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Grosjean I, Roméo B, Domdom MA, Belaid A, D’Andréa G, Guillot N, Gherardi RK, Gal J, Milano G, Marquette CH, Hung RJ, Landi MT, Han Y, Brest P, Von Bergen M, Klionsky DJ, Amos CI, Hofman P, Mograbi B. Autophagopathies: from autophagy gene polymorphisms to precision medicine for human diseases. Autophagy 2022; 18:2519-2536. [PMID: 35383530 PMCID: PMC9629091 DOI: 10.1080/15548627.2022.2039994] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 01/20/2022] [Accepted: 02/06/2022] [Indexed: 12/15/2022] Open
Abstract
At a time when complex diseases affect globally 280 million people and claim 14 million lives every year, there is an urgent need to rapidly increase our knowledge into their underlying etiologies. Though critical in identifying the people at risk, the causal environmental factors (microbiome and/or pollutants) and the affected pathophysiological mechanisms are not well understood. Herein, we consider the variations of autophagy-related (ATG) genes at the heart of mechanisms of increased susceptibility to environmental stress. A comprehensive autophagy genomic resource is presented with 263 single nucleotide polymorphisms (SNPs) for 69 autophagy-related genes associated with 117 autoimmune, inflammatory, infectious, cardiovascular, neurological, respiratory, and endocrine diseases. We thus propose the term 'autophagopathies' to group together a class of complex human diseases the etiology of which lies in a genetic defect of the autophagy machinery, whether directly related or not to an abnormal flux in autophagy, LC3-associated phagocytosis, or any associated trafficking. The future of precision medicine for common diseases will lie in our ability to exploit these ATG SNP x environment relationships to develop new polygenetic risk scores, new management guidelines, and optimal therapies for afflicted patients.Abbreviations: ATG, autophagy-related; ALS-FTD, amyotrophic lateral sclerosis-frontotemporal dementia; ccRCC, clear cell renal cell carcinoma; CD, Crohn disease; COPD, chronic obstructive pulmonary disease; eQTL, expression quantitative trait loci; HCC, hepatocellular carcinoma; HNSCC, head and neck squamous cell carcinoma; GTEx, genotype-tissue expression; GWAS, genome-wide association studies; LAP, LC3-associated phagocytosis; LC3-II, phosphatidylethanolamine conjugated form of LC3; LD, linkage disequilibrium; LUAD, lung adenocarcinoma; MAF, minor allele frequency; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; NSCLC, non-small cell lung cancer; OS, overall survival; PtdIns3K CIII, class III phosphatidylinositol 3 kinase; PtdIns3P, phosphatidylinositol-3-phosphate; SLE, systemic lupus erythematosus; SNPs, single-nucleotide polymorphisms; mQTL, methylation quantitative trait loci; ULK, unc-51 like autophagy activating kinase; UTRs, untranslated regions; WHO, World Health Organization.
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Affiliation(s)
- Iris Grosjean
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
| | - Barnabé Roméo
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
| | - Marie-Angela Domdom
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
| | - Amine Belaid
- Université Côte d’Azur (UCA), INSERM U1065, C3M, Team 5, F-06204, France
| | - Grégoire D’Andréa
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
- ENT and Head and Neck surgery department, Institut Universitaire de la Face et du Cou, CHU de Nice, University Hospital, Côte d’Azur University, Nice, France
| | - Nicolas Guillot
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
| | - Romain K Gherardi
- INSERM U955 Team Relais, Faculty of Health, Paris Est University, France
| | - Jocelyn Gal
- University Côte d’Azur, Centre Antoine Lacassagne, Epidemiology and Biostatistics Department, Nice, France
| | - Gérard Milano
- Université Côte d’Azur, Centre Antoine Lacassagne, UPR7497, Nice, France
| | - Charles Hugo Marquette
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
- University Côte d’Azur, FHU-OncoAge, Department of Pulmonary Medicine and Oncology, CHU de Nice, Nice, France
| | - Rayjean J. Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada; Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Patrick Brest
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
| | - Martin Von Bergen
- Helmholtz Centre for Environmental Research GmbH - UFZ, Dep. of Molecular Systems Biology; University of Leipzig, Faculty of Life Sciences, Institute of Biochemistry, Leipzig, Germany
| | - Daniel J. Klionsky
- University of Michigan, Life Sciences Institute, Ann Arbor, MI, 48109, USA
| | - Christopher I. Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Paul Hofman
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
- University Côte d’Azur, FHU-OncoAge, CHU de Nice, Laboratory of Clinical and Experimental Pathology (LPCE) Biobank(BB-0033-00025), Nice, France
| | - Baharia Mograbi
- University Côte d’Azur, CNRS, INSERM, IRCAN, FHU-OncoAge, Centre Antoine Lacassagne, France
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102
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Gudgeon J, Marín-Rubio JL, Trost M. The role of macrophage scavenger receptor 1 (MSR1) in inflammatory disorders and cancer. Front Immunol 2022; 13:1012002. [PMID: 36325338 PMCID: PMC9618966 DOI: 10.3389/fimmu.2022.1012002] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 09/28/2022] [Indexed: 08/27/2023] Open
Abstract
Macrophage scavenger receptor 1 (MSR1), also named CD204, holds key inflammatory roles in multiple pathophysiologic processes. Present primarily on the surface of various types of macrophage, this receptor variably affects processes such as atherosclerosis, innate and adaptive immunity, lung and liver disease, and more recently, cancer. As highlighted throughout this review, the role of MSR1 is often dichotomous, being either host protective or detrimental to the pathogenesis of disease. We will discuss the role of MSR1 in health and disease with a focus on the molecular mechanisms influencing MSR1 expression, how altered expression affects disease process and macrophage function, the limited cell signalling pathways discovered thus far, the emerging role of MSR1 in tumour associated macrophages as well as the therapeutic potential of targeting MSR1.
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Affiliation(s)
| | - José Luis Marín-Rubio
- Laboratory for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne, United Kingdom
| | - Matthias Trost
- Laboratory for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne, United Kingdom
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103
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Shared Genetic Regulatory Networks Contribute to Neuropathic and Inflammatory Pain: Multi-Omics Systems Analysis. Biomolecules 2022; 12:biom12101454. [PMID: 36291662 PMCID: PMC9599593 DOI: 10.3390/biom12101454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 09/27/2022] [Accepted: 10/07/2022] [Indexed: 11/17/2022] Open
Abstract
The mechanisms of chronic pain are complex, and genetic factors play an essential role in the development of chronic pain. Neuropathic pain (NP) and inflammatory pain (IP) are two primary components of chronic pain. Previous studies have uncovered some common biological processes in NP and IP. However, the shared genetic mechanisms remained poorly studied. We utilized multi-omics systematic analyses to investigate the shared genetic mechanisms of NP and IP. First, by integrating several genome-wide association studies (GWASs) with multi-omics data, we revealed the significant overlap of the gene co-expression modules in NP and IP. Further, we uncovered the shared biological pathways, including the previously reported mitochondrial electron transport and ATP metabolism, and stressed the role of genetic factors in chronic pain with neurodegenerative diseases. Second, we identified 24 conservative key drivers (KDs) contributing to NP and IP, containing two well-established pain genes, IL1B and OPRM1, and some novel potential pain genes, such as C5AR1 and SERPINE1. The subnetwork of those KDs highlighted the processes involving the immune system. Finally, gene expression analysis of the KDs in mouse models underlined two of the KDs, SLC6A15 and KCNQ5, with unidirectional regulatory functions in NP and IP. Our study provides strong evidence to support the current understanding of the shared genetic regulatory networks underlying NP and IP and potentially benefit the future common therapeutic avenues for chronic pain.
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104
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Nevalainen T, Autio A, Hurme M. Composition of the infiltrating immune cells in the brain of healthy individuals: effect of aging. Immun Ageing 2022; 19:45. [PMID: 36209092 PMCID: PMC9547407 DOI: 10.1186/s12979-022-00302-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/21/2022] [Indexed: 11/07/2022]
Abstract
Immune cells infiltrating the central nervous system (CNS) are involved in the defense against invading microbes as well as in the pathogenesis of neuroinflammatory diseases. In these conditions, the presence of several types of immune and inflammatory cells have been demonstrated. However, some studies have also reported low amounts of immune cells that have been detected in the CNS of healthy individuals, but the cell types present have not been systematically analyzed. To do this, we now used brain samples from The Genotype- Tissue Expression (GTEx) project to analyze the relative abundance of 22 infiltrating leukocyte types using a digital cytometry tool (CIBERSORTx). To characterize cell proportions in different parts of the CNS, samples from 13 different anatomic brain regions were used. The data obtained demonstrated that several leukocyte types were present in the CNS. Six leukocyte types (CD4 memory resting T cells, M0 macrophages, plasma cells, CD8 T cells, CD4 memory activated T cells, and monocytes) were present with a proportion higher than 0.05, i.e. 5%. These six cell types were present in most brain regions with only insignificant variation. A consistent association with age was seen with monocytes, CD8 T cells, and follicular helper T cells. Taken together, these data show that several infiltrating immune cell types are present in the non-diseased CNS tissue and that the proportions of infiltrating cells are affected by age in a manner that is consistent with literature on immunosenecence and inflammaging.
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Affiliation(s)
- Tapio Nevalainen
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland ,Gerontology Research Center (GEREC), Tampere, Finland
| | - Arttu Autio
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland ,Gerontology Research Center (GEREC), Tampere, Finland
| | - Mikko Hurme
- grid.502801.e0000 0001 2314 6254Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland ,Gerontology Research Center (GEREC), Tampere, Finland
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105
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Yang L, Yang Z, Zuo C, Lv X, Liu T, Jia C, Chen H. Epidemiological evidence for associations between variants in CHRNA genes and risk of lung cancer and chronic obstructive pulmonary disease. Front Oncol 2022; 12:1001864. [PMID: 36276121 PMCID: PMC9582127 DOI: 10.3389/fonc.2022.1001864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 09/21/2022] [Indexed: 12/24/2022] Open
Abstract
Background Genetic studies have previously reported that single-nucleotide polymorphisms (SNPs) in CHRNA genes (such as CHRNA3, CHRNA4, CHRNA5, or CHRNA3-CHRNA5-CHRNB4 clusters) are linked to the risk of neoplastic and non-neoplastic diseases. However, these conclusions were controversial and no systematic research synopsis has been available. We aimed to synthesize current knowledge of variants in the CHRNA genes on the risk of diseases. Methods We systematically searched for publications using PubMed, Medline, and Web of Science on or before 25 August 2021. A total of 1,818 publications were identified, of which 29 were deemed eligible for inclusion that could be used to perform meta-analysis based on at least three data sources to assess whether the morbidity associated with neoplastic and non-neoplastic diseases can be attributed to SNPs in CHRNA genes. To further evaluate the authenticity of cumulative evidence proving significant associations, the present study covered the Venice criteria and false-positive report probability tests. Through the Encyclopedia of DNA Elements (ENCODE) project, we created functional annotations for strong associations. Results Meta-analyses were done for nine genetic variants with two diseases {chronic obstructive pulmonary disease (COPD) and lung cancer (LC)}that had at least three data sources. Interestingly, eight polymorphisms were significantly related to changes in the susceptibility COPD and LC (p < 0.05). Of these, strong evidence was assigned to six variants (28 significant associations): CHRNA3 rs1051730, CHRNA3 rs6495309, and CHRNA5 rs16969968 with COPD risk, and CHRNA3 rs1051730, CHRNA3 rs578776, CHRNA3 rs6495309, CHRNA3 rs938682, CHRNA5 rs16969968, and CHRNA5 rs588765 with LC risk; moderate evidence was assigned to five SNPs (12 total associations) with LC or COPD risk. Data from ENCODE and other public databases showed that SNPs with strong evidence may be located in presumptive functional regions. Conclusions Our study summarized comprehensive evidence showing that common mutations in CHRNA genes are strongly related to LC and COPD risk. The study also elucidated the vital function of CHRNA genes in genetic predispositions to human diseases.
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Affiliation(s)
- Lei Yang
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zelin Yang
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chunjian Zuo
- Department of Thoracic Surgery, Army Medical Center of People’s Liberation Army of China (PLA), Chongqing, China
| | - Xiaolong Lv
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tianyu Liu
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Chenhao Jia
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Huanwen Chen
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Huanwen Chen,
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Song J, Chow RD, Peña-Hernández MA, Zhang L, Loeb SA, So EY, Liang OD, Ren P, Chen S, Wilen CB, Lee S. LRRC15 inhibits SARS-CoV-2 cellular entry in trans. PLoS Biol 2022; 20:e3001805. [PMID: 36228039 PMCID: PMC9595563 DOI: 10.1371/journal.pbio.3001805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 10/25/2022] [Accepted: 08/25/2022] [Indexed: 11/17/2022] Open
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is mediated by the entry receptor angiotensin-converting enzyme 2 (ACE2). Although attachment factors and coreceptors facilitating entry are extensively studied, cellular entry factors inhibiting viral entry are largely unknown. Using a surfaceome CRISPR activation screen, we identified human LRRC15 as an inhibitory attachment factor for SARS-CoV-2 entry. LRRC15 directly binds to the receptor-binding domain (RBD) of spike protein with a moderate affinity and inhibits spike-mediated entry. Analysis of human lung single-cell RNA sequencing dataset reveals that expression of LRRC15 is primarily detected in fibroblasts and particularly enriched in pathological fibroblasts in COVID-19 patients. ACE2 and LRRC15 are not coexpressed in the same cell types in the lung. Strikingly, expression of LRRC15 in ACE2-negative cells blocks spike-mediated viral entry in ACE2+ cell in trans, suggesting a protective role of LRRC15 in a physiological context. Therefore, LRRC15 represents an inhibitory attachment factor for SARS-CoV-2 that regulates viral entry in trans.
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Affiliation(s)
- Jaewon Song
- Department of Molecular Microbiology and Immunology, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
| | - Ryan D. Chow
- Department of Genetics, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Mario A. Peña-Hernández
- Department of Laboratory Medicine, Yale University, New Haven, Connecticut, United States of America
- Department of Immunobiology, Yale University, New Haven, Connecticut, United States of America
| | - Li Zhang
- Department of Molecular Microbiology and Immunology, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
| | - Skylar A. Loeb
- Department of Molecular Microbiology and Immunology, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
| | - Eui-Young So
- Division of Hematology/Oncology, Department of Medicine, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States of America
| | - Olin D. Liang
- Division of Hematology/Oncology, Department of Medicine, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States of America
| | - Ping Ren
- Department of Genetics, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Sidi Chen
- Department of Genetics, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Craig B. Wilen
- Department of Laboratory Medicine, Yale University, New Haven, Connecticut, United States of America
- Department of Immunobiology, Yale University, New Haven, Connecticut, United States of America
| | - Sanghyun Lee
- Department of Molecular Microbiology and Immunology, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
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107
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Chongtham J, Pandey N, Sharma LK, Mohan A, Srivastava T. SNP rs9387478 at ROS1-DCBLD1 Locus is Significantly Associated with Lung Cancer Risk and Poor Survival in Indian Population. Asian Pac J Cancer Prev 2022; 23:3553-3561. [PMID: 36308382 PMCID: PMC9924343 DOI: 10.31557/apjcp.2022.23.10.3553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Indexed: 02/18/2023] Open
Abstract
OBJECTIVE Receptor tyrosine kinases (RTK) are relevant therapeutic targets in the treatment of lung cancer. Germline susceptibility variants that influence these RTKs may provide new insights into their regulation. rs9387478 is located in the genomic interval between two RTK-genes ROS1/DCBLD1, of which ROS1 alterations are implicated in lung carcinogenesis and treatment response while the latter remains poorly understood. MATERIALS AND METHODS Venous blood was drawn from 100 control and 231 case subjects. Genotype was scored by restriction fragment length polymorphism (RFLP), PCR amplification followed by HindIII digestion. Logistic regression was applied to compare the association between variables. Survival curve was plotted to draw a correlation between the genotype and overall survival. Also, eQTL and chromatin state changes were analyzed and correlated with the survival of patients using available datasets. RESULTS In our population smoking correlated significantly with lung cancer [OR= 2.607] with the presence of the minor allele 'A' enhancing the nicotine dependence [CA (OR=3.23)]. Individuals with homozygous risk allele 'A' had a higher chance of developing lung cancer [OR=2.65] than individuals with CA/CC implying a recessive model of association. Patients with CC/CA genotype had better overall survival than patients with AA genotype [161 days/142 days vs 54 days, p=0.005]. The homozygous risk allele was significantly associated with increased DCBLD1 and ROS1 expression in lung cancer, with enriched active histone marks due to the polymorphism. Interestingly, increased DCBLD1 expression was associated with poor outcomes in lung cancer. CONCLUSION Overall, our study provides strong evidence that rs9387478 is significantly associated with both nicotine dependence and lung cancer in our North Indian cohort. The association of the SNP with prognostic genes, DCBLD1 and ROS1 make rs9387478 a promising prognostic marker in the North Indian population. The results obtained are significant, however, the study needs to be performed in a larger sample size.
