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Tu Q, Zhao R, Lu N. Evaluation of the diagnostic utility of immune microenvironment-related biomarkers in endometriosis using multidimensional transcriptomic data. J Assist Reprod Genet 2024:10.1007/s10815-024-03261-z. [PMID: 39316330 DOI: 10.1007/s10815-024-03261-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Accepted: 09/11/2024] [Indexed: 09/25/2024] Open
Abstract
PURPOSE Endometriosis (EMS) is a relatively common gynecological disorder and almost fifty percent of women with EMS suffer from infertility. There are few treatment options for endometriosis, and often recurrences occur following surgery and medication. We aimed to identify potential diagnostic biomarkers for EMS to improve its diagnostic efficiency. METHODS Differential analysis was utilized to choose EMS-associated abnormal miRNAs (DEMIs) and mRNAs (DEMs). ImmuneAI analysis was to evaluate the levels of immune cells in EMS. Next, the weighted gene co-expression network analysis (WGCNA) was utilized to identify the co-expression modules. Random forest and SVM analyses were used to filter the candidate biomarkers and construct the diagnostic model. qRT-PCR was used to test the expression level of the biomarkers. RESULTS Based on the different analyses, we obtained 32 DEMIs and 516 DEMs and selected 9 abnormal immune cells whose abundance is abnormal in EMS. Next, we identified five co-expression modules associated with these abnormal immune cells. Then, 176 candidate genes which are both miRNA targets and associated with immune cells and aberrantly expressed in EMS were filtered. Subsequently, random forest analysis selected 11 genes as the diagnostic biomarkers and constructed a diagnostic model by SVM. Finally, we demonstrated that 8 of the 11 genes aberrantly expressed and with better diagnostic efficiency in EMS. CONCLUSIONS In total, we identified 11 crucial genes regulated by 8 miRNAs that could serve as promising diagnostic biomarkers for EMS, potentially enhancing disease diagnosis with novel factors.
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Affiliation(s)
- Qing Tu
- Department of Gynecology, Suzhou Ninth People's Hospital, Suzhou, 215200, Jiangsu, China
| | - Ruiheng Zhao
- Department of Gynecology, Suzhou Ninth People's Hospital, Suzhou, 215200, Jiangsu, China
| | - Ning Lu
- Department of Gynecology, Suzhou Ninth People's Hospital, Suzhou, 215200, Jiangsu, China.
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Zhao Q, Wang Q, Li B, Han S, Zhang Y, Wang Y, Lu R, Chen Q, Sun Z, Ding M, Liang Z, Gao Y. The deubiquitinase OTUB1 inhibits gluconeogenesis by stabilizing YWHAB. Cell Signal 2024; 124:111408. [PMID: 39270917 DOI: 10.1016/j.cellsig.2024.111408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 08/30/2024] [Accepted: 09/10/2024] [Indexed: 09/15/2024]
Abstract
Hepatic gluconeogenesis plays a crucial role in maintaining glucose homeostasis and serves as a potential therapeutic target for type 2 diabetes, while its underlying mechanisms are not fully understood. This study elucidates the role of the deubiquitinase OTU domain-containing ubiquitin aldehyde binding protein 1 (OTUB1) in gluconeogenesis. We found that hepatic OTUB1 expression is reduced in both db/db mice and patients with type 2 diabetes. Deletion of hepatic OTUB1 significantly elevates fasting blood glucose levels and increases the expression of key gluconeogenic genes. Conversely, overexpression of OTUB1 in hepatocytes mitigates diabetic hyperglycemia and enhances insulin sensitivity. It is known that the tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein β (YWHAB) functions as an inhibitor of hepatic gluconeogenesis by interacting with forkhead box protein O (FOXO1) and glucagon receptor (GPCR), but its own modification mechanism remains unclear. Our findings indicate that OTUB1 interacts with YWHAB and deubiquitinates it through a catalytic process, which in turn suppresses gluconeogenesis. Therefore, OTUB1 plays a pivotal role in inhibiting hepatic gluconeogenesis, highlighting its potential as a therapeutic target for type 2 diabetes.
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Affiliation(s)
- Qingwen Zhao
- Zhejiang Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Senile Chronic Diseases, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Zhejiang 310006, China
| | - Qianzhuo Wang
- Department of General Practice, The Fourth Clinical School of Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310006, China
| | - Bei Li
- Zhejiang Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Senile Chronic Diseases, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Zhejiang 310006, China
| | - Shuang Han
- Zhejiang Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Senile Chronic Diseases, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Zhejiang 310006, China
| | - Yingjuan Zhang
- Zhejiang Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Senile Chronic Diseases, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Zhejiang 310006, China
| | - Yule Wang
- Zhejiang Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Senile Chronic Diseases, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Zhejiang 310006, China
| | - Ruiling Lu
- Department of General Practice, The Fourth Clinical School of Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310006, China
| | - Qingyan Chen
- Department of General Practice, The Fourth Clinical School of Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310006, China
| | - Zhe Sun
- College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Meng Ding
- Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education, Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Ziwei Liang
- Department of Biomedical Engineering, Research Center for Nano-Biomaterials & Regenerative Medicine, College of Biomedical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Yue Gao
- Zhejiang Key Laboratory of Traditional Chinese Medicine for the Prevention and Treatment of Senile Chronic Diseases, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Zhejiang 310006, China.
