Multi-tissue neocortical transcriptome-wide association study implicates 8 genes across 6 genomic loci in Alzheimer's disease

MTCH2 Suppresses Thermogenesis by Regulating Autophagy in Adipose Tissue

Stimulating adipose tissue thermogenesis has emerged as a promising strategy for combating obesity, with uncoupling protein 1 (UCP1) playing a central role in this process. However, the mechanisms that suppress adipose thermogenesis and energy dissipation in obesity are not fully understood. This study identifies mitochondrial carrier homolog 2 (MTCH2), an obesity susceptibility gene, as a negative regulator of energy homeostasis across flies, rodents, and humans. Notably, adipose-specific MTCH2 depletion in mice protects against high-fat-diet (HFD)-induced obesity and metabolic disorders. Mechanistically, MTCH2 deficiency promotes energy expenditure by stimulating thermogenesis in brown adipose tissue (BAT) and browning of subcutaneous white adipose tissue (scWAT), accompanied by upregulated UCP1 protein expression, enhanced mitochondrial biogenesis, and increased lipolysis in BAT and scWAT. Using integrated RNA sequencing and proteomic analyses, this study demonstrates that MTCH2 is a key suppressor of thermogenesis by negatively regulating autophagy via Bcl-2-dependent mechanism. These findings highlight MTCH2's critical role in energy homeostasis and reveal a previously unrecognized link between MTCH2, thermogenesis, and autophagy in adipose tissue biology, positioning MTCH2 as a promising therapeutic target for obesity and related metabolic disorders. This study provides new opportunities to develop treatments that enhance energy expenditure.

Computational and functional prioritization identifies genes that rescue behavior and reduce tau protein in fly and human cell models of Alzheimer disease

Genome-wide association studies (GWASs) in Alzheimer disease (AD) have uncovered over 70 loci significantly associated with AD risk, but identifying the true causal gene(s) at these loci requires systematic functional validation that is rarely performed due to limitations of time and cost. Here, we integrate transcriptome-wide association study (TWAS) with colocalization analysis, fine-mapping, and additional annotation of AD GWAS variants to identify 123 genes at known and suggestive AD risk loci. A comparison with human AD brain transcriptome data confirmed that many of these candidate genes are dysregulated in human AD and correlate with neuropathology. We then tested all available orthologs in two well-established Drosophila AD models that express either wild-type tau or secreted β-amyloid (β42). Experimental perturbation of the 60 available candidates pinpointed 46 that modulated neuronal dysfunction in one or both fly models. The effects of 18 of these genes were concordant with the TWAS prediction, such that the direction of misexpression predicted to increase AD risk in humans exacerbated behavioral impairments in the AD fly models. Reversing the aberrant down- or upregulation of 11 of these genes (MTCH2, ELL, TAP2, HDC, DMWD, MYCL, SLC4A9, ABCA7, CSTF1, PTK2B, and CD2AP) proved neuroprotective in vivo. We further studied MTCH2 and found that it regulates steady-state tau protein levels in the Drosophila brain and reduces tau accumulation in human neural progenitor cells. This systematic, integrative approach effectively prioritizes genes at GWAS loci and reveals promising AD-relevant candidates for further investigation as risk factors or targets for therapeutic intervention.

Brain and blood transcriptome-wide association studies identify five novel genes associated with Alzheimer's disease

BackgroundGenome-wide association studies (GWAS) have identified numerous genetic variants associated with Alzheimer's disease (AD), but their functional implications remain unclear. Transcriptome-wide association studies (TWAS) offer enhanced statistical power by analyzing genetic associations at the gene level rather than at the variant level, enabling assessment of how genetically-regulated gene expression influences AD risk. However, previous AD-TWAS have been limited by small expression quantitative trait loci (eQTL) reference datasets or reliance on AD-by-proxy phenotypes.ObjectiveTo perform the most powerful AD-TWAS to date using summary statistics from the largest available brain and blood cis-eQTL meta-analyses applied to the largest clinically-adjudicated AD GWAS.MethodsWe implemented the OTTERS TWAS pipeline to predict gene expression using the largest available cis-eQTL data from cortical brain tissue (MetaBrain; N = 2683) and blood (eQTLGen; N = 31,684), and then applied these models to AD-GWAS data (Cases = 21,982; Controls = 44,944).ResultsWe identified and validated five novel gene associations in cortical brain tissue (PRKAG1, C3orf62, LYSMD4, ZNF439, SLC11A2) and six genes proximal to known AD-related GWAS loci (Blood: MYBPC3; Brain: MTCH2, CYB561, MADD, PSMA5, ANXA11). Further, using causal eQTL fine-mapping, we generated sparse models that retained the strength of the AD-TWAS association for MTCH2, MADD, ZNF439, CYB561, and MYBPC3.ConclusionsOur comprehensive AD-TWAS discovered new gene associations and provided insights into the functional relevance of previously associated variants, which enables us to further understand the genetic architecture underlying AD risk.

DNA methylation signature of a lifestyle-based resilience index for cognitive health

Cognitive resilience (CR) contributes to the variability in risk for developing and progressing in Alzheimer's disease (AD) among individuals. Beyond genetics, recent studies highlight the critical role of lifestyle factors in enhancing CR and delaying cognitive decline. DNA methylation (DNAm), an epigenetic mechanism influenced by both genetic and environmental factors, including CR-related lifestyle factors, offers a promising pathway for understanding the biology of CR. We studied DNAm changes associated with the Resilience Index (RI), a composite measure of lifestyle factors, using blood samples from the Healthy Brain Initiative (HBI) cohort. After corrections for multiple comparisons, our analysis identified 19 CpGs and 24 differentially methylated regions significantly associated with the RI, adjusting for covariates age, sex, APOE ε4, and immune cell composition. The RI-associated methylation changes are significantly enriched in pathways related to lipid metabolism, synaptic plasticity, and neuroinflammation, and highlight the connection between cardiovascular health and cognitive function. By identifying RI-associated DNAm, our study provided an alternative approach to discovering future targets and treatment strategies for AD, complementary to the traditional approach of identifying disease-associated variants directly. Furthermore, we developed a Methylation-based Resilience Score (MRS) that successfully predicted future cognitive decline in an external dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI), even after accounting for age, sex, APOE ε4, years of education, baseline diagnosis, and baseline MMSE score. Our findings are particularly relevant for a better understanding of epigenetic architecture underlying cognitive resilience. Importantly, the significant association between baseline MRS and future cognitive decline demonstrated that DNAm could be a predictive marker for AD, laying the foundation for future studies on personalized AD prevention.