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Affiliation(s)
- Jonita Chongtham
- Department of Genetics, University of Delhi South Campus, New Delhi, India.
| | - Namita Pandey
- Department of Genetics, University of Delhi South Campus, New Delhi, India.,Current affiliation: Clinical Genomic Knowledgebase, PerianDx, Pune, Maharashtra, India.
| | | | - Anant Mohan
- Department of Pulmonary, Critical Care and Sleep Medicine, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
| | - Tapasya Srivastava
- Department of Genetics, University of Delhi South Campus, New Delhi, India.,For Correspondence:
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108
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Closa A, Reixachs-Solé M, Fuentes-Fayos AC, Hayer K, Melero J, Adriaanse FRS, Bos R, Torres-Diz M, Hunger S, Roberts K, Mullighan C, Stam R, Thomas-Tikhonenko A, Castaño J, Luque R, Eyras E. A convergent malignant phenotype in B-cell acute lymphoblastic leukemia involving the splicing factor SRRM1. NAR Cancer 2022; 4:zcac041. [DOI: 10.1093/narcan/zcac041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/09/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Abstract
A significant proportion of infant B-cell acute lymphoblastic leukemia (B-ALL) patients remains with a dismal prognosis due to yet undetermined mechanisms. We performed a comprehensive multicohort analysis of gene expression, gene fusions, and RNA splicing alterations to uncover molecular signatures potentially linked to the observed poor outcome. We identified 87 fusions with significant allele frequency across patients and shared functional impacts, suggesting common mechanisms across fusions. We further identified a gene expression signature that predicts high risk independently of the gene fusion background and includes the upregulation of the splicing factor SRRM1. Experiments in B-ALL cell lines provided further evidence for the role of SRRM1 on cell survival, proliferation, and invasion. Supplementary analysis revealed that SRRM1 potentially modulates splicing events associated with poor outcomes through protein-protein interactions with other splicing factors. Our findings reveal a potential convergent mechanism of aberrant RNA processing that sustains a malignant phenotype independently of the underlying gene fusion and that could potentially complement current clinical strategies in infant B-ALL.
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Affiliation(s)
- Adria Closa
- The Shine-Dalgarno Centre for RNA Innovation, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- Centre for Computational Biomedical Sciences, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- EMBL Australia Partner Laboratory Network at the Australian National University , Canberra, Australia
| | - Marina Reixachs-Solé
- The Shine-Dalgarno Centre for RNA Innovation, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- Centre for Computational Biomedical Sciences, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- EMBL Australia Partner Laboratory Network at the Australian National University , Canberra, Australia
| | - Antonio C Fuentes-Fayos
- Maimonides Biomedical Research Institute of Cordoba (IMIBIC) , Cordoba, Spain
- University of Cordoba (UCO) , Cordoba, Spain
- Reina Sofía University Hospital , Cordoba, Spain
| | - Katharina E Hayer
- Division of Cancer Pathobiology, Children's Hospital of Philadelphia , Philadelphia, USA
| | - Juan L Melero
- The Shine-Dalgarno Centre for RNA Innovation, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- Centre for Computational Biomedical Sciences, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- EMBL Australia Partner Laboratory Network at the Australian National University , Canberra, Australia
| | | | - Romy S Bos
- Princess Máxima Center for Pediatric Oncology , Utrecht, The Netherlands
| | - Manuel Torres-Diz
- Division of Cancer Pathobiology, Children's Hospital of Philadelphia , Philadelphia, USA
| | - Stephen P Hunger
- Division of Oncology, Children's Hospital of Philadelphia , Philadelphia, USA
| | - Kathryn G Roberts
- Department of Pathology, St. Jude Children's Research Hospital , Memphis, USA
| | - Charles G Mullighan
- Department of Pathology, St. Jude Children's Research Hospital , Memphis, USA
| | - Ronald W Stam
- Princess Máxima Center for Pediatric Oncology , Utrecht, The Netherlands
| | - Andrei Thomas-Tikhonenko
- Division of Cancer Pathobiology, Children's Hospital of Philadelphia , Philadelphia, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania , Philadelphia, USA
| | - Justo P Castaño
- Maimonides Biomedical Research Institute of Cordoba (IMIBIC) , Cordoba, Spain
- University of Cordoba (UCO) , Cordoba, Spain
- Reina Sofía University Hospital , Cordoba, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición , (CIBERobn), Cordoba, Spain
| | - Raúl M Luque
- Maimonides Biomedical Research Institute of Cordoba (IMIBIC) , Cordoba, Spain
- University of Cordoba (UCO) , Cordoba, Spain
- Reina Sofía University Hospital , Cordoba, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición , (CIBERobn), Cordoba, Spain
| | - Eduardo Eyras
- The Shine-Dalgarno Centre for RNA Innovation, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- Centre for Computational Biomedical Sciences, John Curtin School of Medical Research, Australian National University , Canberra, Australia
- EMBL Australia Partner Laboratory Network at the Australian National University , Canberra, Australia
- Catalan Institution for Research and Advanced Studies (ICREA) , Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM) , Barcelona, Spain
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109
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Louis S, Busch RM, Lal D, Hockings J, Hogue O, Morita-Sherman M, Vegh D, Najm I, Ghosh C, Bazeley P, Eng C, Jehi L, Rotroff DM. Genetic and molecular features of seizure-freedom following surgical resections for focal epilepsy: A pilot study. Front Neurol 2022; 13:942643. [PMID: 36188379 PMCID: PMC9524264 DOI: 10.3389/fneur.2022.942643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/08/2022] [Indexed: 11/23/2022] Open
Abstract
Objective Seizure outcomes after brain surgery for drug-resistant epilepsy (DRE) are very heterogeneous and difficult to predict with models utilizing the current clinical, imaging, and electrophysiological variables. In this pilot study, we investigated whether genetic and molecular biomarkers (e.g., genomic, transcriptomic) can provide additional insight into differential response to surgery. Methods Post-operative seizure-outcomes were collected at last follow-up (>6 months) for 201 adult patients with DRE who underwent surgery between 2004 and 2020. Resected tissue was sent for miRNA sequencing (n = 132) and mRNA sequencing (n = 135). Following the selection of 10 genes (SCN1A, NBEA, PTEN, GABRA1, LGL1, DEPDC5, IL1A, ABCB1, C3, CALHM1), we investigated SNPs in those 10 genes from previously acquired exome sequencing data (n = 106). Logistic regression was performed to test for associations between individual features (mRNAs, miRNAs, and SNPs) and post-operative seizure-outcome with an exploratory FDR P < 0.25 as the threshold for significance. Post-operative time-to-seizure analyses were performed for each SNP using a Cox proportional hazards model. Results The majority of patients (83%) had temporal lobe epilepsy. Mean age at surgery was 38.3 years, and 56% were female. Three SNPs (rs10276036, rs11975994, rs1128503) in multi-drug resistance gene, ABCB1, were associated with post-operative seizure outcomes. Patients with alternate alleles in ABCB1 were more likely to be seizure-free at last follow-up (52–56% reduction in seizure recurrence; FDR P = 0.24). All three SNPs were in linkage disequilibrium and highly correlated with each other. Median post-operative time-to-seizure was 63 months for patients with 2 alternate alleles, 24–33 months with 1 alternate allele, and 10–11 months with 0 alternate alleles. These SNPs improved outcome prediction beyond MRI and sex alone. No independent miRNAs or mRNAs were significantly associated with seizure-outcome (P > 0.05). However, pathway analysis identified “cancer drug resistance by drug efflux” (mir-154 and mir-379) as enriched (P = 0.02), supporting the role of drug response genes in post-operative seizure recurrence. Significance ABCB1 may have a role in epileptogenesis and surgery outcomes independent of its drug efflux activity necessitating further investigation. SNPs in ABCB1 may serve as independent predictors of post-operative outcome.
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Affiliation(s)
- Shreya Louis
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
| | - Robyn M. Busch
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Dennis Lal
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Jennifer Hockings
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Center for Personalized Genetic Healthcare, Community Care and Population Health, Cleveland Clinic, Cleveland, OH, United States
- Department of Pharmacy, Cleveland Clinic, Cleveland, OH, United States
| | - Olivia Hogue
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Marcia Morita-Sherman
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Deborah Vegh
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Imad Najm
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Chaitali Ghosh
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Peter Bazeley
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Charis Eng
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Center for Personalized Genetic Healthcare, Community Care and Population Health, Cleveland Clinic, Cleveland, OH, United States
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, United States
| | - Lara Jehi
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Lara Jehi
| | - Daniel M. Rotroff
- Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, OH, United States
- *Correspondence: Daniel M. Rotroff
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Chen BY, Bone WP, Lorenz K, Levin M, Ritchie MD, Voight BF. ColocQuiaL: a QTL-GWAS colocalization pipeline. Bioinformatics 2022; 38:4409-4411. [PMID: 35894642 PMCID: PMC9477517 DOI: 10.1093/bioinformatics/btac512] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 06/08/2022] [Indexed: 12/24/2022] Open
Abstract
SUMMARY Identifying genomic features responsible for genome-wide association study (GWAS) signals has proven to be a difficult challenge; many researchers have turned to colocalization analysis of GWAS signals with expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) to connect GWAS signals to candidate causal genes. The ColocQuiaL pipeline provides a framework to perform these colocalization analyses at scale across the genome and returns summary files and locus visualization plots to allow for detailed review of the results. As an example, we used ColocQuiaL to perform colocalization between a recent type 2 diabetes GWAS and Genotype-Tissue Expression (GTEx) v8 single-tissue eQTL and sQTL data. AVAILABILITY AND IMPLEMENTATION ColocQuiaL is primarily written in R and is freely available on GitHub: https://github.com/bvoightlab/ColocQuiaL.
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Affiliation(s)
- Brian Y Chen
- School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William P Bone
- Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kim Lorenz
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA.,Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA 19104, USA
| | - Michael Levin
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA 19104, USA.,Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA.,Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Center for Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA.,Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA 19104, USA.,Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.,Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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111
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da Silva MNS, da Veiga Borges Leal DF, Sena C, Pinto P, Gobbo AR, da Silva MB, Salgado CG, dos Santos NPC, dos Santos SEB. Association between SNPs in microRNAs and microRNAs-Machinery Genes with Susceptibility of Leprosy in the Amazon Population. Int J Mol Sci 2022; 23:ijms231810628. [PMID: 36142557 PMCID: PMC9503809 DOI: 10.3390/ijms231810628] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/01/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Leprosy is a chronic neurodermatological disease caused by the bacillus Mycobacterium leprae. Recent studies show that SNPs in genes related to miRNAs have been associated with several diseases in different populations. This study aimed to evaluate the association of twenty-five SNPs in genes encoding miRNAs related to biological processes and immune response with susceptibility to leprosy and its polar forms paucibacillary and multibacillary in the Brazilian Amazon. A total of 114 leprosy patients and 71 household contacts were included in this study. Genotyping was performed using TaqMan Open Array Genotyping. Ancestry-informative markers were used to estimate individual proportions of case and control groups. The SNP rs2505901 (pre-miR938) was associated with protection against the development of paucibacillary leprosy, while the SNPs rs639174 (DROSHA), rs636832 (AGO1), and rs4143815 (miR570) were associated with protection against the development of multibacillary leprosy. In contrast, the SNPs rs10739971 (pri-let-7a1), rs12904 (miR200C), and rs2168518 (miR4513) are associated with the development of the paucibacillary leprosy. The rs10739971 (pri-let-7a1) polymorphism was associated with the development of leprosy, while rs2910164 (miR146A) and rs10035440 (DROSHA) was significantly associated with an increased risk of developing multibacillary leprosy.
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Affiliation(s)
- Mayara Natália Santana da Silva
- Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
- Laboratório de Biologia e Eletrofisiologia Celular, Seção de Parasitologia, Instituto Evandro Chagas, Ananindeua 67030-000, PA, Brazil
- Correspondence:
| | - Diana Feio da Veiga Borges Leal
- Núcleo de Pesquisas em Oncologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66073-000, PA, Brazil
| | - Camille Sena
- Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
| | - Pablo Pinto
- Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
- Laboratório de Dermato-Imunologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
| | - Angélica Rita Gobbo
- Laboratório de Dermato-Imunologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
| | - Moises Batista da Silva
- Laboratório de Dermato-Imunologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
| | - Claudio Guedes Salgado
- Laboratório de Dermato-Imunologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
| | - Ney Pereira Carneiro dos Santos
- Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
- Núcleo de Pesquisas em Oncologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66073-000, PA, Brazil
| | - Sidney Emanuel Batista dos Santos
- Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, PA, Brazil
- Núcleo de Pesquisas em Oncologia, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66073-000, PA, Brazil
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Ping S, Wang S, Zhao Y, He J, Li G, Li D, Wei Z, Chen J. Identification and validation of a ferroptosis-related gene signature for predicting survival in skin cutaneous melanoma. Cancer Med 2022; 11:3529-3541. [PMID: 35373463 PMCID: PMC9487883 DOI: 10.1002/cam4.4706] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 03/03/2022] [Accepted: 03/15/2022] [Indexed: 12/14/2022] Open
Abstract
PURPOSE Ferroptosis plays a crucial role in the initiation and progression of melanoma. This study developed a robust signature with ferroptosis-related genes (FRGs) and assessed the ability of this signature to predict OS in patients with skin cutaneous melanoma (SKCM). METHODS RNA-sequencing data and clinical information of melanoma patients were extracted from TCGA, GEO, and GTEx. Univariate, multivariate, and LASSO regression analyses were conducted to identify the gene signature. A 10 FRG signature was an independent and strong predictor of survival. The predictive performance was assessed using ROC curve. The functions of this gene signature were assessed by GO and KEGG analysis. The statuses of low-risk and high-risk groups according to the gene signature were compared by GSEA. In addition, we investigated the possible relationship of FRGs with immunotherapy efficacy. RESULTS A prognostic signature with 10 FRGs (CYBB, IFNG, FBXW7, ARNTL, PROM2, GPX2, JDP2, SLC7A5, TUBE1, and HAMP) was identified by Cox regression analysis. This signature had a higher prediction efficiency than clinicopathological features (AUC = 0.70). The enrichment analyses of DEGs indicated that ferroptosis-related immune pathways were largely enriched. Furthermore, GSEA showed that ferroptosis was associated with immunosuppression in the high-risk group. Finally, immune checkpoints such as PDCD-1 (PD-1), CTLA4, CD274 (PD-L1), and LAG3 were also differential expression in two risk groups. CONCLUSIONS The 10 FRGs signature were a strong predictor of OS in SKCM and could be used to predict therapeutic targets for melanoma.
