Tensor Decomposition of Stimulated Monocyte and Macrophage Gene Expression Profiles Identifies Neurodegenerative Disease-specific Trans-eQTLs

AbstractRecent human genetic studies suggest that cells of the innate immune system have a primary role in the pathogenesis of neurodegenerative diseases. However, the results from these studies often do not elucidate how the genetic variants affect the biology of these cells to modulate disease risk. Here, we applied a tensor decomposition method to uncover disease-associated gene networks linked to distal genetic variation in stimulated human monocytes and macrophages gene expression profiles. We report robust evidence that some disease-associated genetic variants affect the expression of multiple genes in trans. These include a Parkinson’s disease locus influencing the expression of genes mediated by a protease that controls lysosomal function, and Alzheimer’s disease loci influencing the expression of genes involved in type 1 interferon signaling, myeloid phagocytosis, and complement cascade pathways. Overall, we uncover gene networks in induced innate immune cells linked to disease-associated genetic variants, which may help elucidate the underlying biology of disease.

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Age-related differences in monocyte DNA methylation and immune function in healthy Kenyan adults and children

Immunity & Ageing ◽

10.1186/s12979-021-00223-2 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Katherine R. Dobbs ◽

Paula Embury ◽

Emmily Koech ◽

Sidney Ogolla ◽

Stephen Munga ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Young Adults ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Innate Immune ◽

Inflammatory Gene Expression ◽

Cpg Sites ◽

Age Related ◽

Adults And Children

Abstract Background Age-related changes in adaptive and innate immune cells have been associated with a decline in effective immunity and chronic, low-grade inflammation. Epigenetic, transcriptional, and functional changes in monocytes occur with aging, though most studies to date have focused on differences between young adults and the elderly in populations with European ancestry; few data exist regarding changes that occur in circulating monocytes during the first few decades of life or in African populations. We analyzed DNA methylation profiles, cytokine production, and inflammatory gene expression profiles in monocytes from young adults and children from western Kenya. Results We identified several hypo- and hyper-methylated CpG sites in monocytes from Kenyan young adults vs. children that replicated findings in the current literature of differential DNA methylation in monocytes from elderly persons vs. young adults across diverse populations. Differentially methylated CpG sites were also noted in gene regions important to inflammation and innate immune responses. Monocytes from Kenyan young adults vs. children displayed increased production of IL-8, IL-10, and IL-12p70 in response to TLR4 and TLR2/1 stimulation as well as distinct inflammatory gene expression profiles. Conclusions These findings complement previous reports of age-related methylation changes in isolated monocytes and provide novel insights into the role of age-associated changes in innate immune functions.

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Expression Profiling of Transcriptome and Its Associated Disease Risk in Yang Deficiency Constitution of Healthy Subjects

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2016/1493098 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Ruoxi Yu ◽

Yin Yang ◽

Yuanyuan Han ◽

Pengwei Hou ◽

Yingshuai Li ◽

...

Keyword(s):

Gene Expression ◽

Healthy Subjects ◽

Mononuclear Cells ◽

Clinical Medicine ◽

Disease Risk ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Molecular Evidence ◽

Chinese Han ◽

Peripheral Blood Mononuclear

Objectives. Differences among healthy subjects and associated disease risks are of substantial interest in clinical medicine. According to the theory of “constitution-disease correlation” in traditional Chinese medicine, we try to find out if there is any connection between intolerance of cold in Yang deficiency constitution and molecular evidence and if there is any gene expression basis in specific disorders. Methods. Peripheral blood mononuclear cells were collected from Chinese Han individuals with Yang deficiency constitution (n=20) and balanced constitution (n=8) (aged 18–28) and global gene expression profiles were determined between them using the Affymetrix HG-U133 Plus 2.0 array. Results. The results showed that when the fold change was ≥1.2 and q ≤ 0.05, 909 genes were upregulated in the Yang deficiency constitution, while 1189 genes were downregulated. According to our research differential genes found in Yang deficiency constitution were usually related to lower immunity, metabolic disorders, and cancer tendency. Conclusion. Gene expression disturbance exists in Yang deficiency constitution, which corresponds to the concept of constitution and gene classification. It also suggests people with Yang deficiency constitution are susceptible to autoimmune diseases, enteritis, arthritis, metabolism disorders, and cancer, which provides molecular evidence for the theory of “constitution-disease correlation.”

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Analysis of blood-based gene expression in idiopathic Parkinson disease

Neurology ◽

10.1212/wnl.0000000000004516 ◽

2017 ◽

Vol 89 (16) ◽

pp. 1676-1683 ◽

Cited By ~ 36

Author(s):

Ron Shamir ◽

Christine Klein ◽

David Amar ◽

Eva-Juliane Vollstedt ◽

Michael Bonin ◽

...