Investigating potential drug targets for the treatment of glioblastoma: a Mendelian randomization study

Glioblastoma (GBM), one of the most aggressive brain tumors, has a 5-year survival rate of less than 5%. Current standard therapies, including surgery, radiotherapy, and temozolomide (TMZ) chemotherapy, are limited by drug resistance and the blood-brain barrier. Integrating expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) data has shown promise in uncovering disease mechanisms and therapeutic targets. This study combined eQTL and pQTL analyses to identify potential GBM-related genes and circulating plasma proteins for therapeutic exploration. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we identified 2,528 differentially expressed genes, including GPX7 and CXCL10. eQTL-MR analysis identifies GBM-associated differentially expressed genes and constructs a protein-protein interaction (PPI) network.Integrating pQTL data from the deCODE database, pQTL-MR, and colocalization analyses validated the therapeutic potential of GPX7 and CXCL10.These findings provide new perspectives on GBM biology and suggest actionable targets for therapy. Despite limitations due to sample size and population-specific data, this study highlights GPX7 and CXCL10 as promising candidates for further investigation and lays the foundation for targeted GBM treatments.

Multi-omics analysis reveals aspirin is associated with reduced risk of Alzheimer's disease

The urgent need for safe and effective therapies for Alzheimer's disease (AD) has spurred a growing interest in repurposing existing drugs to treat or prevent AD. In this study, we combined multi-omics and clinical data to investigate possible repurposing opportunities for AD. We performed transcriptome-wide association studies (TWAS) to construct gene expression signatures of AD from publicly available GWAS summary statistics, using both transcriptome prediction models for 49 tissues from the Genotype-Tissue Expression (GTEx) project and microglia-specific models trained on eQTL data from the Microglia Genomic Atlas (MiGA). We then identified compounds capable of reversing the AD-associated changes in gene expression observed in these signatures by querying the Connectivity Map (CMap) drug perturbation database. Out of >2,000 small-molecule compounds in CMap, aspirin emerged as the most promising AD repurposing candidate. To investigate the longitudinal effects of aspirin use on AD, we collected drug exposure and AD coded diagnoses from three independent sources of real-world data: electronic health records (EHRs) from Vanderbilt University Medical Center (VUMC) and the National Institutes of Health All of Us Research Program, along with national healthcare claims from the MarketScan Research Databases. In meta-analysis of EHR data from VUMC and All of Us , we found that aspirin use before age 65 was associated with decreased risk of incident AD (hazard ratio=0.76, 95% confidence interval [CI]: 0.64-0.89, P =0.001). Consistent with the findings utilizing EHR data, analysis of claims data from MarketScan revealed significantly lower odds of aspirin exposure among AD cases compared to matched controls (odds ratio=0.32, 95% CI: 0.28-0.38, P <0.001). Our results demonstrate the value of integrating genetic and clinical data for drug repurposing studies and highlight aspirin as a promising repurposing candidate for AD, warranting further investigation in clinical trials.

High throughput identification of genetic regulators of microglial inflammatory processes in Alzheimer's disease

Genome-wide association studies (GWAS) have identified over a hundred genetic risk factors for Alzheimer's disease (AD), many of which are predominantly expressed in microglia. However, the pathogenic role for most of them remains unclear. To systematically investigate how AD GWAS variants influence human microglial inflammatory responses, we conducted CRISPR inhibition (CRISPRi) screens targeting 119 AD GWAS hits in hiPSC-derived microglia (iMGLs) and used the production of reactive oxygen species (ROS) in response to the viral mimic poly(I:C) as a functional readout. Top hits whose knockdown either increased or decreased ROS levels in response to poly(I:C) were further analyzed using CROP-seq to integrate CRISPRi with single-cell RNA sequencing (scRNA-seq). This analysis identified 9 unique microglial clusters, including a poly(I:C)-driven inflammatory cluster 2. Emerging evidence supports a pathogenic role of viral infections in AD and cross comparison of our scRNA-seq data with iMGLs xenotransplanted into an AD mouse model shows significant overlap between our clusters and AD-relevant microglial clusters. Knockdown of MS4A6A and EED , which resulted in elevated ROS production in the presence of poly(I:C), increased the proportion of cluster 2 cells and induced functionally related changes in gene expression. In addition, KD of MS4A6 led to a reduction in the proportion of iMGLs in the DAM (disease associated microglia) cluster under all conditions, suggesting that this gene may modulate the DAM response. In contrast, KD of INPP5D or RAPEP1 which lead to low levels of ROS in the presence of poly(I:C), did not significantly affect the proportion of cells in cluster 2 but rather shaped the inflammatory response. This included the upregulation of an HLA-associated inflammatory cluster (cluster 6) by INPP5D knockdown under all conditions, independent of poly(I:C) stimulation. Importantly, KD of INPP5D or RAPEP1 had many shared differentially expressed genes (DEGs) under both vehicle and poly(I:C) treated conditions. Overall, our findings demonstrate that despite the diverse biological functions of AD GWAS variants, they converge functionally to regulate human microglial states and shape inflammatory responses relevant to AD pathology.

CLEC11A-Driven Molecular Mechanisms in Intervertebral Disc Degeneration: A Comprehensive Multi-Omics Study

Background

Intervertebral disc degeneration (IVDD) is a common chronic degenerative disease with a complex etiology involving genetic and environmental factors. However, the genetic pathogenesis and key driving factors of IVDD remain largely unknown.

Methods

In this study, we combined MR with transcriptomic sequencing to identify key pathogenic genes implicated in IVDD. Further exploration using single-cell transcriptomics elucidated the specific cell types and pathways through which these genes modulate IVDD. Mediational MR analysis provided insights into the intermediary roles of 91 inflammatory factors and serum metabolites in the genetic causation pathway of IVDD. Finally, we validated these findings through in vitro experiments, confirming the regulatory roles of these critical genes in the progression of IVDD.

