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Lundkvist P, Grönberg A, Carlsson PO, Ludvigsson J, Espes D. Predictive biomarkers of rapidly developing insulin deficiency in children with type 1 diabetes. BMJ Open Diabetes Res Care 2024; 12:e003924. [PMID: 38413173 PMCID: PMC10900379 DOI: 10.1136/bmjdrc-2023-003924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 02/04/2024] [Indexed: 02/29/2024] Open
Abstract
INTRODUCTION The rate of progression to complete insulin deficiency varies greatly in type 1 diabetes. This constitutes a challenge, especially when randomizing patients in intervention trials aiming to preserve beta cell function. This study aimed to identify biomarkers predictive of either a rapid or slow disease progression in children with new-onset type 1 diabetes. RESEARCH DESIGN AND METHODS A retrospective, longitudinal cohort study of children (<18 years) with type 1 diabetes (N=46) was included at diagnosis and followed until complete insulinopenia (C-peptide <0.03 nmol/L). Children were grouped into rapid progressors (n=20, loss within 30 months) and slow progressors (n=26). A sex-matched control group of healthy children (N=45) of similar age was included for comparison. Multiple biomarkers were assessed by proximity extension assay (PEA) at baseline and follow-up. RESULTS At baseline, rapid progressors had lower C-peptide and higher autoantibody levels than slow. Three biomarkers were higher in the rapid group: carbonic anhydrase 9, corticosteroid 11-beta-dehydrogenase isozyme 1, and tumor necrosis factor receptor superfamily member 21. In a linear mixed model, 25 proteins changed over time, irrespective of group. One protein, a coxsackievirus B-adenovirus receptor (CAR) increased over time in rapid progressors. Eighty-one proteins differed between type 1 diabetes and healthy controls. Principal component analysis could not distinguish between rapid, slow, and healthy controls. CONCLUSIONS Despite differences in individual proteins, the combination of multiple biomarkers analyzed by PEA could not distinguish the rate of progression in children with new-onset type 1 diabetes. Only one marker was altered significantly when considering both time and group effects, namely CAR, which increased significantly over time in the rapid group. Nevertheless, we did find some markers that may be useful in predicting the decline of the C-peptide. Moreover, these could potentially be important for understanding type 1 diabetes pathogenesis.
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Affiliation(s)
- Per Lundkvist
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Annika Grönberg
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Per-Ola Carlsson
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden
| | - Johnny Ludvigsson
- Department of Biomedical and Clinical Sciences, Linköping University, Crown Princess Victoria Children's Hospital and Division of Pediatrics, Linköping, Sweden
| | - Daniel Espes
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Science for Life Laboratory, Department of Medical Cell Biology, Uppsala University, Uppsala, Sweden
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Ishikawa Y, Tanaka N, Asano Y, Kodera M, Shirai Y, Akahoshi M, Hasegawa M, Matsushita T, Saito K, Motegi SI, Yoshifuji H, Yoshizaki A, Kohmoto T, Takagi K, Oka A, Kanda M, Tanaka Y, Ito Y, Nakano K, Kasamatsu H, Utsunomiya A, Sekiguchi A, Niiro H, Jinnin M, Makino K, Makino T, Ihn H, Yamamoto M, Suzuki C, Takahashi H, Nishida E, Morita A, Yamamoto T, Fujimoto M, Kondo Y, Goto D, Sumida T, Ayuzawa N, Yanagida H, Horita T, Atsumi T, Endo H, Shima Y, Kumanogoh A, Hirata J, Otomo N, Suetsugu H, Koike Y, Tomizuka K, Yoshino S, Liu X, Ito S, Hikino K, Suzuki A, Momozawa Y, Ikegawa S, Tanaka Y, Ishikawa O, Takehara K, Torii T, Sato S, Okada Y, Mimori T, Matsuda F, Matsuda K, Amariuta T, Imoto I, Matsuo K, Kuwana M, Kawaguchi Y, Ohmura K, Terao C. GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region. Nat Commun 2024; 15:319. [PMID: 38296975 PMCID: PMC10830486 DOI: 10.1038/s41467-023-44541-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 12/18/2023] [Indexed: 02/02/2024] Open
Abstract
Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.
