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Zhao H, Zhou Y, Wang Z, Zhang X, Chen L, Hong Z. Plasma proteins and psoriatic arthritis: a proteome-wide Mendelian randomization study. Front Immunol 2024; 15:1417564. [PMID: 39026678 PMCID: PMC11254630 DOI: 10.3389/fimmu.2024.1417564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 06/21/2024] [Indexed: 07/20/2024] Open
Abstract
Background Previous epidemiological studies have identified a correlation between serum protein levels and Psoriatic Arthritis (PsA). However, the precise nature of this relationship remains uncertain. Therefore, our objective was to assess whether circulating levels of 2,923 plasma proteins are associated with the risk of PsA, utilizing the Mendelian randomization (MR) approach. Methods Two-sample MR analysis was performed to assess the causal impact of proteins on PsA risk. Exposure data for plasma proteins were sourced from a genome-wide association study (GWAS) conducted within the UK Biobank Pharma Proteomics Project, which encompassed 2,923 unique plasma proteins. The outcome data for PsA were sourced from the FinnGen study, a large-scale genomics initiative, comprising 3,537 cases and 262,844 controls. Additionally, colocalization analysis, Phenome-wide MR analysis, and candidate drug prediction were employed to identify potential causal circulating proteins and novel drug targets. Results We thoroughly assessed the association between 1,837 plasma proteins and PsA risk, identifying seven proteins associated with PsA risk. An inverse association of Interleukin-10 (IL-10) with PsA risk was observed [odds ratio (OR)=0.45, 95% confidence interval (CI), 0.28 to 0.70, P FDR=0.072]. Additionally, Apolipoprotein F (APOF) has a positive effect on PsA risk (OR=2.08, 95% CI, 1.51 to 2.86, P FDR=0.005). Subsequently, we found strong evidence indicating that IL-10 and APOF were colocalized with PsA associations (PP.H4 = 0.834 for IL-10 and PP.H4 = 0.900 for APOF). Phenome-wide association analysis suggested that these two proteins may have dual effects on other clinical traits (P FDR<0.1). Conclusion This study identified 7 plasma proteins associated with PsA risk, particularly IL-10 and APOF, which offer new insights into its etiology. Further studies are needed to assess the utility and effectiveness of these candidate proteins.
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Affiliation(s)
- Heran Zhao
- Department of Orthopaedics, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- The Third Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yi Zhou
- Graduate School, Nanjing University of Chinese Medicine, Nanjing, China
| | - Ziyan Wang
- Graduate School, Nanjing University of Chinese Medicine, Nanjing, China
| | - Xuan Zhang
- College of Orthopedics and Traumatology, Guangxi University of Chinese Medicine, Nanning, China
| | - Leilei Chen
- Department of Orthopaedics, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- The Third Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhinan Hong
- Department of Orthopaedics, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- The Third Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, China
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2
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Çam SB, Çiftci E, Gürbüz N, Altun B, Korkusuz P. Allogeneic bone marrow mesenchymal stem cell-derived exosomes alleviate human hypoxic AKI-on-a-Chip within a tight treatment window. Stem Cell Res Ther 2024; 15:105. [PMID: 38600585 PMCID: PMC11005291 DOI: 10.1186/s13287-024-03674-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 02/20/2024] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND Acute hypoxic proximal tubule (PT) injury and subsequent maladaptive repair present high mortality and increased risk of acute kidney injury (AKI) - chronic kidney disease (CKD) transition. Human bone marrow mesenchymal stem cell-derived exosomes (hBMMSC-Exos) as potential cell therapeutics can be translated into clinics if drawbacks on safety and efficacy are clarified. Here, we determined the real-time effective dose and treatment window of allogeneic hBMMSC-Exos, evaluated their performance on the structural and functional integrity of 3D microfluidic acute hypoxic PT injury platform. METHODS hBMMSC-Exos were isolated and characterized. Real-time impedance-based cell proliferation analysis (RTCA) determined the effective dose and treatment window for acute hypoxic PT injury. A 2-lane 3D gravity-driven microfluidic platform was set to mimic PT in vitro. ZO-1, acetylated α-tubulin immunolabelling, and permeability index assessed structural; cell proliferation by WST-1 measured functional integrity of PT. RESULTS hBMMSC-Exos induced PT proliferation with ED50 of 172,582 µg/ml at the 26th hour. Hypoxia significantly decreased ZO-1, increased permeability index, and decreased cell proliferation rate on 24-48 h in the microfluidic platform. hBMMSC-Exos reinforced polarity by a 1.72-fold increase in ZO-1, restored permeability by 20/45-fold against 20/155 kDa dextran and increased epithelial proliferation 3-fold compared to control. CONCLUSIONS The real-time potency assay and 3D gravity-driven microfluidic acute hypoxic PT injury platform precisely demonstrated the therapeutic performance window of allogeneic hBMMSC-Exos on ischemic AKI based on structural and functional cellular data. The novel standardized, non-invasive two-step system validates the cell-based personalized theragnostic tool in a real-time physiological microenvironment prior to safe and efficient clinical usage in nephrology.