Results

Transcriptomic and MR analyses identified six candidate pathogenic genes (AEN, CLEC11A, HMGN1, LRRC25, TAF7, and TREM1) significantly associated with IVDD. Subsequent single-cell analysis suggested that CLEC11A, TREM1, and HMGN1 may play pivotal roles in IVDD progression by modulating chondrocyte function and inflammatory responses. Mediation MR analysis further indicated that CLEC11A might significantly elevate IVDD risk by upregulating the inflammatory mediator ARTN and the uncharacterized serum metabolites X-12731 and X-18901 (ARTN: OR=1.078, 95% CI: 1.004-1.158, P=0.038; X-12731: OR=0.906, 95% CI: 0.852-0.960, P=0.043; X-18901: OR=1.090, 95% CI: 1.007-1.179, P=0.034). In vitro experiments demonstrated that overexpression of CLEC11A in nucleus pulposus cells significantly enhanced mRNA and protein expression of IVDD-related inflammatory markers; conversely, silencing CLEC11A markedly reduced these expressions. Similarly, overexpression of ARTN significantly increased, while knockdown decreased, the expression of these inflammatory markers in nucleus pulposus cells.

Conclusion

Our integrative multi-omics analysis indicates that CLEC11A exacerbates IVDD by upregulating ARTN and inducing metabolic dysregulation, thereby amplifying the inflammatory pathways that drive disease progression.

Ameliorative effect and underlying mechanism of the Xiaxue Kaiqiao formula on age-related dementia in Samp8 mice

BACKGROUND

Dementia, a major symptom of several neurodegenerative diseases, can be improved by acetylcholinesterase inhibitors (AChE); however, due to the complex etiology and long course of dementia, the efficacy of these drugs remains limited. Significant empirical evidence shows that traditional Chinese medicine (TCM) markedly ameliorates intractable disease; nevertheless, a suitable regimen has yet to be widely accepted, which is likely the result of gaps in the understanding of its causality. We propose that taking advantage of the TCM theory of collateral activation and prevention of accumulation by purgation may improve dementia treatment; thus, we designed the Xiaxue Kaiqiao formula (XKF) accordingly.

PURPOSE

To explore the ameliorative effect and underlying mechanism of XKF on dementia in a Samp8 mouse model.

METHODS

Samp8 mice were treated with XKF for eight weeks, and the amelioration of dementia was subsequently assessed using the novel object recognition, Barnes maze, and open-field behavioral tests. Neuropathological alterations were observed by immunofluorescence (IF) and Golgi staining of brain tissue. Drug safety was evaluated by blood biochemical tests, organ coefficients, and hematoxylin-eosin (H&E) staining. Proteomics analysis was performed on frozen brain tissue using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

Behavioral testing revealed that the administration of XKF had significant ameliorative effects on memory discrimination, spatial learning memory, and anxiety in Samp8 mice. IF staining showed that XKF reduced the loss of postsynaptic density protein 95 (PSD95), myelin, neurons, and axons, as well as decreased the proliferation of astrocytes and microglia in the hippocampal and temporal lobe regions. Evaluation of drug safety demonstrated no abnormal organ morphology following XKF treatment.

CONCLUSION

XKF treatment improved the symptoms of dementia in Samp8 mice, indicating the potential for clinical application. The mechanism underlying the ameliorative effect of XKF on dementia is likely increased synaptic transmission between neurons. Our data provide reliable evidence for the TCM theory of collateral activation and prevention of accumulation by purgation.

Identification of JAZF1, KNOP1, and PLEKHA1 as causally associated genes and drug targets for Alzheimer's disease: a summary data-based Mendelian randomization study

BACKGROUND

There is a growing body of evidence indicating the significant role of the immune system and immune cells in the progression of Alzheimer's disease (AD). However, the exact role of genes from various immune cell types in AD remains unclear. We aimed to utilize summary data-based Mendelian randomization (SMR) to explore the potential causal relationships between genes in specific immune cells and the risk of AD.

METHODS

By utilizing data sets of expression quantitative trait loci (eQTL) for 14 different immune cell types and large-scale AD genome-wide association study (GWAS), we employed SMR to identify key genes associated with AD within specific immune cells. Sensitivity analyses, including F-statistic, colocalization, and assessment of horizontal pleiotropy, were further conducted to validate the discovered genes. In addition, replication analyses were performed in AD GWAS from the FinnGen consortium. Finally, we further identified existing drugs that target or interact with the druggable genes and reviewed the studies about the associations between these drugs and AD.

RESULTS

SMR analysis revealed 342 genes associated with AD across 14 immune cell types. Further sensitivity analyses identified nine genes, CTSH, FCER1G, FNBP4, HLA-E, JAZF1, KNOP1, PLEKHA1, RP11-960L18.1, and ZNF638 that had significant associations with AD across nine specific immune cell types. JAZF1, KNOP1 and PLEKHA1 were replicated in an independent analysis using the GWAS data. The review on gene-related drugs also supported these findings.

CONCLUSIONS

Our research suggests that the expression of the genes JAZF1, KNOP1, and PLEKHA1 in specific immune cell types is related to the risk of AD.

DNA Methylation Signature of a Lifestyle-based Resilience Index for Cognitive Health

Cognitive resilience (CR) contributes to the variability in risk for developing and progressing in Alzheimer's disease (AD) among individuals. Beyond genetics, recent studies highlight the critical role of lifestyle factors in enhancing CR and delaying cognitive decline. DNA methylation (DNAm), an epigenetic mechanism influenced by both genetic and environmental factors, including CR-related lifestyle factors, offers a promising pathway for understanding the biology of CR. We studied DNAm changes associated with the Resilience Index (RI), a composite measure of lifestyle factors, using blood samples from the Healthy Brain Initiative (HBI) cohort. After corrections for multiple comparisons, our analysis identified 19 CpGs and 24 differentially methylated regions significantly associated with the RI, adjusting for covariates age, sex, APOE ε4, and immune cell composition. The RI-associated methylation changes are significantly enriched in pathways related to lipid metabolism, synaptic plasticity, and neuroinflammation, and highlight the connection between cardiovascular health and cognitive function. By identifying RI-associated DNAm, our study provided an alternative approach to discovering future targets and treatment strategies for AD, complementary to the traditional approach of identifying disease-associated variants directly. Furthermore, we developed a Methylation-based Resilience Score (MRS) that successfully predicted future cognitive decline in an external dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI), even after accounting for age, sex, APOE ε4, years of education, baseline diagnosis, and baseline MMSE score. Our findings are particularly relevant for a better understanding of epigenetic architecture underlying cognitive resilience. Importantly, the significant association between baseline MRS and future cognitive decline demonstrated that DNAm could be a predictive marker for AD, laying the foundation for future studies on personalized AD prevention.