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Affiliation(s)
- Yuki Ishikawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Nao Tanaka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Rheumatology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yoshihide Asano
- Department of Dermatology, Tohoku University Graduate School of Medicine, Sendai, Japan
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Masanari Kodera
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yuichiro Shirai
- Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan
| | - Mitsuteru Akahoshi
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
- Department of Rheumatology, Saga University Hospital, Saga, Japan
| | - Minoru Hasegawa
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Takashi Matsushita
- Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | - Kazuyoshi Saito
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Sei-Ichiro Motegi
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hajime Yoshifuji
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ayumi Yoshizaki
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Tomohiro Kohmoto
- Aichi Cancer Center Research Institute, Division of Molecular Genetics, Nagoya, Japan
| | - Kae Takagi
- Tokyo Women's Medical University, Adachi Medical Center, Tokyo, Japan
| | - Akira Oka
- Department of Molecular Life Sciences, Division of Basic Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Japan
| | - Miho Kanda
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yoshihito Tanaka
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Yumi Ito
- Department of Dermatology, Chukyo Hospital, Japan Community Health Care Organization, Nagoya, Japan
| | - Kazuhisa Nakano
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Hiroshi Kasamatsu
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Akira Utsunomiya
- Faculty of Medical Sciences, Department of Dermatology, University of Fukui, Fukui, Japan
| | - Akiko Sekiguchi
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hiroaki Niiro
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Masatoshi Jinnin
- Department of Dermatology, Wakayama Medical University Graduate School of Medicine, Wakayama, Japan
| | - Katsunari Makino
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Takamitsu Makino
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Hironobu Ihn
- Department of Dermatology and Plastic Surgery, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - Motohisa Yamamoto
- Department of Rheumatology and Allergy, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Chisako Suzuki
- Department of Rheumatology and Clinical Immunology, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Hiroki Takahashi
- Department of Rheumatology and Clinical Immunology, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Emi Nishida
- Department of Geriatric and Environmental Dermatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Department of Dermatology, Okazaki City Hospital, Okazaki, Japan
| | - Akimichi Morita
- Department of Geriatric and Environmental Dermatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Toshiyuki Yamamoto
- Department of Dermatology, Fukushima Medical University, School of Medicine, Fukushima, Japan
| | - Manabu Fujimoto
- Department of Dermatology, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Yuya Kondo
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Daisuke Goto
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Takayuki Sumida
- Department of Rheumatology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Naho Ayuzawa
- Department of Clinical Immunology, National Hospital Organization, Utano National Hospital, Kyoto, Japan
| | - Hidetoshi Yanagida
- Department of Clinical Immunology, National Hospital Organization, Utano National Hospital, Kyoto, Japan
| | - Tetsuya Horita
- Faculty of Medicine and Graduate School of Medicine, Department of Rheumatology, Endocrinology and Nephrology, Hokkaido University, Sapporo, Japan
| | - Tatsuya Atsumi
- Faculty of Medicine and Graduate School of Medicine, Department of Rheumatology, Endocrinology and Nephrology, Hokkaido University, Sapporo, Japan
| | - Hirahito Endo
- Omori Medical Center, Toho University, Rheumatic Disease Center, Tokyo, Japan
| | - Yoshihito Shima
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Atsushi Kumanogoh
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Jun Hirata
- Immunology Frontier Center, Osaka University, Statistical Immunology, Osaka, Japan
| | - Nao Otomo
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Hiroyuki Suetsugu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Yoshinao Koike
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Kohei Tomizuka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Soichiro Yoshino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Xiaoxi Liu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Shuji Ito
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Keiko Hikino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Pharmacogenomics, Yokohama, Japan
| | - Akari Suzuki
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Autoimmune Diseases, Yokohama, Japan
| | - Yukihide Momozawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Genotyping Development, Yokohama, Japan
| | - Shiro Ikegawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Bone and Joint Diseases, Yokohama, Japan
| | - Yoshiya Tanaka
- The First Department of Internal Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan
| | - Osamu Ishikawa
- Department of Dermatology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kazuhiko Takehara
- Department of Dermatology, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan
| | | | - Shinichi Sato
- Department of Dermatology, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Immunology Frontier Center, Osaka University, Statistical Immunology, Osaka, Japan
| | - Tsuneyo Mimori
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Ijinkai Takeada General Hospital, Kyoto, Japan
| | - Fumihiko Matsuda
- Graduate School of Medicine, Kyoto University, Center for Genomic Medicine, Kyoto, Japan
| | - Koichi Matsuda
- Institute of Medical Science, The University of Tokyo, Laboratory of Genome Technology, Human Genome Center, Tokyo, Japan
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Tiffany Amariuta
- Center for Data Sciences, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Issei Imoto
- Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Keitaro Matsuo
- Aichi Cancer Center Research Institute, Division of Cancer Epidemiology and Prevention, Nagoya, Japan
| | - Masataka Kuwana
- Department of Allergy and Rheumatology, Nippon Medical School Graduate School of Medicine, Tokyo, Japan
| | - Yasushi Kawaguchi
- Tokyo Women's Medical University, Division of Rheumatology, Department of Internal Medicine, Tokyo, Japan
| | - Koichiro Ohmura
- Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Chikashi Terao
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan.
- Shizuoka General Hospital, The Clinical Research Center, Shizuoka, Japan.
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan.