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Affiliation(s)
- Sefa Burak Çam
- Faculty of Medicine, Dept. of Histology and Embryology, Hacettepe University, Ankara, Ankara, 06230, Turkey
| | - Eda Çiftci
- Graduate School of Science and Engineering, Department of Bioengineering, Hacettepe University, Ankara, 06230, Turkey
| | - Nazlıhan Gürbüz
- Graduate School of Science and Engineering, Department of Bioengineering, Hacettepe University, Ankara, 06230, Turkey
| | - Bülent Altun
- Faculty of Medicine, Dept. of Nephrology, Hacettepe University, Ankara, 06230, Turkey
| | - Petek Korkusuz
- Faculty of Medicine, Dept. of Histology and Embryology, Hacettepe University, Ankara, Ankara, 06230, Turkey.
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3
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Wagner VA, Holl KL, Clark KC, Reho JJ, Dwinell MR, Lehmler HJ, Raff H, Grobe JL, Kwitek AE. Genetic background in the rat affects endocrine and metabolic outcomes of bisphenol F exposure. Toxicol Sci 2023; 194:84-100. [PMID: 37191987 PMCID: PMC10306406 DOI: 10.1093/toxsci/kfad046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023] Open
Abstract
Environmental bisphenol compounds like bisphenol F (BPF) are endocrine-disrupting chemicals (EDCs) affecting adipose and classical endocrine systems. Genetic factors that influence EDC exposure outcomes are poorly understood and are unaccounted variables that may contribute to the large range of reported outcomes in the human population. We previously demonstrated that BPF exposure increased body growth and adiposity in male N/NIH heterogeneous stock (HS) rats, a genetically heterogeneous outbred population. We hypothesize that the founder strains of the HS rat exhibit EDC effects that were strain- and sex-dependent. Weanling littermate pairs of male and female ACI, BN, BUF, F344, M520, and WKY rats randomly received either vehicle (0.1% EtOH) or 1.125 mg BPF/l in 0.1% EtOH for 10 weeks in drinking water. Body weight and fluid intake were measured weekly, metabolic parameters were assessed, and blood and tissues were collected. BPF increased thyroid weight in ACI males, thymus and kidney weight in BUF females, adrenal weight in WKY males, and possibly increased pituitary weight in BN males. BUF females also developed a disruption in activity and metabolic rate with BPF exposure. These sex- and strain-specific exposure outcomes illustrate that HS rat founders possess diverse bisphenol-exposure risk alleles and suggest that BPF exposure may intensify inherent organ system dysfunction existing in the HS rat founders. We propose that the HS rat will be an invaluable model for dissecting gene EDC interactions on health.