Tau is required for glial lipid droplet formation and resistance to neuronal oxidative stress

The accumulation of reactive oxygen species (ROS) is a common feature of tauopathies, defined by Tau accumulations in neurons and glia. High ROS in neurons causes lipid production and the export of toxic peroxidated lipids (LPOs). Glia uptake these LPOs and incorporate them into lipid droplets (LDs) for storage and catabolism. We found that overexpressing Tau in glia disrupts LDs in flies and rat neuron-astrocyte co-cultures, sensitizing the glia to toxic, neuronal LPOs. Using a new fly tau loss-of-function allele and RNA-mediated interference, we found that endogenous Tau is required for glial LD formation and protection against neuronal LPOs. Similarly, endogenous Tau is required in rat astrocytes and human oligodendrocyte-like cells for LD formation and the breakdown of LPOs. Behaviorally, flies lacking glial Tau have decreased lifespans and motor defects that are rescuable by administering the antioxidant N-acetylcysteine amide. Overall, this work provides insights into the important role that Tau has in glia to mitigate ROS in the brain.

Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Progressive supranuclear palsy (PSP), a rare Parkinsonian disorder, is characterized by problems with movement, balance, and cognition. PSP differs from Alzheimer's disease (AD) and other diseases, displaying abnormal microtubule-associated protein tau by both neuronal and glial cell pathologies. Genetic contributors may mediate these differences; however, the genetics of PSP remain underexplored. Here we conduct the largest genome-wide association study (GWAS) of PSP which includes 2779 cases (2595 neuropathologically-confirmed) and 5584 controls and identify six independent PSP susceptibility loci with genome-wide significant (P < 5 × 10-8) associations, including five known (MAPT, MOBP, STX6, RUNX2, SLCO1A2) and one novel locus (C4A). Integration with cell type-specific epigenomic annotations reveal an oligodendrocytic signature that might distinguish PSP from AD and Parkinson's disease in subsequent studies. Candidate PSP risk gene prioritization using expression quantitative trait loci (eQTLs) identifies oligodendrocyte-specific effects on gene expression in half of the genome-wide significant loci, and an association with C4A expression in brain tissue, which may be driven by increased C4A copy number. Finally, histological studies demonstrate tau aggregates in oligodendrocytes that colocalize with C4 (complement) deposition. Integrating GWAS with functional studies, epigenomic and eQTL analyses, we identify potential causal roles for variation in MOBP, STX6, RUNX2, SLCO1A2, and C4A in PSP pathogenesis.

Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia

Transcriptome-wide association study (TWAS) tools have been applied to conduct proteome-wide association studies (PWASs) by integrating proteomics data with genome-wide association study (GWAS) summary data. The genetic effects of PWAS-identified significant genes are potentially mediated through genetically regulated protein abundance, thus informing the underlying disease mechanisms better than GWAS loci. However, existing TWAS/PWAS tools are limited by considering only one statistical model. We propose an omnibus PWAS pipeline to account for multiple statistical models and demonstrate improved performance by simulation and application studies of Alzheimer disease (AD) dementia. We employ the Aggregated Cauchy Association Test to derive omnibus PWAS (PWAS-O) p values from PWAS p values obtained by three existing tools assuming complementary statistical models-TIGAR, PrediXcan, and FUSION. Our simulation studies demonstrated improved power, with well-calibrated type I error, for PWAS-O over all three individual tools. We applied PWAS-O to studying AD dementia with reference proteomic data profiled from dorsolateral prefrontal cortex of postmortem brains from individuals of European ancestry. We identified 43 risk genes, including 5 not identified by previous studies, which are interconnected through a protein-protein interaction network that includes the well-known AD risk genes TOMM40, APOC1, and APOC2. We also validated causal genetic effects mediated through the proteome for 27 (63%) PWAS-O risk genes, providing insights into the underlying biological mechanisms of AD dementia and highlighting promising targets for therapeutic development. PWAS-O can be easily applied to studying other complex diseases.

Haploinsufficiency of GABAA Receptor-Associated Clptm1 Enhances Phasic and Tonic Inhibitory Neurotransmission, Suppresses Excitatory Synaptic Plasticity, and Impairs Memory

The mechanisms utilized by neurons to regulate the efficacy of phasic and tonic inhibition and their impacts on synaptic plasticity and behavior are incompletely understood. Cleft lip and palate transmembrane protein 1 (Clptm1) is a membrane-spanning protein that interacts with multiple γ-aminobutyric acid type A receptor (GABAAR) subunits, trapping them in the endoplasmic reticulum and Golgi network. Overexpression and knock-down studies suggest that Clptm1 modulates GABAAR-mediated phasic inhibition and tonic inhibition as well as activity-induced inhibitory synaptic homeostasis in cultured hippocampal neurons. To investigate the role of Clptm1 in the modulation of GABAARs in vivo, we generated Clptm1 knock-out (KO) mice. Here, we show that genetic KO of Clptm1 elevated phasic and tonic inhibitory transmission in both male and female heterozygous mice. Although basal excitatory synaptic transmission was not affected, Clptm1 haploinsufficiency significantly blocked high-frequency stimulation-induced long-term potentiation (LTP) in hippocampal CA3→CA1 synapses. In the hippocampus-dependent contextual fear-conditioning behavior task, both male and female Clptm1 heterozygous KO mice exhibited impairment in contextual fear memory. In addition, LTP and contextual fear memory were rescued by application of L-655,708, a negative allosteric modulator of the extrasynaptic GABAAR α5 subunit. These results suggest that haploinsufficiency of Clptm1 contributes to cognitive deficits through altered synaptic transmission and plasticity by elevation of inhibitory neurotransmission, with tonic inhibition playing a major role.

SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning

Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies show that SR-TWAS improves power, due to increased training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real studies identify 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations are found for these significant risk genes.

CD2AP is Co-Expressed with Tropomyosin-Related Kinase A and Ras-Related Protein Rab-5A in Cholinergic Neurons of the Murine Basal Forebrain

Basal forebrain cholinergic neurons project to the hippocampus and cortex, are critical for learning and memory, and are central to the pathogenesis of Alzheimer's disease (AD). GWAS have consistently shown that genomic variants at the CD2AP gene locus are associated with significant increased risk of AD. GWAS studies have also shown that genetic variants in endocytosis genes, including RAB5A , significantly increase susceptibility to AD. Previous work in our lab has shown that CD2AP functions as a docking-scaffold/adaptor protein as a coordinator of nerve growth factor (NGF) and trophic signaling in neurons. We have also demonstrated that CD2AP positively regulates Rab5-mediated mechanisms of endocytosis in primary sensory neurons. The purpose of this study was to perform an in vivo characterization of CD2AP expression in cholinergic neurons of the brain regions most relevant to AD pathogenesis and to investigate the colocalization of CD2AP and Rab5 in cholinergic neurons of the murine basal forebrain. Brain tissue was perfused, harvested from ChAT BAC -eGFP transgenic mice (N=4 male, N=4 female; aged 10 mo), where cholinergic neurons (co-) express green fluorescence protein (GFP) in central and peripheral neurons that express choline acetyltransferase (ChAT). Frozen tissue sections were used to assess the specificity of the reporter in mouse brain along with localization of both CD2AP and Rab5 (co-) expression using immunofluorescence (IF) analysis of ChAT-GFP+ neurons and primary antibodies against ChAT, CD2AP and Rab5. Image J software was used to develop and optimize a colocalization assay for CD2AP and Rab5 puncta. Experiments were repeated in a follow-up cohort of aged-adult mice (N=2 male, N=2 female; aged 18 mo). IF expression of CD2AP was quantified in the basal forebrain, diagonal band of Broca (vDB), and striatal regions and compared to results from the cortical regions of the adult mouse brain. Colocalization of CD2AP was observed in the cell bodies of ChAT-GFP+ neurons of the striatum, vDB and basal forebrain regions, where CD2AP expression intensity as well as the number of cell bodies with positive signal increased incrementally. Colocalization analyses revealed near-complete overlap of CD2AP and Rab5 expression in ChAT-GFP+ cholinergic neurons of the basal forebrain region. We conclude that cholinergic neurons express CD2AP in healthy adult and aged-adult mouse brains. These data provide the first evidence of quantifiable CD2AP protein expression of cholinergic neurons specific to the diagonal band of Broca (vDB) and basal forebrain. Together with previous research from our lab, these data support a role for CD2AP in the pathogenesis of AD through orchestration of endocytosis and retrograde signaling. Ongoing studies are underway to verify these findings in a novel AD mouse model that incorporates the humanized variant of CD2AP , created by MODEL-AD, where we aim to further investigate how CD2AP variants may affect mechanistic components of Rab5 endocytosis as well as subsequent survival of cholinergic neurons in the context of known amyloid beta and Tau pathologies.

MTCH2 in Metabolic Diseases, Neurodegenerative Diseases, Cancers, Embryonic Development and Reproduction

Mitochondrial carrier homolog 2 (MTCH2) is a member of the solute carrier 25 family, located on the outer mitochondrial membrane. MTCH2 was first identified in 2000. The development in MTCH2 research is rapidly increasing. The most well-known role of MTCH2 is linking to the pro-apoptosis BID to facilitate mitochondrial apoptosis. Genetic variants in MTCH2 have been investigated for their association with metabolic and neurodegenerative diseases, however, no intervention or therapeutic suggestions were provided. Recent studies revealed the physiological and pathological function of MTCH2 in metabolic diseases, neurodegenerative diseases, cancers, embryonic development and reproduction via regulating mitochondrial apoptosis, metabolic shift between glycolysis and oxidative phosphorylation, mitochondrial fusion/fission, epithelial-mesenchymal transition, etc. This review endeavors to assess a total of 131 published articles to summarise the structure and physiological/pathological role of MTCH2, which has not previously been conducted. This review concludes that MTCH2 plays a crucial role in metabolic diseases, neurodegenerative diseases, cancers, embryonic development and reproduction, and the predominant molecular mechanism is regulation of mitochondrial function. This review gives a comprehensive state of current knowledgement on MTCH2, which will promote the therapeutic research of MTCH2.

SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine Learning

Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for TWAS. To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies showed that SR-TWAS improved power, due to increased effective training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real application studies identified 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations were found for these significant risk genes.

Brain and Blood Transcriptome-Wide Association Studies Identify Five Novel Genes Associated with Alzheimer's Disease

INTRODUCTION

Transcriptome-wide Association Studies (TWAS) extend genome-wide association studies (GWAS) by integrating genetically-regulated gene expression models. We performed the most powerful AD-TWAS to date, using summary statistics from cis -eQTL meta-analyses and the largest clinically-adjudicated Alzheimer's Disease (AD) GWAS.

METHODS

We implemented the OTTERS TWAS pipeline, leveraging cis -eQTL data from cortical brain tissue (MetaBrain; N=2,683) and blood (eQTLGen; N=31,684) to predict gene expression, then applied these models to AD-GWAS data (Cases=21,982; Controls=44,944).

RESULTS

We identified and validated five novel gene associations in cortical brain tissue ( PRKAG1 , C3orf62 , LYSMD4 , ZNF439 , SLC11A2 ) and six genes proximal to known AD-related GWAS loci (Blood: MYBPC3 ; Brain: MTCH2 , CYB561 , MADD , PSMA5 , ANXA11 ). Further, using causal eQTL fine-mapping, we generated sparse models that retained the strength of the AD-TWAS association for MTCH2 , MADD , ZNF439 , CYB561 , and MYBPC3 .

