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Wu Y, Feng X, Li M, Hu Z, Zheng Y, Chen S, Luo H. Gut microbiota associated with appetite suppression in high-temperature and high-humidity environments. EBioMedicine 2024; 99:104918. [PMID: 38103514 PMCID: PMC10765014 DOI: 10.1016/j.ebiom.2023.104918] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 11/22/2023] [Accepted: 12/01/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Food is crucial for maintaining vital human and animal activities. Disorders in appetite control can lead to various metabolic disturbances. Alterations in the gut microbial composition can affect appetite and energy metabolism. While alterations in the gut microbiota have been observed in high-temperature and high-humidity (HTH) environments, the relationship between the gut microbiota during HTH and appetite remains unclear. METHODS We utilised an artificial climate box to mimic HTH environments, and established a faecal bacteria transplantation (FMT) mouse model. Mendelian randomisation (MR) analysis was used to further confirm the causal relationship between gut microbiota and appetite or appetite-related hormones. FINDINGS We found that, in the eighth week of exposure to HTH environments, mice showed a decrease in food intake and body weight, and there were significant changes in the intestinal microbiota compared to the control group. After FMT, we observed similar changes in food intake, body weight, and gut bacteria. Appetite-related hormones, including ghrelin, glucagon-like peptide-1, and insulin, were reduced in DH (mice exposed to HTH conditions) and DHF (FMT from mice exposed to HTH environments for 8 weeks), while the level of peptide YY initially increased and then decreased in DH and increased after FMT. Moreover, MR analysis further confirmed that these changes in the intestinal microbiota could affect appetite or appetite-related hormones. INTERPRETATION Together, our data suggest that the gut microbiota is closely associated with appetite suppression in HTH. These findings provide novel insights into the effects of HTH on appetite. FUNDING This work was supported by the National Natural Science Foundation of China and Guangzhou University of Chinese Medicine.
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Affiliation(s)
- Yalan Wu
- Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangzhou, China
| | - Xiangrong Feng
- Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangzhou, China
| | - Mengjun Li
- Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangzhou, China
| | - Zongren Hu
- Department of Rehabilitation and Healthcare, Hunan University of Medicine, Hunan, China
| | - Yuhua Zheng
- Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangzhou, China
| | - Song Chen
- Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, China.
| | - Huanhuan Luo
- Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangzhou, China; State Key Laboratory of Traditional Chinese Medicine Syndrome, Guangzhou University of Chinese Medicine, Guangzhou, China.
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Liu TY, Liao CC, Chang YS, Chen YC, Chen HD, Lai IL, Peng CY, Chung CC, Chou YP, Tsai FJ, Jeng LB, Chang JG. Identification of 13 Novel Loci in a Genome-Wide Association Study on Taiwanese with Hepatocellular Carcinoma. Int J Mol Sci 2023; 24:16417. [PMID: 38003606 PMCID: PMC10671380 DOI: 10.3390/ijms242216417] [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: 10/02/2023] [Revised: 11/09/2023] [Accepted: 11/10/2023] [Indexed: 11/26/2023] Open
Abstract
Liver cancer is caused by complex interactions among genetic factors, viral infection, alcohol abuse, and metabolic diseases. We conducted a genome-wide association study and polygenic risk score (PRS) model in Taiwan, employing a nonspecific etiology approach, to identify genetic risk factors for hepatocellular carcinoma (HCC). Our analysis of 2836 HCC cases and 134,549 controls revealed 13 novel associated loci such as the FAM66C gene, noncoding genes, liver-fibrosis-related genes, metabolism-related genes, and HCC-related pathway genes. We incorporated the results from the UK Biobank and Japanese database into our study for meta-analysis to validate our findings. We also identified specific subtypes of the major histocompatibility complex that influence both viral infection and HCC progression. Using this data, we developed a PRS to predict HCC risk in the general population, patients with HCC, and HCC-affected families. The PRS demonstrated higher risk scores in families with multiple HCCs and other cancer cases. This study presents a novel approach to HCC risk analysis, identifies seven new genes associated with HCC development, and introduces a reproducible PRS model for risk assessment.