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Affiliation(s)
- Valerie A Wagner
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Katie L Holl
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Karen C Clark
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - John J Reho
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Comprehensive Rodent Metabolic Phenotyping Core, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Melinda R Dwinell
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Rat Genome Database, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Hans-Joachim Lehmler
- Department of Occupational and Environmental Health, University of Iowa, Iowa City, Iowa 52246, USA
| | - Hershel Raff
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Endocrine Research Laboratory, Aurora St. Luke’s Medical Center, Advocate Aurora Research Institute, Milwaukee, Wisconsin 53233, USA
| | - Justin L Grobe
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Comprehensive Rodent Metabolic Phenotyping Core, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Anne E Kwitek
- Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Cardiovascular Center, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Rat Genome Database, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
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Vedi M, Smith JR, Thomas Hayman G, Tutaj M, Brodie KC, De Pons JL, Demos WM, Gibson AC, Kaldunski ML, Lamers L, Laulederkind SJF, Thota J, Thorat K, Tutaj MA, Wang SJ, Zacher S, Dwinell MR, Kwitek AE. 2022 updates to the Rat Genome Database: a Findable, Accessible, Interoperable, and Reusable (FAIR) resource. Genetics 2023; 224:iyad042. [PMID: 36930729 PMCID: PMC10474928 DOI: 10.1093/genetics/iyad042] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 03/07/2023] [Accepted: 03/08/2023] [Indexed: 03/19/2023] Open
Abstract
The Rat Genome Database (RGD, https://rgd.mcw.edu) has evolved from simply a resource for rat genetic markers, maps, and genes, by adding multiple genomic data types and extensive disease and phenotype annotations and developing tools to effectively mine, analyze, and visualize the available data, to empower investigators in their hypothesis-driven research. Leveraging its robust and flexible infrastructure, RGD has added data for human and eight other model organisms (mouse, 13-lined ground squirrel, chinchilla, naked mole-rat, dog, pig, African green monkey/vervet, and bonobo) besides rat to enhance its translational aspect. This article presents an overview of the database with the most recent additions to RGD's genome, variant, and quantitative phenotype data. We also briefly introduce Virtual Comparative Map (VCMap), an updated tool that explores synteny between species as an improvement to RGD's suite of tools, followed by a discussion regarding the refinements to the existing PhenoMiner tool that assists researchers in finding and comparing quantitative data across rat strains. Collectively, RGD focuses on providing a continuously improving, consistent, and high-quality data resource for researchers while advancing data reproducibility and fulfilling Findable, Accessible, Interoperable, and Reusable (FAIR) data principles.
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Affiliation(s)
- Mahima Vedi
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jennifer R Smith
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - G Thomas Hayman
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Monika Tutaj
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Kent C Brodie
- Clinical and Translational Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jeffrey L De Pons
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Wendy M Demos
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Adam C Gibson
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Mary L Kaldunski
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Logan Lamers
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Stanley J F Laulederkind
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Jyothi Thota
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Ketaki Thorat
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Marek A Tutaj
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Shur-Jen Wang
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Stacy Zacher
- Finance and Administration, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Melinda R Dwinell
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Anne E Kwitek
- The Rat Genome Database, Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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5
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Hong-Le T, Crouse WL, Keele GR, Holl K, Seshie O, Tschannen M, Craddock A, Das SK, Szalanczy AM, McDonald B, Grzybowski M, Klotz J, Sharma NK, Geurts AM, Key CCC, Hawkins G, Valdar W, Mott R, Solberg Woods LC. Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats. Diabetes 2023; 72:135-148. [PMID: 36219827 PMCID: PMC9797320 DOI: 10.2337/db22-0252] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 10/04/2022] [Indexed: 01/21/2023]
Abstract
Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.
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Affiliation(s)
- Thu Hong-Le
- Genetics Institute, University College London, London, U.K
| | - Wesley L. Crouse
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Katie Holl
- Medical College of Wisconsin, Milwaukee, WI
| | - Osborne Seshie
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | - Ann Craddock
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Swapan K. Das
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Alexandria M. Szalanczy
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Bailey McDonald
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | | | - Neeraj K. Sharma
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | | | - Chia-Chi Chuang Key
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Gregory Hawkins
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC
| | - William Valdar
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Richard Mott
- Genetics Institute, University College London, London, U.K
| | - Leah C. Solberg Woods
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
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6
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Wang J, Li D, Sun Y, Tian Y. Air pollutants, genetic factors, and risk of chronic kidney disease: Findings from the UK Biobank. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 247:114219. [PMID: 36306611 DOI: 10.1016/j.ecoenv.2022.114219] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/10/2022] [Accepted: 10/19/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Experiment studies have suggested the emerging role of air pollutants in chronic kidney disease (CKD). However, only a few population studies conducted in Asia and North America have assessed their association, and the conclusions remained controversial. This study aims to investigate the effect of air pollutants exposure on CKD in the European population and first explores the modification effect of genetic risk on this association. METHODS 458,968 participants from the UK Biobank were included in this study. Cox proportional hazards model was used to assess the associations of air pollutants (PM2.5, PM10, NO2, and NOx) with incident CKD. A genetic risk score of 53 single nucleotide polymorphisms was constructed to represent the genetic susceptibility to CKD. To assess the interaction effect between air pollutants and the genetic risk, we added a multiplicative interaction term and did a stratified analysis. RESULTS During a median follow-up of 11.7 years, 16,637 incidents of CKD were identified. We observed positive associations between air pollutants exposure and CKD risk with the HRs for CKD were 1.09 (1.07, 1.11), 1.08 (1.06, 1.10), 1.05 (1.03, 1.07), 1.06 (1.04, 1.08) with per IQR (interquartile range) increment in PM2.5, PM10, NO2, and NOx, respectively. Stratified analysis showed that the associations between air pollutants and CKD were modest and marginal in the high genetic risk population (P > 0.05), while the associations were statistically significant in the low and intermediate genetic risk groups. CONCLUSIONS Our study indicated that exposure to various air pollutants, including PM2.5, PM10, NO2, and NOx, was associated with an elevated risk of CKD. This finding provide evidence that formulating strategies to improve air quality can be helpful to reduce the burden of CKD.