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Affiliation(s)
- Shuai Ping
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Siyuan Wang
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yingsong Zhao
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Jinbing He
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Guanglei Li
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Dinglin Li
- Department of Integrated Traditional Chinese and Western Medicine, Liyuan HospitalTongji Medical College of Huazhong University of Science and TechnologyWuhanChina
| | - Zhuo Wei
- Department of Orthopaedics, Liyuan Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Jianghai Chen
- Department of Hand Surgery, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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Pan-Cancer Analysis Reveals the Relation between TRMT112 and Tumor Microenvironment. JOURNAL OF ONCOLOGY 2022; 2022:1445932. [PMID: 36081672 PMCID: PMC9448524 DOI: 10.1155/2022/1445932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 11/17/2022]
Abstract
Dysregulated epigenetic modifications play a critical role in cancer development where TRMT112 is a member of the transfer RNA (tRNA) methyltransferase family. Till now, no studies have revealed the linkage between TRMT112 expression and diverse types of tumors. Based on TCGA data, we first probed into the relation between TRMT112 and prognosis and the potential role of TRMT112 in tumor microenvironment across 33 types of tumor. TRMT112 presented with increased expression in most cancers, which was significantly prognostic. Furthermore, TRMT112 was associated with tumor-associated fibroblasts in a variety of cancers. Additionally, a positive relationship was identified between TRMT112 expression and multiple tumor-related immune infiltrations, such as dendritic cells, CD8+ T cells, macrophages, CD4+ T cells, neutrophils, and B cells in lung adenocarcinoma and breast invasive carcinoma. In summary, our results suggest that TRMT112 might be a potential prognostic predictor of cancers and involved in regulating multiple cancer-related immune responses to some extent.
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Castaneda-Garcia C, Iyer V, Nsengimana J, Trower A, Droop A, Brown KM, Choi J, Zhang T, Harland M, Newton-Bishop JA, Bishop DT, Adams DJ, Iles MM, Robles-Espinoza CD. Defining novel causal SNPs and linked phenotypes at melanoma-associated loci. Hum Mol Genet 2022; 31:2845-2856. [PMID: 35357426 PMCID: PMC9433725 DOI: 10.1093/hmg/ddac074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
A number of genomic regions have been associated with melanoma risk through genome-wide association studies; however, the causal variants underlying the majority of these associations remain unknown. Here, we sequenced either the full locus or the functional regions including exons of 19 melanoma-associated loci in 1959 British melanoma cases and 737 controls. Variant filtering followed by Fisher's exact test analyses identified 66 variants associated with melanoma risk. Sequential conditional logistic regression identified the distinct haplotypes on which variants reside, and massively parallel reporter assays provided biological insights into how these variants influence gene function. We performed further analyses to link variants to melanoma risk phenotypes and assessed their association with melanoma-specific survival. Our analyses replicate previously known associations in the melanocortin 1 receptor (MC1R) and tyrosinase (TYR) loci, while identifying novel potentially causal variants at the MTAP/CDKN2A and CASP8 loci. These results improve our understanding of the architecture of melanoma risk and outcome.
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Affiliation(s)
- Carolina Castaneda-Garcia
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, México 76230, USA
| | - Vivek Iyer
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
| | - Jérémie Nsengimana
- Biostatistics Research Group, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4BN, UK
| | - Adam Trower
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds LS9 7TF, USA
| | - Alastair Droop
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
| | - Kevin M Brown
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mark Harland
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
| | - Julia A Newton-Bishop
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
| | - D Timothy Bishop
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds LS9 7TF, USA
| | - David J Adams
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
| | - Mark M Iles
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds LS9 7TF, USA
| | - Carla Daniela Robles-Espinoza
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, México 76230, USA
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
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Feronato SG, Silva MLM, Izbicki R, Farias TDJ, Shigunov P, Dallagiovanna B, Passetti F, dos Santos HG. Selecting Genetic Variants and Interactions Associated with Amyotrophic Lateral Sclerosis: A Group LASSO Approach. J Pers Med 2022; 12:jpm12081330. [PMID: 36013279 PMCID: PMC9410070 DOI: 10.3390/jpm12081330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 08/10/2022] [Accepted: 08/12/2022] [Indexed: 11/16/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a multi-system neurodegenerative disease that affects both upper and lower motor neurons, resulting from a combination of genetic, environmental, and lifestyle factors. Usually, the association between single-nucleotide polymorphisms (SNPs) and this disease is tested individually, which leads to the testing of multiple hypotheses. In addition, this classical approach does not support the detection of interaction-dependent SNPs. We applied a two-step procedure to select SNPs and pairwise interactions associated with ALS. SNP data from 276 ALS patients and 268 controls were analyzed by a two-step group LASSO in 2000 iterations. In the first step, we fitted a group LASSO model to a bootstrap sample and a random subset of predictors (25%) from the original data set aiming to screen for important SNPs and, in the second step, we fitted a hierarchical group LASSO model to evaluate pairwise interactions. An in silico analysis was performed on a set of variables, which were prioritized according to their bootstrap selection frequency. We identified seven SNPs (rs16984239, rs10459680, rs1436918, rs1037666, rs4552942, rs10773543, and rs2241493) and two pairwise interactions (rs16984239:rs2118657 and rs16984239:rs3172469) potentially involved in nervous system conservation and function. These results may contribute to the understanding of ALS pathogenesis, its diagnosis, and therapeutic strategy improvement.
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Affiliation(s)
| | | | - Rafael Izbicki
- Department of Statistics, Universidade Federal de São Carlos, São Carlos 13565-905, Brazil
| | - Ticiana D. J. Farias
- Instituto Carlos Chagas, Fundação Oswaldo Cruz, Curitiba 81310-020, Brazil
- Division of Biomedical Informatics, Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Patrícia Shigunov
- Instituto Carlos Chagas, Fundação Oswaldo Cruz, Curitiba 81310-020, Brazil
| | | | - Fabio Passetti
- Instituto Carlos Chagas, Fundação Oswaldo Cruz, Curitiba 81310-020, Brazil
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Kim H, Bae S, Yoon HY, Yee J, Gwak HS. Association of the SLC47A1 Gene Variant With Responses to Metformin Monotherapy in Drug-naive Patients With Type 2 Diabetes. J Clin Endocrinol Metab 2022; 107:2684-2690. [PMID: 35639991 DOI: 10.1210/clinem/dgac333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Although metformin is the first-line treatment for type 2 diabetes, the blood sugar-lowering effect of metformin varies among populations. SLC47A1 plays an important role in metformin pharmacokinetics and pharmacodynamics. OBJECTIVE We performed a systematic review and meta-analysis to investigate the association between SLC47A1 rs2289669 (G > A) and the metformin response in drug-naive patients with type 2 diabetes. METHODS Studies published until January 27, 2022, were retrieved from Cochrane CENTRAL, Embase, PubMed, and Web of Science. Two reviewers independently screened titles, abstracts, and full-text articles. Studies conducted in newly diagnosed or drug-naive patients with type 2 diabetes who received metformin monotherapy were included. A total of 6 studies involving 953 patients were included in this meta-analysis. We extracted the study characteristics and changes in glycated hemoglobin (HbA1c) levels before and after treatment according to the SLC47A1 rs2289669 genotype. Changes in HbA1c levels were analyzed using mean differences (MDs) and 95% CIs. SLC47A1 rs2289669 was associated with changes in HbA1c levels (A carrier vs GG; MD = -0.55; 95% CI, -0.91 to - 0.20; I² = 63%). The sensitivity analysis yielded similar results to the main analysis (MD range, -0.64 to -0.37). When comparing all 3 genotypes, there were significant differences in HbA1c level changes between AA vs GG and GA vs GG, but not in GA vs AA. CONCLUSION This meta-analysis showed that SLC47A1 rs2289669 is associated with the glycemic response to metformin in drug-naive patients with type 2 diabetes.
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Affiliation(s)
- Hamin Kim
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, Republic of Korea
| | - Suhyun Bae
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, Republic of Korea
| | - Ha Young Yoon
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, Republic of Korea
| | - Jeong Yee
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, Republic of Korea
| | - Hye Sun Gwak
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, Republic of Korea
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Hu Y, Rehawi G, Moyon L, Gerstner N, Ogris C, Knauer-Arloth J, Bittner F, Marsico A, Mueller NS. Network Embedding Across Multiple Tissues and Data Modalities Elucidates the Context of Host Factors Important for COVID-19 Infection. Front Genet 2022; 13:909714. [PMID: 35903362 PMCID: PMC9315940 DOI: 10.3389/fgene.2022.909714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/06/2022] [Indexed: 11/30/2022] Open
Abstract
COVID-19 is a heterogeneous disease caused by SARS-CoV-2. Aside from infections of the lungs, the disease can spread throughout the body and damage many other tissues, leading to multiorgan failure in severe cases. The highly variable symptom severity is influenced by genetic predispositions and preexisting diseases which have not been investigated in a large-scale multimodal manner. We present a holistic analysis framework, setting previously reported COVID-19 genes in context with prepandemic data, such as gene expression patterns across multiple tissues, polygenetic predispositions, and patient diseases, which are putative comorbidities of COVID-19. First, we generate a multimodal network using the prior-based network inference method KiMONo. We then embed the network to generate a meaningful lower-dimensional representation of the data. The input data are obtained via the Genotype-Tissue Expression project (GTEx), containing expression data from a range of tissues with genomic and phenotypic information of over 900 patients and 50 tissues. The generated network consists of nodes, that is, genes and polygenic risk scores (PRS) for several diseases/phenotypes, as well as for COVID-19 severity and hospitalization, and links between them if they are statistically associated in a regularized linear model by feature selection. Applying network embedding on the generated multimodal network allows us to perform efficient network analysis by identifying nodes close by in a lower-dimensional space that correspond to entities which are statistically linked. By determining the similarity between COVID-19 genes and other nodes through embedding, we identify disease associations to tissues, like the brain and gut. We also find strong associations between COVID-19 genes and various diseases such as ischemic heart disease, cerebrovascular disease, and hypertension. Moreover, we find evidence linking PTPN6 to a range of comorbidities along with the genetic predisposition of COVID-19, suggesting that this kinase is a central player in severe cases of COVID-19. In conclusion, our holistic network inference coupled with network embedding of multimodal data enables the contextualization of COVID-19-associated genes with respect to tissues, disease states, and genetic risk factors. Such contextualization can be exploited to further elucidate the biological importance of known and novel genes for severity of the disease in patients.
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Affiliation(s)
- Yue Hu
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
- Informatics 12 Chair of Bioinformatics, Technical University Munich, Garching, Germany
| | - Ghalia Rehawi
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
- Translational Research in Psychiatry, MaxPlanck Institute of Psychiatry, Munich, Germany
| | - Lambert Moyon
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
| | - Nathalie Gerstner
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
- Translational Research in Psychiatry, MaxPlanck Institute of Psychiatry, Munich, Germany
| | - Christoph Ogris
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
| | - Janine Knauer-Arloth
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
- Translational Research in Psychiatry, MaxPlanck Institute of Psychiatry, Munich, Germany
| | | | - Annalisa Marsico
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
- *Correspondence: Annalisa Marsico, ; Nikola S. Mueller,
| | - Nikola S. Mueller
- Computational Health Department, Helmholtz Center Munich, Neuherberg, Germany
- knowing01 GmbH, Munich, Germany
- *Correspondence: Annalisa Marsico, ; Nikola S. Mueller,
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Brennan K, Zheng H, Fahrner JA, Shin JH, Gentles AJ, Schaefer B, Sunwoo JB, Bernstein JA, Gevaert O. NSD1 mutations deregulate transcription and DNA methylation of bivalent developmental genes in Sotos syndrome. Hum Mol Genet 2022; 31:2164-2184. [PMID: 35094088 PMCID: PMC9262396 DOI: 10.1093/hmg/ddac026] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 01/04/2022] [Accepted: 01/19/2022] [Indexed: 11/13/2022] Open
Abstract
Sotos syndrome (SS), the most common overgrowth with intellectual disability (OGID) disorder, is caused by inactivating germline mutations of NSD1, which encodes a histone H3 lysine 36 methyltransferase. To understand how NSD1 inactivation deregulates transcription and DNA methylation (DNAm), and to explore how these abnormalities affect human development, we profiled transcription and DNAm in SS patients and healthy control individuals. We identified a transcriptional signature that distinguishes individuals with SS from controls and was also deregulated in NSD1-mutated cancers. Most abnormally expressed genes displayed reduced expression in SS; these downregulated genes consisted mostly of bivalent genes and were enriched for regulators of development and neural synapse function. DNA hypomethylation was strongly enriched within promoters of transcriptionally deregulated genes: overexpressed genes displayed hypomethylation at their transcription start sites while underexpressed genes featured hypomethylation at polycomb binding sites within their promoter CpG island shores. SS patients featured accelerated molecular aging at the levels of both transcription and DNAm. Overall, these findings indicate that NSD1-deposited H3K36 methylation regulates transcription by directing promoter DNA methylation, partially by repressing polycomb repressive complex 2 (PRC2) activity. These findings could explain the phenotypic similarity of SS to OGID disorders that are caused by mutations in PRC2 complex-encoding genes.
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Affiliation(s)
- Kevin Brennan
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Hong Zheng
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Jill A Fahrner
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - June Ho Shin
- Department of Otolaryngology – Head and Neck Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Andrew J Gentles
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Bradley Schaefer
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - John B Sunwoo
- Department of Otolaryngology – Head and Neck Surgery, Stanford University School of Medicine, Palo Alto, CA 94305, USA
| | - Jonathan A Bernstein
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA 94305, USA
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Xin Y, Lyu P, Jiang J, Zhou F, Wang J, Blackshaw S, Qian J. LRLoop: a method to predict feedback loops in cell-cell communication. Bioinformatics 2022; 38:4117-4126. [PMID: 35788263 PMCID: PMC9438954 DOI: 10.1093/bioinformatics/btac447] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 06/24/2022] [Accepted: 07/03/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Intercellular communication (i.e. cell-cell communication) plays an essential role in multicellular organisms coordinating various biological processes. Previous studies discovered that feedback loops between two cell types are a widespread and vital signaling motif regulating development, regeneration and cancer progression. While many computational methods have been developed to predict cell-cell communication based on gene expression datasets, these methods often predict one-directional ligand-receptor interactions from sender to receiver cells and are not suitable to identify feedback loops. RESULTS Here, we describe ligand-receptor loop (LRLoop), a new method for analyzing cell-cell communication based on bi-directional ligand-receptor interactions, where two pairs of ligand-receptor interactions are identified that are responsive to each other and thereby form a closed feedback loop. We first assessed LRLoop using bulk datasets and found our method significantly reduces the false positive rate seen with existing methods. Furthermore, we developed a new strategy to assess the performance of these methods in single-cell datasets. We used the between-tissue interactions as an indicator of potential false-positive prediction and found that LRLoop produced a lower fraction of between-tissue interactions than traditional methods. Finally, we applied LRLoop to the single-cell datasets obtained from retinal development. We discovered many new bi-directional ligand-receptor interactions among individual cell types that potentially control proliferation, neurogenesis and/or cell fate specification. AVAILABILITY AND IMPLEMENTATION An R package is available at https://github.com/Pinlyu3/LRLoop. The source code can be found at figshare (https://doi.org/10.6084/m9.figshare.20126138.v1). The datasets can be found at figshare (https://doi.org/10.6084/m9.figshare.20126021.v1). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | - Junyao Jiang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Fengquan Zhou
- Department of Orthopedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA,Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Jie Wang
- CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Seth Blackshaw
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA,Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Jiang Qian
- To whom correspondence should be addressed.