DISCUSSION

Our comprehensive AD-TWAS discovered new gene associations and provided insights into the functional relevance of previously associated variants.

The biology of mitochondrial carrier homolog 2

The mitochondrial carrier system is in charge of small molecule transport between the mitochondria and the cytoplasm as well as being an integral portion of the core mitochondrial function. One member of the mitochondrial carrier family of proteins, mitochondrial carrier homolog 2 (MTCH2), is characterized as a critical mitochondrial outer membrane protein insertase participating in mitochondrial homeostasis. Accumulating evidence demonstrate that MTCH2 is integrally linked to cell death and mitochondrial metabolism, and its genetic alterations cause a variety of disease phenotypes, ranging from obesity, Alzheimer's disease, and tumor. To provide a comprehensive insight into the current understanding of MTCH2, we present a detailed description of the physiopathological functions of MTCH2, ranging from apoptosis, mitochondrial dynamics, and metabolic homeostasis regulation. Moreover, we summarized the impact of MTCH2 in human diseases, and highlighted tumors, to assess the role of MTCH2 mutations or variable expression on pathogenesis and target therapeutic options.

Characterization of brain resilience in Alzheimer's disease using polygenic risk scores and further improvement by integrating mitochondria-associated loci

INTRODUCTION

Identification of high-risk people for Alzheimer's disease (AD) is critical for prognosis and early management. Longitudinal epidemiologic studies have observed heterogeneity in the brain and cognitive aging. Brain resilience was described as above-expected cognitive function. The "resilience" framework has been shown to correlate with individual characteristics such as genetic factors and age. Besides, accumulative evidence has confirmed the association of mitochondria with the pathogenesis of AD. However, it is challenging to assess resilience through genetic metrics, in particular incorporating mitochondria-associated loci.

OBJECTIVES

In this paper, we first demonstrated that polygenic risk scores (PRS) could characterize individuals' resilience levels. Then, we indicated that mitochondria-associated loci could improve the performance of PRSs, providing more reliable measurements for the prevention and diagnosis of AD.

METHODS

The discovery (N = 1,550) and independent validation samples (N = 2,090) were used to construct nine types of PRSs containing mitochondria-related loci (PRSMT) from both biological and statistical aspects and combined them with known AD risk loci derived from genome-wide association studies (GWAS).Individuals' levels of brain resilience were comprehensively measured by linear regression models using eight pathological characteristics.

RESULTS

It was found that PRSs could characterize brain resilience levels (e.g., Pearson correlation test Pmin = 7.96×10-9). Moreover, the performance of PRS models could be efficiently improved by incorporating a small number of mitochondria-related loci (e.g., Pearson correlation test P improved from 1.41×10-3 to 6.09×10-6). PRSs' ability to characterize brain resilience was validated. More importantly, by incorporating some mitochondria-related loci, the performance of PRSs in measuring brain resilience could be significantly improved.

CONCLUSION

Our findings imply that mitochondria may play an important role in brain resilience, and targeting mitochondria may open a new door to AD prevention and therapy.

Multilayer Analysis of RNA Sequencing Data in Alzheimer's Disease to Unravel Molecular Mysteries

Alzheimer's disease (AD) is a complex disease, and numerous cellular events may be involved in etiology. RNAseq-based transcriptome data hold multilayer information content, which could be crucial in unraveling molecular mysteries of AD. It enables quantification of gene expression levels, identification of genomic variants, and elucidation of splicing anomalies such as exon skipping and intron retention. Additional integration of this information into protein-protein interaction networks and genome-scale metabolic models from the literature has potential to decipher functional modules and affected mechanisms for complex scenarios such as AD. In this chapter, we review the application areas of the multilayer content of RNAseq and associated integrative approaches available, with a special focus on AD.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Coexistence of Multiple Functional Variants and Genes Underlies Genetic Risk Locus 11p11.2 of Alzheimer's Disease

BACKGROUND

Genome-wide association studies have identified dozens of genetic risk loci for Alzheimer's disease (AD), yet the underlying causal variants and biological mechanisms remain elusive, especially for loci with complex linkage disequilibrium and regulation.

METHODS

To fully untangle the causal signal at a single locus, we performed a functional genomic study of 11p11.2 (the CELF1/SPI1 locus). Genome-wide association study signals at 11p11.2 were integrated with datasets of histone modification, open chromatin, and transcription factor binding to distill potentially functional variants (fVars). Their allelic regulatory activities were confirmed by allele imbalance, reporter assays, and base editing. Expressional quantitative trait loci and chromatin interaction data were incorporated to assign target genes to fVars. The relevance of these genes to AD was assessed by convergent functional genomics using bulk brain and single-cell transcriptomic, epigenomic, and proteomic datasets of patients with AD and control individuals, followed by cellular assays.

RESULTS

We found that 24 potential fVars, rather than a single variant, were responsible for the risk of 11p11.2. These fVars modulated transcription factor binding and regulated multiple genes by long-range chromatin interactions. Besides SPI1, convergent evidence indicated that 6 target genes (MTCH2, ACP2, NDUFS3, PSMC3, C1QTNF4, and MADD) of fVars were likely to be involved in AD development. Disruption of each gene led to cellular amyloid-β and phosphorylated tau changes, supporting the existence of multiple likely causal genes at 11p11.2.

CONCLUSIONS

Multiple variants and genes at 11p11.2 may contribute to AD risk. This finding provides new insights into the mechanistic and therapeutic challenges of AD.