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Affiliation(s)
- Jianing Wang
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dankang Li
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yu Sun
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yaohua Tian
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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7
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Das AS, Sherry EC, Vaughan RM, Henderson ML, Zieba J, Uhl KL, Koehn O, Bupp CP, Rajasekaran S, Li X, Chhetri SB, Nissim S, Williams CL, Prokop JW. The complex, dynamic SpliceOme of the small GTPase transcripts altered by technique, sex, genetics, tissue specificity, and RNA base editing. Front Cell Dev Biol 2022; 10:1033695. [PMID: 36467401 PMCID: PMC9714508 DOI: 10.3389/fcell.2022.1033695] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/01/2022] [Indexed: 04/04/2024] Open
Abstract
The small GTPase family is well-studied in cancer and cellular physiology. With 162 annotated human genes, the family has a broad expression throughout cells of the body. Members of the family have multiple exons that require splicing. Yet, the role of splicing within the family has been underexplored. We have studied the splicing dynamics of small GTPases throughout 41,671 samples by integrating Nanopore and Illumina sequencing techniques. Within this work, we have made several discoveries. 1). Using the GTEx long read data of 92 samples, each small GTPase gene averages two transcripts, with 83 genes (51%) expressing two or more isoforms. 2). Cross-tissue analysis of GTEx from 17,382 samples shows 41 genes (25%) expressing two or more protein-coding isoforms. These include protein-changing transcripts in genes such as RHOA, RAB37, RAB40C, RAB4B, RAB5C, RHOC, RAB1A, RAN, RHEB, RAC1, and KRAS. 3). The isolation and library technique of the RNAseq influences the abundance of non-sense-mediated decay and retained intron transcripts of small GTPases, which are observed more often in genes than appreciated. 4). Analysis of 16,243 samples of "Blood PAXgene" identified seven genes (3.7%; RHOA, RAB40C, RAB4B, RAB37, RAB5B, RAB5C, RHOC) with two or more transcripts expressed as the major isoform (75% of the total gene), suggesting a role of genetics in altering splicing. 5). Rare (ARL6, RAB23, ARL13B, HRAS, NRAS) and common variants (GEM, RHOC, MRAS, RAB5B, RERG, ARL16) can influence splicing and have an impact on phenotypes and diseases. 6). Multiple genes (RAB9A, RAP2C, ARL4A, RAB3A, RAB26, RAB3C, RASL10A, RAB40B, and HRAS) have sex differences in transcript expression. 7). Several exons are included or excluded for small GTPase genes (RASEF, KRAS, RAC1, RHEB, ARL4A, RHOA, RAB30, RHOBTB1, ARL16, RAP1A) in one or more forms of cancer. 8). Ten transcripts are altered in hypoxia (SAR1B, IFT27, ARL14, RAB11A, RAB10, RAB38, RAN, RIT1, RAB9A) with RHOA identified to have a transient 3'UTR RNA base editing at a conserved site found in all of its transcripts. Overall, we show a remarkable and dynamic role of splicing within the small GTPase family that requires future explorations.