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AlGeffari MA, Mansour D, Ahmed-Farid O, Mohamed Yousef E, Mohamed SA, Moustafa MMA, Barakat H, Abd El Ghany K. Lactiplantibacillus plantarum and Saussurea costus as Therapeutic Agents against a Diabetic Rat Model-Approaches to Investigate Pharmacophore Modeling of Human IkB Kinase and Molecular Interaction with Dehydrocostus Lactone of Saussurea costus. Metabolites 2023; 13:764. [PMID: 37367922 DOI: 10.3390/metabo13060764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/16/2023] [Accepted: 06/09/2023] [Indexed: 06/28/2023] Open
Abstract
Lactic acid bacteria is well-known as a vital strategy to alleviate or prevent diabetes. Similarly, the plant Saussurea costus (Falc) Lipsch is a preventive power against diabetes. Here, we aimed to determine whether lactic acid bacteria or Saussurea costus is more effective in treating a diabetic rat model in a comparative study manner. An in vivo experiment was conducted to test the therapeutic activity of Lactiplantibacillus plantarum (MW719476.1) and S. costus plants against an alloxan-induced diabetic rat model. Molecular, biochemical, and histological analyses were investigated to evaluate the therapeutic characteristics of different treatments. The high dose of S. costus revealed the best downregulated expression for the IKBKB, IKBKG, NfkB1, IL-17A, IL-6, IL-17F, IL-1β, TNF-α, TRAF6, and MAPK genes compared to Lactiplantibacillus plantarum and the control groups. The downregulation of IKBKB by S. costus could be attributed to dehydrocostus lactone as an active compound with proposed antidiabetic activity. So, we performed another pharmacophore modeling analysis to test the possible interaction between human IkB kinase beta protein and dehydrocostus lactone as an antidiabetic drug. Molecular docking and MD simulation data confirmed the interaction between human IkB kinase beta protein and dehydrocostus lactone as a possible drug. The target genes are important in regulating type 2 diabetes mellitus signaling, lipid and atherosclerosis signaling, NF-κB signaling, and IL-17 signaling pathways. In conclusion, the S. costus plant could be a promising source of novel therapeutic agents for treating diabetes and its complications. Dehydrocostus lactone caused the ameliorative effect of S. costus by its interaction with human IkB kinase beta protein. Further, future studies could be conducted to find the clinical efficacy of dehydrocostus lactone.
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Affiliation(s)
- Metab A AlGeffari
- Department of Family and Community Medicine, College of Medicine, Qassim University, Buraydah 51452, Saudi Arabia
- Diabetes Center, Medical City, Qassim University, Buraydah 51452, Saudi Arabia
| | - Dina Mansour
- Pharmacology Department, Medical Research and Clinical Studies Institute, National Research Centre, Giza 12622, Egypt
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Galala University, Attaka, Suez 43511, Egypt
| | - Omar Ahmed-Farid
- Department of Physiology, Egyptian Drug Authority, EL-Manial, Cairo 11511, Egypt
| | - Einas Mohamed Yousef
- Department of Histology and Cell Biology, Faculty of Medicine, Menoufia University, Shibin el Kom 32511, Egypt
| | - Shereen A Mohamed
- Department of Genetics and Genetic Engineering, Faculty of Agriculture, Benha University, Moshtohor 13736, Egypt
| | - Mahmoud M A Moustafa
- Department of Genetics and Genetic Engineering, Faculty of Agriculture, Benha University, Moshtohor 13736, Egypt
| | - Hassan Barakat
- Department of Food Science and Human Nutrition, College of Agriculture and Veterinary Medicine, Qassim University, Buraydah 51452, Saudi Arabia
- Food Technology Department, Faculty of Agriculture, Benha University, Moshtohor 13736, Egypt
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Derr AG, Arowosegbe A, Satish B, Redick SD, Qaisar N, Guo Z, Vanderleeden E, Trombly MI, Baer CE, Harlan DM, Greiner DL, Garber M, Wang JP. An Early Islet Transcriptional Signature Is Associated With Local Inflammation in Autoimmune Diabetes. Diabetes 2023; 72:261-274. [PMID: 36346618 PMCID: PMC9871196 DOI: 10.2337/db22-0521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 10/27/2022] [Indexed: 11/11/2022]
Abstract
Identifying the early islet cellular processes of autoimmune type 1 diabetes (T1D) in humans is challenging given the absence of symptoms during this period and the inaccessibility of the pancreas for sampling. In this article, we study temporal events in pancreatic islets in LEW.1WR1 rats, in which autoimmune diabetes can be induced with virus infection, by performing transcriptional analysis of islets harvested during the prediabetic period. Single-cell RNA-sequencing and differential expression analyses of islets from prediabetic rats reveal subsets of β- and α-cells under stress as evidenced by heightened expression, over time, of a transcriptional signature characterized by interferon-stimulated genes, chemokines including Cxcl10, major histocompatibility class I, and genes for the ubiquitin-proteasome system. Mononuclear phagocytes show increased expression of inflammatory markers. RNA-in situ hybridization of rat pancreatic tissue defines the spatial distribution of Cxcl10+ β- and α-cells and their association with CD8+ T cell infiltration, a hallmark of insulitis and islet destruction. Our studies define early islet transcriptional events during immune cell recruitment to islets and reveal spatial associations between stressed β- and α-cells and immune cells. Insights into such early processes can assist in the development of therapeutic and prevention strategies for T1D.