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Azevedo ALKD, Gomig THB, Giner IS, Batista M, Marchini FK, Lima RS, de Andrade Urban C, Sebastião APM, Cavalli IJ, Ribeiro EMDSF. Comprehensive analysis of the large and small ribosomal proteins in breast cancer: Insights on proteomic and transcriptomic expression patterns, regulation, mutational landscape, and prognostic significance. Comput Biol Chem 2022; 100:107746. [DOI: 10.1016/j.compbiolchem.2022.107746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 07/11/2022] [Accepted: 07/25/2022] [Indexed: 11/29/2022]
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Rajabli F, Beecham GW, Hendrie HC, Baiyewu O, Ogunniyi A, Gao S, Kushch NA, Lipkin-Vasquez M, Hamilton-Nelson KL, Young JI, Dykxhoorn DM, Nuytemans K, Kunkle BW, Wang L, Jin F, Liu X, Feliciano-Astacio BE, Schellenberg GD, Dalgard CL, Griswold AJ, Byrd GS, Reitz C, Cuccaro ML, Haines JL, Pericak-Vance MA, Vance JM. A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer's Disease in African Ancestry. PLoS Genet 2022; 18:e1009977. [PMID: 35788729 PMCID: PMC9286282 DOI: 10.1371/journal.pgen.1009977] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 07/15/2022] [Accepted: 05/27/2022] [Indexed: 11/18/2022] Open
Abstract
African descent populations have a lower Alzheimer disease risk from ApoE ε4 compared to other populations. Ancestry analysis showed that the difference in risk between African and European populations lies in the ancestral genomic background surrounding the ApoE locus (local ancestry). Identifying the mechanism(s) of this protection could lead to greater insight into the etiology of Alzheimer disease and more personalized therapeutic intervention. Our objective is to follow up the local ancestry finding and identify the genetic variants that drive this risk difference and result in a lower risk for developing Alzheimer disease in African ancestry populations. We performed association analyses using a logistic regression model with the ApoE ε4 allele as an interaction term and adjusted for genome-wide ancestry, age, and sex. Discovery analysis included imputed SNP data of 1,850 Alzheimer disease and 4,331 cognitively intact African American individuals. We performed replication analyses on 63 whole genome sequenced Alzheimer disease and 648 cognitively intact Ibadan individuals. Additionally, we reproduced results using whole-genome sequencing of 273 Alzheimer disease and 275 cognitively intact admixed Puerto Rican individuals. A further comparison was done with SNP imputation from an additional 8,463 Alzheimer disease and 11,365 cognitively intact non-Hispanic White individuals. We identified a significant interaction between the ApoE ε4 allele and the SNP rs10423769_A allele, (β = -0.54,SE = 0.12,p-value = 7.50x10-6) in the discovery data set, and replicated this finding in Ibadan (β = -1.32,SE = 0.52,p-value = 1.15x10-2) and Puerto Rican (β = -1.27,SE = 0.64,p-value = 4.91x10-2) individuals. The non-Hispanic Whites analyses showed an interaction trending in the "protective" direction but failing to pass a 0.05 significance threshold (β = -1.51,SE = 0.84,p-value = 7.26x10-2). The presence of the rs10423769_A allele reduces the odds ratio for Alzheimer disease risk from 7.2 for ApoE ε4/ε4 carriers lacking the A allele to 2.1 for ApoE ε4/ε4 carriers with at least one A allele. This locus is located approximately 2 mB upstream of the ApoE locus, in a large cluster of pregnancy specific beta-1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943. This study identified a new African-ancestry specific locus that reduces the risk effect of ApoE ε4 for developing Alzheimer disease. The mechanism of the interaction with ApoEε4 is not known but suggests a novel mechanism for reducing the risk for ε4 carriers opening the possibility for potential ancestry-specific therapeutic intervention.
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Affiliation(s)
- Farid Rajabli
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Gary W. Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Hugh C. Hendrie
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | | | | | - Sujuan Gao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | - Nicholas A. Kushch
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Marina Lipkin-Vasquez
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Kara L. Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Juan I. Young
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Derek M. Dykxhoorn
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Karen Nuytemans
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Brian W. Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Liyong Wang
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Fulai Jin
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | | | | | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Clifton L. Dalgard
- Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America
| | - Anthony J. Griswold
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Goldie S. Byrd
- Maya Angelou Center for Health Equity, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York State, United States of America
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Jonathan L. Haines
- Department of Population & Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
| | - Jeffery M. Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, United States of America
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Tian J, Wang Y, Dong Y, Chang J, Wu Y, Chang S, Che G. Cumulative Evidence for Relationships Between Multiple Variants in the TERT and CLPTM1L Region and Risk of Cancer and Non-Cancer Disease. Front Oncol 2022; 12:946039. [PMID: 35847915 PMCID: PMC9279858 DOI: 10.3389/fonc.2022.946039] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 05/30/2022] [Indexed: 12/01/2022] Open
Abstract
Background Genetic studies previously reported that variants in TERT-CLPTM1L genes were related to susceptibility of cancer and non-cancer diseases. However, conclusions were not always concordant. Methods We performed meta-analyses to assess correlations between 23 variants within TERT-CLPTM1L region and susceptibility to 12 cancers and 1 non-cancer disease based on data in 109 papers (involving 139,510 cases and 208,530 controls). Two approaches (false-positive report probability test and Venice criteria) were adopted for assessing the cumulative evidence of significant associations. Current study evaluated the potential role of these variants based on data in Encyclopedia of DNA Elements (ENCODE) Project. Results Thirteen variants were statistically associated with susceptibility to 11 cancers and 1 non-cancer disease (p < 0.05). Besides, 12 variants with eight cancers and one non-cancer disease were rated as strong evidence (rs2736098, rs401681, and rs402710 in bladder cancer; rs2736100, rs2853691, and rs401681 in esophageal cancer; rs10069690 in gastric cancer; rs2736100 and rs2853676 in glioma; rs2242652, rs2736098, rs2736100, rs2853677, rs31489, rs401681, rs402710, rs465498, and rs4975616 in lung cancer; rs2736100 in idiopathic pulmonary fibrosis and myeloproliferative neoplasms; and rs401681 in pancreatic and skin cancer). According to data from ENCODE and other public databases, 12 variants with strong evidence might fall within putative functional regions. Conclusions This paper demonstrated that common variants of TERT-CLPTM1L genes were related to susceptibility to bladder, esophageal, gastric, lung, pancreatic, and skin cancer, as well as to glioma, myeloproliferative neoplasms, and idiopathic pulmonary fibrosis, and, besides, the crucial function of the TERT-CLPTM1L region in the genetic predisposition to human diseases is elucidated.
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Affiliation(s)
- Jie Tian
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yan Wang
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yingxian Dong
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Junke Chang
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Yongming Wu
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Shuai Chang
- Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China
| | - Guowei Che
- Department of Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Guowei Che,
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The topology of genome-scale metabolic reconstructions unravels independent modules and high network flexibility. PLoS Comput Biol 2022; 18:e1010203. [PMID: 35759507 PMCID: PMC9269948 DOI: 10.1371/journal.pcbi.1010203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 07/08/2022] [Accepted: 05/14/2022] [Indexed: 11/30/2022] Open
Abstract
The topology of metabolic networks is recognisably modular with modules weakly connected apart from sharing a pool of currency metabolites. Here, we defined modules as sets of reversible reactions isolated from the rest of metabolism by irreversible reactions except for the exchange of currency metabolites. Our approach identifies topologically independent modules under specific conditions associated with different metabolic functions. As case studies, the E.coli iJO1366 and Human Recon 2.2 genome-scale metabolic models were split in 103 and 321 modules respectively, displaying significant correlation patterns in expression data. Finally, we addressed a fundamental question about the metabolic flexibility conferred by reversible reactions: “Of all Directed Topologies (DTs) defined by fixing directions to all reversible reactions, how many are capable of carrying flux through all reactions?”. Enumeration of the DTs for iJO1366 model was performed using an efficient depth-first search algorithm, rejecting infeasible DTs based on mass-imbalanced and loopy flux patterns. We found the direction of 79% of reversible reactions must be defined before all directions in the network can be fixed, granting a high degree of flexibility. Genome-scale metabolic reconstructions represent all biochemical reactions that an organism can accomplish. These reconstructions are complex and often difficult to study in great detail. A way to overcome this limitation is to focus on specific pathways or subsystems. We present a novel method to identify metabolic modules based on the network topology. The method relies on reaction directions and ignores currency metabolites, which artificially connect distant metabolic reactions. In this way, topologically independent modules are built, where inputs and outputs are controlled by irreversible reactions. The method is automatic and unbiased, and, the result is a set of condition specific modules with defined metabolic functions. As a proof-of-concept we generated biologically relevant modules for the E.coli and Human genome-scale metabolic reconstructions supported by transcriptomic data. Finally, we applied the novel approach to study the network flexibility conferred by reversible reactions. In the case of the E. coli model, we found that the direction of 79% of structurally reversible reactions (those not directionally constrained by surrounding irreversible reactions) must be fixed to determine all the reaction directions in the network. Therefore, reversible reactions operate practically independent of each other.
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von Berg J, ten Dam M, van der Laan SW, de Ridder J. PolarMorphism enables discovery of shared genetic variants across multiple traits from GWAS summary statistics. Bioinformatics 2022; 38:i212-i219. [PMID: 35758773 PMCID: PMC9235478 DOI: 10.1093/bioinformatics/btac228] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Pleiotropic SNPs are associated with multiple traits. Such SNPs can help pinpoint biological processes with an effect on multiple traits or point to a shared etiology between traits. We present PolarMorphism, a new method for the identification of pleiotropic SNPs from genome-wide association studies (GWAS) summary statistics. PolarMorphism can be readily applied to more than two traits or whole trait domains. PolarMorphism makes use of the fact that trait-specific SNP effect sizes can be seen as Cartesian coordinates and can thus be converted to polar coordinates r (distance from the origin) and theta (angle with the Cartesian x-axis, in the case of two traits). r describes the overall effect of a SNP, while theta describes the extent to which a SNP is shared. r and theta are used to determine the significance of SNP sharedness, resulting in a P-value per SNP that can be used for further analysis. RESULTS We apply PolarMorphism to a large collection of publicly available GWAS summary statistics enabling the construction of a pleiotropy network that shows the extent to which traits share SNPs. We show how PolarMorphism can be used to gain insight into relationships between traits and trait domains and contrast it with genetic correlation. Furthermore, pathway analysis of the newly discovered pleiotropic SNPs demonstrates that analysis of more than two traits simultaneously yields more biologically relevant results than the combined results of pairwise analysis of the same traits. Finally, we show that PolarMorphism is more efficient and more powerful than previously published methods. AVAILABILITY AND IMPLEMENTATION code: https://github.com/UMCUGenetics/PolarMorphism, results: 10.5281/zenodo.5844193. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Joanna von Berg
- Center for Molecular Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Michelle ten Dam
- Center for Molecular Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Sander W van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Jeroen de Ridder
- Center for Molecular Medicine, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
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McLendon JM, Zhang X, Matasic DS, Kumar M, Koval OM, Grumbach IM, Sadayappan S, London B, Boudreau RL. Knockout of Sorbin And SH3 Domain Containing 2 (Sorbs2) in Cardiomyocytes Leads to Dilated Cardiomyopathy in Mice. J Am Heart Assoc 2022; 11:e025687. [PMID: 35730644 PMCID: PMC9333371 DOI: 10.1161/jaha.122.025687] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Background Sorbin and SH3 domain containing 2 (Sorbs2) protein is a cytoskeletal adaptor with an emerging role in cardiac biology and disease; yet, its potential relevance to adult‐onset cardiomyopathies remains underexplored. Sorbs2 global knockout mice display lethal arrhythmogenic cardiomyopathy; however, the causative mechanisms remain unclear. Herein, we examine Sorbs2 dysregulation in heart failure, characterize novel Sorbs2 cardiomyocyte‐specific knockout mice (Sorbs2‐cKO), and explore associations between Sorbs2 genetic variations and human cardiovascular disease. Methods and Results Bioinformatic analyses show myocardial Sorbs2 mRNA is consistently upregulated in humans with adult‐onset cardiomyopathies and in heart failure models. We generated Sorbs2‐cKO mice and report that they develop progressive systolic dysfunction and enlarged cardiac chambers, and they die with congestive heart failure at about 1 year old. After 3 months, Sorbs2‐cKO mice begin to show atrial enlargement and P‐wave anomalies, without dysregulation of action potential–associated ion channel and gap junction protein expressions. After 6 months, Sorbs2‐cKO mice exhibit impaired contractility in dobutamine‐treated hearts and skinned myofibers, without dysregulation of contractile protein expressions. From our comprehensive survey of potential mechanisms, we found that within 4 months, Sorbs2‐cKO hearts have defective microtubule polymerization and compensatory upregulation of structural cytoskeletal and adapter proteins, suggesting that this early intracellular structural remodeling is responsible for contractile dysfunction. Finally, we identified genetic variants that associate with decreased Sorbs2 expression and human cardiac phenotypes, including conduction abnormalities, atrial enlargement, and dilated cardiomyopathy, consistent with Sorbs2‐cKO mice phenotypes. Conclusions Our studies show that Sorbs2 is essential for maintaining structural integrity in cardiomyocytes, likely through strengthening the interactions between microtubules and other cytoskeletal proteins at cross‐link sites.
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Affiliation(s)
- Jared M McLendon
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Xiaoming Zhang
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Daniel S Matasic
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Department of Molecular Physiology and Biophysics University of Iowa Carver College of Medicine Iowa City IA
| | - Mohit Kumar
- Department of Pharmacology and Systems Physiology University of Cincinnati OH.,Division of Cardiovascular Health and Disease Department of Internal Medicine Heart, Lung, and Vascular Institute University of Cincinnati OH
| | - Olha M Koval
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Isabella M Grumbach
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Sakthivel Sadayappan
- Department of Pharmacology and Systems Physiology University of Cincinnati OH.,Division of Cardiovascular Health and Disease Department of Internal Medicine Heart, Lung, and Vascular Institute University of Cincinnati OH
| | - Barry London
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
| | - Ryan L Boudreau
- Department of Internal Medicine University of Iowa Carver College of Medicine Iowa City IA.,Abboud Cardiovascular Research Center University of Iowa Carver College of Medicine Iowa City IA
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126
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Qi L, Xu R, Ren X, Zhang W, Yang Z, Tu C, Li Z. Comprehensive Profiling Reveals Prognostic and Immunogenic Characteristics of Necroptosis in Soft Tissue Sarcomas. Front Immunol 2022; 13:877815. [PMID: 35663937 PMCID: PMC9159500 DOI: 10.3389/fimmu.2022.877815] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 04/14/2022] [Indexed: 12/31/2022] Open
Abstract
Soft tissue sarcomas (STSs) are heterogeneous malignancies derived from mesenchymal cells. Due to its rarity, heterogeneity, and limited overall response to chemotherapy, STSs represent a therapeutic challenge. Necroptosis is a novel therapeutic strategy for enhancing immunotherapy of cancer. Nevertheless, no research has explored the relationship between necroptosis-related genes (NRGs) and STSs. In this study, differentially expressed NRGs were identified using The Cancer Genome Atlas (TCGA) and The Cancer Genotype-Tissue Expression (GTEx) project. The expression levels of 34 NRGs were significantly different. Several key NRGs were validated using RT-qPCR and our own sequencing data. Patients with STSs were divided into two clusters using consensus cluster analysis, and significant differences were observed in their survival (p=0.002). We found the differentially expressed genes (DEGs) between the two clusters and carried out subsequent analysis. The necroptosis-related gene signatures with 10 key DEGs were identified with a risk score constructed. The prognosis of TCGA-SARC cohort with low necroptosis-related risk score was better (p<0.001). Meanwhile, the low-risk group had a significantly increased immune infiltration. Using the data of GSE17118 and another immunotherapy cohort as external validations, we observed significant survival differences between the two risk groups (p=0.019). The necroptosis-related risk score proved to be an independent prognostic factor, and a nomogram was further established and integrated with other clinical features. Notably, the necroptosis-related gene signature could also act as the prognostic indicator in other malignancies based on pan-cancer analysis. In summary, the study outlines NRGs in STSs and their potential role in prognosis and will be one of the important directions for future research.