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Affiliation(s)
- Akansha S. Das
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- Department of Biology, Washington and Jefferson College, Washington, PA, United States
| | - Emily C. Sherry
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- Department of Cell and Molecular Biology, Grand Valley State University, Allendale, MI, United States
| | - Robert M. Vaughan
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
| | - Marian L. Henderson
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- The Department of Biology, Calvin University, Grand Rapids, MI, United States
| | - Jacob Zieba
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- Genetics and Genome Sciences Program, BioMolecular Science, Michigan State University, East Lansing, MI, United States
| | - Katie L. Uhl
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
| | - Olivia Koehn
- Department of Pharmacology and Toxicology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Caleb P. Bupp
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- Medical Genetics, Spectrum Health and Helen DeVos Children’s Hospital, Grand Rapids, MI, United States
| | - Surender Rajasekaran
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- Department of Pediatric Critical Care Medicine, Helen DeVos Children’s Hospital Spectrum Health, Grand Rapids, MI, United States
- Office of Research, Spectrum Health, Grand Rapids, MI, United States
| | - Xiaopeng Li
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
| | - Surya B. Chhetri
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MA, United States
| | - Sahar Nissim
- Genetics and Gastroenterology Divisions, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Dana-Farber Cancer Institute, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States
| | - Carol L. Williams
- Department of Pharmacology and Toxicology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jeremy W. Prokop
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States
- Genetics and Genome Sciences Program, BioMolecular Science, Michigan State University, East Lansing, MI, United States
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, United States
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8
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Munro D, Wang T, Chitre AS, Polesskaya O, Ehsan N, Gao J, Gusev A, Woods LS, Saba L, Chen H, Palmer A, Mohammadi P. The regulatory landscape of multiple brain regions in outbred heterogeneous stock rats. Nucleic Acids Res 2022; 50:10882-10895. [PMID: 36263809 PMCID: PMC9638908 DOI: 10.1093/nar/gkac912] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/17/2022] [Accepted: 10/05/2022] [Indexed: 11/14/2022] Open
Abstract
Heterogeneous Stock (HS) rats are a genetically diverse outbred rat population that is widely used for studying genetics of behavioral and physiological traits. Mapping Quantitative Trait Loci (QTL) associated with transcriptional changes would help to identify mechanisms underlying these traits. We generated genotype and transcriptome data for five brain regions from 88 HS rats. We identified 21 392 cis-QTLs associated with expression and splicing changes across all five brain regions and validated their effects using allele specific expression data. We identified 80 cases where eQTLs were colocalized with genome-wide association study (GWAS) results from nine physiological traits. Comparing our dataset to human data from the Genotype-Tissue Expression (GTEx) project, we found that the HS rat data yields twice as many significant eQTLs as a similarly sized human dataset. We also identified a modest but highly significant correlation between genetic regulatory variation among orthologous genes. Surprisingly, we found less genetic variation in gene regulation in HS rats relative to humans, though we still found eQTLs for the orthologs of many human genes for which eQTLs had not been found. These data are available from the RatGTEx data portal (RatGTEx.org) and will enable new discoveries of the genetic influences of complex traits.