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Affiliation(s)
- Alan G. Derr
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
| | - Adediwura Arowosegbe
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Basanthi Satish
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Sambra D. Redick
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Natasha Qaisar
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Zhiru Guo
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Emma Vanderleeden
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Melanie I. Trombly
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Christina E. Baer
- Department of Microbiology and Physiological Systems, University of Massachusetts Chan Medical School, Worcester, MA
| | - David M. Harlan
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Dale L. Greiner
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Manuel Garber
- Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, MA
- Program in Bioinformatics and Integrative Medicine, University of Massachusetts Chan Medical School, Worcester, MA
| | - Jennifer P. Wang
- Diabetes Center of Excellence, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA
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Syed F, Singhal D, Raedschelders K, Krishnan P, Bone RN, McLaughlin MR, Van Eyk JE, Mirmira RG, Yang ML, Mamula MJ, Wu H, Liu X, Evans-Molina C. A discovery-based proteomics approach identifies protein disulphide isomerase (PDIA1) as a biomarker of β cell stress in type 1 diabetes. EBioMedicine 2023; 87:104379. [PMID: 36463755 PMCID: PMC9719098 DOI: 10.1016/j.ebiom.2022.104379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Stress responses within the β cell have been linked with both increased β cell death and accelerated immune activation in type 1 diabetes (T1D). At present, information on the timing and scope of these responses as well as disease-related changes in islet β cell protein expression during T1D development is lacking. METHODS Data independent acquisition-mass spectrometry was performed on islets collected longitudinally from NOD mice and NOD-SCID mice rendered diabetic through T cell adoptive transfer. FINDINGS In islets collected from female NOD mice at 10, 12, and 14 weeks of age, we found a time-restricted upregulation of proteins involved in stress mitigation and maintenance of β cell function, followed by loss of expression of protective proteins that heralded diabetes onset. EIF2 signalling and the unfolded protein response, mTOR signalling, mitochondrial function, and oxidative phosphorylation were commonly modulated pathways in both NOD mice and NOD-SCID mice rendered acutely diabetic by T cell adoptive transfer. Protein disulphide isomerase A1 (PDIA1) was upregulated in NOD islets and pancreatic sections from human organ donors with autoantibody positivity or T1D. Moreover, PDIA1 plasma levels were increased in pre-diabetic NOD mice and in the serum of children with recent-onset T1D compared to non-diabetic controls. INTERPRETATION We identified a core set of modulated pathways across distinct mouse models of T1D and identified PDIA1 as a potential human biomarker of β cell stress in T1D. FUNDING NIH (R01DK093954, DK127308, U01DK127786, UC4DK104166, R01DK060581, R01GM118470, and 5T32DK101001-09). VA Merit Award I01BX001733. JDRF (2-SRA-2019-834-S-B, 2-SRA-2018-493-A-B, 3-PDF-20016-199-A-N, 5-CDA-2022-1176-A-N, and 3-PDF-2017-385-A-N).
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Affiliation(s)
- Farooq Syed
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN, USA, 46202; Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, 1044 W Walnut St, Indianapolis, IN, USA, 46202
| | - Divya Singhal
- Department of Biochemistry and Molecular Biology, University of Calgary, 2500 University Drive NW, Alberta, Canada, T2N1N4
| | - Koen Raedschelders
- Advanced Clinical Biosystems Research Institute, Precision Health, Barbra Streisand Women's Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., Suite A9227, Los Angeles, CA, USA, 90048
| | - Preethi Krishnan
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN, USA, 46202; Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, 1044 W Walnut St, Indianapolis, IN, USA, 46202
| | - Robert N Bone
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN, USA, 46202; Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, 1044 W Walnut St, Indianapolis, IN, USA, 46202
| | - Madeline R McLaughlin
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN, USA, 46202
| | - Jennifer E Van Eyk
- Advanced Clinical Biosystems Research Institute, Precision Health, Barbra Streisand Women's Heart Center at the Smidt Heart Institute, Cedars-Sinai Medical Center, 127 S. San Vicente Blvd., Suite A9227, Los Angeles, CA, USA, 90048
| | - Raghavendra G Mirmira
- Kovler Diabetes Center, University of Chicago, 900 E 57th St, Chicago, IL, USA, 60637
| | - Mei-Ling Yang
- Department of Medicine, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, USA, 06510
| | - Mark J Mamula
- Department of Medicine, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, USA, 06510
| | - Huanmei Wu
- Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, 535 W. Michigan Street, Indianapolis, IN, USA, 46202; Department of Health Services Administration and Policy, Temple University College of Public Health, 1101 W. Montgomery Ave, Philadelphia, PA, USA, 19122
| | - Xiaowen Liu
- Deming Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, USA, 70112
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, 635 Barnhill Drive, Indianapolis, IN, USA, 46202; Department of Pediatrics and the Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, 1044 W Walnut St, Indianapolis, IN, USA, 46202; Department of Medicine, Indiana University School of Medicine, 340 W 10th St, Indianapolis, IN, USA, 46202; Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Dr, Indianapolis, IN, USA, 46202; Richard L. Roudebush VA Medical Center, Indiana University School of Informatics and Computing, 1481 W 10th St, Indianapolis, IN, USA, 46202.
