A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases

Genomic medicine has paved the way for identifying biomarkers and therapeutically actionable targets for complex diseases, but is complicated by the involvement of thousands of variably expressed genes across multiple cell types. Single-cell RNA-sequencing study (scRNA-seq) allows the characterization of such complex changes in whole organs. The study is based on applying network tools to organize and analyze scRNA-seq data from a mouse model of arthritis and human rheumatoid arthritis, in order to find diagnostic biomarkers and therapeutic targets. Diagnostic validation studies were performed using expression profiling data and potential protein biomarkers from prospective clinical studies of 13 diseases. A candidate drug was examined by a treatment study of a mouse model of arthritis, using phenotypic, immunohistochemical, and cellular analyses as read-outs. We performed the first systematic analysis of pathways, potential biomarkers, and drug targets in scRNA-seq data from a complex disease, starting with inflamed joints and lymph nodes from a mouse model of arthritis. We found the involvement of hundreds of pathways, biomarkers, and drug targets that differed greatly between cell types. Analyses of scRNA-seq and GWAS data from human rheumatoid arthritis (RA) supported a similar dispersion of pathogenic mechanisms in different cell types. Thus, systems-level approaches to prioritize biomarkers and drugs are needed. Here, we present a prioritization strategy that is based on constructing network models of disease-associated cell types and interactions using scRNA-seq data from our mouse model of arthritis, as well as human RA, which we term multicellular disease models (MCDMs). We find that the network centrality of MCDM cell types correlates with the enrichment of genes harboring genetic variants associated with RA and thus could potentially be used to prioritize cell types and genes for diagnostics and therapeutics. We validated this hypothesis in a large-scale study of patients with 13 different autoimmune, allergic, infectious, malignant, endocrine, metabolic, and cardiovascular diseases, as well as a therapeutic study of the mouse arthritis model. Overall, our results support that our strategy has the potential to help prioritize diagnostic and therapeutic targets in human disease.

[1]  Syed Haider,et al.  Ensembl BioMarts: a hub for data retrieval across taxonomic space , 2011, Database J. Biol. Databases Curation.

[2]  Andrew Butler,et al.  Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation , 2018, Nature Communications.

[3]  A. Tarkowski,et al.  Requirement of type I interferon signaling for arthritis triggered by double-stranded RNA. , 2006, Arthritis and rheumatism.

[4]  Mona Singh,et al.  Genome-Wide Detection and Analysis of Multifunctional Genes , 2015, PLoS Comput. Biol..

[5]  S. Steinhubl,et al.  High-Definition Medicine , 2017, Cell.

[6]  Jolien Wolbert,et al.  Deciphering immune mechanisms in chronic inflammatory demyelinating polyneuropathies. , 2020, JCI insight.

[7]  Dawei Li,et al.  High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery , 2020, Frontiers in Genetics.

[8]  Stephen T. C. Wong,et al.  Systems biology–based drug repositioning identifies digoxin as a potential therapy for groups 3 and 4 medulloblastoma , 2018, Science Translational Medicine.

[9]  K. Yoon.  Proliferation Signal Inhibitors for the Treatment of Refractory Autoimmune Rheumatic Diseases , 2009, Annals of the New York Academy of Sciences.

[10]  Mika Gustafsson,et al.  Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis. , 2016, Cell reports.

[11]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[12]  Daniel A. Skelly,et al.  Single-Cell Transcriptional Profiling Reveals Cellular Diversity and Intercommunication in the Mouse Heart. , 2018, Cell reports.

[13]  R. Brook,et al.  The Peroxisome Proliferator Activated Receptor‐γ Pioglitazone Improves Vascular Function and Decreases Disease Activity in Patients With Rheumatoid Arthritis , 2013, Journal of the American Heart Association.

[14]  Mikael Benson,et al.  Single-cell analyses to tailor treatments , 2017, Science Translational Medicine.

[15]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[16]  C. Stein,et al.  Peroxisome proliferator-activated receptor γ agonist effect on rheumatoid arthritis: a randomized controlled trial , 2013, Arthritis Research & Therapy.

[17]  Pablo Villoslada,et al.  Modules, networks and systems medicine for understanding disease and aiding diagnosis , 2014, Genome Medicine.

[18]  Zhangang Xiao,et al.  CD4+ T cells in obesity and obesity-associated diseases. , 2018, Cellular immunology.

[19]  M. Dougados,et al.  Comparative effectiveness of rituximab, abatacept, and tocilizumab in adults with rheumatoid arthritis and inadequate response to TNF inhibitors: prospective cohort study , 2019, British Medical Journal.

[20]  Boxi Kang,et al.  Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing , 2017, Cell.

[21]  L. J. K. Wee,et al.  Author Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors , 2018, Nature Genetics.

[22]  Andrew J. Hill,et al.  Single-cell mRNA quantification and differential analysis with Census , 2017, Nature Methods.

[23]  David A. Knowles,et al.  Inferring relevant cell types for complex traits using single-cell gene expression , 2017, bioRxiv.

[24]  Kerstin B. Meyer,et al.  Single-cell reconstruction of the early maternal–fetal interface in humans , 2018, Nature.

[25]  Manuel A. R. Ferreira,et al.  Multiancestry association study identifies new asthma risk loci that colocalize with immune cell enhancer marks , 2017, Nature Genetics.

[26]  Yang I Li,et al.  An Expanded View of Complex Traits: From Polygenic to Omnigenic , 2017, Cell.

[27]  J. Aguillón,et al.  The role of interleukin‐6 signalling and its therapeutic blockage in skewing the T cell balance in rheumatoid arthritis , 2017, Clinical and experimental immunology.

[28]  J. C. Love,et al.  Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput , 2017, Nature Methods.

[29]  Rabia Begum.  A decade of Genome Medicine: toward precision medicine , 2019, Genome Medicine.

[30]  Cole Trapnell,et al.  The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells , 2014, Nature Biotechnology.

[31]  A. Shilatifard,et al.  Enhancer Logic and Mechanics in Development and Disease. , 2018, Trends in cell biology.

[32]  Sergio Gómez,et al.  Ranking in interconnected multilayer networks reveals versatile nodes , 2015, Nature Communications.

[33]  Tso-Jung Yen,et al.  Discussion on "Stability Selection" by Meinshausen and Buhlmann , 2010 .

[34]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[35]  A. Regev,et al.  Spatial reconstruction of single-cell gene expression , 2015, Nature Biotechnology.

[36]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[37]  Florian Wagner,et al.  K-nearest neighbor smoothing for high-throughput single-cell RNA-Seq data , 2017, bioRxiv.

[38]  S. Uppugunduri,et al.  Local but Not Systemic Administration of Uridine Prevents Development of Antigen-Induced Arthritis , 2015, PloS one.

[39]  J. C. Love,et al.  Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples , 2017 .

[40]  Sergio Gómez,et al.  Ranking in interconnected multilayer networks reveals versatile nodes , 2013, Nature Communications.

[41]  Andreas Krämer,et al.  Causal analysis approaches in Ingenuity Pathway Analysis , 2013, Bioinform..

[42]  G. Hansson.  Inflammation, atherosclerosis, and coronary artery disease. , 2005, The New England journal of medicine.

[43]  Mika Gustafsson,et al.  A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases , 2015, Science Translational Medicine.

[44]  Qi Wang,et al.  Drug Target Protein-Protein Interaction Networks: A Systematic Perspective , 2017, BioMed research international.

[45]  Tracy T Batchelor,et al.  Developmental and oncogenic programs in H3K27M gliomas dissected by single-cell RNA-seq , 2018, Science.

[46]  John C. Earls,et al.  A wellness study of 108 individuals using personal, dense, dynamic data clouds , 2017, Nature Biotechnology.