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Affiliation(s)
- Daniel Munro
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA,Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, USA
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Apurva S Chitre
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Nava Ehsan
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, USA
| | - Jianjun Gao
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Alexander Gusev
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Leah C Solberg Woods
- Section of Molecular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Laura M Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Abraham A Palmer
- Correspondence may also be addressed to Abraham A. Palmer. Tel: +1 858 534 2093;
| | - Pejman Mohammadi
- To whom correspondence should be addressed. Tel: +1 858 784 8746;
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9
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Chen YC, Chang YP, Huang KT, Hsu PY, Hsiao CC, Lin MC. Unraveling the Pathogenesis of Asthma and Chronic Obstructive Pulmonary Disease Overlap: Focusing on Epigenetic Mechanisms. Cells 2022; 11:cells11111728. [PMID: 35681424 PMCID: PMC9179497 DOI: 10.3390/cells11111728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/05/2022] [Accepted: 05/21/2022] [Indexed: 12/10/2022] Open
Abstract
Asthma and COPD overlap (ACO) is characterized by patients presenting with persistent airflow limitation and features of both asthma and COPD. It is associated with a higher frequency and severity of exacerbations, a faster lung function decline, and a higher healthcare cost. Systemic inflammation in COPD and asthma is driven by type 1 T helper (Th1) and Th2 immune responses, respectively, both of which may contribute to airway remodeling in ACO. ACO-related biomarkers can be classified into four categories: neutrophil-mediated inflammation, Th2 cell responses, arachidonic acid-eicosanoids pathway, and metabolites. Gene–environment interactions are key contributors to the complexity of ACO and are regulated by epigenetic mechanisms, including DNA methylation, histone modifications, and non-coding RNAs. Thus, this review focuses on the link between epigenetics and ACO, and outlines the following: (I) inheriting epigenotypes without change with environmental stimuli, or epigenetic changes in response to long-term exposure to inhaled particles plus intermittent exposure to specific allergens; (II) epigenetic markers distinguishing ACO from COPD and asthma; (III) potential epigenetic drugs that can reverse oxidative stress, glucocorticoid insensitivity, and cell injury. Improved understanding of the epigenetic regulations holds great value to give deeper insight into the mechanisms, and clarify their implications for biomedical research in ACO.
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Affiliation(s)
- Yung-Che Chen
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
- Department of Medicine, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Correspondence: (Y.-C.C.); (C.-C.H.); (M.-C.L.); Tel.: +886-7-731-7123 (ext. 8199) (Y.-C.C. & M.-C.L.); +886-7-731-7123 (ext. 8979) (C.-C.H.)
| | - Yu-Ping Chang
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
| | - Kuo-Tung Huang
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
| | - Po-Yuan Hsu
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
| | - Chang-Chun Hsiao
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
- Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Correspondence: (Y.-C.C.); (C.-C.H.); (M.-C.L.); Tel.: +886-7-731-7123 (ext. 8199) (Y.-C.C. & M.-C.L.); +886-7-731-7123 (ext. 8979) (C.-C.H.)
| | - Meng-Chih Lin
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; (Y.-P.C.); (K.-T.H.); (P.-Y.H.)
- Correspondence: (Y.-C.C.); (C.-C.H.); (M.-C.L.); Tel.: +886-7-731-7123 (ext. 8199) (Y.-C.C. & M.-C.L.); +886-7-731-7123 (ext. 8979) (C.-C.H.)
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10
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Crouse WL, Das SK, Le T, Keele G, Holl K, Seshie O, Craddock A, Sharma NK, Comeau ME, Langefeld C, Hawkins GA, Mott R, Valdar W, Solberg Woods LC. Transcriptome-wide analyses of adipose tissue in outbred rats reveal genetic regulatory mechanisms relevant for human obesity. Physiol Genomics 2022; 54:206-219. [PMID: 35467982 DOI: 10.1152/physiolgenomics.00172.2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Transcriptomic analysis in metabolically active tissues allows a systems genetics approach to identify causal genes and networks involved in metabolic disease. Outbred heterogeneous stock (HS) rats are used for genetic mapping of complex traits, but to-date, a systems genetics analysis of metabolic tissues has not been done. We investigated whether adiposity-associated genes and gene co-expression networks in outbred heterogeneous stock (HS) rats overlap those found in humans. We analyzed RNAseq data from adipose tissue of 415 male HS rats, correlated these transcripts with body weight (BW) and compared transcriptome signatures to two human cohorts: the "African American Genetics of Metabolism and Expression" and "Metabolic Syndrome in Men". We used weighted gene co-expression network analysis to identify adiposity-associated gene networks and mediation analysis to identify genes under genetic control whose expression drives adiposity. We identified 554 orthologous "consensus genes" whose expression correlates with BW in the rat and with body mass index (BMI) in both human cohorts. Consensus genes fell within eight co-expressed networks and were enriched for genes involved in immune system function, cell growth, extracellular matrix organization and lipid metabolic processes. We identified 19 consensus genes for which genetic variation may influence BW via their expression, including those involved in lipolysis (e.g., Hcar1), inflammation (e.g., Rgs1), adipogenesis (e.g., Tmem120b) or no previously known role in obesity (e.g., St14, Msa4a6). Strong concordance between HS rat and human BW/BMI associated transcripts demonstrates translational utility of the rat model, while identification of novel genes expands our knowledge of the genetics underlying obesity.