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García-Pérez R, Ramirez JM, Ripoll-Cladellas A, Chazarra-Gil R, Oliveros W, Soldatkina O, Bosio M, Rognon PJ, Capella-Gutierrez S, Calvo M, Reverter F, Guigó R, Aguet F, Ferreira PG, Ardlie KG, Melé M. The landscape of expression and alternative splicing variation across human traits. CELL GENOMICS 2022; 3:100244. [PMID: 36777183 PMCID: PMC9903719 DOI: 10.1016/j.xgen.2022.100244] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/08/2022] [Accepted: 12/07/2022] [Indexed: 12/31/2022]
Abstract
Understanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as drivers of gene expression and alternative splicing variation across 46 human tissues and 781 individuals from the Genotype-Tissue Expression project. We demonstrate that ancestry, sex, age, and BMI make additive and tissue-specific contributions to expression variability, whereas interactions are rare. Variation in splicing is dominated by ancestry and is under genetic control in most tissues, with ribosomal proteins showing a strong enrichment of tissue-shared splicing events. Our analyses reveal a systemic contribution of types 1 and 2 diabetes to tissue transcriptome variation with the strongest signal in the nerve, where histopathology image analysis identifies novel genes related to diabetic neuropathy. Our multi-tissue and multi-trait approach provides an extensive characterization of the main drivers of human transcriptome variation in health and disease.
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Affiliation(s)
- Raquel García-Pérez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Jose Miguel Ramirez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Aida Ripoll-Cladellas
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Ruben Chazarra-Gil
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Winona Oliveros
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Oleksandra Soldatkina
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Mattia Bosio
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Paul Joris Rognon
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain,Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Catalonia 08005, Spain,Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Catalonia 08034, Spain
| | - Salvador Capella-Gutierrez
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain
| | - Miquel Calvo
- Statistics Section, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain
| | - Ferran Reverter
- Statistics Section, Faculty of Biology, Universitat de Barcelona (UB), Barcelona, Catalonia 08028, Spain
| | - Roderic Guigó
- Bioinformatics and Genomics, Center for Genomic Regulation, Barcelona, Catalonia 08003, Spain
| | | | - Pedro G. Ferreira
- Department of Computer Science, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal,Laboratory of Artificial Intelligence and Decision Support, INESC TEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal,Institute of Molecular Pathology and Immunology of the University of Porto, Institute for Research and Innovation in Health (i3s), R. Alfredo Allen 208, 4200-135 Porto, Portugal
| | | | - Marta Melé
- Department of Life Sciences, Barcelona Supercomputing Center (BCN-CNS), Barcelona, Catalonia 08034, Spain,Corresponding author
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Martínez-Ramírez OC, Salazar-Piña A, Cerón-Ramírez X, Rubio-Lightbourn J, Torres-Romero F, Casas-Avila L, Castro-Hernández C. Effect of Inulin Intervention on Metabolic Control and Methylation of INS and IRS1 Genes in Patients with Type 2 Diabetes Mellitus. Nutrients 2022; 14:nu14235195. [PMID: 36501225 PMCID: PMC9737482 DOI: 10.3390/nu14235195] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/25/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND AND AIMS Currently, treatments are being sought to improve the control of type II diabetes mellitus (T2DM), and inulin has been shown to be effective in reducing glucose levels and other metabolic control parameters. These effects on metabolic control may be associated with changes in the epigenetic modulation of genes of the insulin pathway. Therefore, our objective is to determine the effect of agave inulin in metabolic control parameters and in INS and IRS1 genes' methylation in T2DM patients. METHODS This was a longitudinal experimental study with 67 Mexican participants who received an intervention of inulin agave (10 g daily) for 2 months. The methylation of the INS and IRS1 genes was determined by MSP. RESULTS For the INS gene, we found a significant decrease in the proportions of T2DM patients with methylated DNA after inulin intervention (p = 0.0001). In contrast, the difference in the proportions of the unmethylated IRS1 gene before and after the inulin intervention was not significant (p = 0.79). On the other hand, we observed changes in the number of T2DM patients' recommended categories for metabolic control depending on the methylation of INS and IRS1 genes before and after treatment with inulin. CONCLUSION For the first time, we report the modification in the methylation of two genes, INS and IRS1, of the insulin pathway and provide information on the possible relevant role of epigenetics as a key factor in positive changes in metabolic control parameters by inulin intake in T2DM patients.
