The genomic landscape of Ménière's disease: a path to endolymphatic hydrops.

BACKGROUND: Ménière's disease (MD) is a disorder of the inner ear that causes episodic bouts of severe dizziness, roaring tinnitus, and fluctuating hearing loss. To date, no targeted therapy exists. As such, we have undertaken a large whole genome sequencing study on carefully phenotyped unilateral MD patients with the goal of gene/pathway discovery and a move towards targeted intervention. This study was a retrospective review of patients with a history of Ménière's disease. Genomic DNA, acquired from saliva samples, was purified and subjected to whole genome sequencing. RESULTS: Stringent variant calling, performed on 511 samples passing quality checks, followed by gene-based filtering by recurrence and proximity in molecular interaction networks, led to 481 high priority MD genes. These high priority genes, including MPHOSPH8, MYO18A, TRIOBP, OTOGL, TNC, and MYO6, were previously implicated in hearing loss, balance, and cochlear function, and were significantly enriched in common variant studies of hearing loss. Validation in an independent MD cohort confirmed 82 recurrent genes. Pathway analysis pointed to cell-cell adhesion, extracellular matrix, and cellular energy maintenance as key mediators of MD. Furthermore, the MD-prioritized genes were highly expressed in human inner ear hair cells and dark/vestibular cells, and were differentially expressed in a mouse model of hearing loss. CONCLUSION: By enabling the development of model systems that may lead to targeted therapies and MD screening panels, the genes and variants identified in this study will inform diagnosis and treatment of MD.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Axon-derived PACSIN1 binds to the Schwann cell survival receptor, LRP1, and transactivates TrkC to promote gliatrophic activities.

Schwann cells (SCs) undergo phenotypic transformation and then orchestrate nerve repair following PNS injury. The ligands and receptors that activate and sustain SC transformation remain incompletely understood. Proteins released by injured axons represent important candidates for activating the SC Repair Program. The low-density lipoprotein receptor-related protein-1 (LRP1) is acutely up-regulated in SCs in response to injury, activating c-Jun, and promoting SC survival. To identify novel LRP1 ligands released in PNS injury, we applied a discovery-based approach in which extracellular proteins in the injured nerve were captured using Fc-fusion proteins containing the ligand-binding motifs of LRP1 (CCR2 and CCR4). An intracellular neuron-specific protein, Protein Kinase C and Casein Kinase Substrate in Neurons (PACSIN1) was identified and validated as an LRP1 ligand. Recombinant PACSIN1 activated c-Jun and ERK1/2 in cultured SCs. Silencing Lrp1 or inhibiting the LRP1 cell-signaling co-receptor, the NMDA-R, blocked the effects of PACSIN1 on c-Jun and ERK1/2 phosphorylation. Intraneural injection of PACSIN1 into crush-injured sciatic nerves activated c-Jun in wild-type mice, but not in mice in which Lrp1 is conditionally deleted in SCs. Transcriptome profiling of SCs revealed that PACSIN1 mediates gene expression events consistent with transformation to the repair phenotype. PACSIN1 promoted SC migration and viability following the TNFα challenge. When Src family kinases were pharmacologically inhibited or the receptor tyrosine kinase, TrkC, was genetically silenced or pharmacologically inhibited, PACSIN1 failed to induce cell signaling and prevent SC death. Collectively, these studies demonstrate that PACSIN1 is a novel axon-derived LRP1 ligand that activates SC repair signaling by transactivating TrkC.

The Origin and Fate of Liver Myofibroblasts.

Liver fibrosis of different etiologies is a serious health problem worldwide. There is no effective therapy available for liver fibrosis except the removal of the underlying cause of injury or liver transplantation. Development of liver fibrosis is caused by fibrogenic myofibroblasts that are not present in the normal liver, but rather activate from liver resident mesenchymal cells in response to chronic toxic or cholestatic injury. Many studies indicate that liver fibrosis is reversible when the causative agent is removed. Regression of liver fibrosis is associated with the disappearance of activated myofibroblasts and resorption of the fibrous scar. In this review, we discuss the results of genetic tracing and cell fate mapping of hepatic stellate cells and portal fibroblasts, their specific characteristics, and potential phenotypes. We summarize research progress in the understanding of the molecular mechanisms underlying the development and reversibility of liver fibrosis, including activation, apoptosis, and inactivation of myofibroblasts.