Keyword(s):

Gene Expression ◽

Parkinson Disease ◽

Gene Networks ◽

Large Scale ◽

Expression Profiles ◽

Area Under The Curve ◽

Gene Expression Profiles ◽

Gene Signature ◽

Gene Profiles ◽

Independent Test

Objective:To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples).Methods:Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks.Results:A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E–6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E–4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1, ATP5A1, and VDAC3.Conclusions:We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers.

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P02.10 FocuSCOPE: a single cell, multi-omics solution to simultaneously analyze tumor variants and microenvironment

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-itoc8.22 ◽

2021 ◽

Vol 9 (Suppl 1) ◽

pp. A12.1-A12

Author(s):

Y Arjmand Abbassi ◽

N Fang ◽

W Zhu ◽

Y Zhou ◽

Y Chen ◽

...

Keyword(s):

Gene Expression ◽

Tumor Microenvironment ◽

Single Cell ◽

High Throughput ◽

Immune Cells ◽

Genetic Variants ◽

Expression Profiles ◽

Single Cells ◽

Gene Expression Profiles ◽

Single Cell Sequencing

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.

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A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

10.21203/rs.3.rs-766884/v2 ◽

2021 ◽

Author(s):

Taguchi Y-h. ◽

Turki Turki

Keyword(s):

Gene Expression ◽

Learning Strategies ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Tensor Decomposition ◽

Integrated Analysis ◽

Rna Seq ◽

Prior Learning ◽

Multiple Gene ◽

Machine Learning Applications

Abstract The integrated analysis of multiple gene expression profiles measured in distinct studies is always problematic. Especially, missing sample matching and missing common labeling between distinct studies prevent the integration of multiple studies in fully data-driven and unsupervised manner. In this study, we propose a strategy enabling the integration of multiple gene expression profiles among multiple independent studies without either labeling or sample matching, using tensor decomposition-based unsupervised feature extraction. As an example, we applied this strategy to Alzheimer’s disease (AD)-related gene expression profiles that lack exact correspondence among samples as well as AD single-cell RNA-seq (scRNA-seq) data. We found that we could select biologically reasonable genes with integrated analysis. Overall, integrated gene expression profiles can function analogously to prior learning and/or transfer learning strategies in other machine learning applications. For scRNA-seq, the proposed approach was able to drastically reduce the required computational memory.

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Novel analysis of drug-drug interactions reveals the appearance of non-linear dose dependence under the single drug treatment

10.1101/2020.05.13.092718 ◽

2020 ◽

Author(s):

Yh. Taguchi ◽

Turki Turki

Keyword(s):

Gene Expression ◽

Drug Interactions ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Tensor Decomposition ◽

Dose Dependence ◽

Linear Dose ◽

Non Linear ◽

New Interactions ◽

Dose Dependent

ABSTRACTThe accurate prediction of new interactions between drugs is important for avoiding unknown (mild or severe) adverse reactions to drug combinations. The development of effective in silico methods for evaluating drug interactions based on gene expression data requires an under-standing of how various drugs alter gene expression. Current computational methods for the prediction of drug-drug interactions (DDIs) utilize data for known DDIs to predict unknown interactions. However, these methods are limited in the absence of known predictive DDIs. To improve DDIs’ interpretation, a recent study has demonstrated strong non-linear (i.e., dose-dependent) effects of DDIs. In this study, we present a new unsupervised learning approach involving tensor decomposition (TD)-based unsupervised feature extraction (FE) in 3D. We utilize our approach to reanalyze available gene expression profiles for Saccharomyces cerevisiae. We found that non-linearity is possible, even for single drugs. Thus, non-linear dose-dependence cannot always be attributed to DDIs. Our analysis provides a basis for the design of effective methods for evaluating DDIs.

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Building Gene Networks by Analyzing Gene Expression Profiles

Advanced Methodologies and Technologies in Medicine and Healthcare - Advances in Medical Diagnosis, Treatment, and Care ◽

10.4018/978-1-5225-7489-7.ch003 ◽

2019 ◽

pp. 27-44

Author(s):

Crescenzio Gallo

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Gene Networks ◽

Dna Microarrays ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Expression Data ◽

Gene Expressions ◽

Over Time

The possible applications of modeling and simulation in the field of bioinformatics are very extensive, ranging from understanding basic metabolic paths to exploring genetic variability. Experimental results carried out with DNA microarrays allow researchers to measure expression levels for thousands of genes simultaneously, across different conditions and over time. A key step in the analysis of gene expression data is the detection of groups of genes that manifest similar expression patterns. In this chapter, the authors examine various methods for analyzing gene expression data, addressing the important topics of (1) selecting the most differentially expressed genes, (2) grouping them by means of their relationships, and (3) classifying samples based on gene expressions.