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Affiliation(s)
- Ollin Celeste Martínez-Ramírez
- Facultad de Nutrición, Universidad Autónoma del Estado de Morelos, Cuernavaca C.P. 62350, Morelos, Mexico
- Correspondence:
| | - Azucena Salazar-Piña
- Facultad de Nutrición, Universidad Autónoma del Estado de Morelos, Cuernavaca C.P. 62350, Morelos, Mexico
| | - Ximena Cerón-Ramírez
- Facultad de Nutrición, Universidad Autónoma del Estado de Morelos, Cuernavaca C.P. 62350, Morelos, Mexico
| | - Julieta Rubio-Lightbourn
- Departamento de Medicina Genómica y Toxicología Ambiental, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Ciudad de México C.P. 04510, Mexico
| | - Fernando Torres-Romero
- Facultad de Nutrición, Universidad Autónoma del Estado de Morelos, Cuernavaca C.P. 62350, Morelos, Mexico
| | - Leonora Casas-Avila
- Laboratorio de Medicina Genómica, Instituto Nacional de Rehabilitación, Ciudad de Mexico C.P. 14389, Mexico
| | - Clementina Castro-Hernández
- Unidad de Investigación Biomédica en Cáncer, Instituto Nacional de Cancerología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Ciudad de México C.P. 14080, Mexico
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8
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Wang JH, Wong RCB, Liu GS. Retinal Transcriptome and Cellular Landscape in Relation to the Progression of Diabetic Retinopathy. Invest Ophthalmol Vis Sci 2022; 63:26. [PMID: 36006018 PMCID: PMC9424969 DOI: 10.1167/iovs.63.9.26] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Purpose Previous studies that identify putative genes associated with diabetic retinopathy are only focusing on specific clinical stages, thus resulting genes are not necessarily reflective of disease progression. This study identified genes associated with the severity level of diabetic retinopathy using the likelihood-ratio test (LRT) and ordinal logistic regression (OLR) model, as well as to profile immune and retinal cell landscape in progressive diabetic retinopathy using a machine learning deconvolution approach. Methods This study used a published transcriptomic dataset (GSE160306) from macular regions of donors with different degrees of diabetic retinopathy (10 healthy controls, 10 cases of diabetes, 9 cases of nonproliferative diabetic retinopathy, and 10 cases of proliferative diabetic retinopathy or combined with diabetic macular edema). LRT and OLR models were applied to identify severity-associated genes. In addition, CIBERSORTx was used to estimate proportional changes of immune and retinal cells in progressive diabetic retinopathy. Results By controlling for gender and age using LRT and OLR, 50 genes were identified to be significantly increased in expression with the severity of diabetic retinopathy. Functional enrichment analyses suggested these severity-associated genes are related to inflammation and immune responses. CCND1 and FCGR2B are further identified as key regulators to interact with many other severity-associated genes and are crucial to inflammation. Deconvolution analyses demonstrated that the proportions of memory B cells, M2 macrophages, and Müller glia were significantly increased with the progression of diabetic retinopathy. Conclusions These findings demonstrate that deep analyses of transcriptomic data can advance our understanding of progressive ocular diseases, such as diabetic retinopathy, by applying LRT and OLR models as well as bulk gene expression deconvolution.
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Affiliation(s)
- Jiang-Hui Wang
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, East Melbourne, Victoria, Australia
| | - Raymond C B Wong
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, East Melbourne, Victoria, Australia
| | - Guei-Sheung Liu
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, East Melbourne, Victoria, Australia.,Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.,Aier Eye Institute, Changsha, Hunan, China
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9
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De Silva K, Demmer RT, Jönsson D, Mousa A, Forbes A, Enticott J. Highly perturbed genes and hub genes associated with type 2 diabetes in different tissues of adult humans: a bioinformatics analytic workflow. Funct Integr Genomics 2022; 22:1003-1029. [PMID: 35788821 PMCID: PMC9255467 DOI: 10.1007/s10142-022-00881-5] [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: 05/09/2021] [Revised: 06/19/2022] [Accepted: 06/24/2022] [Indexed: 11/28/2022]
Abstract
Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.
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Affiliation(s)
- Kushan De Silva
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, 3168, Australia.
| | - Ryan T Demmer
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.,Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Daniel Jönsson
- Department of Periodontology, Faculty of Odontology, Malmö University, 21119, Malmö, Sweden.,Department of Clinical Sciences, Lund University, 21428, Malmö, Sweden
| | - Aya Mousa
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, 3168, Australia
| | - Andrew Forbes
- Biostatistics Unit, Division of Research Methodology, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Melbourne, 3004, Australia
| | - Joanne Enticott
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, 3168, Australia
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10
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Yip L, Alkhataybeh R, Taylor C, Fuhlbrigge R, Fathman CG. Identification of Novel Disease-Relevant Genes and Pathways in the Pathogenesis of Type 1 Diabetes: A Potential Defect in Pancreatic Iron Homeostasis. Diabetes 2022; 71:1490-1507. [PMID: 35499603 PMCID: PMC9233262 DOI: 10.2337/db21-0948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 04/06/2022] [Indexed: 11/13/2022]
Abstract
Multiple pathways contribute to the pathophysiological development of type 1 diabetes (T1D); however, the exact mechanisms involved are unclear. We performed differential gene expression analysis in pancreatic islets of NOD mice versus age-matched congenic NOD.B10 controls to identify genes that may contribute to disease pathogenesis. Novel genes related to extracellular matrix development and glucagon and insulin signaling/secretion were changed in NOD mice during early inflammation. During "respective" insulitis, the expression of genes encoding multiple chemosensory olfactory receptors were upregulated, and during "destructive" insulitis, the expression of genes involved in antimicrobial defense and iron homeostasis were downregulated. Islet inflammation reduced the expression of Hamp that encodes hepcidin. Hepcidin is expressed in β-cells and serves as the key regulator of iron homeostasis. We showed that Hamp and hepcidin levels were lower, while iron levels were higher in the pancreas of 12-week-old NOD versus NOD.B10 mice, suggesting that a loss of iron homeostasis may occur in the islets during the onset of "destructive" insulitis. Interestingly, we showed that the severity of NOD disease correlates with dietary iron intake. NOD mice maintained on low-iron diets had a lower incidence of hyperglycemia, while those maintained on high-iron diets had an earlier onset and higher incidence of disease, suggesting that high iron exposure combined with a loss of pancreatic iron homeostasis may exacerbate NOD disease. This mechanism may explain the link seen between high iron exposure and the increased risk for T1D in humans.
