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A H Ludwig-Slomczynska Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Krakow, Poland

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S Borys Department of Metabolic Diseases, Jagiellonian University Medical College
University Hospital, Krakow, Poland

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M T Seweryn Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Krakow, Poland

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J Hohendorff Department of Metabolic Diseases, Jagiellonian University Medical College
University Hospital, Krakow, Poland

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P Kapusta Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Krakow, Poland

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B Kiec-Wilk Department of Metabolic Diseases, Jagiellonian University Medical College
University Hospital, Krakow, Poland

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E Pitera Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Krakow, Poland

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P P Wolkow Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Krakow, Poland

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M T Malecki Department of Metabolic Diseases, Jagiellonian University Medical College
University Hospital, Krakow, Poland

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following extension and staining. Imaging was performed using HiScan (Illumina, USA). Bioinformatics and statistical analysis For analysis of the characteristics of the study groups, we used Statistica Software v. 12.0 (StatSoft, Tulsa, OK, USA). The

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0373
Volume/Issue:
Volume 8: Issue 11
Open access
Jia Li Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China
Department of Electronic Science, State Key Laboratory of Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, China

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Yan Zhao Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China

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Caoxin Huang Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China

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Zheng Chen Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China

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Xiulin Shi Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China

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Long Li Institute of Drug Discovery Technology, Ningbo University, Ningbo, China

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Zhong Chen Department of Electronic Science, State Key Laboratory of Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, China

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Xuejun Li Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China

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), ceramides and related sphingolipids can interfere with insulin signaling ( 26 ), which suggests that they are important players in NAFLD. Bioinformatics strategies and gene array analyses have demonstrated a strong association between the hepatic ceramide

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0023
Volume/Issue:
Volume 8: Issue 4
Open access
Lilit Egshatyan ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Daria Kashtanova ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Anna Popenko ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Olga Tkacheva ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Alexander Tyakht ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Dmitry Alexeev ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Natalia Karamnova ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Elena Kostryukova ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Vladislav Babenko ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Maria Vakhitova ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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Sergey Boytsov ‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation

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://ngs.biodiv.tw/NGSCore/wp-content/uploads/application%20forms/16s-metagenomic-library-prep-guide-15044223-b.pdf ) using the Nextera XT Index Kit (Illumina) with a dual indexing strategy. Bioinformatic processing Quality reads filtering and taxonomic classification were performed using QIIME Software (12

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-15-0094
Volume/Issue:
Volume 5: Issue 1
Open access
Roberto Cosimo Melcangi Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy

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Livio Casarini Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Center for Genomic Research, University of Modena and Reggio Emilia, Modena, Italy

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Marco Marino Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Center for Genomic Research, University of Modena and Reggio Emilia, Modena, Italy

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Daniele Santi Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Department of Medical Specialties, Azienda Ospedaliero-Universitaria di Modena, Modena, Italy

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Samantha Sperduti Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Center for Genomic Research, University of Modena and Reggio Emilia, Modena, Italy

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Silvia Giatti Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy

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Silvia Diviccaro Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy

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Maria Grimoldi Neurology Division, Papa Giovanni XXIII Hospital, Bergamo, Italy

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Donatella Caruso Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy

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Guido Cavaletti Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano Bicocca, Monza, Italy

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Manuela Simoni Unit of Endocrinology, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Center for Genomic Research, University of Modena and Reggio Emilia, Modena, Italy
Department of Medical Specialties, Azienda Ospedaliero-Universitaria di Modena, Modena, Italy

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Urology 2015 194 . ( https://doi.org/10.1016/j.juro.2015.04.079 ) 33 Li LC Dahiya R . MethPrimer: designing primers for methylation PCRs . Bioinformatics 2002 18 . ( https://doi.org/10.1093/bioinformatics/18.11.1427 ) 34 Misawa Y

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0199
Volume/Issue:
Volume 8: Issue 8
Open access
Lukas Plachy Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Lenka Petruzelkova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Petra Dusatkova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Klara Maratova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Dana Zemkova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Lenka Elblova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Vit Neuman Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Stanislava Kolouskova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Barbora Obermannova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Marta Snajderova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Zdenek Sumnik Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Jan Lebl Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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Stepanka Pruhova Department of Pediatrics, 2nd Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic

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M Meyer R & Massouras A . VarSome: the human genomic variant search engine . Bioinformatics 2019 35 1978 – 1980 . ( https://doi.org/10.1093/bioinformatics/bty897 ) 26 Jarvik GP & Browning BL . Consideration of cosegregation in the

