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Arnaud Lagarde Aix Marseille Univ, APHM, INSERM, MMG, Laboratory of Molecular Biology Hospital La Conception, Marseille, France

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Grégory Mougel Aix Marseille Univ, APHM, INSERM, MMG, Laboratory of Molecular Biology Hospital La Conception, Marseille, France

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Lucie Coppin Univ. Lille, CNRS, Inserm, CHU Lille, UMR9020-U1277 – CANTHER – Cancer – Heterogeneity Plasticity and Resistance to Therapies, Lille, France

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Magalie Haissaguerre Service d’Endocrinologie, Centre Hospitalier Universitaire, Hôpital du Haut Levêque, Pessac, France

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Lauriane Le Collen Endocrinology, Diabetology and Nutrition Unit, University Hospital of Reims, Reims, France
Inserm/CNRS UMR 1283/8199, Pasteur Institute of Lille, EGID, Lille, France

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Amira Mohamed Laboratory of Molecular Biology, Hospital La Conception, APHM, Marseille, France

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Marc Klein Service Endocrinologie, CHU de Nancy, Hôpital de Brabois, Vandoeuvre-lès-Nancy, France

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Marie-Françoise Odou CHU Lille, Service de Biochimie et Biologie Moléculaire ‘Hormonologie, Métabolisme-Nutrition, Oncologie’, Lille, France
Univ. Lille, Inserm, CHU Lille, U1286 – Infinite – Institute for Translational Research in Inflammation, Lille, France

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Antoine Tabarin Service d’Endocrinologie, Centre Hospitalier Universitaire, Hôpital du Haut Levêque, Pessac, France

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Hedia Brixi Department of Gastroenterology and Digestive Oncology, Reims University Hospital, Reims, France

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Thomas Cuny Aix Marseille Univ, APHM, INSERM, MMG, Department of Endocrinology, Hospital La Conception, Marseille, France

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Brigitte Delemer Endocrinology, Diabetology and Nutrition Unit, University Hospital of Reims, Reims, France

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Anne Barlier Aix Marseille Univ, APHM, INSERM, MMG, Laboratory of Molecular Biology Hospital La Conception, Marseille, France

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Pauline Romanet Aix Marseille Univ, APHM, INSERM, MMG, Laboratory of Molecular Biology Hospital La Conception, Marseille, France

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. The observed AF of the MEN1 AMVs correlated well with the expected AFs (correlation coefficient R 2 = 0.95 y = 0.8255*x + 0.3102, Fig. 1A ). Using the UMI-specific bioinformatic process, false positive MEN1 variants were detected in only 3 out of

Article Type:
Research Article
Collections:
Hormones and Cancer
DOI:
https://doi.org/10.1530/EC-22-0093
Volume/Issue:
Volume 11: Issue 11
Open access
Susana Pastor Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Abdelmounaim Akdi Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Eddy R González Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Juan Castell Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Josefina Biarnés Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Ricard Marcos Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Antonia Velázquez Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
Grup de Mutagènesi, CIBER Epidemiología y Salud Pública, Servei de Medicina Nuclear, Unidad de Endocrinología, Departament de Genètica i de Microbiologia, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain

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Valls J Iniesta R Moreno V . SNPStats: a web tool for the analysis of association studies . Bioinformatics 2006 22 1928 – 1929 . ( doi:10.1093/bioinformatics/btl268 ). 31 Barrett JC Fry B Maller J Daly MJ . Haploview: analysis and

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-12-0017
Volume/Issue:
Volume 1: Issue 2
Open access
Qinglei Yin Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Guangdong Geriatric Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

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Zhou Jin Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Yulin Zhou Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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Dalong Song Guangdong Geriatric Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
Reproductive Medicine Center, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

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Chenyang Fu Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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FengJiao Huang Reproductive Medicine Center, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
Division of Endocrinology, Department of Internal Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China

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Shu Wang Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

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combined analysis were performed using homemade scripts. Bioinformatics analysis Pathway analysis and gene ontology (GO) analysis were applied to explore the potential roles that the differentially expressed mRNAs play in a biological pathway or GO