Role of Hepatic Stellate and Liver Sinusoidal Endothelial Cells in a Human Primary Cell Three-Dimensional Model of Nonalcoholic Steatohepatitis.

Nonalcoholic steatohepatitis (NASH) is an inflammatory and fibrotic liver disease that has reached epidemic proportions and has no approved pharmacologic therapies. Research and drug development efforts are hampered by inadequate preclinical models. This research describes a three-dimensional bioprinted liver tissue model of NASH built using primary human hepatocytes and nonparenchymal liver cells (hepatic stellate cells, liver sinusoidal endothelial cells, and Kupffer cells) from either healthy or NASH donors. Three-dimensional tissues bioprinted with cells sourced from diseased patients showed a NASH phenotype, including fibrosis. More importantly, this NASH phenotype occurred without the addition of disease-inducing agents. Bioprinted tissues composed entirely of healthy cells exhibited significantly less evidence of disease. The role of individual cell types in driving the NASH phenotype was examined by producing chimeric bioprinted tissues composed of healthy cells together with the addition of one or more diseased nonparenchymal cell types. These experiments reveal a role for both hepatic stellate and liver sinusoidal endothelial cells in the disease process. This model represents a fully human system with potential to detect clinically active targets and eventually therapies.

Resident microbes shape the vaginal epithelial glycan landscape.

Epithelial cells are covered in carbohydrates (glycans). This glycan coat or "glycocalyx" interfaces directly with microbes, providing a protective barrier against potential pathogens. Bacterial vaginosis (BV) is a condition associated with adverse health outcomes in which bacteria reside in direct proximity to the vaginal epithelium. Some of these bacteria, including Gardnerella, produce glycosyl hydrolase enzymes. However, glycans of the human vaginal epithelial surface have not been studied in detail. Here, we elucidate key characteristics of the "normal" vaginal epithelial glycan landscape and analyze the impact of resident microbes on the surface glycocalyx. In human BV, glycocalyx staining was visibly diminished in electron micrographs compared to controls. Biochemical and mass spectrometric analysis showed that, compared to normal vaginal epithelial cells, BV cells were depleted of sialylated N- and O-glycans, with underlying galactose residues exposed on the surface. Treatment of primary epithelial cells from BV-negative women with recombinant Gardnerella sialidases generated BV-like glycan phenotypes. Exposure of cultured VK2 vaginal epithelial cells to recombinant Gardnerella sialidase led to desialylation of glycans and induction of pathways regulating cell death, differentiation, and inflammatory responses. These data provide evidence that vaginal epithelial cells exhibit an altered glycan landscape in BV and suggest that BV-associated glycosidic enzymes may lead to changes in epithelial gene transcription that promote cell turnover and regulate responses toward the resident microbiome.

Lithium Response in Bipolar Disorder is Associated with Focal Adhesion and PI3K-Akt Networks: A Multi-omics Replication Study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2,039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

A Network Landscape of HPVOPC Reveals Methylation Alterations as Significant Drivers of Gene Expression via an Immune-Mediated GPCR Signal.