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Affiliation(s)
- Ting-Yuan Liu
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
- Million-Person Precision Medicine Initiative, Department of Medical Research, China Medical University Hospital, Taichung 40447, Taiwan
| | - Chi-Chou Liao
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
| | - Ya-Sian Chang
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
| | - Yu-Chia Chen
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
- Million-Person Precision Medicine Initiative, Department of Medical Research, China Medical University Hospital, Taichung 40447, Taiwan
| | - Hong-Da Chen
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
- Department of Laboratory Medicine, China Medical University Hospital, Taichung 404, Taiwan
| | - I-Lu Lai
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
| | - Cheng-Yuan Peng
- Department of Internal Medicine, Section of Hepatobiliary Tract, China Medical University Hospital, Taichung 40447, Taiwan;
| | - Chin-Chun Chung
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
| | - Yu-Pao Chou
- Center for Precision Medicine and Epigenome Research Center, China Medical University Hospital, Taichung 40447, Taiwan; (T.-Y.L.); (C.-C.L.); (Y.-S.C.); (Y.-C.C.); (H.-D.C.); (I.-L.L.); (C.-C.C.); (Y.-P.C.)
| | - Fuu-Jen Tsai
- Department of Medical Research, China Medical University Hospital, Taichung 40447, Taiwan
- School of Chinese Medicine, China Medical University, Taichung 40402, Taiwan
- Division of Pediatric Genetics, Children’s Hospital of China Medical University, Taichung 40447, Taiwan
- Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung 41354, Taiwan
| | - Long-Bin Jeng
- Department of Surgery, Section of Hepatobiliary Tract, China Medical University Hospital, Taichung 40447, Taiwan;
| | - Jan-Gowth Chang
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung 41354, Taiwan
- Department of Medical Laboratory Science and Biotechnology, China Medical University, Taichung 40402, Taiwan
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Peng S, Yang S, Fan X, Zhu J, Liu C, Yue Y, Wang T, Zhu W. Integrative analysis of negatively regulated miRNA-mRNA axes for esophageal squamous cell carcinoma. Cancer Biomark 2023:CBM220309. [PMID: 37302024 DOI: 10.3233/cbm-220309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
BACKGROUND MicroRNAs regulating mRNA expression by targeting at mRNAs is known constructive in tumor occurrence, immune escape, and metastasis. OBJECTIVE This research aims at finding negatively regulatory miRNA-mRNA pairs in esophageal squamous cell carcinoma (ESCC). METHODS GENE expression data of The Cancer Genome Atlas (TCGA) and GEO database were employed in differently expressed RNA and miRNA (DE-miRNAs/DE-mRNAs) screening. Function analysis was conducted with DAVID-mirPath. MiRNA-mRNA axes were identified by MiRTarBase and TarBase and verified in esophageal specimen by real-time reverse transcription polymerase chain reaction (RT-qPCR). Receiver operation characteristic (ROC) curve and Decision Curve Analysis (DCA) were applied in miRNA-mRNA pairs predictive value estimation. Interactions between miRNA-mRNA regulatory pairs and immune features were analyzed using CIBERSORT. RESULTS Combining TCGA database, 4 miRNA and 10 mRNA GEO datasets, totally 26 DE-miRNAs (13 up and 13 down) and 114 DE-mRNAs (64 up and 50 down) were considered significant. MiRTarBase and TarBase identified 37 reverse regulation miRNA-mRNA pairs, 14 of which had been observed in esophageal tissue or cell line. Through analysis of RT-qPCR outcome, miR-106b-5p/KIAA0232 signature was chosen as characteristic pair of ESCC. ROC and DCA verified the predictive value of model containing miRNA-mRNA axis in ESCC. Via affecting mast cells, miR-106b-5p/KIAA0232 may contribute to tumor microenvironment. CONCLUSIONS The diagnostic model of miRNA-mRNA pair in ESCC was established. Their complex role in ESCC pathogenesis especially tumor immunity was partly disclosed.