Expanding causal genes for Parkinson's disease via multi-omics analysis

Genome‑wide association studies (GWASs) have revealed numerous loci associated with Parkinson's disease (PD). However, some potential causal/risk genes were still not revealed and no etiological therapies are available. To find potential causal genes and explore genetically supported drug targets for PD is urgent. By integrating the expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets from multiple tissues (blood, cerebrospinal fluid (CSF) and brain) and PD GWAS summary statistics, a pipeline combing Mendelian randomization (MR), Steiger filtering analysis, Bayesian colocalization, fine mapping, Protein-protein network and enrichment analysis were applied to identify potential causal genes for PD. As a result, GPNMB displayed a robust causal role for PD at the protein level in the blood, CSF and brain, and transcriptional level in the brain, while the protective role of CD38 (in brain pQTL and eQTL) was also identified. We also found inconsistent roles of DGKQ on PD between protein and mRNA levels. Another 9 proteins (CTSB, ARSA, SEC23IP, CD84, ENTPD1, FCGR2B, BAG3, SNCA, FCGR2A) were associated with the risk for PD based on only a single pQTL after multiple corrections. We also identified some proteins' interactions with known PD causative genes and therapeutic targets. In conclusion, this study suggested GPNMB, CD38, and DGKQ may act in the pathogenesis of PD, but whether the other proteins involved in PD needs more evidence. These findings would help to uncover the genes underlying PD and prioritize targets for future therapeutic interventions.

Sex differences in brain protein expression and disease

Most complex human traits differ by sex, but we have limited insight into the underlying mechanisms. Here, we investigated the influence of biological sex on protein expression and its genetic regulation in 1,277 human brain proteomes. We found that 13.2% (1,354) of brain proteins had sex-differentiated abundance and 1.5% (150) of proteins had sex-biased protein quantitative trait loci (sb-pQTLs). Among genes with sex-biased expression, we found 67% concordance between sex-differentiated protein and transcript levels; however, sex effects on the genetic regulation of expression were more evident at the protein level. Considering 24 psychiatric, neurologic and brain morphologic traits, we found that an average of 25% of their putatively causal genes had sex-differentiated protein abundance and 12 putatively causal proteins had sb-pQTLs. Furthermore, integrating sex-specific pQTLs with sex-stratified genome-wide association studies of six psychiatric and neurologic conditions, we uncovered another 23 proteins contributing to these traits in one sex but not the other. Together, these findings begin to provide insights into mechanisms underlying sex differences in brain protein expression and disease.

Integrative Transcriptomic Analyses of Hippocampal-Entorhinal System Subfields Identify Key Regulators in Alzheimer's Disease

The hippocampal-entorhinal system supports cognitive function and is selectively vulnerable to Alzheimer's disease (AD). Little is known about global transcriptomic changes in the hippocampal-entorhinal subfields during AD. Herein, large-scale transcriptomic analysis is performed in five hippocampal-entorhinal subfields of postmortem brain tissues (262 unique samples). Differentially expressed genes are assessed across subfields and disease states, and integrated genotype data from an AD genome-wide association study. An integrative gene network analysis of bulk and single-nucleus RNA sequencing (snRNA-Seq) data identifies genes with causative roles in AD progression. Using a system-biology approach, pathology-specific expression patterns for cell types are demonstrated, notably upregulation of the A1-reactive astrocyte signature in the entorhinal cortex (EC) during AD. SnRNA-Seq data show that PSAP signaling is involved in alterations of cell- communications in the EC during AD. Further experiments validate the key role of PSAP in inducing astrogliosis and an A1-like reactive astrocyte phenotype. In summary, this study reveals subfield-, cell type-, and AD pathology-specific changes and demonstrates PSAP as a potential therapeutic target in AD.

Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 93 risk genes for Alzheimer's disease dementia

Background

Transcriptome-wide association study (TWAS) is an influential tool for identifying novel genes associated with complex diseases, where their genetic effects may be mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate genetic effect sizes on expression quantitative traits of target genes (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are then employed as variant weights in burden gene-based association test statistics, facilitating the mapping of risk genes for complex diseases with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia have primarily focused on cis -eQTL, disregarding potential trans -eQTL. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method which incorporated both cis - and trans -eQTL of brain and blood tissues to enhance mapping risk genes for AD dementia.

Methods

We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis - and trans -eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Subsequently, estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per tissue type. Finally, we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene.

Results

We identified 37 genes in prefrontal cortex, 55 in cortex, and 51 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 93 significant risk genes including 29 genes primarily due to trans -eQTL and 50 novel genes. Utilizing protein-protein interaction network and phenotype enrichment analyses with these 93 significant risk genes, we detected 5 functional clusters comprised of both known and novel AD risk genes and 7 enriched phenotypes.

Conclusion

We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis - and trans -eQTL data of brain and blood tissues with GWAS summary data to identify risk genes of AD dementia. The risk genes we identified provide novel insights into the underlying biological pathways implicated in AD dementia.

A splicing transcriptome-wide association study identifies novel altered splicing for Alzheimer's disease susceptibility

Alzheimer's disease (AD) is a common neurodegenerative disease in aging individuals. Alternative splicing is reported to be relevant to AD development while their roles in etiology of AD remain largely elusive. We performed a comprehensive splicing transcriptome-wide association study (spTWAS) using intronic excision expression genetic prediction models of 12 brain tissues developed through three modelling strategies, to identify candidate susceptibility splicing introns for AD risk. A total of 111,326 (46,828 proxy) cases and 677,663 controls of European ancestry were studied. We identified 343 associations of 233 splicing introns (143 genes) with AD risk after Bonferroni correction (0.05/136,884 = 3.65 × 10^-7). Fine-mapping analyses supported 155 likely causal associations corresponding to 83 splicing introns of 55 genes. Eighteen causal splicing introns of 15 novel genes (EIF2D, WDR33, SAP130, BYSL, EPHB6, MRPL43, VEGFB, PPP1R13B, TLN2, CLUHP3, LRRC37A4P, CRHR1, LINC02210, ZNF45-AS1, and XPNPEP3) were identified for the first time to be related to AD susceptibility. Our study identified novel genes and splicing introns associated with AD risk, which can improve our understanding of the etiology of AD.

Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis

Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.