HPV-associated oropharynx carcinoma (HPVOPC) tumors have a relatively low mutational burden. Elucidating the relative contributions of other tumor alterations, such as DNA methylation alterations, alternative splicing events (ASE), and copy number variation (CNV), could provide a deeper understanding of carcinogenesis drivers in this disease. We applied network propagation analysis to multiple classes of tumor alterations in a discovery cohort of 46 primary HPVOPC tumors and 25 cancer-unaffected controls and validated our findings with TCGA data. We identified significant overlap between differential gene expression networks and all alteration classes, and this association was highest for methylation and lowest for CNV. Significant overlap was seen for gene clusters of G protein-coupled receptor (GPCR) pathways. HPV16-human protein interaction analysis identified an enriched cluster defined by an immune-mediated GPCR signal, including CXCR3 cytokines CXCL9, CXCL10, and CXCL11. CXCR3 was found to be expressed in primary HPVOPC, and scRNA-seq analysis demonstrated CXCR3 ligands to be highly expressed in M2 macrophages. In vivo models demonstrated decreased tumor growth with antagonism of the CXCR3 receptor in immunodeficient but not immunocompetent mice, suggesting that the CXCR3 axis can drive tumor proliferation in an autocrine fashion, but the effect is tempered by an intact immune system. In conclusion, methylation, ASE, and SNV alterations are highly associated with network gene expression changes in HPVOPC, suggesting that ASE and methylation alterations have an important role in driving the oncogenic phenotype. Network analysis identifies GPCR networks, specifically the CXCR3 chemokine axis, as modulators of tumor-immune interactions that may have proliferative effects on primary tumors as well as a role for immunosurveillance; however, CXCR3 inhibition should be used with caution, as these agents may both inhibit and stimulate tumor growth considering the competing effects of this cytokine axis. Further investigation is needed to explore opportunities for targeted therapy in this setting.

Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks.

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis.

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Regulation of Human Endogenous Metabolites by Drug Transporters and Drug Metabolizing Enzymes: An Analysis of Targeted SNP-Metabolite Associations.

Drug transporters and drug-metabolizing enzymes are primarily known for their role in the absorption, distribution, metabolism, and excretion (ADME) of small molecule drugs, but they also play a key role in handling endogenous metabolites. Recent cross-tissue co-expression network analyses have revealed a "Remote Sensing and Signaling Network" of multispecific, oligo-specific, and monospecific transporters and enzymes involved in endogenous metabolism. This includes many proteins from families involved in ADME (e.g., SLC22, SLCO, ABCC, CYP, UGT). Focusing on the gut-liver-kidney axis, we identified the endogenous metabolites potentially regulated by this network of ~1000 proteins by associating SNPs in these genes with the circulating levels of thousands of small, polar, bioactive metabolites, including free fatty acids, eicosanoids, bile acids, and other signaling metabolites that act in part via G-protein coupled receptors (GPCRs), nuclear receptors, and kinases. We identified 77 genomic loci associated with 7236 unique metabolites. This included metabolites that were associated with multiple, distinct loci, indicating coordinated regulation between multiple genes (including drug transporters and drug-metabolizing enzymes) of specific metabolites. We analyzed existing pharmacogenomic data and noted SNPs implicated in endogenous metabolite handling (e.g., rs4149056 in SLCO1B1) also affecting drug ADME. The overall results support the existence of close relationships, via interactions with signaling metabolites, between drug transporters and drug-metabolizing enzymes that are part of the Remote Sensing and Signaling Network, and with GPCRs and nuclear receptors. These analyses highlight the potential for drug-metabolite interactions at the interfaces of the Remote Sensing and Signaling Network and the ADME protein network.

Safer at school early alert: an observational study of wastewater and surface monitoring to detect COVID-19 in elementary schools.

Background: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021. Findings: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Smarcd3 is an epigenetic modulator of the metabolic landscape in pancreatic ductal adenocarcinoma.

Pancreatic cancer is characterized by extensive resistance to conventional therapies, making clinical management a challenge. Here we map the epigenetic dependencies of cancer stem cells, cells that preferentially evade therapy and drive progression, and identify SWI/SNF complex member SMARCD3 as a regulator of pancreatic cancer cells. Although SWI/SNF subunits often act as tumor suppressors, we show that SMARCD3 is amplified in cancer, enriched in pancreatic cancer stem cells and upregulated in the human disease. Diverse genetic mouse models of pancreatic cancer and stage-specific Smarcd3 deletion reveal that Smarcd3 loss preferentially impacts established tumors, improving survival especially in context of chemotherapy. Mechanistically, SMARCD3 acts with FOXA1 to control lipid and fatty acid metabolism, programs associated with therapy resistance and poor prognosis in cancer. These data identify SMARCD3 as an epigenetic modulator responsible for establishing the metabolic landscape in aggressive pancreatic cancer cells and a potential target for new therapies.

Mapping the common gene networks that underlie related diseases.

A longstanding goal of biomedicine is to understand how alterations in molecular and cellular networks give rise to the spectrum of human diseases. For diseases with shared etiology, understanding the common causes allows for improved diagnosis of each disease, development of new therapies and more comprehensive identification of disease genes. Accordingly, this protocol describes how to evaluate the extent to which two diseases, each characterized by a set of mapped genes, are colocalized in a reference gene interaction network. This procedure uses network propagation to measure the network 'distance' between gene sets. For colocalized diseases, the network can be further analyzed to extract common gene communities at progressive granularities. In particular, we show how to: (1) obtain input gene sets and a reference gene interaction network; (2) identify common subnetworks of genes that encompass or are in close proximity to all gene sets; (3) use multiscale community detection to identify systems and pathways represented by each common subnetwork to generate a network colocalized systems map; (4) validate identified genes and systems using a mouse variant database; and (5) visualize and further investigate select genes, interactions and systems for relevance to phenotype(s) of interest. We demonstrate the utility of this approach by identifying shared biological mechanisms underlying autism and congenital heart disease. However, this protocol is general and can be applied to any gene sets attributed to diseases or other phenotypes with suspected joint association. A typical NetColoc run takes less than an hour. Software and documentation are available at https://github.com/ucsd-ccbb/NetColoc .

Wastewater and surface monitoring to detect COVID-19 in elementary school settings: The Safer at School Early Alert project.

Background: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 - March 2021. Findings: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88% - 98%); 67% were associated with a positive wastewater sample (95% CI: 57% - 77%), and 40% were associated with a positive surface sample (95% CI: 29% - 52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Nonalcoholic fatty liver disease risk and histologic severity are associated with genetic polymorphisms in children.

BACKGROUND AND AIMS: NAFLD is the most common chronic liver disease in children. Large pediatric studies identifying single nucleotide polymorphisms (SNPs) associated with risk and histologic severity of NAFLD are limited. Study aims included investigating SNPs associated with risk for NAFLD using family trios and association of candidate alleles with histologic severity. APPROACH AND RESULTS: Children with biopsy-confirmed NAFLD were enrolled from the NASH Clinical Research Network. The Expert Pathology Committee reviewed liver histology. Genotyping was conducted with allele-specific primers for 60 candidate SNPs. Parents were enrolled for trio analysis. To assess risk for NAFLD, the transmission disequilibrium test was conducted in trios. Among cases, regression analysis assessed associations with histologic severity. A total of 822 children with NAFLD had mean age 13.2 years (SD 2.7) and mean ALT 101 U/L (SD 90). PNPLA3 (rs738409) demonstrated the strongest risk ( p = 2.24 × 10 -14 ) for NAFLD. Among children with NAFLD, stratifying by PNPLA3 s738409 genotype, the variant genotype associated with steatosis ( p = 0.005), lobular ( p = 0.03) and portal inflammation ( p = 0.002). Steatosis grade associated with TM6SF2 ( p = 0.0009), GCKR ( p = 0.0032), PNPLA3 rs738409 ( p = 0.0053), and MTTP ( p = 0.0051). Fibrosis stage associated with PARVB rs6006473 ( p = 0.0001), NR1I2 ( p = 0.0021), ADIPOR2 ( p = 0.0038), and OXTR ( p = 0.0065). PNPLA3 rs738409 ( p = 0.0002) associated with borderline zone 1 NASH. CONCLUSIONS: This study demonstrated disease-associated SNPs in children with NAFLD. In particular, rs6006473 was highly associated with severity of fibrosis. These hypothesis-generating results support future mechanistic studies of development of adverse outcomes such as fibrosis and generation of therapeutic targets for NAFLD in children.

Collagenolysis-dependent DDR1 signalling dictates pancreatic cancer outcome.