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-20-0373
Volume/Issue:
Volume 9: Issue 12
Open access
Ja Hye Kim Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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Yunha Choi Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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Soojin Hwang Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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Ji-Hee Yoon Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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Jieun Lee Department of Pediatrics, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea

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Min Jae Kang Department of Pediatrics, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea

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Gu-Hwan Kim Medical Genetics Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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Han-Wook Yoo Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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Jin-Ho Choi Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

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testing of the ANOS1 gene To detect single nucleotide variants (SNVs), Sanger sequencing or NGS was performed. MLPA or chromosomal microarray was conducted for the detection of CNVs. Some CNVs were identified by bioinformatic algorithms for CNV

Article Type:
Research Article
Collections:
Pituitary and Hypothalamus
DOI:
https://doi.org/10.1530/EC-22-0413
Volume/Issue:
Volume 12: Issue 5
Open access
Anna-Pauliina Iivonen Institute of Biomedicine/Physiology, Biomedicum Helsinki and Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland

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Johanna Känsäkoski Institute of Biomedicine/Physiology, Biomedicum Helsinki and Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland

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Kirsi Vaaralahti Institute of Biomedicine/Physiology, Biomedicum Helsinki and Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland

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Taneli Raivio Institute of Biomedicine/Physiology, Biomedicum Helsinki and Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
New Children’s Hospital, Pediatric Research Center, Helsinki University Hospital, Helsinki, Finland

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bioinformatic analyses by using miRWalk 3.0 ( 10 , 11 ) and BLAT ( 12 ) and BLASTN ( 13 ) tools in Ensembl ( 14 ). Subjects and methods We studied a set of 19 KS and 5 normosmic cHH patients without previously found mutations in known cHH-causing genes

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0080
Volume/Issue:
Volume 8: Issue 5
Open access
Elisabet Einarsdottir Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland
Molecular Neurology Research Program, University of Helsinki, Helsinki, Finland
Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden

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Minna Pekkinen Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland
Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

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Kaarel Krjutškov Molecular Neurology Research Program, University of Helsinki, Helsinki, Finland
Competence Centre on Health Technologies, Tartu, Estonia

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Shintaro Katayama Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden

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Juha Kere Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland
Molecular Neurology Research Program, University of Helsinki, Helsinki, Finland
Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
School of Basic and Medical Biosciences, King’s College London, Guy’s Hospital, London, United Kingdom

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Outi Mäkitie Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland
Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden

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Heli Viljakainen Folkhälsan Institute of Genetics, University of Helsinki, Helsinki, Finland
Department of Food and Environmental Sciences, University of Helsinki, Helsinki, Finland

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pathway, from the DAVID bioinformatics portal ( https://david.ncifcrf.gov/ ). Genes significantly upregulated at the second time point in obese subjects receiving vitamin D are marked with a red star. Discussion In the present study, we

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-18-0537
Volume/Issue:
Volume 8: Issue 5
Open access
Kristian Almstrup Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark

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Hanne Frederiksen Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark

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Anna-Maria Andersson Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark

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Anders Juul Department of Growth and Reproduction, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health (EDMaRC), Rigshospitalet, University of Copenhagen, Copenhagen, Denmark

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.01.007 ) 23 Aryee MJ Jaffe AE Corrada-Bravo H Ladd-Acosta C Feinberg AP Hansen KD Irizarry RA . Minfi: a flexible and comprehensive Bioconductor package for the analysis of infinium DNA methylation microarrays . Bioinformatics 2014 30

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-20-0286
Volume/Issue:
Volume 9: Issue 8
Open access
Nathalia G B P Ferreira Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Joao L O Madeira Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Peter Gergics Laboratório de Sequenciamento em Larga Escala (SELA), Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil

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Renata Kertsz Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Juliana M Marques Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Nicholas S S Trigueiro Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Anna Flavia Figueredo Benedetti University of Michigan Medical School, Department of Human Genetics, Ann Arbor, Michigan, United States

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Bruna V Azevedo Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Bianca H V Fernandes Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil
Universidade de São Paulo, Zebrafish Facility, São Paulo, São Paulo, Brazil

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Debora D Bissegatto Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Isabela P Biscotto Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Qing Fang Laboratório de Sequenciamento em Larga Escala (SELA), Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil

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Qianyi Ma Laboratório de Sequenciamento em Larga Escala (SELA), Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil

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Asye B Ozel Laboratório de Sequenciamento em Larga Escala (SELA), Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil

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Jun Li Laboratório de Sequenciamento em Larga Escala (SELA), Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil

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Sally A Camper Laboratório de Sequenciamento em Larga Escala (SELA), Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil

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Alexander A L Jorge Unidade de Endocrinologia Genética, Laboratório de Endocrinologia Celular e Molecular LIM25, Disciplina de Endocrinologia da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil

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Berenice B Mendonça Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Ivo J P Arnhold Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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Luciani R Carvalho Unidade de Endocrinologia do Desenvolvimento, Laboratório de Hormônios e Genética Molecular LIM42, Disciplina de Endocrinologia, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil

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, Illumina’s DRAGEN copy number variation pipeline was used, which detects alteration from three contiguous exons ( 11 ). CDH2 variant effects on splicing were evaluated by bioinformatic analysis and cDNA amplification The web site https

Article Type:
Research Article
Collections:
Paediatric Endocrinology
DOI:
https://doi.org/10.1530/EC-22-0473
Volume/Issue:
Volume 12: Issue 8
Open access
Danielle Christine Maria van der Kaay Erasmus University Medical Center, Department of Pediatrics, Subdivision of Endocrinology, Rotterdam, Netherlands

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Anne Rochtus Department of Pediatric Endocrinology, University Hospitals Leuven, Leuven, Belgium

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Gerhard Binder University Children’s Hospital, Pediatric Endocrinology, University of Tübingen, Tübingen, Germany

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Ingo Kurth Institute of Human Genetics, Medical Faculty, RWTH Aachen University, Aachen, Germany

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Dirk Prawitt Center for Paediatrics and Adolescent Medicine, University Medical Center, Mainz, Germany

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Irène Netchine Sorbonne Université, Centre de Recherche Saint-Antoine, INSERM, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France

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Gudmundur Johannsson Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
Department of Endocrinology at Sahlgrenska University Hospital, Gothenburg, Sweden

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Anita C S Hokken-Koelega Erasmus University Medical Center, Department of Pediatrics, Subdivision of Endocrinology, Rotterdam, Netherlands

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Miriam Elbracht Institute of Human Genetics, Medical Faculty, RWTH Aachen University, Aachen, Germany

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Thomas Eggermann Institute of Human Genetics, Medical Faculty, RWTH Aachen University, Aachen, Germany

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analysis of specific genes, either based on a targeted enrichment or a targeted bioinformatics analysis of whole exome/genome data. The choice of genes might be leaned on https://panelapp.genomicsengland.co.uk/panels . 2 Decision on first-line test

Article Type:
Review Article
Collections:
Paediatric Endocrinology
DOI:
https://doi.org/10.1530/EC-22-0277
Volume/Issue:
Volume 11: Issue 11
Open access
Weiwei He School of Medicine, Xiamen University, Xiamen, China
Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Caoxin Huang Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Xiulin Shi Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China
Department of Endocrinology and Diabetes, The First Affiliated Hospital of Xiamen University, Xiamen, China

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Menghua Wu School of Medicine, Xiamen University, Xiamen, China
Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Han Li School of Medicine, Xiamen University, Xiamen, China
Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Qiuhong Liu School of Medicine, Xiamen University, Xiamen, China
Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Xiaofang Zhang Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Yan Zhao Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China

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Xuejun Li Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Fujian Provincial Key Laboratory of Translational Medicine for Diabetes, Xiamen, China
Department of Endocrinology and Diabetes, The First Affiliated Hospital of Xiamen University, Xiamen, China
Xiamen Clinical Medical Center for Endocrine and Metabolic Diseases, Xiamen Diabetes Prevention and Treatment Center, Xiamen, China

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, we tried to uncover those key regulators or transcription factor analyses for determining the functional change of aHSCs in NASH by two bioinformatic methods. Several key upstream regulators related to the functional changes of HSCs in NASH were

Article Type:
Research Article
Collections:
Metabolic Syndrome and Diabetes
DOI:
https://doi.org/10.1530/EC-22-0502
Volume/Issue:
Volume 12: Issue 2
Open access