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Hemophilia A Inhibitor Subjects Show Unique PBMC Gene Expression Profiles That Include Up-Regulated Innate Immune Modulators

Frontiers in Immunology ◽

10.3389/fimmu.2020.01219 ◽

2020 ◽

Vol 11 ◽

Author(s):

Ahmad Faisal Karim ◽

Anthony R. Soltis ◽

Gauthaman Sukumar ◽

Christoph Königs ◽

Nadia P. Ewing ◽

...

Keyword(s):

Gene Expression ◽

Hemophilia A ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Innate Immune ◽

Immune Modulators

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Profiles of Local and Systemic Inflammation in the Outcome of Treatment of Human Cutaneous Leishmaniasis Caused by Leishmania (Viannia)

Infection and Immunity ◽

10.1128/iai.00764-19 ◽

2019 ◽

Vol 88 (3) ◽

Cited By ~ 1

Author(s):

Adriana Navas ◽

Olga Fernández ◽

Carolina Gallego-Marín ◽

María del Mar Castro ◽

Mariana Rosales-Chilama ◽

...

Keyword(s):

Gene Expression ◽

Immune Responses ◽

Treatment Failure ◽

Cutaneous Leishmaniasis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Neutrophil Activation ◽

Innate Immune ◽

Innate Immune Responses ◽

Biopsy Specimens

ABSTRACT The immune mechanisms that contribute to the efficacy of treatment of cutaneous leishmaniasis (CL) are not fully understood. The aim of this study was to define immune correlates of the outcome of treatment of CL caused by Leishmania (Viannia) species during standard of care treatment with pentavalent antimonials. We conducted a comparative expression profiling of immune response genes in peripheral blood mononuclear cells (PBMCs) and lesion biopsy specimens obtained from CL patients before and at the end of treatment (EoT) with meglumine antimoniate. The ex vivo response of PBMCs to L. (V.) panamensis partially reflected that of lesion microenvironments. Significant downregulation of gene expression profiles consistent with local innate immune responses (monocyte and neutrophil activation and chemoattractant molecules) was observed at EoT in biopsy specimens of patients who cured (n = 8), compared to those from patients with treatment failure (n = 8). Among differentially expressed genes, pretreatment expression of CCL2 was significantly predictive of the therapeutic response (receiver operating characteristic [ROC] curve, area under the curve [AUC] = 0.82, P = 0.02). Polymorphisms in regulatory regions of the CCL2 promoter were analyzed in a pilot cohort of DNA samples from CL patients (cures, n = 20, and treatment failure, n = 20), showing putative association of polymorphisms rs13900(C/T) and rs2857656(G/C) with treatment outcome. Our data indicate that dampening gene expression profiles of monocyte and neutrophil activation characterize clinical cure after treatment of CL, supporting participation of parasite-sustained inflammation or deregulated innate immune responses in treatment failure.

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Monitoring expression of genes involved in drug metabolism and toxicology using DNA microarrays

Physiological Genomics ◽

10.1152/physiolgenomics.2001.5.4.161 ◽

2001 ◽

Vol 5 (4) ◽

pp. 161-170 ◽

Cited By ~ 96

Author(s):

DAVID GERHOLD ◽

MEIQING LU ◽

JIAN XU ◽

CHRISTOPHER AUSTIN ◽

C. THOMAS CASKEY ◽

...

Keyword(s):

Gene Expression ◽

Drug Metabolism ◽

Stress Responses ◽

Dna Microarrays ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Metabolic Effects ◽

Microarray Technology ◽

Drug Candidates ◽

Expression Of Genes

Oligonucleotide DNA microarrays were investigated for utility in measuring global expression profiles of drug metabolism genes. This study was performed to investigate the feasibility of using microarray technology to minimize the long, expensive process of testing drug candidates for safety in animals. In an evaluation of hybridization specificity, microarray technology from Affymetrix distinguished genes up to a threshold of ∼90% DNA identity. Oligonucleotides representing human cytochrome P-450 gene CYP3A5 showed heterologous hybridization to CYP3A4 and CYP3A7 RNAs. These genes could be clearly distinguished by selecting a subset of oligonucleotides that hybridized selectively to CYP3A5. Further validation of the technology was performed by measuring gene expression profiles in livers of rats treated with vehicle, 3-methylcholanthrene (3MC), phenobarbital, dexamethasone, or clofibrate and by confirming data for six genes using quantitative RT-PCR. Responses of drug metabolism genes, including CYPs, epoxide hydrolases ( EHs), UDP-glucuronosyl transferases ( UGTs), glutathione sulfotransferases ( GSTs), sulfotransferases ( STs), drug transporter genes, and peroxisomal genes, to these well-studied compounds agreed well with, and extended, published observations. Additional gene regulatory responses were noted that characterize metabolic effects or stress responses to these compounds. Thus microarray technology can provide a facile overview of gene expression responses relevant to drug metabolism and toxicology.

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