Pancreatic ductal adenocarcinoma (PDAC) is a highly desmoplastic, aggressive cancer that frequently progresses and spreads by metastasis to the liver1. Cancer-associated fibroblasts, the extracellular matrix and type I collagen (Col I) support2,3 or restrain the progression of PDAC and may impede blood supply and nutrient availability4. The dichotomous role of the stroma in PDAC, and the mechanisms through which it influences patient survival and enables desmoplastic cancers to escape nutrient limitation, remain poorly understood. Here we show that matrix-metalloprotease-cleaved Col I (cCol I) and intact Col I (iCol I) exert opposing effects on PDAC bioenergetics, macropinocytosis, tumour growth and metastasis. Whereas cCol I activates discoidin domain receptor 1 (DDR1)-NF-κB-p62-NRF2 signalling to promote the growth of PDAC, iCol I triggers the degradation of DDR1 and restrains the growth of PDAC. Patients whose tumours are enriched for iCol I and express low levels of DDR1 and NRF2 have improved median survival compared to those whose tumours have high levels of cCol I, DDR1 and NRF2. Inhibition of the DDR1-stimulated expression of NF-κB or mitochondrial biogenesis blocks tumorigenesis in wild-type mice, but not in mice that express MMP-resistant Col I. The diverse effects of the tumour stroma on the growth and metastasis of PDAC and on the survival of patients are mediated through the Col I-DDR1-NF-κB-NRF2 mitochondrial biogenesis pathway, and targeting components of this pathway could provide therapeutic opportunities.

Mutant Huntingtin Protein Interaction Map Implicates Dysregulation of Multiple Cellular Pathways in Neurodegeneration of Huntington's Disease.

BACKGROUND: Huntington's disease (HD) is a genetic neurodegenerative disease caused by trinucleotide repeat (CAG) expansions in the human HTT gene encoding the huntingtin protein (Htt) with an expanded polyglutamine tract. OBJECTIVE: HD models from yeast to transgenic mice have investigated proteins interacting with mutant Htt that may initiate molecular pathways of cell death. There is a paucity of datasets of published Htt protein interactions that include the criteria of 1) defining fragments or full-length Htt forms, 2) indicating the number of poly-glutamines of the mutant and wild-type Htt forms, and 3) evaluating native Htt interaction complexes. This research evaluated such interactor data to gain understanding of Htt dysregulation of cellular pathways. METHODS: Htt interacting proteins were compiled from the literature that meet our criteria and were subjected to network analysis via clustering, gene ontology, and KEGG pathways using rigorous statistical methods. RESULTS: The compiled data of Htt interactors found that both mutant and wild-type Htt interact with more than 2,971 proteins. Application of a community detection algorithm to all known Htt interactors identified significant signal transduction, membrane trafficking, chromatin, and mitochondrial clusters, among others. Binomial analyses of a subset of reported protein interactor information determined that chromatin organization, signal transduction and endocytosis were diminished, while mitochondria, translation and membrane trafficking had enriched overall edge effects. CONCLUSION: The data support the hypothesis that mutant Htt disrupts multiple cellular processes causing toxicity. This dataset is an open resource to aid researchers in formulating hypotheses of HD mechanisms of pathogenesis.

Mapping the gene network landscape of Alzheimer's disease through integrating genomics and transcriptomics.

Integration of multi-omics data with molecular interaction networks enables elucidation of the pathophysiology of Alzheimer's disease (AD). Using the latest genome-wide association studies (GWAS) including proxy cases and the STRING interactome, we identified an AD network of 142 risk genes and 646 network-proximal genes, many of which were linked to synaptic functions annotated by mouse knockout data. The proximal genes were confirmed to be enriched in a replication GWAS of autopsy-documented cases. By integrating the AD gene network with transcriptomic data of AD and healthy temporal cortices, we identified 17 gene clusters of pathways, such as up-regulated complement activation and lipid metabolism, down-regulated cholinergic activity, and dysregulated RNA metabolism and proteostasis. The relationships among these pathways were further organized by a hierarchy of the AD network pinpointing major parent nodes in graph structure including endocytosis and immune reaction. Control analyses were performed using transcriptomics from cerebellum and a brain-specific interactome. Further integration with cell-specific RNA sequencing data demonstrated genes in our clusters of immunoregulation and complement activation were highly expressed in microglia.