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Affiliation(s)
- Shuang Peng
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Shiyu Yang
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xingchen Fan
- Department of Geriatrics, The First People's Hospital of Lianyungang, Lianyungang, Jiangsu, China
| | - Jingfeng Zhu
- Department of Nephrology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Cheng Liu
- Department of Gastroenterology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yulin Yue
- Department of Laboratory, Children's Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Tongshan Wang
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wei Zhu
- Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
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Raghubar AM, Pham DT, Tan X, Grice LF, Crawford J, Lam PY, Andersen SB, Yoon S, Teoh SM, Matigian NA, Stewart A, Francis L, Ng MSY, Healy HG, Combes AN, Kassianos AJ, Nguyen Q, Mallett AJ. Spatially Resolved Transcriptomes of Mammalian Kidneys Illustrate the Molecular Complexity and Interactions of Functional Nephron Segments. Front Med (Lausanne) 2022; 9:873923. [PMID: 35872784 PMCID: PMC9300864 DOI: 10.3389/fmed.2022.873923] [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: 02/11/2022] [Accepted: 05/23/2022] [Indexed: 11/30/2022] Open
Abstract
Available transcriptomes of the mammalian kidney provide limited information on the spatial interplay between different functional nephron structures due to the required dissociation of tissue with traditional transcriptome-based methodologies. A deeper understanding of the complexity of functional nephron structures requires a non-dissociative transcriptomics approach, such as spatial transcriptomics sequencing (ST-seq). We hypothesize that the application of ST-seq in normal mammalian kidneys will give transcriptomic insights within and across species of physiology at the functional structure level and cellular communication at the cell level. Here, we applied ST-seq in six mice and four human kidneys that were histologically absent of any overt pathology. We defined the location of specific nephron structures in the captured ST-seq datasets using three lines of evidence: pathologist's annotation, marker gene expression, and integration with public single-cell and/or single-nucleus RNA-sequencing datasets. We compared the mouse and human cortical kidney regions. In the human ST-seq datasets, we further investigated the cellular communication within glomeruli and regions of proximal tubules-peritubular capillaries by screening for co-expression of ligand-receptor gene pairs. Gene expression signatures of distinct nephron structures and microvascular regions were spatially resolved within the mouse and human ST-seq datasets. We identified 7,370 differentially expressed genes (p adj < 0.05) distinguishing species, suggesting changes in energy production and metabolism in mouse cortical regions relative to human kidneys. Hundreds of potential ligand-receptor interactions were identified within glomeruli and regions of proximal tubules-peritubular capillaries, including known and novel interactions relevant to kidney physiology. Our application of ST-seq to normal human and murine kidneys confirms current knowledge and localization of transcripts within the kidney. Furthermore, the generated ST-seq datasets provide a valuable resource for the kidney community that can be used to inform future research into this complex organ.
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Affiliation(s)
- Arti M. Raghubar
- Kidney Health Service, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
- Conjoint Internal Medicine Laboratory, Chemical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- Anatomical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Duy T. Pham
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Xiao Tan
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Laura F. Grice
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, Australia
| | - Joanna Crawford
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Pui Yeng Lam
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Stacey B. Andersen
- Genome Innovation Hub, University of Queensland, Brisbane, QLD, Australia
- UQ Sequencing Facility, Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Sohye Yoon
- Genome Innovation Hub, University of Queensland, Brisbane, QLD, Australia
| | - Siok Min Teoh
- UQ Diamantina Institute, Faculty of Medicine, The University of Queensland, Woolloongabba, QLD, Australia
| | - Nicholas A. Matigian
- QCIF Facility for Advanced Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Anne Stewart
- Anatomical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
| | - Leo Francis
- Anatomical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
| | - Monica S. Y. Ng
- Kidney Health Service, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
- Conjoint Internal Medicine Laboratory, Chemical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Nephrology Department, Princess Alexandra Hospital, Woolloongabba, QLD, Australia
| | - Helen G. Healy
- Kidney Health Service, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