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Affiliation(s)
- Wesley L Crouse
- University of North Carolina at Chapel Hill, Department of Genetics, Chapel Hill, NC, United States
| | - Swapan Kumar Das
- Wake Forest University School of Medicine, Department of Internal Medicine, Winston Salem, NC, United States
| | - Thu Le
- University College London, Department of Genetics, Evolution and Environment, Division of Biosciences, London, United Kingdom
| | - Gregory Keele
- Jackson Laboratories, Roux Center for Genomics and Computational Biology, Bar Harbor, ME, United States
| | - Katie Holl
- Medical College of Wisconsin, Department of Pediatrics, Milwaukee, WI, United States
| | - Osborne Seshie
- Wake Forest University School of Medicine, Department of Internal Medicine, Winston Salem, NC, United States
| | - Ann Craddock
- Wake Forest University School of Medicine, Department of Biochemistry, Winston Salem, NC, United States
| | - Neeraj Kumar Sharma
- Wake Forest University School of Medicine, Department of Internal Medicine, Winston Salem, NC, United States
| | - Mary Elizabeth Comeau
- Wake Forest University School of Medicine, Department of Biostatistics and Data Sciences, Winston Salem, NC, United States
| | - Carl Langefeld
- Wake Forest University School of Medicine, Department of Biostatistics and Data Sciences, Winston Salem, NC, United States
| | - Gregory A Hawkins
- Wake Forest University School of Medicine, Department of Biochemistry, Winston Salem, NC, United States
| | - Richard Mott
- University College London, Department of Genetics, Evolution and Environment, Division of Biosciences, London, United Kingdom
| | - William Valdar
- University of North Carolina at Chapel Hill, Department of Genetics, Chapel Hill, NC, United States
| | - Leah C Solberg Woods
- Wake Forest University School of Medicine, Department of Internal Medicine, Winston Salem, NC, United States
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11
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Prokop JW, Jdanov V, Savage L, Morris M, Lamb N, VanSickle E, Stenger CL, Rajasekaran S, Bupp CP. Computational and Experimental Analysis of Genetic Variants. Compr Physiol 2022; 12:3303-3336. [PMID: 35578967 DOI: 10.1002/cphy.c210012] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Genomics has grown exponentially over the last decade. Common variants are associated with physiological changes through statistical strategies such as Genome-Wide Association Studies (GWAS) and quantitative trail loci (QTL). Rare variants are associated with diseases through extensive filtering tools, including population genomics and trio-based sequencing (parents and probands). However, the genomic associations require follow-up analyses to narrow causal variants, identify genes that are influenced, and to determine the physiological changes. Large quantities of data exist that can be used to connect variants to gene changes, cell types, protein pathways, clinical phenotypes, and animal models that establish physiological genomics. This data combined with bioinformatics including evolutionary analysis, structural insights, and gene regulation can yield testable hypotheses for mechanisms of genomic variants. Molecular biology, biochemistry, cell culture, CRISPR editing, and animal models can test the hypotheses to give molecular variant mechanisms. Variant characterizations can be a significant component of educating future professionals at the undergraduate, graduate, or medical training programs through teaching the basic concepts and terminology of genetics while learning independent research hypothesis design. This article goes through the computational and experimental analysis strategies of variant characterization and provides examples of these tools applied in publications. © 2022 American Physiological Society. Compr Physiol 12:3303-3336, 2022.
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Affiliation(s)
- Jeremy W Prokop
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, Michigan, USA.,Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan, USA
| | - Vladislav Jdanov
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, Michigan, USA
| | - Lane Savage
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, Michigan, USA
| | - Michele Morris
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Neil Lamb
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | | | - Cynthia L Stenger
- Department of Mathematics, University of North Alabama, Florence, Alabama, USA
| | - Surender Rajasekaran
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, Michigan, USA.,Pediatric Intensive Care Unit, Helen DeVos Children's Hospital, Grand Rapids, Michigan, USA.,Office of Research, Spectrum Health, Grand Rapids, Michigan, USA
| | - Caleb P Bupp
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, Michigan, USA.,Medical Genetics, Spectrum Health, Grand Rapids, Michigan, USA
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