Integration of transcriptome-wide association study with neuronal dysfunction assays provides functional genomics evidence for Parkinson's disease genes

Genome-wide association studies (GWAS) have markedly advanced our understanding of the genetics of Parkinson's disease (PD), but they currently do not account for the full heritability of PD. In many cases it is difficult to unambiguously identify a specific gene within each locus because GWAS does not provide functional information on the identified candidate loci. Here we present an integrative approach that combines transcriptome-wide association study (TWAS) with high-throughput neuronal dysfunction analyses in Drosophila to discover and validate candidate PD genes. We identified 160 candidate genes whose misexpression is associated with PD risk via TWAS. Candidates were validated using orthogonal in silico methods and found to be functionally related to PD-associated pathways (i.e. endolysosome). We then mimicked these TWAS-predicted transcriptomic alterations in a Drosophila PD model and discovered that 50 candidates can modulate α-Synuclein(α-Syn)-induced neurodegeneration, allowing us to nominate new genes in previously known PD loci. We also uncovered additional novel PD candidate genes within GWAS suggestive loci (e.g. TTC19, ADORA2B, LZTS3, NRBP1, HN1L), which are also supported by clinical and functional evidence. These findings deepen our understanding of PD, and support applying our integrative approach to other complex trait disorders.

Clptm1, a new target in suppressing epileptic seizure by regulating GABAA R-mediated inhibitory synaptic transmission in a PTZ-induced epilepsy model

Disruption of gamma-amino butyric acid type A receptors (GABAA Rs) synaptic clustering and a decrease in the number of GABAA Rs in the plasma membrane are thought to contribute to alteration of the balance between excitatory and inhibitory neurotransmission, which promotes seizure induction and propagation. The multipass transmembrane protein cleft lip and palate transmembrane protein 1 (Clptm1) controls the forward trafficking of GABAA R, thus decaying miniature inhibitory postsynaptic current (mIPSC) of inhibitory synapses. In this study, using a pentylenetetrazol (PTZ)-induced epilepsy rat model, we found that Clptm1 regulates epileptic seizures by modulating GABAA R-mediated inhibitory synaptic transmission. First, we showed that Clptm1 expression was elevated in the PTZ-induced epileptic rats. Subsequently, we found that downregulation of Clptm1 expression protected against PTZ-induced seizures, which was attributed to an increase in the number of GABAA Rγ2s in the plasma membrane and the amplitude of mIPSC. Taken together, our findings identify a new anti-seizure target that provides a theoretical basis for the development of novel strategies for the prevention and treatment of epilepsy.

PICALM and Alzheimer's Disease: An Update and Perspectives

Genome-wide association studies (GWAS) have identified the PICALM (Phosphatidylinositol binding clathrin-assembly protein) gene as the most significant genetic susceptibility locus after APOE and BIN1. PICALM is a clathrin-adaptor protein that plays a critical role in clathrin-mediated endocytosis and autophagy. Since the effects of genetic variants of PICALM as AD-susceptibility loci have been confirmed by independent genetic studies in several distinct cohorts, there has been a number of in vitro and in vivo studies attempting to elucidate the underlying mechanism by which PICALM modulates AD risk. While differential modulation of APP processing and Aβ transcytosis by PICALM has been reported, significant effects of PICALM modulation of tau pathology progression have also been evidenced in Alzheimer's disease models. In this review, we summarize the current knowledge about PICALM, its physiological functions, genetic variants, post-translational modifications and relevance to AD pathogenesis.

Omics-based biomarkers discovery for Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorders presenting with the pathological hallmarks of amyloid plaques and tau tangles. Over the past few years, great efforts have been made to explore reliable biomarkers of AD. High-throughput omics are a technology driven by multiple levels of unbiased data to detect the complex etiology of AD, and it provides us with new opportunities to better understand the pathophysiology of AD and thereby identify potential biomarkers. Through revealing the interaction networks between different molecular levels, the ultimate goal of multi-omics is to improve the diagnosis and treatment of AD. In this review, based on the current AD pathology and the current status of AD diagnostic biomarkers, we summarize how genomics, transcriptomics, proteomics and metabolomics are all conducing to the discovery of reliable AD biomarkers that could be developed and used in clinical AD management.

Shared mechanisms across the major psychiatric and neurodegenerative diseases

Several common psychiatric and neurodegenerative diseases share epidemiologic risk; however, whether they share pathophysiology is unclear and is the focus of our investigation. Using 25 GWAS results and LD score regression, we find eight significant genetic correlations between psychiatric and neurodegenerative diseases. We integrate the GWAS results with human brain transcriptomes (n = 888) and proteomes (n = 722) to identify cis- and trans- transcripts and proteins that are consistent with a pleiotropic or causal role in each disease, referred to as causal proteins for brevity. Within each disease group, we find many distinct and shared causal proteins. Remarkably, 30% (13 of 42) of the neurodegenerative disease causal proteins are shared with psychiatric disorders. Furthermore, we find 2.6-fold more protein-protein interactions among the psychiatric and neurodegenerative causal proteins than expected by chance. Together, our findings suggest these psychiatric and neurodegenerative diseases have shared genetic and molecular pathophysiology, which has important ramifications for early treatment and therapeutic development.

Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder

Genome-wide association studies (GWAS) have identified several risk loci for post-traumatic stress disorder (PTSD); however, how they confer PTSD risk remains unclear. We aimed to identify genes that confer PTSD risk through their effects on brain protein abundance to provide new insights into PTSD pathogenesis. To that end, we integrated human brain proteomes with PTSD GWAS results to perform a proteome-wide association study (PWAS) of PTSD, followed by Mendelian randomization, using a discovery and confirmatory study design. Brain proteomes (N = 525) were profiled from the dorsolateral prefrontal cortex using mass spectrometry. The Million Veteran Program (MVP) PTSD GWAS (n = 186,689) was used for the discovery PWAS, and the Psychiatric Genomics Consortium PTSD GWAS (n = 174,659) was used for the confirmatory PWAS. To understand whether genes identified at the protein-level were also evident at the transcript-level, we performed a transcriptome-wide association study (TWAS) using human brain transcriptomes (N = 888) and the MVP PTSD GWAS results. We identified 11 genes that contribute to PTSD pathogenesis via their respective cis-regulated brain protein abundance. Seven of 11 genes (64%) replicated in the confirmatory PWAS and 4 of 11 also had their cis-regulated brain mRNA levels associated with PTSD. High confidence level was assigned to 9 of 11 genes after considering evidence from the confirmatory PWAS and TWAS. Most of the identified genes are expressed in other PTSD-relevant brain regions and several are preferentially expressed in excitatory neurons, astrocytes, and oligodendrocyte precursor cells. These genes are novel, promising targets for mechanistic and therapeutic studies to find new treatments for PTSD.