- Conjoint Internal Medicine Laboratory, Chemical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Alexander N. Combes
- Department of Anatomy and Developmental Biology, Stem Cells and Development Program, Monash Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Andrew J. Kassianos
- Kidney Health Service, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
- Conjoint Internal Medicine Laboratory, Chemical Pathology, Pathology Queensland, Health Support Queensland, Herston, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Quan Nguyen
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Andrew J. Mallett
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- College of Medicine & Dentistry, James Cook University, Townsville, Queensland, QLD, Australia
- Department of Renal Medicine, Townsville University Hospital, Townsville, Queensland, QLD, Australia
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Meeks KAC, Bentley AR, Gouveia MH, Chen G, Zhou J, Lei L, Adeyemo AA, Doumatey AP, Rotimi CN. Genome-wide analyses of multiple obesity-related cytokines and hormones informs biology of cardiometabolic traits. Genome Med 2021; 13:156. [PMID: 34620218 PMCID: PMC8499470 DOI: 10.1186/s13073-021-00971-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/16/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans. METHODS We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses. RESULTS GWAS identified 39 significant (P value < 5 × 10-8) loci across all 13 traits. Notably, 14 loci were African-ancestry specific. In this first GWAS for adipsin and ghrelin, we detected 13 and 4 genome-wide significant loci respectively. Stratified analyses by sex, BMI, and T2D showed a strong effect of these variables on detected loci. Eight novel loci were successfully replicated: adipsin (3), GIP (1), GLP-1 (1), and insulin (3). Annotation of these loci revealed promising links between these adipocytokines and cardiometabolic outcomes as illustrated by rs201751833 for adipsin and blood pressure and locus rs759790 for insulin level and T2D in lean individuals. CONCLUSIONS Our study identified genetic variants underlying variation in multiple adipocytokines, including the first loci for adipsin and ghrelin. We identified population differences in variants associated with adipocytokines and highlight the importance of stratification for discovery of loci. The high number of African-specific loci detected emphasizes the need for GWAS in African-ancestry populations, as these loci could not have been detected in other populations. Overall, our work contributes to the understanding of the biology linking adipocytokines to cardiometabolic traits.
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Affiliation(s)
- Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Jie Zhou
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Lin Lei
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA.
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive Bldg 12A rm 4047, Bethesda, MD, 20814, USA.
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Brito MDF, Torre C, Silva-Lima B. Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative. Front Med (Lausanne) 2021; 8:688438. [PMID: 34295913 PMCID: PMC8290522 DOI: 10.3389/fmed.2021.688438] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/02/2021] [Indexed: 12/16/2022] Open
Abstract
Diabetes Mellitus is one of the World Health Organization's priority diseases under research by the first and second programmes of Innovative Medicines Initiative, with the acronyms IMI1 and IMI2, respectively. Up to October of 2019, 13 projects were funded by IMI for Diabetes & Metabolic disorders, namely SUMMIT, IMIDIA, DIRECT, StemBANCC, EMIF, EBiSC, INNODIA, RHAPSODY, BEAT-DKD, LITMUS, Hypo-RESOLVE, IM2PACT, and CARDIATEAM. In general, a total of €447 249 438 was spent by IMI in the area of Diabetes. In order to prompt a better integration of achievements between the different projects, we perform a literature review and used three data sources, namely the official project's websites, the contact with the project's coordinators and co-coordinator, and the CORDIS database. From the 662 citations identified, 185 were included. The data collected were integrated into the objectives proposed for the four IMI2 program research axes: (1) target and biomarker identification, (2) innovative clinical trials paradigms, (3) innovative medicines, and (4) patient-tailored adherence programmes. The IMI funded projects identified new biomarkers, medical and research tools, determinants of inter-individual variability, relevant pathways, clinical trial designs, clinical endpoints, therapeutic targets and concepts, pharmacologic agents, large-scale production strategies, and patient-centered predictive models for diabetes and its complications. Taking into account the scientific data produced, we provided a joint vision with strategies for integrating personalized medicine into healthcare practice. The major limitations of this article were the large gap of data in the libraries on the official project websites and even the Cordis database was not complete and up to date.