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Collections:
Paediatric Endocrinology
DOI:
https://doi.org/10.1530/EC-23-0238
Volume/Issue:
Volume 12: Issue 10
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Yi Wang Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Yingying Xu Department of Pediatrics, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

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Rongrong Xie Department of Endocrinology, Children’s Hospital of Soochow University, Suzhou, China

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Bingyan Cao Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Yuan Ding Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Jiayun Guo Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Xiaoqiao Li Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Xiaolin Ni Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Zheng Yuan Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Linqi Chen Department of Endocrinology, Children’s Hospital of Soochow University, Suzhou, China

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Liyang Liang Department of Pediatrics, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

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Chunxiu Gong Department of Endocrinology, Genetics and Metabolism, Beijing Children’s Hospital, Capital Medical University, Beijing, China
National Center for Children’s Health, Beijing, China

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Mygenostics co., LTD, Beijing, China) includes three steps: DNA Library Preparation, targeted genes enrichment and sequencing, and bioinformatics analysis. Approximately 2 mL peripheral blood (EDTA anticoagulant) of the patients and their parents was collected

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Collections:
Pituitary and Hypothalamus
DOI:
https://doi.org/10.1530/EC-24-0189
Volume/Issue:
Volume 13: Issue 11
Open access
Qiuli Liu Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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Lin-ang Wang Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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Jian Su Department of Urology, Affiliated Hospital of Nanjing University of Traditional Chinese Medical, Nanjing, People’s Republic of China

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Dali Tong Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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Weihua Lan Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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Luofu Wang Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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Gaolei Liu Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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Jun Zhang Department of Obstetrics, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of China

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Victor Wei Zhang Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
AmCare Genomics Lab, Guangzhou, People’s Republic of China

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Dianzheng Zhang Department of Bio-Medical Sciences, Philadelphia College of Osteopathic Medicine, Philadelphia, Pennsylvania, USA

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Rongrong Chen Geneplus-Beijing Institute, Beijing, People’s Republic of China

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Qingyi Zhu Department of Urology, Affiliated Hospital of Nanjing University of Traditional Chinese Medical, Nanjing, People’s Republic of China

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Jun Jiang Department of Urology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, People’s Republic of China

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length according to the manufactory’s specification. The bioinformatics analysis was performed with in-house pipeline to identify rare or novel variants with Gnomad, HMGD, ClinVar, dbSNP for filtering and computational prediction algorithms, PolyPhen-2

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-18-0273
Volume/Issue:
Volume 7: Issue 11
Open access
Yu Lin State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Yingying Zhang State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Lei Xu Maternal and Child Health Care Hospital of Dongchangfu District, Liaocheng, People’s Republic of China

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Wei Long State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Chunjian Shan State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Hongjuan Ding State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Lianghui You State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Chun Zhao State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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Zhonghua Shi State Key Laboratory of Reproductive Medicine, Women’s Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, People’s Republic of China

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transcription position bioinformatic anaylsis and found RP11 sites located within pleckstrin homology-like domain, family A, member 1 (PHLDA1) ( Fig. 5A ). We also examined the expression of PHLDA1 in RP11-overexpressed adipocytes. However, the expression of

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-20-0584
Volume/Issue:
Volume 10: Issue 2
Open access
Zi-Di Xu Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Wei Zhang Department of Children Health Care, Xiamen Maternal and Child Health Hospital, Xiamen, China

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Min Liu Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Huan-Min Wang Department of Surgical Oncology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Pei-Pei Hui Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Xue-Jun Liang Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Jie Yan Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Yu-Jun Wu Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Yan-Mei Sang Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Cheng Zhu Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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Gui-Chen Ni Department of Pediatric Endocrinology, Genetic and Metabolism, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

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, bioinformatics analysis software predicted that it may have pathogenicity. The child had a normal birth weight, had onset on day one after birth, and was effective in the treatment of diazoxide. The clinical characteristics were consistent with the clinical

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-18-0240
Volume/Issue:
Volume 7: Issue 12
Open access
Lian Hollander-Cohen Department of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot, Israel

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Benjamin Böhm Department of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot, Israel

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Krist Hausken Department of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot, Israel

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Berta Levavi-Sivan Department of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot, Israel

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. The rapid generation of mutation data matrices from protein sequences . Computer Applications in the Biosciences 1992 275 – 282 . ( https://doi.org/10.1093/bioinformatics/8.3.275 ) 6 Kumar S Stecher G Tamura K . MEGA7: molecular

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Research Article
DOI:
https://doi.org/10.1530/EC-19-0389
Volume/Issue:
Volume 8: Issue 11
Open access