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11
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Ahmed SS, Al Nohair SF, Abdulmonem WA, Alhomaidan HT, Rasheed N, Ismail MS, Albatanony MA, Rasheed Z. Honey polyphenolic fraction inhibits cyclooxygenase-2 expression via upregulation of microRNA-26a-5p expression in pancreatic islets. EUR J INFLAMM 2022. [DOI: 10.1177/20587392221076473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Objectives Honey total polyphenolic fraction (HTPF) is reported to have anti-disease potential, however the role of HTPF in the regulation of microRNAs (miRNAs) has never been investigated. This study was undertaken to investigate the potential of HTPF against inflammation via regulation of miRNAs in pancreatic islets of Langerhans. Methods Pancreatic islets were isolated from C57BL/6 mice and HTPF was purified from honey. Bioinformatics algorithms were used to determine miRNA target genes. Expression of miRNA and mRNA was determined using their specific taqman assays. Pairing between miRNA and 3′ untranslated region (3′UTR) of mRNA was confirmed using luciferase reporter clone containing the 3′UTR of mRNA sequences and results were verified by transfection of mouse pancreatic β-cell line Min6 with miRNA inhibitors. Results The data showed that mmu-miR-26a-5p is a direct regulator of cyclooxygenase-2 (COX-2) expression and HTPF inhibits COX-2 expression or prostaglandin E2 (PGE2) production via up-regulating mmu-miR-26a-5p expression. Transfection of islets with anti-miR-26a-5p significantly enhanced COX-2 expression and PGE2 production ( p < .01), while HTPF treatment significantly inhibited anti-miR-26a-5p transfection-induced COX-2 expression or PGE2 production ( p < .05). These findings were further verified in pancreatic β-cells Min6. Moreover, the data also determined that HTPF also inhibits glucose-induced nuclear transcription factor (NF)-κB activity. Conclusion HTPF suppresses glucose-induced PGE2 production and activation of NF-κB via negative regulation of COX-2 and mmu-miR26a-5p. These novel pharmacological actions of HTPF on glucose-stimulated pancreatic islets provide new suggestions that HTPF or HTPF-derived compounds inhibit glucose induced inflammation in pancreas by up-regulating the expression of microRNAs.
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Affiliation(s)
- Syed Suhail Ahmed
- Department of Medical Microbiology, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Sultan Fahad Al Nohair
- Department of Family and Community Medicine, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Waleed Al Abdulmonem
- Department of Pathology, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Homaidan T Alhomaidan
- Department of Family and Community Medicine, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Naila Rasheed
- Department of Medical Biochemistry, College of Medicine, Qassim University, Buraidah, Saudi Arabia
| | - Mohamed S Ismail
- Department of Nutrition and Food Sciences, Menoufia University, Shebin El-Kom, Egypt
| | - Manal A Albatanony
- Department of Family Medicine, College of Medicine, Qassim University, Unaizah, Saudi Arabia
| | - Zafar Rasheed
- Department of Medical Biochemistry, College of Medicine, Qassim University, Buraidah, Saudi Arabia
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12
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Chen Y, Shen M, Ji C, Huang Y, Shi Y, Ji L, Qin Y, Gu Y, Fu Q, Chen H, Xu K, Yang T. Genome-Wide Identification of N6-Methyladenosine Associated SNPs as Potential Functional Variants for Type 1 Diabetes. Front Endocrinol (Lausanne) 2022; 13:913345. [PMID: 35784577 PMCID: PMC9243540 DOI: 10.3389/fendo.2022.913345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES N6-methyladenosine (m6A) is essential in the regulation of the immune system, but the role that its single nucleotide polymorphisms (SNPs) play in the pathogenesis of type 1 diabetes (T1D) remains unknown. This study demonstrated the association between genetic variants in m6A regulators and T1D risk based on a case-control study in a Chinese population. METHODS The tagging SNPs in m6A regulators were genotyped in 1005 autoantibody-positive patients with T1D and 1257 controls using the Illumina Human OmniZhongHua-8 platform. Islet-specific autoantibodies were examined by radioimmunoprecipitation in all the patients. The mixed-meal glucose tolerance test was performed on 355 newly diagnosed patients to evaluate their residual islet function. The functional annotations for the identified SNPs were performed in silico. Using 102 samples from a whole-genome expression microarray, key signaling pathways associated with m6A regulators in T1D were comprehendingly evaluated. RESULTS Under the additive model, we observed three tag SNPs in the noncoding region of the PRRC2A (rs2260051, rs3130623) and YTHDC2 (rs1862315) gene are associated with T1D risk. Although no association was found between these SNPs and islet function, patients carrying risk variants had a higher positive rate for ZnT8A, GADA, and IA-2A. Further analyses showed that rs2260051[T] was associated with