A Network of SLC and ABC Transporter and DME Genes Involved in Remote Sensing and Signaling in the Gut-Liver-Kidney Axis.

Genes central to drug absorption, distribution, metabolism and elimination (ADME) also regulate numerous endogenous molecules. The Remote Sensing and Signaling Hypothesis argues that an ADME gene-centered network-including SLC and ABC "drug" transporters, "drug" metabolizing enzymes (DMEs), and regulatory genes-is essential for inter-organ communication via metabolites, signaling molecules, antioxidants, gut microbiome products, uremic solutes, and uremic toxins. By cross-tissue co-expression network analysis, the gut, liver, and kidney (GLK) formed highly connected tissue-specific clusters of SLC transporters, ABC transporters, and DMEs. SLC22, SLC25 and SLC35 families were network hubs, having more inter-organ and intra-organ connections than other families. Analysis of the GLK network revealed key physiological pathways (e.g., involving bile acids and uric acid). A search for additional genes interacting with the network identified HNF4α, HNF1α, and PXR. Knockout gene expression data confirmed ~60-70% of predictions of ADME gene regulation by these transcription factors. Using the GLK network and known ADME genes, we built a tentative gut-liver-kidney "remote sensing and signaling network" consisting of SLC and ABC transporters, as well as DMEs and regulatory proteins. Together with protein-protein interactions to prioritize likely functional connections, this network suggests how multi-specificity combines with oligo-specificity and mono-specificity to regulate homeostasis of numerous endogenous small molecules

Ten Simple Rules for Reproducible Research in Jupyter Notebooks

Reproducibility of computational studies is a hallmark of scientific methodology. It enables researchers to build with confidence on the methods and findings of others, reuse and extend computational pipelines, and thereby drive scientific progress. Since many experimental studies rely on computational analyses, biologists need guidance on how to set up and document reproducible data analyses or simulations. In this paper, we address several questions about reproducibility. For example, what are the technical and non-technical barriers to reproducible computational studies? What opportunities and challenges do computational notebooks offer to overcome some of these barriers? What tools are available and how can they be used effectively? We have developed a set of rules to serve as a guide to scientists with a specific focus on computational notebook systems, such as Jupyter Notebooks, which have become a tool of choice for many applications. Notebooks combine detailed workflows with narrative text and visualization of results. Combined with software repositories and open source licensing, notebooks are powerful tools for transparent, collaborative, reproducible, and reusable data analyses

Primary Alcohol-Activated Human and Mouse Hepatic Stellate Cells Share Similarities in Gene-Expression Profiles.

Alcoholic liver disease (ALD) is a leading cause of cirrhosis in the United States, which is characterized by extensive deposition of extracellular matrix proteins and formation of a fibrous scar. Hepatic stellate cells (HSCs) are the major source of collagen type 1 producing myofibroblasts in ALD fibrosis. However, the mechanism of alcohol-induced activation of human and mouse HSCs is not fully understood. We compared the gene-expression profiles of primary cultured human HSCs (hHSCs) isolated from patients with ALD (n = 3) or without underlying liver disease (n = 4) using RNA-sequencing analysis. Furthermore, the gene-expression profile of ALD hHSCs was compared with that of alcohol-activated mHSCs (isolated from intragastric alcohol-fed mice) or CCl4-activated mouse HSCs (mHSCs). Comparative transcriptome analysis revealed that ALD hHSCs, in addition to alcohol-activated and CCl4-activated mHSCs, share the expression of common HSC activation (Col1a1 [collagen type I alpha 1 chain], Acta1 [actin alpha 1, skeletal muscle], PAI1 [plasminogen activator inhibitor-1], TIMP1 [tissue inhibitor of metalloproteinase 1], and LOXL2 [lysyl oxidase homolog 2]), indicating that a common mechanism underlies the activation of human and mouse HSCs. Furthermore, alcohol-activated mHSCs most closely recapitulate the gene-expression profile of ALD hHSCs. We identified the genes that are similarly and uniquely up-regulated in primary cultured alcohol-activated hHSCs and freshly isolated mHSCs, which include CSF1R (macrophage colony-stimulating factor 1 receptor), PLEK (pleckstrin), LAPTM5 (lysosmal-associated transmembrane protein 5), CD74 (class I transactivator, the invariant chain), CD53, MMP9 (matrix metallopeptidase 9), CD14, CTSS (cathepsin S), TYROBP (TYRO protein tyrosine kinase-binding protein), and ITGB2 (integrin beta-2), and other genes (compared with CCl4-activated mHSCs). Conclusion: We identified genes in alcohol-activated mHSCs from intragastric alcohol-fed mice that are largely consistent with the gene-expression profile of primary cultured hHSCs from patients with ALD. These genes are unique to alcohol-induced HSC activation in two species, and therefore may become targets or readout for antifibrotic therapy in experimental models of ALD

Causal association of cognitive reserve on Alzheimer's disease with putative sex difference

IntroductionSex-dependent risk factors may underlie sex differences in Alzheimer's disease (AD).MethodsUsing sex-stratified genome-wide association studies (GWAS) of AD, we evaluated associations of 12 traits with AD through polygenic risk scores (PRS) and Mendelian randomization (MR), and explored joint genetic architecture among significant traits by genomic structural equation modeling and network analysis.ResultsAD was associated with lower PRS for premorbid cognitive performance, intelligence, and educational attainment. MR showed a causal role for the cognition-related traits in AD, particularly among females. Their joint genetic components encompassed RNA processing, neuron projection development, and cell cycle pathways that overlap with cellular senescence. Cholesterol and C-reactive protein showed pleiotropy but no causality with AD.DiscussionLower cognitive reserve is causally related to AD. The stronger causal link between cognitive performance and AD in females, despite similar PRS between sexes, suggest these differences may result from gene-environmental interactions accumulated over the lifespan

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

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

BackgroundMénière'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.ResultsStringent 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.ConclusionBy 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

Lipid-associated macrophages’ promotion of fibrosis resolution during MASH regression requires TREM2

While macrophage heterogeneity during metabolic dysfunction-associated steatohepatitis (MASH) has been described, the fate of these macrophages during MASH regression is poorly understood. Comparing macrophage heterogeneity during MASH progression vs regression, we identified specific macrophage subpopulations that are critical for MASH/fibrosis resolution. We elucidated the restorative pathways and gene signatures that define regression-associated macrophages and establish the importance of TREM2+ macrophages during MASH regression. Liver-resident Kupffer cells are lost during MASH and are replaced by four distinct monocyte-derived macrophage subpopulations. Trem2 is expressed in two macrophage subpopulations: i) monocyte-derived macrophages occupying the Kupffer cell niche (MoKC) and ii) lipid-associated macrophages (LAM). In regression livers, no new transcriptionally distinct macrophage subpopulation emerged. However, the relative macrophage composition changed during regression compared to MASH. While MoKC was the major macrophage subpopulation during MASH, they decreased during regression. LAM was the dominant macrophage subtype during MASH regression and maintained Trem2 expression. Both MoKC and LAM were enriched in disease-resolving pathways. Absence of TREM2 restricted the emergence of LAMs and formation of hepatic crown-like structures. TREM2+ macrophages are functionally important not only for restricting MASH-fibrosis progression but also for effective regression of inflammation and fibrosis. TREM2+ macrophages are superior collagen degraders. Lack of TREM2+ macrophages also prevented elimination of hepatic steatosis and inactivation of HSC during regression, indicating their significance in metabolic coordination with other cell types in the liver. TREM2 imparts this protective effect through multifactorial mechanisms, including improved phagocytosis, lipid handling, and collagen degradation

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.publishedVersio

NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab