Yulin Dai

The University of Texas Health Science Center at Houston

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Zhongming Zhao

The University of Texas Health Science Center at Houston

118

Peilin Jia

Beijing Institute of Genomics

Holger K. Eltzschig

The University of Texas Health Science Center at Houston

Powel H. Brown

The University of Texas MD Anderson Cancer Center

Kanchan Singh

Bhagwant University

Altaf Mohammed

University of Oklahoma Health Sciences Center

Tingting Mills

The University of Texas Health Science Center at Houston

Florencia McAllister

The University of Texas MD Anderson Cancer Center

Erika Y. Faraoni

The University of Texas Health Science Center at Houston

Emily Vucic

Zephyr Software (United States)

Cooperative Institutions

The University of Texas Health Science Center at Houston

127

The University of Texas MD Anderson Cancer Center

Chinese Academy of Sciences

University of Chinese Academy of Sciences

Sichuan University

Brown Foundation

Chinese Academy of Medical Sciences & Peking Union Medical College

Baylor College of Medicine

Sun Yat-sen University

Shanghai Jiao Tong University

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Biological Psychiatry (2024)

Katherine Thompson Yulin Dai Brisa S. Fernandes Zhongming Zhao Mariam Gachechiladze

Table (database)

10.1016/s0006-3223(24)01152-1

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Economic burden attributable to healthcare-associated infections at western China hospitals: 6 Year, prospective cohort study

Journal of Infection (2023)

Yu Lv Xiaobo Huang Jiayu Wu Xueqin Xiao Chunhua Ma

Healthcare-associated infections (HAIs) represent a major threat to patient safety and are associated with significant economic burden. Calculating the costs attributable to HAIs is challenging given the various sources of bias. Although HAIs as a reasonably preventable medical harm should have been closely linked to medical insurance incentives, there was little linkage between HAIs and medicare in western China owing to the lack of economic evaluation data. The present study aimed to generate estimates of the attributable costs associated with HAIs and the magnitude of costs growth.

10.1016/j.jinf.2023.12.008

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Additional file 3 of Characterization of genome-wide association study data reveals spatiotemporal heterogeneity of mental disorders

Figshare (2020)

Yulin Dai Timothy O’Brien Guangsheng Pei Zhongming Zhao Peilin Jia

Additional file 3. Gene lists merged from the statistically significant modules. Each sheet contains the gene list corresponding to the five psychiatric diseases. (A) ADHD: attention deficit hyperactivity disorder; (B) ASD: autism spectrum disorder; (C) BIP: bipolar disorder; (D) MDD: major depressive disorder; (E) SCZ: schizophrenia; FC: frontal cortex region, SM: sensory motor region, SC: sub-cortical region, TP: temporal-parietal cortex region, ST1: stage 1 (prenatal), ST2: stage 2 (after birth to 11 years old), ST3: stage 3 (older than 13 years)

Association (psychology)

Characterization

10.6084/m9.figshare.13498060

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Genome-Wide Correlation of DNA Methylation and Gene Expression in Postmortem Brain Tissues of Opioid Use Disorder Patients

The International Journal of Neuropsychopharmacology (2021)

Andi Liu Yulin Dai Emily Méndez Ruifeng Hu Gabriel R. Fries

Abstract Background Opioid use disorder (OUD) affects millions of people, causing nearly 50 000 deaths annually in the United States. While opioid exposure and OUD are known to cause widespread transcriptomic and epigenetic changes, few studies in human samples have been conducted. Understanding how OUD affects the brain at the molecular level could help decipher disease pathogenesis and shed light on OUD treatment. Methods We generated genome-wide transcriptomic and DNA methylation profiles of 22 OUD subjects and 19 non-psychiatric controls. We applied weighted gene co-expression network analysis to identify genetic markers consistently associated with OUD at both transcriptomic and methylomic levels. We then performed functional enrichment for biological interpretation. We employed cross-omics analysis to uncover OUD-specific regulatory networks. Results We found 6 OUD-associated co-expression gene modules and 6 co-methylation modules (false discovery rate <0.1). Genes in these modules are involved in astrocyte and glial cell differentiation, gliogenesis, response to organic substance, and response to cytokine (false discovery rate <0.05). Cross-omics analysis revealed immune-related transcription regulators, suggesting the role of transcription factor-targeted regulatory networks in OUD pathogenesis. Conclusions Our integrative analysis of multi-omics data in OUD postmortem brain samples suggested complex gene regulatory mechanisms involved in OUD-associated expression patterns. Candidate genes and their upstream regulators revealed in astrocyte, and glial cells could provide new insights into OUD treatment development.

10.1093/ijnp/pyab043

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Gene expression in mice with endothelium-specific telomerase knockout

Frontiers in Cell and Developmental Biology (2023)

Zhan‐Guo Gao Yongmei Yu Yulin Dai Zhongming Zhao Kristin Eckel‐Mahan

DATA REPORT article Front. Cell Dev. Biol., 07 December 2023Sec. Molecular and Cellular Pathology Volume 11 - 2023 | https://doi.org/10.3389/fcell.2023.1295072

Knockout mouse

Gene knockout

10.3389/fcell.2023.1295072

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CD73-Dependent Adenosine Signaling through Adora2b Drives Immunosuppression in Ductal Pancreatic Cancer

Cancer Research (2023)

Erika Y. Faraoni Kanchan Singh Vidhi Chandra Olivereen Le Roux Yulin Dai

Abstract The microenvironment that surrounds pancreatic ductal adenocarcinoma (PDAC) is profoundly desmoplastic and immunosuppressive. Understanding triggers of immunosuppression during the process of pancreatic tumorigenesis would aid in establishing targets for effective prevention and therapy. Here, we interrogated differential molecular mechanisms dependent on cell of origin and subtype that promote immunosuppression during PDAC initiation and in established tumors. Transcriptomic analysis of cell-of-origin–dependent epithelial gene signatures revealed that Nt5e/CD73, a cell-surface enzyme required for extracellular adenosine generation, is one of the top 10% of genes overexpressed in murine tumors arising from the ductal pancreatic epithelium as opposed to those rising from acinar cells. These findings were confirmed by IHC and high-performance liquid chromatography. Analysis in human PDAC subtypes indicated that high Nt5e in murine ductal PDAC models overlaps with high NT5E in human PDAC squamous and basal subtypes, considered to have the highest immunosuppression and worst prognosis. Multiplex immunofluorescent analysis showed that activated CD8+ T cells in the PDAC tumor microenvironment express high levels of CD73, indicating an opportunity for immunotherapeutic targeting. Delivery of CD73 small-molecule inhibitors through various delivery routes reduced tumor development and growth in genetically engineered and syngeneic mouse models. In addition, the adenosine receptor Adora2b was a determinant of adenosine-mediated immunosuppression in PDAC. These findings highlight a molecular trigger of the immunosuppressive PDAC microenvironment elevated in the ductal cell of origin, linking biology with subtype classification, critical components for PDAC immunoprevention and personalized approaches for immunotherapeutic intervention. Significance: Ductal-derived pancreatic tumors have elevated epithelial and CD8+GZM+ T-cell CD73 expression that confers sensitivity to small-molecule inhibition of CD73 or Adora2b to promote CD8+ T-cell–mediated tumor regression. See related commentary by DelGiorno, p. 977

Immunosuppression

Ectodomain

10.1158/0008-5472.can-22-2553

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Shared genetic components between brain regions identify potential therapeutic targets for Alzheimer’s disease by integrative proteomic analysis

Alzheimer s & Dementia (2022)

Andi Liu Astrid M. Manuel Yulin Dai Brisa S. Fernandes Nitesh Enduru

Abstract Background Genome‐wide association studies (GWAS) have identified >30 genetic loci associated with Alzheimer’s disease (AD). However, how those variants impact protein expression in different brain regions remain elusive. Large‐scale quantitative proteomic datasets of AD postmortem brain tissues have become available with the breakthrough of high‐throughput mass spectrometry‐based technologies. Thus, we utilized these datasets to understand brain region‐specific molecular pathways underlying AD pathogenesis and their potential drug targets. Method We extended our multi‐omics network‐based tool, Edge‐Weighted Dense Module Search of GWAS (EW_dmGWAS), to integrate genetic variants with brain region‐specific proteomic profiles. We performed this analysis by leveraging publicly available AD GWAS statistics of 472,868 individuals (Schwartzentruber et al., 2021) and protein expression profiles covering 190 parahippocampal gyrus (PHG) samples from the Mount Sinai Brain Bank (MSBB) and 192 dorsolateral prefrontal cortex (DLPFC) samples from the Religious Orders Study and Memory and Aging Project (ROSMAP). The resulting modules were evaluated using a scale‐free network index. We highlighted key overlapped genes between region‐specific top module genes (TMGs) and further examined region‐specific differentially co‐expressed genes to identify investigational AD drug targets. Gene set enrichment analyses were performed to assess the functions and cell‐type‐specificity of region‐specific TMGs. Result The EW_dmGWAS analyses prioritized 52 TMGs from PHG and 58 TMGs from DLPFC. The TMGs in both regions were found to be enriched in excitatory neurons through cell‐type‐specific enrichment analysis (combined p‐value = 0.03 in PHG; combined p‐value = 0.09 in DLPFC). We found four key overlapped genes with high genetic risk (gene‐level FDR < 0.05), CLU , PICALM , PRRC2A , and NDUFS3 . In addition, the differentially co‐expressed drug target analysis pinpointed three potentially drug‐targetable genes, APP , SNCA , and VCAM1 , in PHG but none in DLPFC. Additional enrichment analyses of TMGs revealed region‐specific biological processes and drug signatures, including disulfiram in PHG (‐log 2 FDR = 9.5). Conclusion Our network‐based analyses of PHG and DLPFC proteomic profiles prioritized potential key shared genetic factors, which were further proved to play possible roles in the excitatory neurons in AD pathology. Our drug signature analyses validated three known investigational drugs targets, suggesting our findings might serve as a repurposing strategy for AD.

Parahippocampal gyrus

Genome-wide Association Study

Dorsolateral prefrontal cortex

10.1002/alz.061072

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CSEA-DB: an omnibus for human complex trait and cell type associations

Nucleic Acids Research (2020)

Yulin Dai Ruifeng Hu Astrid M. Manuel Andi Liu Peilin Jia

During the past decade, genome-wide association studies (GWAS) have identified many genetic variants with susceptibility to several thousands of complex diseases or traits. The genetic regulation of gene expression is highly tissue-specific and cell type-specific. Recently, single-cell technology has paved the way to dissect cellular heterogeneity in human tissues. Here, we present a reference database for GWAS trait-associated cell type-specificity, named Cell type-Specific Enrichment Analysis DataBase (CSEA-DB, available at https://bioinfo.uth.edu/CSEADB/). Specifically, we curated total of 5120 GWAS summary statistics data for a wide range of human traits and diseases followed by rigorous quality control. We further collected >900 000 cells from the leading consortia such as Human Cell Landscape, Human Cell Atlas, and extensive literature mining, including 752 tissue cell types from 71 adult and fetal tissues across 11 human organ systems. The tissues and cell types were annotated with Uberon and Cell Ontology. By applying our deTS algorithm, we conducted 10 250 480 times of trait-cell type associations, reporting a total of 598 (11.68%) GWAS traits with at least one significantly associated cell type. In summary, CSEA-DB could serve as a repository of association map for human complex traits and their underlying cell types, manually curated GWAS, and single-cell transcriptome resources.

Genome-wide Association Study

Cell type

Trait

Genetic Association

10.1093/nar/gkaa1064

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Additional file 6: of Multiple transcription factors contribute to inter-chromosomal interaction in yeast

Figshare (2018)

Yulin Dai Chao Li Guangsheng Pei Xiao Dong Guohui Ding

Table is for the result of 105 TFs conducted by â Test For Trend In Proportionsâ (prop.trend.test function in R). (XLSX 9Â kb)

Transcription

10.6084/m9.figshare.7502801

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Causal inference of genetic variants and genes in amyotrophic lateral sclerosis

Research Square (Research Square) (2022)

Siyu Pan Xinxuan Liu Tianzi Liu Zhongming Zhao Yulin Dai

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal progressive multisystem disorder with limited therapeutic options. Although genome-wide association studies (GWASs) have revealed multiple ALS susceptibility loci, unraveling causal relationships between genetic variants, genes, cell types, tissues, and risk of ALS remains challenging. Here, we reported a comprehensive post-GWAS analysis of the recent large ALS GWAS (n = 80610), including functional mapping and annotation (FUMA), transcriptome-wide association study (TWAS), colocalization (COLOC) and summary da-ta-based Mendelian Randomization analyses (SMR) in extensive multi-omics datasets. Gene property analysis highlighted inhibitory neuron 6, oligodendrocytes and GABAergic neurons (Gad1/Gad2) as functional cell types of ALS and confirmed cerebellum and cerebellar hemisphere as functional tissues of ALS. Functional annotation detected the presence of multiple deleterious variants at 3 loci (9p21.2, 12q13.3, 12q14.2) and highlighted a list of SNPs that are potentially functional. TWAS, COLOC, and SMR identified 43 genes at 24 loci, including 23 novel genes and 10 novel loci, showing significant evidence of causality. Integrating multiple lines of evidence, we further propose that rs2453555 at 9p21.2 and rs229243 at 14q12 functionally contribute to the development of ALS by regulating the expression of C9orf72 in pituitary and SCFD1 in skeletal muscle, respectively. Overall, our study represents the most comprehensive post GWAS study of ALS to date and provides important new insights into the etiology of ALS.

Genome-wide Association Study

Mendelian Randomization

Genetic Association

Candidate gene

C9ORF72

10.21203/rs.3.rs-1450376/v1

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