increased expression of PRRC2A mRNA (P = 7.0E-13), and PRRC2A mRNA was significantly higher in peripheral blood mononuclear cell samples from patients with T1D compared to normal samples (P = 0.022). Enrichment analyses indicated that increased PRRC2A expression engages in the most significant hallmarks of cytokine-cytokine receptor interaction, cell adhesion and chemotaxis, and neurotransmitter regulation pathways. The potential role of increased PRRC2A in disrupting immune homeostasis is through the PI3K/AKT pathway and neuro-immune interactions. CONCLUSION This study found intronic variants in PRRC2A and YTHDC2 associated with T1D risk in a Chinese Han population. PRRC2A rs2260051[T] may be implicated in unbalanced immune homeostasis by affecting the expression of PRRC2A mRNA. These findings enriched our understanding of m6A regulators and their intronic SNPs that underlie the pathogenesis of T1D.
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Affiliation(s)
- Yang Chen
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Min Shen
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Chen Ji
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yanqian Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yun Shi
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Li Ji
- Department of Emergency Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yao Qin
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yong Gu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Qi Fu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Heng Chen
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kuanfeng Xu
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Tao Yang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Tao Yang,
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13
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Watase C, Fuse M, Ino Y, Naito C, Hiraoka N. Novel insights into immunohistochemical analysis for diagnosing serous neoplasm of the pancreas: aquaporin 1, stereocilin, and transmembrane protein 255B. Histopathology 2021; 79:872-879. [PMID: 34288030 DOI: 10.1111/his.14456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 07/08/2021] [Accepted: 07/18/2021] [Indexed: 11/26/2022]
Abstract
AIMS Serous (cystic) neoplasm (SCN) of the pancreas is generally benign, and surgical treatment is recommended in only a limited number of cases. To avoid unnecessary surgery, an accurate diagnosis of SCN is essential. In the present study, we aimed to identify new immunohistochemical markers with which to distinguish SCN from other tumours. METHODS AND RESULTS We compared the comprehensive gene expression profiles of SCN with those of normal pancreas and pancreatic ductal adenocarcinoma (PDAC). We selected the candidate molecules that were up-regulated in SCN, were minimally expressed or unexpressed in PDAC, and had specific and available antibodies suitable for immunohistochemistry, and then analysed their immunohistochemical expression in various tumours. We selected aquaporin 1 (AQP1), stereocilin (STRC), fibroblast growth factor receptor 3 (FGFR3), and transmembrane protein 255B (TMEM255B), which were diffusely expressed in SCN cells in 79%, 100%, 100% and 100% of SCN cases. AQP1 was not expressed in other tumours, except in 20% of mucinous cystic neoplasms (MCNs) and 19% of PDACs. STRC was rarely expressed in MCNs, neuroendocrine neoplasms (NENs), and PDACs. FGFR3 was expressed in 31% of intraductal papillary mucinous neoplasms (IPMNs), 50% of intraductal oncocytic papillary neoplasms, 40% of NENs, 30% of acinar cell carcinomas, 40% of solid pseudopapillary neoplasms, and 52% of PDACs. TMEM255B was not expressed in the other tumours, except in 50% of MCNs, 80% of gastric-subtype IPMNs, and 29% of PDACs. All antigens were usually expressed in a small proportion of cells when they were positive in tumours other than SCN. CONCLUSIONS These findings indicate that AQP1 and STRC, and potentially TMEM255B, may act as SCN markers.
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Affiliation(s)
- Chikashi Watase
- Division of Molecular Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Analytical Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Molecular Oncology, Graduate School of Medicine, Jikei University, Tokyo, Japan
| | - Masanori Fuse
- Division of Molecular Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Analytical Pathology, National Cancer Centre Research Institute, Tokyo, Japan
| | - Yoshinori Ino
- Division of Molecular Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Analytical Pathology, National Cancer Centre Research Institute, Tokyo, Japan
| | - Chie Naito
- Division of Molecular Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Analytical Pathology, National Cancer Centre Research Institute, Tokyo, Japan
| | - Nobuyoshi Hiraoka
- Division of Molecular Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Analytical Pathology, National Cancer Centre Research Institute, Tokyo, Japan
- Department of Molecular Oncology, Graduate School of Medicine, Jikei University, Tokyo, Japan
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