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Affiliation(s)
- Lin Qi
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China
| | - Ruiling Xu
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China
| | - Xiaolei Ren
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China
| | - Wenchao Zhang
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China
| | - Zhimin Yang
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China.,Department of Microbiology, Immunology & Molecular Genetics, UT Health Science Center, University of Texas Long School of Medicine, San Antonio, TX, United States
| | - Chao Tu
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China
| | - Zhihong Li
- Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China
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127
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Jang EJ, Kim YJ, Hwang HS, Yee J, Gwak HS. Associations of GNAS and RGS Gene Polymorphisms with the Risk of Ritodrine-Induced Adverse Events in Korean Women with Preterm Labor: A Cohort Study. Pharmaceutics 2022; 14:pharmaceutics14061220. [PMID: 35745791 PMCID: PMC9227008 DOI: 10.3390/pharmaceutics14061220] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/02/2022] [Accepted: 06/07/2022] [Indexed: 02/04/2023] Open
Abstract
Ritodrine, a β2-adrenergic receptor agonist, is among most commonly prescribed tocolytic agents. This study aimed to evaluate the associations of single nucleotide polymorphisms in GNAS, RGS2, and RGS5 with the risk of ritodrine-induced adverse events (AEs) and develop a risk scoring system to identify high-risk patients. This is the prospective cohort study conducted at the Ewha Woman’s University Mokdong Hospital between January 2010 and October 2016. Pregnant women were included if they were treated with ritodrine for preterm labor with regular uterine contractions (at least 3 every 10 min) and cervical dilation. A total of 6, 3, and 5 single nucleotide polymorphisms (SNPs) of GNAS, RGS2, and RGS5 genes were genotyped and compared in patients with and without ritodrine-induced AEs. A total of 163 patients were included in this study. After adjusting confounders, GNAS rs3730168 (per-allele odds ratio (OR): 2.1; 95% confidence interval (95% CI): 1.0–4.3) and RGS2 rs1152746 (per-allele OR: 2.6, 95% CI: 1.1–6.5) were significantly associated with ritodrine-induced AEs. According to the constructed risk scoring models, patients with 0, 1, 2, 3, 4, and 5 points showed 0%, 13%, 19%, 31%, 46%, and 100% risks of AEs. This study suggested that GNAS and RGS2 polymorphisms could affect the risk of AEs in patients treated with ritodrine.
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Affiliation(s)
- Eun-Jeong Jang
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea;
| | - Young-Ju Kim
- Department of Obstetrics and Gynecology, Ewha Womans University School of Medicine, Seoul 07985, Korea;
| | - Han-Sung Hwang
- Department of Obstetrics and Gynecology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul 05030, Korea;
| | - Jeong Yee
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea;
- Correspondence: (J.Y.); (H.-S.G.); Tel.: +82-2-3277-3052 (J.Y.); +82-2-3277-4376 (H.-S.G.); Fax: +82-2-3277-3051 (J.Y. & H.-S.G.)
| | - Hye-Sun Gwak
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea;
- Correspondence: (J.Y.); (H.-S.G.); Tel.: +82-2-3277-3052 (J.Y.); +82-2-3277-4376 (H.-S.G.); Fax: +82-2-3277-3051 (J.Y. & H.-S.G.)
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128
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Nieves-Colón MA, Badillo Rivera KM, Sandoval K, Villanueva Dávalos V, Enriquez Lencinas LE, Mendoza-Revilla J, Adhikari K, González-Buenfil R, Chen JW, Zhang ET, Sockell A, Ortiz-Tello P, Hurtado GM, Condori Salas R, Cebrecos R, Manzaneda Choque JC, Manzaneda Choque FP, Yábar Pilco GP, Rawls E, Eng C, Huntsman S, Burchard E, Ruiz-Linares A, González-José R, Bedoya G, Rothhammer F, Bortolini MC, Poletti G, Gallo C, Bustamante CD, Baker JC, Gignoux CR, Wojcik GL, Moreno-Estrada A. Clotting factor genes are associated with preeclampsia in high-altitude pregnant women in the Peruvian Andes. Am J Hum Genet 2022; 109:1117-1139. [PMID: 35588731 PMCID: PMC9247825 DOI: 10.1016/j.ajhg.2022.04.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 04/25/2022] [Indexed: 11/20/2022] Open
Abstract
Preeclampsia is a multi-organ complication of pregnancy characterized by sudden hypertension and proteinuria that is among the leading causes of preterm delivery and maternal morbidity and mortality worldwide. The heterogeneity of preeclampsia poses a challenge for understanding its etiology and molecular basis. Intriguingly, risk for the condition increases in high-altitude regions such as the Peruvian Andes. To investigate the genetic basis of preeclampsia in a population living at high altitude, we characterized genome-wide variation in a cohort of preeclamptic and healthy Andean families (n = 883) from Puno, Peru, a city located above 3,800 meters of altitude. Our study collected genomic DNA and medical records from case-control trios and duos in local hospital settings. We generated genotype data for 439,314 SNPs, determined global ancestry patterns, and mapped associations between genetic variants and preeclampsia phenotypes. A transmission disequilibrium test (TDT) revealed variants near genes of biological importance for placental and blood vessel function. The top candidate region was found on chromosome 13 of the fetal genome and contains clotting factor genes PROZ, F7, and F10. These findings provide supporting evidence that common genetic variants within coagulation genes play an important role in preeclampsia. A selection scan revealed a potential adaptive signal around the ADAM12 locus on chromosome 10, implicated in pregnancy disorders. Our discovery of an association in a functional pathway relevant to pregnancy physiology in an understudied population of Native American origin demonstrates the increased power of family-based study design and underscores the importance of conducting genetic research in diverse populations.
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Affiliation(s)
- Maria A Nieves-Colón
- Laboratorio Nacional de Genómica para la Biodiversidad (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, México; School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85281, USA; Department of Anthropology, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA.
| | | | - Karla Sandoval
- Laboratorio Nacional de Genómica para la Biodiversidad (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, México
| | | | | | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru; Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes MK7 6AA, UK; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, WC1E 6BT London, UK
| | - Ram González-Buenfil
- Laboratorio Nacional de Genómica para la Biodiversidad (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, México
| | - Jessica W Chen
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Elisa T Zhang
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Alexandra Sockell
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | | | - Gloria Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Ramiro Condori Salas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Ricardo Cebrecos
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | | | | | | | - Erin Rawls
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85281, USA
| | - Celeste Eng
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Scott Huntsman
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Esteban Burchard
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Andrés Ruiz-Linares
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, WC1E 6BT London, UK; Aix-Marseille Université, CNRS, EFS, ADES, 13005 Marseille, France; Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China
| | - Rolando González-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico-CONICET y Programa Nacional de Referencia y Biobanco Genómico de la Población Argentina (PoblAr), Ministerio de Ciencia, Tecnología e Innovación, Puerto Madryn, Chubut, Argentina
| | - Gabriel Bedoya
- Genética Molecular (GENMOL), Universidad de Antioquía, Medellin, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación Universidad de Tarapacá, Tarapacá, Chile; Programa de Genética Humana, ICBM Facultad de Medicina, Universidad de Chile, Santiago, Chile
| | - Maria Cátira Bortolini
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Caixa Postal 15053, 91501-970 Porto Alegre, Rio Grande do Sul, Brazil
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Carlos D Bustamante
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Julie C Baker
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | | | - Genevieve L Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, John Hopkins University, Baltimore, MD 21205, USA
| | - Andrés Moreno-Estrada
- Laboratorio Nacional de Genómica para la Biodiversidad (UGA-LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36821, México.
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129
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Chromosome-specific retention of cancer-associated DNA hypermethylation following pharmacological inhibition of DNMT1. Commun Biol 2022; 5:528. [PMID: 35654826 PMCID: PMC9163065 DOI: 10.1038/s42003-022-03509-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 05/20/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractThe DNA methylation status of the X-chromosome in cancer cells is often overlooked because of computational difficulties. Most of the CpG islands on the X-chromosome are mono-allelically methylated in normal female cells and only present as a single copy in male cells. We treated two colorectal cancer cell lines from a male (HCT116) and a female (RKO) with increasing doses of a DNA methyltransferase 1 (DNMT1)-specific inhibitor (GSK3685032/GSK5032) over several months to remove as much non-essential CpG methylation as possible. Profiling of the remaining DNA methylome revealed an unexpected, enriched retention of DNA methylation on the X-chromosome. Strikingly, the identified retained X-chromosome DNA methylation patterns accurately predicted de novo DNA hypermethylation in colon cancer patient methylomes in the TCGA COAD/READ cohort. These results suggest that a re-examination of tumors for X-linked DNA methylation changes may enable greater understanding of the importance of epigenetic silencing of cancer related genes.
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130
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Wu Y, Biswas D, Usaite I, Angelova M, Boeing S, Karasaki T, Veeriah S, Czyzewska-Khan J, Morton C, Joseph M, Hessey S, Reading J, Georgiou A, Al-Bakir M, McGranahan N, Jamal-Hanjani M, Hackshaw A, Quezada SA, Hayday AC, Swanton C. A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer. NATURE CANCER 2022; 3:696-709. [PMID: 35637401 PMCID: PMC9236901 DOI: 10.1038/s43018-022-00376-z] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/11/2022] [Indexed: 01/26/2023]
Abstract
Murine tissues harbor signature γδ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident γδ cells are less well defined. In the present study, we show that human lung tissues harbor a resident Vδ1 γδ T cell population. Moreover, we demonstrate that Vδ1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral Vδ1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8+ T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RA-CD27- effector memory Vδ1 T cells in tumors and, most strikingly, with the numbers of CD103+ tissue-resident Vδ1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating Vδ1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer.
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Affiliation(s)
- Yin Wu
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
- Peter Gorer Department of Immunobiology, School of Immunology & Microbial Sciences, King's College London, London, UK.
- Immunosurveillance Laboratory, The Francis Crick Institute, London, UK.
| | - Dhruva Biswas
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
- Bill Lyons Informatics Centre, University College London Cancer Institute, London, UK
| | - Ieva Usaite
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Mihaela Angelova
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Stefan Boeing
- Bioinformatics & Biostatistics and Software Development & Machine Learning Team, The Francis Crick Institute, London, UK
| | - Takahiro Karasaki
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Selvaraju Veeriah
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Justyna Czyzewska-Khan
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Cienne Morton
- Peter Gorer Department of Immunobiology, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Magdalene Joseph
- Peter Gorer Department of Immunobiology, School of Immunology & Microbial Sciences, King's College London, London, UK
- Immunosurveillance Laboratory, The Francis Crick Institute, London, UK
| | - Sonya Hessey
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Metastasis Lab, University College London Cancer Institute, London, UK
| | - James Reading
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Immunology Unit, Research Department of Haematology, University College London Cancer Institute, London, UK
| | - Andrew Georgiou
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Immunology Unit, Research Department of Haematology, University College London Cancer Institute, London, UK
| | - Maise Al-Bakir
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Nicholas McGranahan
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, University College London Cancer Institute, London, UK
| | - Mariam Jamal-Hanjani
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Metastasis Lab, University College London Cancer Institute, London, UK
| | - Allan Hackshaw
- Cancer Research UK & University College London Cancer Trials Centre, University College London, London, UK
| | - Sergio A Quezada
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Immunology Unit, Research Department of Haematology, University College London Cancer Institute, London, UK
| | - Adrian C Hayday
- Peter Gorer Department of Immunobiology, School of Immunology & Microbial Sciences, King's College London, London, UK.
- Immunosurveillance Laboratory, The Francis Crick Institute, London, UK.
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
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131
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Sohn YB, Rogers C, Stallworth J, Cooley Coleman JA, Buch L, Jozwiak E, Johnson JA, Wood T, Harmatz P, Pollard L, Louie RJ. RNA analysis of the GALNS transcript reveals novel pathogenic mechanisms associated with Morquio syndrome A. Mol Genet Metab Rep 2022; 31:100875. [PMID: 35782621 PMCID: PMC9248232 DOI: 10.1016/j.ymgmr.2022.100875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 04/22/2022] [Indexed: 11/29/2022] Open
Abstract
Morquio syndrome A (Mucopolysaccharidosis IVA, MPS IVA) is an autosomal recessive lysosomal storage disorder caused by deficiency of N-acetyl-galactosamine-6-sulfatase (GALNS) which catabolizes the glycosaminoglycans (GAG), keratan sulfate and chondroitin-6-sulfate. Homozygous or compound heterozygous pathogenic variants in the GALNS result in the deficiency of the enzyme and consequent GAG accumulations. DNA sequence and copy number analysis of the GALNS coding region fails to identify biallelic causative pathogenic variants in up to 15% of patients with Morquio syndrome A. RNA transcript analysis was performed to identify pathogenic alterations in two unrelated families with Morquio syndrome A in whom a single heterozygous or no pathogenic alteration was detected by standard analysis of the GALNS gene. RNA sequencing and quantitative expression analysis identified the overabundance of an aberrant GALNS transcript isoform and a reduction of the clinically relevant isoform (NM_000512.4) in the Morquio syndrome A patients from both families. The aberrant isoform (ENST00000568613.1) was produced by alternative splicing and contained intronic sequence that was likely a cryptic exon predicted to result in a reading frame shift and generation of a premature termination codon. These findings indicated that the aberrant splicing is likely the novel molecular defect in our patients. RNA transcript analysis could be useful to identify pathogenic alterations and increase the yield of molecular diagnosis in patients with Morquio syndrome A whose genetic variants are not found by standard sequencing or gene dosage analysis.
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Affiliation(s)
- Young Bae Sohn
- Department of Medical Genetics, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea
- Corresponding author at: Department of Medical Genetics, Ajou University Hospital, Ajou University School of Medicine, 164 Worldcup-ro, Yeongtong-gu, Suwon 16499, Republic of Korea.
| | | | | | | | - Laura Buch
- Greenwood Genetic Center, Greenwood, SC, USA
| | - Erin Jozwiak
- UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
| | - Jo Ann Johnson
- UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
| | - Tim Wood
- Section of Genetics and Metabolism, University of Colorado/Children's Hospital of Colorado, Aurora, CO, USA
| | - Paul Harmatz
- UCSF Benioff Children's Hospital Oakland, Oakland, CA, USA
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132
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Lengger B, Hoch-Schneider EE, Jensen CN, Jakočiu̅nas T, Petersen AA, Frimurer TM, Jensen ED, Jensen MK. Serotonin G Protein-Coupled Receptor-Based Biosensing Modalities in Yeast. ACS Sens 2022; 7:1323-1335. [PMID: 35452231 PMCID: PMC9150182 DOI: 10.1021/acssensors.1c02061] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/17/2022] [Indexed: 11/29/2022]
Abstract
Serotonin is a key neurotransmitter involved in numerous physiological processes and serves as an important precursor for manufacturing bioactive indoleamines and alkaloids used in the treatment of human pathologies. In humans, serotonin sensing and signaling can occur by 12 G protein-coupled receptors (GPCRs) coupled to Gα proteins. In yeast, human serotonin GPCRs coupled to Gα proteins have previously been shown to function as whole-cell biosensors of serotonin. However, systematic characterization of serotonin biosensing modalities between variant serotonin GPCRs and application thereof for high-resolution serotonin quantification is still awaiting. To systematically assess GPCR signaling in response to serotonin, we characterized reporter gene expression at two different pHs of a 144-sized library encoding all 12 human serotonin GPCRs in combination with 12 different Gα proteins engineered in yeast. From this screen, we observed changes in the biosensor sensitivities of >4 orders of magnitude. Furthermore, adopting optimal biosensing designs and pH conditions enabled high-resolution high-performance liquid chromatography-validated sensing of serotonin produced in yeast. Lastly, we used the yeast platform to characterize 19 serotonin GPCR polymorphisms found in human populations. While major differences in signaling were observed among the individual polymorphisms when studied in yeast, a cross-comparison of selected variants in mammalian cells showed both similar and disparate results. Taken together, our study highlights serotonin biosensing modalities of relevance to both biotechnological and potential human health applications.