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Affiliation(s)
| | - Carla Torre
- Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal.,Laboratory of Systems Integration Pharmacology, Clinical & Regulatory Science-Research Institute for Medicines (iMED.ULisboa), Lisbon, Portugal
| | - Beatriz Silva-Lima
- Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal.,Laboratory of Systems Integration Pharmacology, Clinical & Regulatory Science-Research Institute for Medicines (iMED.ULisboa), Lisbon, Portugal
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7
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Müller TD, Finan B, Bloom SR, D'Alessio D, Drucker DJ, Flatt PR, Fritsche A, Gribble F, Grill HJ, Habener JF, Holst JJ, Langhans W, Meier JJ, Nauck MA, Perez-Tilve D, Pocai A, Reimann F, Sandoval DA, Schwartz TW, Seeley RJ, Stemmer K, Tang-Christensen M, Woods SC, DiMarchi RD, Tschöp MH. Glucagon-like peptide 1 (GLP-1). Mol Metab 2019; 30:72-130. [PMID: 31767182 PMCID: PMC6812410 DOI: 10.1016/j.molmet.2019.09.010] [Citation(s) in RCA: 893] [Impact Index Per Article: 178.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 09/10/2019] [Accepted: 09/22/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The glucagon-like peptide-1 (GLP-1) is a multifaceted hormone with broad pharmacological potential. Among the numerous metabolic effects of GLP-1 are the glucose-dependent stimulation of insulin secretion, decrease of gastric emptying, inhibition of food intake, increase of natriuresis and diuresis, and modulation of rodent β-cell proliferation. GLP-1 also has cardio- and neuroprotective effects, decreases inflammation and apoptosis, and has implications for learning and memory, reward behavior, and palatability. Biochemically modified for enhanced potency and sustained action, GLP-1 receptor agonists are successfully in clinical use for the treatment of type-2 diabetes, and several GLP-1-based pharmacotherapies are in clinical evaluation for the treatment of obesity. SCOPE OF REVIEW In this review, we provide a detailed overview on the multifaceted nature of GLP-1 and its pharmacology and discuss its therapeutic implications on various diseases. MAJOR CONCLUSIONS Since its discovery, GLP-1 has emerged as a pleiotropic hormone with a myriad of metabolic functions that go well beyond its classical identification as an incretin hormone. The numerous beneficial effects of GLP-1 render this hormone an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, and neurodegenerative disorders.
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Affiliation(s)
- T D Müller
- Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany; Department of Pharmacology and Experimental Therapy, Institute of Experimental and Clinical Pharmacology and Toxicology, Eberhard Karls University Hospitals and Clinics, Tübingen, Germany.
| | - B Finan
- Novo Nordisk Research Center Indianapolis, Indianapolis, IN, USA
| | - S R Bloom
- Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
| | - D D'Alessio
- Division of Endocrinology, Duke University Medical Center, Durham, NC, USA
| | - D J Drucker
- The Department of Medicine, Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, University of Toronto, Ontario, M5G1X5, Canada
| | - P R Flatt
- SAAD Centre for Pharmacy & Diabetes, Ulster University, Coleraine, Northern Ireland, UK
| | - A Fritsche
- German Center for Diabetes Research (DZD), Neuherberg, Germany; Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany; Division of Endocrinology, Diabetology, Vascular Disease, Nephrology and Clinical Chemistry, Department of Internal Medicine, University of Tübingen, Tübingen, Germany
| | - F Gribble
- Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, Wellcome Trust-Medical Research Council, Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - H J Grill
- Institute of Diabetes, Obesity and Metabolism, Department of Psychology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - J F Habener
- Laboratory of Molecular Endocrinology, Massachusetts General Hospital, Harvard University, Boston, MA, USA
| | - J J Holst
- Novo Nordisk Foundation Center for Basic Metabolic Research, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - W Langhans
- Physiology and Behavior Laboratory, ETH Zurich, Schwerzenbach, Switzerland
| | - J J Meier
- Diabetes Division, St Josef Hospital, Ruhr-University Bochum, Bochum, Germany
| | - M A Nauck
- Diabetes Center Bochum-Hattingen, St Josef Hospital (Ruhr-Universität Bochum), Bochum, Germany
| | - D Perez-Tilve
- Department of Internal Medicine, University of Cincinnati-College of Medicine, Cincinnati, OH, USA
| | - A Pocai
- Cardiovascular & ImmunoMetabolism, Janssen Research & Development, Welsh and McKean Roads, Spring House, PA, 19477, USA
| | - F Reimann
- Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, Wellcome Trust-Medical Research Council, Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - D A Sandoval
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA
| | - T W Schwartz
