulator capable of staving off amyloid pathogenesis. Moreover, our findings provide new insights for developing AD treatment strategies with miRNA oligonucleotide(s).

Tutorial: Guidelines for Single-Cell RT-qPCR

Reverse transcription quantitative PCR (RT-qPCR) has delivered significant insights in understanding the gene expression landscape. Thanks to its precision, sensitivity, flexibility, and cost effectiveness, RT-qPCR has also found utility in advanced single-cell analysis. Single-cell RT-qPCR now represents a well-established method, suitable for an efficient screening prior to single-cell RNA sequencing (scRNA-Seq) experiments, or, oppositely, for validation of hypotheses formulated from high-throughput approaches. Here, we aim to provide a comprehensive summary of the scRT-qPCR method by discussing the limitations of single-cell collection methods, describing the importance of reverse transcription, providing recommendations for the preamplification and primer design, and summarizing essential data processing steps. With the detailed protocol attached in the appendix, this tutorial provides a set of guidelines that allow any researcher to perform scRT-qPCR measurements of the highest standard.

Cocaine induces paradigm-specific changes to the transcriptome within the ventral tegmental area

During the initial stages of drug use, cocaine-induced neuroadaptations within the ventral tegmental area (VTA) are critical for drug-associated cue learning and drug reinforcement processes. These neuroadaptations occur, in part, from alterations to the transcriptome. Although cocaine-induced transcriptional mechanisms within the VTA have been examined, various regimens and paradigms have been employed to examine candidate target genes. In order to identify key genes and biological processes regulating cocaine-induced processes, we employed genome-wide RNA-sequencing to analyze transcriptional profiles within the VTA from male mice that underwent one of four commonly used paradigms: acute home cage injections of cocaine, chronic home cage injections of cocaine, cocaine-conditioning, or intravenous-self administration of cocaine. We found that cocaine alters distinct sets of VTA genes within each exposure paradigm. Using behavioral measures from cocaine self-administering mice, we also found several genes whose expression patterns corelate with cocaine intake. In addition to overall gene expression levels, we identified several predicted upstream regulators of cocaine-induced transcription shared across all paradigms. Although distinct gene sets were altered across cocaine exposure paradigms, we found, from Gene Ontology (GO) term analysis, that biological processes important for energy regulation and synaptic plasticity were affected across all cocaine paradigms. Coexpression analysis also identified gene networks that are altered by cocaine. These data indicate that cocaine alters networks enriched with glial cell markers of the VTA that are involved in gene regulation and synaptic processes. Our analyses demonstrate that transcriptional changes within the VTA depend on the route, dose and context of cocaine exposure, and highlight several biological processes affected by cocaine. Overall, these findings provide a unique resource of gene expression data for future studies examining novel cocaine gene targets that regulate drug-associated behaviors.

Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution

Similarities and differences in the associations of biological entities among species can provide us with a better understanding of evolutionary relationships. Often the evolution of new phenotypes results from changes to interactions in pre-existing biological networks and comparing networks across species can identify evidence of conservation or adaptation. Gene co-expression networks (GCNs), constructed from high-throughput gene expression data, can be used to understand evolution and the rise of new phenotypes. The increasing abundance of gene expression data makes GCNs a valuable tool for the study of evolution in non-model organisms. In this paper, we cover motivations for why comparing these networks across species can be valuable for the study of evolution. We also review techniques for comparing GCNs in the context of evolution, including local and global methods of graph alignment. While some protein-protein interaction (PPI) bioinformatic methods can be used to compare co-expression networks, they often disregard highly relevant properties, including the existence of continuous and negative values for edge weights. Also, the lack of comparative datasets in non-model organisms has hindered the study of evolution using PPI networks. We also discuss limitations and challenges associated with cross-species comparison using GCNs, and provide suggestions for utilizing co-expression network alignments as an indispensable tool for evolutionary studies going forward.