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Affiliation(s)
- Bettina Lengger
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
| | - Emma E. Hoch-Schneider
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
| | - Christina N. Jensen
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
| | - Tadas Jakočiu̅nas
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
| | - Anja A. Petersen
- Novo
Nordisk Foundation Center for Basic Metabolic Research, Faculty of
Health and Medical Sciences, University
of Copenhagen, Maersk
Tower, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Thomas M. Frimurer
- Novo
Nordisk Foundation Center for Basic Metabolic Research, Faculty of
Health and Medical Sciences, University
of Copenhagen, Maersk
Tower, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Emil D. Jensen
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
| | - Michael K. Jensen
- Novo
Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
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Anderegg MA, Gyimesi G, Ho TM, Hediger MA, Fuster DG. The Less Well-Known Little Brothers: The SLC9B/NHA Sodium Proton Exchanger Subfamily—Structure, Function, Regulation and Potential Drug-Target Approaches. Front Physiol 2022; 13:898508. [PMID: 35694410 PMCID: PMC9174904 DOI: 10.3389/fphys.2022.898508] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 05/04/2022] [Indexed: 12/15/2022] Open
Abstract
The SLC9 gene family encodes Na+/H+ exchangers (NHEs), a group of membrane transport proteins critically involved in the regulation of cytoplasmic and organellar pH, cell volume, as well as systemic acid-base and volume homeostasis. NHEs of the SLC9A subfamily (NHE 1–9) are well-known for their roles in human physiology and disease. Much less is known about the two members of the SLC9B subfamily, NHA1 and NHA2, which share higher similarity to prokaryotic NHEs than the SLC9A paralogs. NHA2 (also known as SLC9B2) is ubiquitously expressed and has recently been shown to participate in renal blood pressure and electrolyte regulation, insulin secretion and systemic glucose homeostasis. In addition, NHA2 has been proposed to contribute to the pathogenesis of polycystic kidney disease, the most common inherited kidney disease in humans. NHA1 (also known as SLC9B1) is mainly expressed in testis and is important for sperm motility and thus male fertility, but has not been associated with human disease thus far. In this review, we present a summary of the structure, function and regulation of expression of the SLC9B subfamily members, focusing primarily on the better-studied SLC9B paralog, NHA2. Furthermore, we will review the potential of the SLC9B subfamily as drug targets.
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Affiliation(s)
- Manuel A. Anderegg
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- *Correspondence: Manuel A. Anderegg,
| | - Gergely Gyimesi
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Membrane Transport Discovery Lab, Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Tin Manh Ho
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Matthias A. Hediger
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Membrane Transport Discovery Lab, Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Daniel G. Fuster
- Department of Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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134
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Eraslan G, Drokhlyansky E, Anand S, Fiskin E, Subramanian A, Slyper M, Wang J, Van Wittenberghe N, Rouhana JM, Waldman J, Ashenberg O, Lek M, Dionne D, Win TS, Cuoco MS, Kuksenko O, Tsankov AM, Branton PA, Marshall JL, Greka A, Getz G, Segrè AV, Aguet F, Rozenblatt-Rosen O, Ardlie KG, Regev A. Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. Science 2022; 376:eabl4290. [PMID: 35549429 PMCID: PMC9383269 DOI: 10.1126/science.abl4290] [Citation(s) in RCA: 144] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.
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Affiliation(s)
- Gökcen Eraslan
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Eugene Drokhlyansky
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shankara Anand
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Evgenij Fiskin
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ayshwarya Subramanian
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Michal Slyper
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jiali Wang
- Department of Ophthalmology, Harvard Medical School, Boston, MA 02115, USA
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - John M. Rouhana
- Department of Ophthalmology, Harvard Medical School, Boston, MA 02115, USA
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Julia Waldman
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Orr Ashenberg
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Monkol Lek
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Danielle Dionne
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Thet Su Win
- Department of Dermatology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Michael S. Cuoco
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Olena Kuksenko
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Philip A. Branton
- The Joint Pathology Center Gynecologic/Breast Pathology, Silver Spring, MD 20910, USA
| | | | - Anna Greka
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Gad Getz
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Cancer Research and Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Ayellet V. Segrè
- Department of Ophthalmology, Harvard Medical School, Boston, MA 02115, USA
- Ocular Genomics Institute, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA 02114, USA
- Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - François Aguet
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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135
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Noda Y, Okada S, Suzuki T. Regulation of A-to-I RNA editing and stop codon recoding to control selenoprotein expression during skeletal myogenesis. Nat Commun 2022; 13:2503. [PMID: 35523818 PMCID: PMC9076623 DOI: 10.1038/s41467-022-30181-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 04/05/2022] [Indexed: 12/13/2022] Open
Abstract
Selenoprotein N (SELENON), a selenocysteine (Sec)-containing protein with high reductive activity, maintains redox homeostasis, thereby contributing to skeletal muscle differentiation and function. Loss-of-function mutations in SELENON cause severe neuromuscular disorders. In the early-to-middle stage of myoblast differentiation, SELENON maintains redox homeostasis and modulates endoplasmic reticulum (ER) Ca2+ concentration, resulting in a gradual reduction from the middle-to-late stages due to unknown mechanisms. The present study describes post-transcriptional mechanisms that regulate SELENON expression during myoblast differentiation. Part of an Alu element in the second intron of SELENON pre-mRNA is frequently exonized during splicing, resulting in an aberrant mRNA that is degraded by nonsense-mediated mRNA decay (NMD). In the middle stage of myoblast differentiation, ADAR1-mediated A-to-I RNA editing occurs in the U1 snRNA binding site at 5' splice site, preventing Alu exonization and producing mature mRNA. In the middle-to-late stage of myoblast differentiation, the level of Sec-charged tRNASec decreases due to downregulation of essential recoding factors for Sec insertion, thereby generating a premature termination codon in SELENON mRNA, which is targeted by NMD.
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Affiliation(s)
- Yuta Noda
- Department of Chemistry and Biotechnology, Graduate School of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Shunpei Okada
- Department of Chemistry and Biotechnology, Graduate School of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
- Department of Microbiology, Faculty of Medicine, Shimane University, 89-1 Enyacho, Izumo, Shimane, 693-8501, Japan
| | - Tsutomu Suzuki
- Department of Chemistry and Biotechnology, Graduate School of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan.
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136
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Kellman BP, Richelle A, Yang JY, Chapla D, Chiang AWT, Najera JA, Liang C, Fürst A, Bao B, Koga N, Mohammad MA, Bruntse AB, Haymond MW, Moremen KW, Bode L, Lewis NE. Elucidating Human Milk Oligosaccharide biosynthetic genes through network-based multi-omics integration. Nat Commun 2022; 13:2455. [PMID: 35508452 PMCID: PMC9068700 DOI: 10.1038/s41467-022-29867-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 04/04/2022] [Indexed: 12/18/2022] Open
Abstract
Human Milk Oligosaccharides (HMOs) are abundant carbohydrates fundamental to infant health and development. Although these oligosaccharides were discovered more than half a century ago, their biosynthesis in the mammary gland remains largely uncharacterized. Here, we use a systems biology framework that integrates glycan and RNA expression data to construct an HMO biosynthetic network and predict glycosyltransferases involved. To accomplish this, we construct models describing the most likely pathways for the synthesis of the oligosaccharides accounting for >95% of the HMO content in human milk. Through our models, we propose candidate genes for elongation, branching, fucosylation, and sialylation of HMOs. Our model aggregation approach recovers 2 of 2 previously known gene-enzyme relations and 2 of 3 empirically confirmed gene-enzyme relations. The top genes we propose for the remaining 5 linkage reactions are consistent with previously published literature. These results provide the molecular basis of HMO biosynthesis necessary to guide progress in HMO research and application with the goal of understanding and improving infant health and development. Human milk oligosaccharides are fundamental to infant health. Here the authors deploy a multi-omics systems biology approach to elucidate their biosynthetic network, including the associated enzymes and likely structures of ambiguous oligosaccharides.
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Affiliation(s)
- Benjamin P Kellman
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA.,Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Anne Richelle
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Jeong-Yeh Yang
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - Digantkumar Chapla
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - Austin W T Chiang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Julia A Najera
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Chenguang Liang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Annalee Fürst
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Bokan Bao
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA.,Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA.,Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Natalia Koga
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Mahmoud A Mohammad
- Department of Pediatrics, Children's Nutrition Research Center, US Department of Agriculture/Agricultural Research Service, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Anders Bech Bruntse
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Morey W Haymond
- Department of Pediatrics, Children's Nutrition Research Center, US Department of Agriculture/Agricultural Research Service, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Kelley W Moremen
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
| | - Lars Bode
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA.,Larsson-Rosenquist Foundation Mother-Milk-Infant Center of Research Excellence (MOMI CORE), University of California, San Diego, La Jolla, CA, 92093, USA
| | - Nathan E Lewis
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, 92093, USA. .,Department of Bioengineering, University of California, San Diego, La Jolla, CA, 92093, USA.
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137
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Abstract
Altered lipid metabolism is a characteristic feature and potential driving factor of acute kidney injury (AKI). Of the lipids that accumulate in injured renal tissues, ceramides are potent regulators of metabolism and cell fate. Up-regulation of ceramide synthesis is a common feature shared across several AKI etiologies in vitro and in vivo. Furthermore, ceramide accumulation is an early event in the natural history of AKI that precedes cell death and organ dysfunction. Emerging evidence suggests that inhibition of ceramide accumulation may improve renal outcomes in several models of AKI. This review examines the landscape of ceramide metabolism and regulation in the healthy and injured kidney. Furthermore, we discuss the body of literature regarding ceramides as therapeutic targets for AKI and consider potential mechanisms by which ceramides drive kidney pathogenesis.
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Affiliation(s)
- Rebekah J Nicholson
- Department of Nutrition and Integrative Physiology, Diabetes and Metabolism Research Center, University of Utah, Salt Lake City, UT
| | - William L Holland
- Department of Nutrition and Integrative Physiology, Diabetes and Metabolism Research Center, University of Utah, Salt Lake City, UT
| | - Scott A Summers
- Department of Nutrition and Integrative Physiology, Diabetes and Metabolism Research Center, University of Utah, Salt Lake City, UT.
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138
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Ma Y, Zhang X, Yang J, Jin Y, Xu Y, Qiu J. Comprehensive Molecular Analyses of a TNF Family-Based Gene Signature as a Potentially Novel Prognostic Biomarker for Cervical Cancer. Front Oncol 2022; 12:854615. [PMID: 35392242 PMCID: PMC8980547 DOI: 10.3389/fonc.2022.854615] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 02/28/2022] [Indexed: 12/14/2022] Open
Abstract
Background Increasing evidence suggests that tumour necrosis factor (TNF) family genes play important roles in cervical cancer (CC). However, whether TNF family genes can be used as prognostic biomarkers of CC and the molecular mechanisms of TNF family genes remain unclear. Methods A total of 306 CC and 13 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We identified differentially expressed TNF family genes between CC and normal samples and subjected them to univariate Cox regression analysis for selecting prognostic TNF family genes. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to screen genes to establish a TNF family gene signature. Gene set enrichment analysis (GSEA) was performed to investigate the biological functions of the TNF family gene signature. Finally, methylation and copy number variation data of CC were used to analyse the potential molecular mechanisms of TNF family genes. Results A total of 26 differentially expressed TNF family genes were identified between the CC and normal samples. Next, a TNF family gene signature, including CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 was constructed based on univariate Cox, LASSO, and multivariate Cox regression analyses. The TNF family gene signature was related to age, pathological stages M and N, and could predict patient survival independently of clinical factors. Moreover, KEGG enrichment analysis suggested that the TNF family gene signature was mainly involved in the TGF-β signaling pathway, and the TNF family gene signature could affect the immunotherapy response. Finally, we confirmed that the mRNA expressions of CD27, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 were upregulated in CC, while that of EDA was downregulated. The mRNA expressions of CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be influenced by gene methylation and copy number variation. Conclusion Our study is the first to demonstrate that CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be used as prognostic biomarkers of CC and are associated with the immunotherapy response of CC.
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Affiliation(s)
- Yan Ma
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoyan Zhang
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Jiancheng Yang
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Yanping Jin
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Ying Xu
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Jianping Qiu
- Department of Gynecology and Obstetrics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
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139
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Hinkle ER, Wiedner HJ, Torres EV, Jackson M, Black AJ, Blue RE, Harris SE, Guzman BB, Gentile GM, Lee EY, Tsai YH, Parker J, Dominguez D, Giudice J. Alternative splicing regulation of membrane trafficking genes during myogenesis. RNA (NEW YORK, N.Y.) 2022; 28:523-540. [PMID: 35082143 PMCID: PMC8925968 DOI: 10.1261/rna.078993.121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 12/17/2021] [Indexed: 06/14/2023]
Abstract
Alternative splicing transitions occur during organ development, and, in numerous diseases, splicing programs revert to fetal isoform expression. We previously found that extensive splicing changes occur during postnatal mouse heart development in genes encoding proteins involved in vesicle-mediated trafficking. However, the regulatory mechanisms of this splicing-trafficking network are unknown. Here, we found that membrane trafficking genes are alternatively spliced in a tissue-specific manner, with striated muscles exhibiting the highest levels of alternative exon inclusion. Treatment of differentiated muscle cells with chromatin-modifying drugs altered exon inclusion in muscle cells. Examination of several RNA-binding proteins revealed that the poly-pyrimidine tract binding protein 1 (PTBP1) and quaking regulate splicing of trafficking genes during myogenesis, and that removal of PTBP1 motifs prevented PTBP1 from binding its RNA target. These findings enhance our understanding of developmental splicing regulation of membrane trafficking proteins which might have implications for muscle disease pathogenesis.
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Affiliation(s)
- Emma R Hinkle
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Curriculum in Genetics and Molecular Biology (GMB), The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Hannah J Wiedner
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Curriculum in Genetics and Molecular Biology (GMB), The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Eduardo V Torres
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Micaela Jackson
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Adam J Black
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - R Eric Blue
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Sarah E Harris
- Department of Biochemistry and Biophysics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Bryan B Guzman
- Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Gabrielle M Gentile
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Curriculum in Genetics and Molecular Biology (GMB), The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Eunice Y Lee
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Yi-Hsuan Tsai
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Joel Parker
- Curriculum in Genetics and Molecular Biology (GMB), The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Daniel Dominguez
- Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Jimena Giudice
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Curriculum in Genetics and Molecular Biology (GMB), The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- McAllister Heart Institute, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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140
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Sui S, Wang Z, Cui X, Jin L, Zhu C. The biological behavior of tRNA-derived fragment tRF-Leu-AAG in pancreatic cancer cells. Bioengineered 2022; 13:10617-10628. [PMID: 35442152 PMCID: PMC9161985 DOI: 10.1080/21655979.2022.2064206] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/29/2022] [Accepted: 04/05/2022] [Indexed: 01/01/2023] Open
Abstract
Pancreatic cancer (PC) is a life-threatening cancer with increasing incidence in developed countries. Reports indicate that tRNA-derived fragments (tRFs) are possible therapeutic targets and biomarkers for cancer treatment. Nonetheless, the effect of tRF-Leu-AAG on PC is unclear. This study aims to explore the role of tRF-Leu-AAG and upstream frameshift mutant 1 (UPF1) in the development of PC and its potential underlying mechanisms. High-throughput second-generation sequencing techniques were used to detect the expression of tRFs in cancerous and adjacent normal tissues from PC patients. The role of tRF-Leu-AAG proliferation in PC cells was investigated via the Cell Counting Kit-8 (CCK8) assay. The effect of tRF-Leu-AAG on the invasion and migration ability of PC cells was also determined by the transwell assay. Thereafter, the downstream target genes of tRF-Leu-AAG were comprehensively predicted using bioinformatics analysis databases. We also used the Dual-Luciferase Reporter assay to assess the nexus between tRF-Leu-AAG and UPF1. Eventually, Western Blot was used to validate the expression of UPF1 in PC cells. A total of 33 tRF expressions significantly varied from PC patients. RT-qPCR confirmed that the expression of tRF-Leu-AAG was observably up-regulated in PC cells as compared to the control cells. Importantly, knockdown of tRF-Leu-AAG observably inhibited cell proliferation, migration, and invasion. Furthermore, according to the predicted frameshift database results, the UPF1 acted as downstream target genes for tRF-Leu-AAG and significantly down-regulated UPF1 expression.