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, DL-2200, Copenhagen, Denmark; Department of Biomedical Sciences, University of Copenhagen, DK-2200, Copenhagen, Denmark
| | - R J Seeley
- Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA
| | - K Stemmer
- Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - M Tang-Christensen
- Obesity Research, Global Drug Discovery, Novo Nordisk A/S, Måløv, Denmark
| | - S C Woods
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - R D DiMarchi
- Novo Nordisk Research Center Indianapolis, Indianapolis, IN, USA; Department of Chemistry, Indiana University, Bloomington, IN, USA
| | - M H Tschöp
- German Center for Diabetes Research (DZD), Neuherberg, Germany; Division of Metabolic Diseases, Department of Medicine, Technische Universität München, Munich, Germany; Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
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8
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Enriched developmental biology molecular pathways impact on antipsychotics-induced weight gain. Pharmacogenet Genomics 2019; 30:9-20. [PMID: 31651721 DOI: 10.1097/fpc.0000000000000390] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Psychotropic-induced weight gain (PIWG) may lead to increased risk for cardiovasculardiseases, metabolic disorders and treatment discontinuation. PIWG may be genetically driven. The analysis of complete molecular pathways may grant suffcient power to tackle the biologic variance of PIWG. Such identifcation would help to move a step forward in the direction of personalized treatment in psychiatry. A genetic sample from the CATIE trial (n = 765; M = 556, mean age = 40.93 ± 11.03) treated with diverse antipsychotic drugs was investigated. A molecular pathway analysis was conducted for the identifcation of the molecular pathways enriched in variations associated with PIWG. The developmental biology molecular pathway was signifcantly (P.adj = 0.018) enriched in genetic variations signifcantly (P < 0.01) associated with PIWG. A total of 18 genes were identifed and discussed. The developmental biology molecular pathway is involved in the regulation of β-cell development, and the transcriptional regulation of white adipocyte differentiation. Results from the current contribution correlate with previous evidence and it is consistent with our earlier result on the STAR*D sample. Furthermore, the involvement of the β-cell development and the transcriptional regulation of white adipocyte differentiation pathways stress the relevance of the peripheral tissue rearrangement, rather than increased food intake, in the biologic modifcations that follow psychotropic treatment and may lead to PIWG. Further research is warranted.
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Gupta MK, Vadde R. Identification and characterization of differentially expressed genes in Type 2 Diabetes using in silico approach. Comput Biol Chem 2019; 79:24-35. [PMID: 30708140 DOI: 10.1016/j.compbiolchem.2019.01.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 12/26/2018] [Accepted: 01/23/2019] [Indexed: 12/14/2022]
Abstract
Diabetes mellitus is clinically characterized by hyperglycemia. Though many studies have been done to understand the mechanism of Type 2 Diabetes (T2D), however, the complete network of diabetes and its associated disorders through polygenic involvement is still under debate. The present study designed to re-analyze publicly available T2D related microarray raw datasets present in GEO database and T2D genes information present in GWAS catalog for screening out differentially expressed genes (DEGs) and identify key hub genes associated with T2D. T2D related microarray data downloaded from Gene Expression Omnibus (GEO) database and re-analysis performed with in house R packages scripts for background correction, normalization and identification of DEGs in T2D. Also retrieved T2D related DEGs information from GWAS catalog. Both DEGs lists were grouped after removal of overlapping genes. These screened DEGs were utilized further for identification and characterization of key hub genes in T2D and its associated diseases using STRING, WebGestalt and Panther databases. Computational analysis reveal that out of 99 identified key hub gene candidates from 348 DEGs, only four genes (CCL2, ELMO1, VEGFA and TCF7L2) along with FOS playing key role in causing T2D and its associated disorders, like nephropathy, neuropathy, rheumatoid arthritis and cancer via p53 or Wnt signaling pathways. MIR-29, and MAZ_Q6 are identified potential target microRNA and TF along with probable drugs alprostadil, collagenase and dinoprostone for the key hub gene candidates. The results suggest that identified key DEGs may play promising roles in prevention of diabetes.
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Affiliation(s)
- Manoj Kumar Gupta
- Department of Biotechnology & Bioinformatics, Yogi Vemana University, Kadapa 516003, Andhra Pradesh, India.
| | - Ramakrishna Vadde
- Department of Biotechnology & Bioinformatics, Yogi Vemana University, Kadapa 516003, Andhra Pradesh, India.
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