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Clemens Z, Wang K, Ambrosio F, Barchowsky A. Arsenic disrupts extracellular vesicle-mediated signaling in regenerating myofibers. Toxicol Sci 2023; 195:231-245. [PMID: 37527016 PMCID: PMC10535782 DOI: 10.1093/toxsci/kfad075] [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: 08/03/2023] Open
Abstract
Chronic exposure to environmental arsenic is a public health crisis affecting hundreds of millions of individuals worldwide. Though arsenic is known to contribute to many pathologies and diseases, including cancers, cardiovascular and pulmonary diseases, and neurological impairment, the mechanisms for arsenic-promoted disease remain unresolved. This is especially true for arsenic impacts on skeletal muscle function and metabolism, despite the crucial role that skeletal muscle health plays in maintaining cardiovascular health, systemic homeostasis, and cognition. A barrier to researching this area is the challenge of interrogating muscle cell-specific effects in biologically relevant models. Ex vivo studies investigating mechanisms for muscle-specific responses to arsenic or other environmental contaminants primarily utilize traditional 2-dimensional culture models that cannot elucidate effects on muscle physiology or function. Therefore, we developed a contractile 3-dimensional muscle construct model-composed of primary mouse muscle progenitor cells differentiated in a hydrogel matrix-to study arsenic exposure impacts on skeletal muscle regeneration. Muscle constructs exposed to low-dose (50 nM) arsenic exhibited reduced strength and myofiber diameter following recovery from muscle injury. These effects were attributable to dysfunctional paracrine signaling mediated by extracellular vesicles (EVs) released from muscle cells. Specifically, we found that EVs collected from arsenic-exposed muscle constructs recapitulated the inhibitory effects of direct arsenic exposure on myofiber regeneration. In addition, muscle constructs treated with EVs isolated from muscles of arsenic-exposed mice displayed significantly decreased strength. Our findings highlight a novel model for muscle toxicity research and uncover a mechanism of arsenic-induced muscle dysfunction by the disruption of EV-mediated intercellular communication.
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Affiliation(s)
- Zachary Clemens
- Department of Environmental and Occupational Health, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Kai Wang
- Discovery Center for Musculoskeletal Recovery, Schoen Adams Research Institute at Spaulding, Boston, Massachusetts, USA
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA
| | - Fabrisia Ambrosio
- Discovery Center for Musculoskeletal Recovery, Schoen Adams Research Institute at Spaulding, Boston, Massachusetts, USA
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA
| | - Aaron Barchowsky
- Department of Environmental and Occupational Health, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
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Brotman SM, Raulerson CK, Vadlamudi S, Currin KW, Shen Q, Parsons VA, Iyengar AK, Roman TS, Furey TS, Kuusisto J, Collins FS, Boehnke M, Laakso M, Pajukanta P, Mohlke KL. Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits. Am J Hum Genet 2022; 109:66-80. [PMID: 34995504 PMCID: PMC8764203 DOI: 10.1016/j.ajhg.2021.11.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/23/2021] [Indexed: 01/13/2023] Open
Abstract
Alternate splicing events can create isoforms that alter gene function, and genetic variants associated with alternate gene isoforms may reveal molecular mechanisms of disease. We used subcutaneous adipose tissue of 426 Finnish men from the METSIM study and identified splice junction quantitative trait loci (sQTLs) for 6,077 splice junctions (FDR < 1%). In the same individuals, we detected expression QTLs (eQTLs) for 59,443 exons and 15,397 genes (FDR < 1%). We identified 595 genes with an sQTL and exon eQTL but no gene eQTL, which could indicate potential isoform differences. Of the significant sQTL signals, 2,114 (39.8%) included at least one proxy variant (linkage disequilibrium r2 > 0.8) located within an intron spanned by the splice junction. We identified 203 sQTLs that colocalized with 141 genome-wide association study (GWAS) signals for cardiometabolic traits, including 25 signals for lipid traits, 24 signals for body mass index (BMI), and 12 signals for waist-hip ratio adjusted for BMI. Among all 141 GWAS signals colocalized with an sQTL, we detected 26 that also colocalized with an exon eQTL for an exon skipped by the sQTL splice junction. At a GWAS signal for high-density lipoprotein cholesterol colocalized with an NR1H3 sQTL splice junction, we show that the alternative splice product encodes an NR1H3 transcription factor that lacks a DNA binding domain and fails to activate transcription. Together, these results detect splicing events and candidate mechanisms that may contribute to gene function at GWAS loci.
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Affiliation(s)
- Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Chelsea K Raulerson
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Qiujin Shen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Victoria A Parsons
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Apoorva K Iyengar
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Tamara S Roman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Terrence S Furey
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio 70210, Finland
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio 70210, Finland
| | - Päivi Pajukanta
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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