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Affiliation(s)
- Shizhen Sui
- Graduate School of Dalian Medical University, Dalian Medical University, Dalian, Liaoning, China
| | - Zhihuai Wang
- Graduate School of Dalian Medical University, Dalian Medical University, Dalian, Liaoning, China
| | - Xiaohan Cui
- Department of Hepatobiliary Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
| | - Lei Jin
- Department of Hepatobiliary Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
| | - Chunfu Zhu
- Department of Hepatobiliary Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
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Maihofer AX, Choi KW, Coleman JR, Daskalakis NP, Denckla CA, Ketema E, Morey RA, Polimanti R, Ratanatharathorn A, Torres K, Wingo AP, Zai CC, Aiello AE, Almli LM, Amstadter AB, Andersen SB, Andreassen OA, Arbisi PA, Ashley-Koch AE, Austin SB, Avdibegović E, Borglum AD, Babić D, Bækvad-Hansen M, Baker DG, Beckham JC, Bierut LJ, Bisson JI, Boks MP, Bolger EA, Bradley B, Brashear M, Breen G, Bryant RA, Bustamante AC, Bybjerg-Grauholm J, Calabrese JR, Caldas-de-Almeida JM, Chen CY, Dale AM, Dalvie S, Deckert J, Delahanty DL, Dennis MF, Disner SG, Domschke K, Duncan LE, Kulenović AD, Erbes CR, Evans A, Farrer LA, Feeny NC, Flory JD, Forbes D, Franz CE, Galea S, Garrett ME, Gautam A, Gelaye B, Gelernter J, Geuze E, Gillespie CF, Goçi A, Gordon SD, Guffanti G, Hammamieh R, Hauser MA, Heath AC, Hemmings SM, Hougaard DM, Jakovljević M, Jett M, Johnson EO, Jones I, Jovanovic T, Qin XJ, Karstoft KI, Kaufman ML, Kessler RC, Khan A, Kimbrel NA, King AP, Koen N, Kranzler HR, Kremen WS, Lawford BR, Lebois LA, Lewis C, Liberzon I, Linnstaedt SD, Logue MW, Lori A, Lugonja B, Luykx JJ, Lyons MJ, Maples-Keller JL, Marmar C, Martin NG, Maurer D, Mavissakalian MR, McFarlane A, McGlinchey RE, McLaughlin KA, McLean SA, Mehta D, Mellor R, Michopoulos V, Milberg W, Miller MW, Morris CP, Mors O, Mortensen PB, Nelson EC, Nordentoft M, Norman SB, O’Donnell M, Orcutt HK, Panizzon MS, Peters ES, Peterson AL, Peverill M, Pietrzak RH, Polusny MA, Rice JP, Risbrough VB, Roberts AL, Rothbaum AO, Rothbaum BO, Roy-Byrne P, Ruggiero KJ, Rung A, Rutten BP, Saccone NL, Sanchez SE, Schijven D, Seedat S, Seligowski AV, Seng JS, Sheerin CM, Silove D, Smith AK, Smoller JW, Sponheim SR, Stein DJ, Stevens JS, Teicher MH, Thompson WK, Trapido E, Uddin M, Ursano RJ, van den Heuvel LL, Van Hooff M, Vermetten E, Vinkers C, Voisey J, Wang Y, Wang Z, Werge T, Williams MA, Williamson DE, Winternitz S, Wolf C, Wolf EJ, Yehuda R, Young KA, Young RM, Zhao H, Zoellner LA, Haas M, Lasseter H, Provost AC, Salem RM, Sebat J, Shaffer RA, Wu T, Ripke S, Daly MJ, Ressler KJ, Koenen KC, Stein MB, Nievergelt CM. Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information. Biol Psychiatry 2022; 91:626-636. [PMID: 34865855 PMCID: PMC8917986 DOI: 10.1016/j.biopsych.2021.09.020] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 08/25/2021] [Accepted: 09/21/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). METHODS A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. RESULTS GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. CONCLUSIONS Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.
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142
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Castaneda AB, Petty LE, Scholz M, Jansen R, Weiss S, Zhang X, Schramm K, Beutner F, Kirsten H, Schminke U, Hwang SJ, Marzi C, Dhana K, Seldenrijk A, Krohn K, Homuth G, Wolf P, Peters MJ, Dörr M, Peters A, van Meurs JBJ, Uitterlinden AG, Kavousi M, Levy D, Herder C, van Grootheest G, Waldenberger M, Meisinger C, Rathmann W, Thiery J, Polak J, Koenig W, Seissler J, Bis JC, Franceshini N, Giambartolomei C, Hofman A, Franco OH, Penninx BWJH, Prokisch H, Völzke H, Loeffler M, O'Donnell CJ, Below JE, Dehghan A, de Vries PS. Associations of carotid intima media thickness with gene expression in whole blood and genetically predicted gene expression across 48 tissues. Hum Mol Genet 2022; 31:1171-1182. [PMID: 34788810 PMCID: PMC8976428 DOI: 10.1093/hmg/ddab236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/11/2021] [Accepted: 08/11/2021] [Indexed: 11/13/2022] Open
Abstract
Carotid intima media thickness (cIMT) is a biomarker of subclinical atherosclerosis and a predictor of future cardiovascular events. Identifying associations between gene expression levels and cIMT may provide insight to atherosclerosis etiology. Here, we use two approaches to identify associations between mRNA levels and cIMT: differential gene expression analysis in whole blood and S-PrediXcan. We used microarrays to measure genome-wide whole blood mRNA levels of 5647 European individuals from four studies. We examined the association of mRNA levels with cIMT adjusted for various potential confounders. Significant associations were tested for replication in three studies totaling 3943 participants. Next, we applied S-PrediXcan to summary statistics from a cIMT genome-wide association study (GWAS) of 71 128 individuals to estimate the association between genetically determined mRNA levels and cIMT and replicated these analyses using S-PrediXcan on an independent GWAS on cIMT that included 22 179 individuals from the UK Biobank. mRNA levels of TNFAIP3, CEBPD and METRNL were inversely associated with cIMT, but these associations were not significant in the replication analysis. S-PrediXcan identified associations between cIMT and genetically determined mRNA levels for 36 genes, of which six were significant in the replication analysis, including TLN2, which had not been previously reported for cIMT. There was weak correlation between our results using differential gene expression analysis and S-PrediXcan. Differential expression analysis and S-PrediXcan represent complementary approaches for the discovery of associations between phenotypes and gene expression. Using these approaches, we prioritize TNFAIP3, CEBPD, METRNL and TLN2 as new candidate genes whose differential expression might modulate cIMT.
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Affiliation(s)
- Andy B Castaneda
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.,LIFE Research Center of Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Rick Jansen
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.,DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Xiaoling Zhang
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.,The Framingham Heart Study, Framingham, MA, USA
| | - Katharina Schramm
- Institute of Neurogenomics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Technical University Munich, Munich, Germany
| | | | - Holger Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.,LIFE Research Center of Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Ulf Schminke
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Shih-Jen Hwang
- The Framingham Heart Study, Framingham, MA, USA.,Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Carola Marzi
- Institute of Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Klodian Dhana
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Adrie Seldenrijk
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Knut Krohn
- Interdisciplinary Center of Clinical Research, University of Leipzig, Leipzig, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Petra Wolf
- Institute of Neurogenomics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Marjolein J Peters
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.,Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.,Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA, USA.,Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Christian Herder
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,German Center for Diabetes Research (DZD e.V.), München-Neuherberg, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Melanie Waldenberger
- Institute of Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christa Meisinger
- Institute of Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Augsburg, Germany
| | - Wolfgang Rathmann
- Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Joachim Thiery
- LIFE Research Center of Civilization Diseases, University of Leipzig, Leipzig, Germany.,Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University of Leipzig, Leipzig, Germany
| | - Joseph Polak
- Tufts University School of Medicine, Boston, MA, USA
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.,DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.,Department of Internal Medicine II-Cardiology, University of Ulm Medical Center, Ulm, Germany
| | - Jochen Seissler
- Diabetes Center, Diabetes Research Group, Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-Universität, Munich, Germany
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nora Franceshini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | | | | | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.,Institute of Social and Preventive Medicine, University of Bern, Switzerland
| | - Brenda W J H Penninx
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Holger Prokisch
- Institute of Neurogenomics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Henry Völzke
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.,Institute of Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.,LIFE Research Center of Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Christopher J O'Donnell
- The Framingham Heart Study, Framingham, MA, USA.,Cardiology Section, Department of Medicine, Boston Veteran's Administration Healthcare and Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.,Department of Epidemiology and Biostatistics, Imperial College London, London, UK.,MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK.,UK Dementia Research Institute at Imperial College London, Burlington Danes Building, Hammersmith Hospital, Du Cane Road, London W12 0NN UK
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.,Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
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Chen D, Wu H, Wang X, Huang T, Jia J. Shared Genetic Basis and Causal Relationship Between Television Watching, Breakfast Skipping and Type 2 Diabetes: Evidence From a Comprehensive Genetic Analysis. Front Endocrinol (Lausanne) 2022; 13:836023. [PMID: 35399945 PMCID: PMC8988136 DOI: 10.3389/fendo.2022.836023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 03/01/2022] [Indexed: 11/13/2022] Open
Abstract
Background Epidemiological investigations have established unhealthy lifestyles, such as excessive leisurely sedentary behavior (especially TV/television watching) and breakfast skipping, increase the risk of type 2 diabetes (T2D), but the causal relationship is unclear. We aimed to understand how single nucleotide variants contribute to the co-occurrence of unhealthy lifestyles and T2D, thereby providing meaningful insights into disease mechanisms. Methods Combining summary statistics from genome-wide association studies (GWAS) on TV watching (N = 422218), breakfast skipping (N = 193860) and T2D (N = 159208) in European pedigrees, we conducted comprehensive pairwise genetic analysis, including high-definition likelihood (HDL-method), cross-phenotype association studies (CPASSOC), GWAS-eQTL colocalization analysis and transcriptome-wide association studies (TWAS), to understand the genetic overlap between them. We also performed bidirectional two-sample Mendelian randomization (MR) analysis for causal inference using genetic instrumental variables, and two-step MR mediation analysis was used to assess any effects explained by body mass index, lipid traits and glycemic traits. Results HDL-method showed that T2D shared a strong genetic correlation with TV watching (rg = 0.26; P = 1.63×10-29) and skipping breakfast (rg = 0.15; P =2.02×10-6). CPASSOC identifies eight independent SNPs shared between T2D and TV watching, including one novel shared locus. TWAS and CPASSOC showed that shared genes were enriched in lung, esophageal, adipose, and thyroid tissues and highlighted potential shared regulatory pathways for lipoprotein metabolism, pancreatic β-cell function, cellular senescence and multi-mediator factors. MR showed TV watching had a causal effect on T2D (βIVW = 0.629, PIVW = 1.80×10-10), but no significant results were observed between breakfast skipping and T2D. Mediation analysis provided evidence that body mass index, fasting glucose, hemoglobin A1c and high-density lipoprotein are potential factors that mediate the causal relationship between TV and T2D. Conclusions Our findings provide strong evidence of shared genetics and causation between TV watching and T2D and facilitate our identification of common genetic architectures shared between them.
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Affiliation(s)
- Dongze Chen
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Hanyu Wu
- Department of Bioinformatics, School of Life Science, Peking University, Beijing, China
| | - Xinpei Wang
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China
| | - Jinzhu Jia
- Department of Biostatistics, School of Public Health, Peking University, Beijing, China
- Center for Statistical Science, Peking University, Beijing, China
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144
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Maria M, Pouyanfar N, Örd T, Kaikkonen MU. The Power of Single-Cell RNA Sequencing in eQTL Discovery. Genes (Basel) 2022; 13:genes13030502. [PMID: 35328055 PMCID: PMC8949403 DOI: 10.3390/genes13030502] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 03/07/2022] [Accepted: 03/10/2022] [Indexed: 02/05/2023] Open
Abstract
Genome-wide association studies have successfully mapped thousands of loci associated with complex traits. During the last decade, functional genomics approaches combining genotype information with bulk RNA-sequencing data have identified genes regulated by GWAS loci through expression quantitative trait locus (eQTL) analysis. Single-cell RNA-Sequencing (scRNA-Seq) technologies have created new exciting opportunities for spatiotemporal assessment of changes in gene expression at the single-cell level in complex and inherited conditions. A growing number of studies have demonstrated the power of scRNA-Seq in eQTL mapping across different cell types, developmental stages and stimuli that could be obscured when using bulk RNA-Seq methods. In this review, we outline the methodological principles, advantages, limitations and the future experimental and analytical considerations of single-cell eQTL studies. We look forward to the explosion of single-cell eQTL studies applied to large-scale population genetics to take us one step closer to understanding the molecular mechanisms of disease.
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145
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Autio A, Kettunen J, Nevalainen T, Kimura B, Hurme M. Herpesviruses and their genetic diversity in the blood virome of healthy individuals: effect of aging. Immun Ageing 2022; 19:15. [PMID: 35279192 PMCID: PMC8917371 DOI: 10.1186/s12979-022-00268-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND As we age, the functioning of the human immune system declines. The results of this are increases in morbidity and mortality associated with infectious diseases, cancer, cardiovascular disease, and neurodegenerative disease in elderly individuals, as well as a weakened vaccination response. The aging of the immune system is thought to affect and be affected by the human virome, the collection of all viruses present in an individual. Persistent viral infections, such as those caused by certain herpesviruses, can be present in an individual for long periods of time without any overt pathology, yet are associated with disease in states of compromised immune function. To better understand the effects on human health of such persistent viral infections, we must first understand how the human virome changes with age. We have now analyzed the composition of the whole blood virome of 317 individuals, 21-70 years old, using a metatranscriptomic approach. Use of RNA sequencing data allows for the unbiased detection of RNA viruses and active DNA viruses. RESULTS The data obtained showed that Epstein-Barr virus (EBV) was the most frequently expressed virus, with other detected viruses being herpes simplex virus 1, human cytomegalovirus, torque teno viruses, and papillomaviruses. Of the 317 studied blood samples, 68 (21%) had EBV expression, whereas the other detected viruses were only detected in at most 6 samples (2%). We therefore focused on EBV in our further analyses. Frequency of EBV detection, relative EBV RNA abundance and the genetic diversity of EBV was not significantly different between age groups (21-59 and 60-70 years old). No significant correlation was seen between EBV RNA abundance and age. Deconvolution analysis revealed a significant difference in proportions of activated dendritic cells, macrophages M1, and activated mast cells between EBV expression positive and negative individuals. CONCLUSIONS As it is likely that the EBV RNA quantified in this work is derived from reactivation of the latent EBV virus, these data suggest that age does not affect the rate of reactivation nor the genetic landscape of EBV. These findings offer new insight on the genetic diversity of a persistent EBV infection in the long-term.
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Affiliation(s)
- Arttu Autio
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland
- Gerontology Research Center (GEREC), Tampere, Finland
| | - Jalmari Kettunen
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland
| | - Tapio Nevalainen
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland
- Gerontology Research Center (GEREC), Tampere, Finland
- Science Centre, Pirkanmaa Hospital District, Tampere, Finland
| | - Bryn Kimura
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland
| | - Mikko Hurme
- Faculty of Medicine and Health Technology, Tampere University, Arvo Ylpön katu 34, 33520 Tampere, Finland
- Gerontology Research Center (GEREC), Tampere, Finland
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146
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Seyres D, Cabassi A, Lambourne JJ, Burden F, Farrow S, McKinney H, Batista J, Kempster C, Pietzner M, Slingsby O, Cao TH, Quinn PA, Stefanucci L, Sims MC, Rehnstrom K, Adams CL, Frary A, Ergüener B, Kreuzhuber R, Mocciaro G, D'Amore S, Koulman A, Grassi L, Griffin JL, Ng LL, Park A, Savage DB, Langenberg C, Bock C, Downes K, Wareham NJ, Allison M, Vacca M, Kirk PDW, Frontini M. Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes. Clin Epigenetics 2022; 14:39. [PMID: 35279219 PMCID: PMC8917653 DOI: 10.1186/s13148-022-01257-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/25/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND This work is aimed at improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis by generating a multi-omic disease signature. METHODS/RESULTS We combined classic plasma biochemistry and plasma biomarkers with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (morbidly obese and lipodystrophy) and lean individuals to identify the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells. Our analyses showed that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, 6 months after bariatric surgery, revealed the loss of the abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurred via the establishment of novel gene expression landscapes. NETosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. CONCLUSIONS We showed that the morbidly obese and lipodystrophy groups, despite some differences, shared a common cardiometabolic syndrome signature. We also showed that this could be used to discriminate, amongst the normal population, those individuals with a higher likelihood of presenting with the disease, even when not displaying the classic features.