[47]  K. Van Steen,et al.  New serological markers in inflammatory bowel disease are associated with complicated disease behaviour , 2007, Gut.

[48]  L. Klareskog,et al.  Mechanisms leading from systemic autoimmunity to joint-specific disease in rheumatoid arthritis , 2017, Nature Reviews Rheumatology.

[49]  C. Parish,et al.  Monitoring lymphocyte proliferation in vitro and in vivo with the intracellular fluorescent dye carboxyfluorescein diacetate succinimidyl ester , 2007, Nature Protocols.

[50]  Eun Jung Lee,et al.  Meta-Analysis of Expression Profiling Data Indicates Need for Combinatorial Biomarkers in Pediatric Ulcerative Colitis , 2020, Journal of immunology research.

[51]  Jesper Tegnér,et al.  Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder , 2020, Nature Communications.

[52]  Alex Arenas,et al.  Correction to: A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases , 2020, Genome Medicine.

[53]  Shane J. Neph,et al.  Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.

[54]  J. Loscalzo,et al.  Putting the Patient Back Together - Social Medicine, Network Medicine, and the Limits of Reductionism. , 2017, The New England journal of medicine.

[55]  Colm E. Nestor,et al.  A Generally Applicable Translational Strategy Identifies S100A4 as a Candidate Gene in Allergy , 2014, Science Translational Medicine.

[56]  Weiping Chen,et al.  A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks , 2016, Briefings Bioinform..

[57]  Alex K. Shalek,et al.  Allergic inflammatory memory in human respiratory epithelial progenitor cells , 2018, Nature.

[58]  A. Barabasi,et al.  Network-based in silico drug efficacy screening , 2016, Nature Communications.

[59]  N. Meinshausen,et al.  Stability selection , 2008, 0809.2932.

[60]  G. Lichtenstein.  New serological markers in inflammatory bowel disease are associated with complicated disease behaviour , 2008 .

[61]  T. Meehan,et al.  An atlas of active enhancers across human cell types and tissues , 2014, Nature.

[62]  I. McInnes,et al.  Rheumatoid arthritis , 2016, The Lancet.

[63]  Shawn M. Gillespie,et al.  Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Head and Neck Cancer , 2017, Cell.

[64]  A. Tenenbaum,et al.  Bezafibrate for the treatment of dyslipidemia in patients with coronary artery disease: 20-year mortality follow-up of the BIP randomized control trial , 2016, Cardiovascular Diabetology.

[65]  Ernesto Estrada,et al.  Communicability in complex networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[66]  Y. Okada,et al.  Genetics of rheumatoid arthritis: 2018 status , 2018, Annals of the rheumatic diseases.

[67]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[68]  Daniel Marbach,et al.  Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases , 2016, Nature Methods.

[69]  Núria Queralt-Rosinach,et al.  DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants , 2016, Nucleic Acids Res..

[70]  Damian Szklarczyk,et al.  The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible , 2016, Nucleic Acids Res..

[71]  D. Higham,et al.  A weighted communicability measure applied to complex brain networks , 2009, Journal of The Royal Society Interface.

[72]  Medicine in the digital age , 2019, Nature Medicine.

[73]  Geoffrey S. Ginsburg,et al.  Realizing the Full Potential of Precision Medicine in Health and Health Care. , 2016, JAMA.

[74]  C. Werning.  [Rheumatoid arthritis]. , 1983, Medizinische Monatsschrift fur Pharmazeuten.

[75]  A. Shintani,et al.  Peroxisome proliferator-activated receptor gamma agonist effect on rheumatoid arthritis : a randomized controlled trial , 2013 .

[76]  Shuqiang Li,et al.  Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue , 2018, Arthritis Research & Therapy.

[77]  Charles H. Yoon,et al.  IFNγ-Dependent Tissue-Immune Homeostasis Is Co-opted in the Tumor Microenvironment , 2017, Cell.