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Most disease-gene association methods do not account for gene-gene interactions, even though these play a crucial role in complex, polygenic diseases like Alzheimer's disease (AD). To discover new genes whose interactions may contribute to pathology, we introduce GeneEMBED. This approach compares the functional perturbations induced in gene interaction network neighborhoods by coding variants from disease versus healthy subjects. In two independent AD cohorts of 5,169 exomes and 969 genomes, GeneEMBED identified novel candidates. These genes were differentially expressed in

Heterozygous variants in the glucocerebrosidase (GBA) gene are common and potent risk factors for Parkinson’s disease (PD). GBA also causes the autosomal recessive lysosomal storage disorder (LSD), Gaucher disease, and emerging evidence from human genetics implicates many other LSD genes in PD susceptibility. We have systemically tested 88 conserved fly homologs of 38 human LSD genes for requirements in the aging adult Drosophila brain and for potential genetic interactions with neurodegeneration caused by α-synuclein (αSyn), which forms Lewy body pathology in PD. Our screen identifies 15 genetic enhancers of αSyn-induced progressive locomotor dysfunction, following knockdown of fly homologs of GBA and other LSD genes with independent support as PD susceptibility factors from human genetics (SCARB2, SMPD1, CTSD, GNPTAB, SLC17A5). For several genes, results from multiple alleles support dose-sensitivity and context-dependent pleiotropy in the presence or absence of αSyn. Homologs of 2 genes causing cholesterol storage disorders, Npc1a / NPC1 and Lip4 / LIPA, were independently confirmed as loss-of-function enhancers of αSyn-induced brain structural degeneration. The enzymes encoded by several modifier genes are upregulated in αSyn transgenic flies, based on unbiased proteomics, revealing a possible compensatory response. Overall, our results reinforce the important role of lysosomal genes in brain health and PD pathogenesis, and implicate several metabolic pathways, including cholesterol homeostasis, in αSyn-mediated neurodegeneration.

Background Tau neurofibrillary tangle pathology characterizes Alzheimer’s disease and other neurodegenerative tauopathies. Brain gene expression profiles can reveal mechanisms; however, few studies have systematically examined both the transcriptome and proteome or differentiated Tau- versus age-dependent changes. Methods Paired, longitudinal RNA-sequencing and mass-spectrometry were performed in a Drosophila model of tauopathy, based on pan-neuronal expression of human wildtype Tau (TauWT) or a mutant form causing frontotemporal dementia (TauR406W). Tau-induced, differentially expressed transcripts and proteins were examined cross-sectionally or using linear regression and adjusting for age. Hierarchical clustering was performed to highlight network perturbations, and we examined overlaps with human brain gene expression profiles in tauopathy. Results TauWT induced 1514 and 213 differentially expressed transcripts and proteins, respectively. TauR406W had a substantially greater impact, causing changes in 5494 transcripts and 697 proteins. There was a ~ 70% overlap between age- and Tau-induced changes and our analyses reveal pervasive bi-directional interactions. Strikingly, 42% of Tau-induced transcripts were discordant in the proteome, showing opposite direction of change. Tau-responsive gene expression networks strongly implicate innate immune activation. Cross-species analyses pinpoint human brain gene perturbations specifically triggered by Tau pathology and/or aging, and further differentiate between disease amplifying and protective changes. Conclusions Our results comprise a powerful, cross-species functional genomics resource for tauopathy, revealing Tau-mediated disruption of gene expression, including dynamic, age-dependent interactions between the brain transcriptome and proteome.

SUMMARY We present a consensus atlas of the human brain transcriptome in Alzheimer’s disease (AD), based on meta-analysis of differential gene expression in 2,114 postmortem samples. We discover 30 brain coexpression modules from seven regions as the major source of AD transcriptional perturbations. We next examine overlap with 251 brain differentially expressed gene sets from mouse models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus tau pathology and reveal age- and sex-dependent expression signatures for disease progression. Human coexpression modules enriched for neuronal and/or microglial genes broadly overlap with mouse models of AD, Huntington’s disease, amyotrophic lateral sclerosis, and aging. Other human coexpression modules, including those implicated in proteostasis, are not activated in AD models but rather following other, unexpected genetic manipulations. Our results comprise a cross-species resource, highlighting transcriptional networks altered by human brain pathophysiology and identifying correspondences with mouse models for AD preclinical studies., Graphical Abstract, In Brief Wan et al. develop a consensus atlas of the human brain transcriptome in Alzheimer’s disease, based on 2,114 postmortem samples, and examine overlap with 251 expression signatures from mouse brain RNA sequencing experiments, including many neurodegenerative disease models.

Target nomination for drug development has been a major challenge in the path to finding a cure for several neurological disorders. Comprehensive transcriptome profiles have revealed brain gene expression changes associated with many neurological disorders, and the functional validation of these changes is a critical next step. Model organisms are a proven approach for the elucidation of disease mechanisms, including screening of gene candidates as therapeutic targets. Frequently, multiple models exist for a given disease, creating a challenge to select the optimal model for validation and functional follow-up. To help in nominating the best mouse models for studying neurological diseases, we developed a web portal to visualize mouse transcriptomic data related to neurological disorders: http://mmad.nrihub.org. Users can examine gene expression changes across mouse model studies to help select the optimal mouse model for further investigation. The portal provides access to mouse studies related to Alzheimer&rsquo, s diseases (AD), Parkinson&rsquo, s disease (PD), Huntington&rsquo, s disease (HD), Amyotrophic Lateral Sclerosis (ALS), Spinocerebellar ataxia (SCA), and models related to aging.

SUMMARYHuman brain transcriptomes can highlight biological pathways associated with Alzheimer’s disease (AD); however, challenges remain to link expression changes with causal triggers. We have examined 30 AD-associated, gene coexpression modules from human brains for overlap with 251 differentially-expressed gene sets from mouse brain RNA-sequencing experiments, including from models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus neurofibrillary tangle pathology and further reveal age- and sex-dependent expression signatures for AD progression. Human coexpression modules enriched for neuronal and/or microglial genes overlap broadly with signatures from mouse models of AD, Huntington’s disease, Amyotrophic Lateral Sclerosis, and also aging. Several human AD coexpression modules, including those implicated in the unfolded protein response and oxidative phosphorylation, were not activated in AD models, but instead were detected following other, unexpected mouse genetic manipulations. Our results comprise a powerful, cross-species resource and pinpoint experimental models for diverse features of AD pathophysiology from human brain transcriptomes.