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Affiliation(s)
- Denis Seyres
- National Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK.
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK.
| | - Alessandra Cabassi
- MRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - John J Lambourne
- National Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Frances Burden
- National Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Samantha Farrow
- National Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Harriet McKinney
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Joana Batista
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Carly Kempster
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Oliver Slingsby
- Department of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Thong Huy Cao
- Department of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Paulene A Quinn
- Department of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Luca Stefanucci
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Cambridge, UK
| | - Matthew C Sims
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- Oxford Haemophilia and Thrombosis Centre, Oxford University Hospitals NHS Foundation Trust, NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Karola Rehnstrom
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Claire L Adams
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Amy Frary
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Bekir Ergüener
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Roman Kreuzhuber
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Gabriele Mocciaro
- Department of Biochemistry and the Cambridge Systems Biology Centre, University of Cambridge, The Sanger Building, 80 Tennis Court Road, Cambridge, CB2 1GA, UK
| | - Simona D'Amore
- Addenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Medicine, Aldo Moro University of Bari, Piazza Giulio Cesare 11, 70124, Bari, Italy
- National Cancer Research Center, IRCCS Istituto Tumori 'Giovanni Paolo II', Viale Orazio Flacco, 65, 70124, Bari, Italy
| | - Albert Koulman
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- MRC Elsie Widdowson Laboratory, Cambridge, UK
- National Institute for Health Research Biomedical Research Centres Core Nutritional Biomarker Laboratory, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- National Institute for Health Research Biomedical Research Centres Core Metabolomics and Lipidomics Laboratory, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
| | - Luigi Grassi
- National Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Julian L Griffin
- Department of Biochemistry and the Cambridge Systems Biology Centre, University of Cambridge, The Sanger Building, 80 Tennis Court Road, Cambridge, CB2 1GA, UK
| | - Leong Loke Ng
- Department of Cardiovascular Sciences, Glenfield Hospital, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Adrian Park
- Addenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - David B Savage
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | | | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
- Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, Vienna, Austria
- Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Kate Downes
- National Institute for Health Research BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- East Midlands and East of England Genomic Laboratory Hub, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Michael Allison
- Addenbrooke's Hospital, NIHR Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Michele Vacca
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Biochemistry and the Cambridge Systems Biology Centre, University of Cambridge, The Sanger Building, 80 Tennis Court Road, Cambridge, CB2 1GA, UK
| | - Paul D W Kirk
- MRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
- Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge Biomedical Campus, Puddicombe Way, Cambridge, CB2 0AW, UK.
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK.
- British Heart Foundation Centre of Excellence, Cambridge Biomedical Campus, Cambridge, UK.
- Institute of Biomedical & Clinical Science, College of Medicine and Health, University of Exeter Medical School, RILD Building, Barrack Road, Exeter, EX2 5DW, UK.
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147
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Li JR, Tang M, Li Y, Amos CI, Cheng C. Genetic variants associated mRNA stability in lung. BMC Genomics 2022; 23:196. [PMID: 35272635 PMCID: PMC8915503 DOI: 10.1186/s12864-022-08405-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 02/21/2022] [Indexed: 12/04/2022] Open
Abstract
Background Expression quantitative trait loci (eQTLs) analyses have been widely used to identify genetic variants associated with gene expression levels to understand what molecular mechanisms underlie genetic traits. The resultant eQTLs might affect the expression of associated genes through transcriptional or post-transcriptional regulation. In this study, we attempt to distinguish these two types of regulation by identifying genetic variants associated with mRNA stability of genes (stQTLs). Results Here, we presented a computational framework that takes advantage of recently developed methods to infer the mRNA stability of genes based on RNA-seq data and performed association analysis to identify stQTLs. Using the Genotype-Tissue Expression (GTEx) lung RNA-Seq data, we identified a total of 142,801 stQTLs for 3942 genes and 186,132 eQTLs for 4751 genes from 15,122,700 genetic variants for 13,476 genes on the autosomes, respectively. Interestingly, our results indicated that stQTLs were enriched in the CDS and 3’UTR regions, while eQTLs are enriched in the CDS, 3’UTR, 5’UTR, and upstream regions. We also found that stQTLs are more likely than eQTLs to overlap with RNA binding protein (RBP) and microRNA (miRNA) binding sites. Our analyses demonstrate that simultaneous identification of stQTLs and eQTLs can provide more mechanistic insight on the association between genetic variants and gene expression levels. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08405-y.
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Affiliation(s)
- Jian-Rong Li
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA.,Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Mabel Tang
- Department of BioSciences, Biochemistry and Cell Biology, Rice University, Houston, TX, USA
| | - Yafang Li
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA.,Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.,Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Christopher I Amos
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA.,Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA.,Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Chao Cheng
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA. .,Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA. .,Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
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148
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Kim KH, Oh Y, Liu J, Dababneh S, Xia Y, Kim RY, Kim DK, Ban K, Husain M, Hui CC, Backx PH. Irx5 and transient outward K + currents contribute to transmural contractile heterogeneities in the mouse ventricle. Am J Physiol Heart Circ Physiol 2022; 322:H725-H741. [PMID: 35245131 DOI: 10.1152/ajpheart.00572.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Previous studies have established that fast transmural gradients of transient outward K+ current (Ito,f) correlate with regional differences in action potential (AP) profile and excitation-contraction coupling (ECC) with high Ito,f expression in the epimyocardium (EPI) being associated with short APs and low contractility and vice versa. Herein, we investigated the effects of disrupted Ito,f gradient on contractile properties using mouse models of Irx5 knockout (Irx5-KO) for selective Ito,f elevation in the endomyocardium (ENDO) of the left ventricle (LV) and Kcnd2 ablation (KV4.2-KO) for selective Ito,freduction in the EPI. Irx5-KO mice exhibited decreased global LV contractility in association with reductions in cell shortening and Ca2+ transient amplitudes in isolated ENDO but not EPI cardiomyocytes. Moreover, transcriptional profiling revealed that the primary effect of Irx5 ablation on ECC-related genes was to increase Ito,f gene expression (i.e. Kcnd2 and Kcnip2) in the ENDO, but not the EPI. Indeed, KV4.2-KO mice showed selective increases in cell shortening and Ca2+ transients in isolated EPI cardiomyocytes, leading to enhanced ventricular contractility and mice lacking both Irx5 and Kcnd2 displayed elevated ventricular contractility comparable to KV4.2-KO mice. Our findings demonstrate that the transmural electromechanical heterogeneities in the healthy ventricles depend on the Irx5-dependent Ito,f gradients. These observations provide a useful framework for assessing the molecular mechanisms underlying the alterations in contractile heterogeneity seen in the diseased heart.
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Affiliation(s)
- Kyoung-Han Kim
- University of Ottawa Heart Institute, Ottawa, ON, Canada.,Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada.,Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Yena Oh
- University of Ottawa Heart Institute, Ottawa, ON, Canada.,Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Jie Liu
- Department of Physiology, University of Toronto, Toronto, ON, Canada.,Department of Biology, Faculty of Science, York University, Toronto, ON, Canada
| | - Saif Dababneh
- University of Ottawa Heart Institute, Ottawa, ON, Canada
| | - Ying Xia
- University of Ottawa Heart Institute, Ottawa, ON, Canada.,Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Ri Youn Kim
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Dae-Kyum Kim
- University of Ottawa Heart Institute, Ottawa, ON, Canada.,Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Kiwon Ban
- Department of Physiology, University of Toronto, Toronto, ON, Canada.,Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China
| | - Mansoor Husain
- Department of Physiology, University of Toronto, Toronto, ON, Canada.,Toronto General Research Institute, University Health Network, Toronto, ON, Canada
| | - Chi-Chung Hui
- Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Peter H Backx
- Department of Physiology, University of Toronto, Toronto, ON, Canada.,Department of Biology, Faculty of Science, York University, Toronto, ON, Canada.,Toronto General Research Institute, University Health Network, Toronto, ON, Canada
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149
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Joseph CB, Mariniello M, Yoshifuji A, Schiano G, Lake J, Marten J, Richmond A, Huffman JE, Campbell A, Harris SE, Troyanov S, Cocca M, Robino A, Thériault S, Eckardt KU, Wuttke M, Cheng Y, Corre T, Kolcic I, Black C, Bruat V, Concas MP, Sala C, Aeschbacher S, Schaefer F, Bergmann S, Campbell H, Olden M, Polasek O, Porteous DJ, Deary IJ, Madore F, Awadalla P, Girotto G, Ulivi S, Conen D, Wuehl E, Olinger E, Wilson JF, Bochud M, Köttgen A, Hayward C, Devuyst O. Meta-GWAS Reveals Novel Genetic Variants Associated with Urinary Excretion of Uromodulin. J Am Soc Nephrol 2022; 33:511-529. [PMID: 35228297 PMCID: PMC8975067 DOI: 10.1681/asn.2021040491] [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: 04/11/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Uromodulin, the most abundant protein excreted in normal urine, plays major roles in kidney physiology and disease. The mechanisms regulating the urinary excretion of uromodulin remain essentially unknown. METHODS We conducted a meta-analysis of genome-wide association studies for raw (uUMOD) and indexed to creatinine (uUCR) urinary levels of uromodulin in 29,315 individuals of European ancestry from 13 cohorts. We tested the distribution of candidate genes in kidney segments and investigated the effects of keratin-40 (KRT40) on uromodulin processing. RESULTS Two genome-wide significant signals were identified for uUMOD: a novel locus (P 1.24E-08) over the KRT40 gene coding for KRT40, a type 1 keratin expressed in the kidney, and the UMOD-PDILT locus (P 2.17E-88), with two independent sets of single nucleotide polymorphisms spread over UMOD and PDILT. Two genome-wide significant signals for uUCR were identified at the UMOD-PDILT locus and at the novel WDR72 locus previously associated with kidney function. The effect sizes for rs8067385, the index single nucleotide polymorphism in the KRT40 locus, were similar for both uUMOD and uUCR. KRT40 colocalized with uromodulin and modulating its expression in thick ascending limb (TAL) cells affected uromodulin processing and excretion. CONCLUSIONS Common variants in KRT40, WDR72, UMOD, and PDILT associate with the levels of uromodulin in urine. The expression of KRT40 affects uromodulin processing in TAL cells. These results, although limited by lack of replication, provide insights into the biology of uromodulin, the role of keratins in the kidney, and the influence of the UMOD-PDILT locus on kidney function.
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Affiliation(s)
- Christina B Joseph
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Marta Mariniello
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Ayumi Yoshifuji
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Guglielmo Schiano
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jennifer Lake
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Anne Richmond
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
| | - Jennifer E Huffman
- Center for Population Genomics,VA Boston Healthcare System, Jamaica Plain, Massachusetts
- The Framingham Heart Study, Framingham, Massachusetts
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephan Troyanov
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Massimiliano Cocca
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Antonietta Robino
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Sébastien Thériault
- Department of Molecular Biology, Medical Biochemistry and Pathology, Laval University, Quebec City, Canada
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany
- Department of Nephrology and Medical Intensive Care, Charite Universitätsmedizin Berlin, Berlin, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Yurong Cheng
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Tanguy Corre
- Center for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Corrinda Black
- Aberdeen Centre for Health Data Science, School of Medicine, Medical Science and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Vanessa Bruat
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Maria Pina Concas
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - Cinzia Sala
- Genetics of Common Disorders Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Franz Schaefer
- Division of Pediatric Nephrology, Center for Pediatrics and Adolescent Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Harry Campbell
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthias Olden
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - David J Porteous
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Francois Madore
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Philip Awadalla
- Division of Nephrology, Hôpital du Sacre-Coeur de Montreal, Montreal, Canada
| | - Giorgia Girotto
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, 34149, Trieste, Italy
| | - Sheila Ulivi
- Institute for Maternal and Child Health IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) "Burlo Garofolo" 34127 Trieste, Italy
| | - David Conen
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Elke Wuehl
- Cardiology Division, University Hospital Basel, Basel, Switzerland
| | - Eric Olinger
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
- Translational and Clinical Research Institute, Newcastle upon Tyne, Newcastle, United Kingdom
| | - James F Wilson
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic & Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Olivier Devuyst
- Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology Institute of Physiology, University of Zurich, Zurich, Switzerland
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150
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Ma XR, Prudencio M, Koike Y, Vatsavayai SC, Kim G, Harbinski F, Briner A, Rodriguez CM, Guo C, Akiyama T, Schmidt HB, Cummings BB, Wyatt DW, Kurylo K, Miller G, Mekhoubad S, Sallee N, Mekonnen G, Ganser L, Rubien JD, Jansen-West K, Cook CN, Pickles S, Oskarsson B, Graff-Radford NR, Boeve BF, Knopman DS, Petersen RC, Dickson DW, Shorter J, Myong S, Green EM, Seeley WW, Petrucelli L, Gitler AD. TDP-43 represses cryptic exon inclusion in the FTD-ALS gene UNC13A. Nature 2022; 603:124-130. [PMID: 35197626 PMCID: PMC8891019 DOI: 10.1038/s41586-022-04424-7] [Citation(s) in RCA: 197] [Impact Index Per Article: 98.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 01/13/2022] [Indexed: 02/08/2023]
Abstract
A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord1. A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing2-4. Single nucleotide polymorphisms in UNC13A are among the strongest hits associated with FTD and ALS in human genome-wide association studies5,6, but how those variants increase risk for disease is unknown. Here we show that TDP-43 represses a cryptic exon-splicing event in UNC13A. Loss of TDP-43 from the nucleus in human brain, neuronal cell lines and motor neurons derived from induced pluripotent stem cells resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. The top variants associated with FTD or ALS risk in humans are located in the intron harbouring the cryptic exon, and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD and ALS (UNC13A genetic variants), and loss of TDP-43 function.
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Affiliation(s)
- X Rosa Ma
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Mercedes Prudencio
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Yuka Koike
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Sarat C Vatsavayai
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - Garam Kim
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Neurosciences Interdepartmental Program, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Adam Briner
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Clem Jones Centre for Ageing Dementia Research (CJCADR), Queensland Brain Institute (QBI), The University of Queensland, Brisbane, Queensland, Australia
| | - Caitlin M Rodriguez
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Caiwei Guo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Tetsuya Akiyama
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - H Broder Schmidt
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
| | | | | | | | | | | | | | - Gemechu Mekonnen
- Program in Cell, Molecular, Developmental Biology, and Biophysics, Johns Hopkins University, Baltimore, MD, USA
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Laura Ganser
- Department of Biophysics, Johns Hopkins University, Baltimore, MD, USA
| | - Jack D Rubien
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Casey N Cook
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - Sarah Pickles
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | | | | | | | | | | | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA
| | - James Shorter
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sua Myong
- Program in Cell, Molecular, Developmental Biology, and Biophysics, Johns Hopkins University, Baltimore, MD, USA
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
- Department of Biophysics, Johns Hopkins University, Baltimore, MD, USA
| | | | - William W Seeley
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - Leonard Petrucelli
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
- Neuroscience Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Jacksonville, FL, USA.
| | - Aaron D Gitler
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
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