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McFarling RJ, Teixeira Alves M, Lange A, Clark M, Woodrow HJ, Katsiadaki I, van Aerle R, Santos EM. The potential for heat shock exposure during early development to alter the molecular responses to subsequent exposure to heat stress in the rainbow trout. Comp Biochem Physiol A Mol Integr Physiol 2025; 302:111817. [PMID: 39863055 DOI: 10.1016/j.cbpa.2025.111817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 12/23/2024] [Accepted: 01/20/2025] [Indexed: 01/27/2025]
Abstract
Fish are ectothermic animals with temperature playing a key role in their health, growth and survival. Greater occurrence of heat waves and temperature extremes, as a result of global climate change, has the potential to impact both wild and farmed populations. Within aquaculture, production is threatened by a multitude of stressors, including adverse temperatures. The propensity for environmental temperature during early embryo development to influence later life transcriptomic responses has been observed in numerous animal species, and, if harnessed, could provide a method for inducing phenotypic changes in adult aquaculture species. We hypothesise that exposure of rainbow trout embryos to temperature stress results in alterations to transcriptional responsiveness upon re-exposure later in life. To test this hypothesis, we exposed embryos to a range of different heat shock treatments during early development and then analysed their response to thermal stress at five days post hatch (dph), in comparison to naïve fish that experienced no early development heat shock. Hsp70a and hsp70b transcription was measured (using RT-QPCR) as a biomarker for thermal stress response. Significantly greater transcriptional induction of hsp70a in response to post-hatch thermal stress was found in heat shocked larvae compared to naïve larvae (p = 0.0085). The timing, intensity and duration of the initial heat shock was not found to statistically influence the alteration of hsp induction when compared to that of naïve larvae. Together, these results support our hypothesis that heat shock during early development has the potential to affect responsiveness to the same stressor later in life. Future studies should focus on understanding whether this could be utilised to increase robustness of fish in aquaculture.
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Affiliation(s)
- Rob J McFarling
- Biosciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK; Centre for Sustainable Aquaculture Futures, University of Exeter, Exeter, UK.
| | | | - Anke Lange
- Biosciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Millie Clark
- Biosciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Harry J Woodrow
- Biosciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Ioanna Katsiadaki
- Centre for Environment, Fisheries and Aquaculture Science (Cefas), Weymouth, Dorset, UK; Centre for Sustainable Aquaculture Futures, University of Exeter, Exeter, UK
| | - Ronny van Aerle
- Centre for Environment, Fisheries and Aquaculture Science (Cefas), Weymouth, Dorset, UK; Centre for Sustainable Aquaculture Futures, University of Exeter, Exeter, UK
| | - Eduarda M Santos
- Biosciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK; Centre for Sustainable Aquaculture Futures, University of Exeter, Exeter, UK.
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2
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Diane A, Mu-U-Min RBA, Al-Siddiqi HH. Epigenetic memory as crucial contributing factor in directing the differentiation of human iPSC into pancreatic β-cells in vitro. Cell Tissue Res 2025; 399:267-276. [PMID: 39883142 PMCID: PMC11870940 DOI: 10.1007/s00441-025-03952-8] [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: 10/16/2024] [Accepted: 01/20/2025] [Indexed: 01/31/2025]
Abstract
Impaired insulin secretion contributes to the pathogenesis of type 1 diabetes mellitus through autoimmune destruction of pancreatic β-cells and the pathogenesis of severe forms of type 2 diabetes mellitus through β-cell dedifferentiation and other mechanisms. Replenishment of malfunctioning β-cells via islet transplantation has the potential to induce long-term glycemic control in the body. However, this treatment option cannot widely be implemented in clinical due to healthy islet donor shortage. Emerging β-cell replacement with human-induced pluripotent stem cell (iPSC) provides high remedial therapy hopes. Thus, tremendous progress has been made in developing β-cell differentiation protocols in vitro; however, most of the differentiated iPSC-derived β-cells showed immature phenotypes associated with low efficiency depending on the iPSC lines used, creating a crucial barrier for their clinical implementation. Multiple mechanisms including differences in genetic, cell cycle patterns, and mitochondrial dysfunction underlie the defective differentiation propensity of iPSC into insulin-producing β-cells. Accumulating evidence recently indicated that, following the reprogramming, epigenetic memory inherited from parental cells substantially affects the differentiation capacity of many iPSC lines. Therefore, differences in epigenetic signature are likely to be essential contributing factors influencing the propensity of iPSC differentiation. In this review, we will document the impact of the epigenome on the reprogramming efficacy and differentiation potential of iPSCs and how targeting the epigenetic residual memory could be an additional strategy to improve the differentiation efficiency of existing protocols to generate fully functional hPSC-derived pancreatic β-cells for diabetes therapy and drug screening.
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Affiliation(s)
- Abdoulaye Diane
- Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Qatar Foundation (QF), Hamad Bin Khalifa University (HBKU), Doha, Qatar.
| | - Razik Bin Abdul Mu-U-Min
- Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Qatar Foundation (QF), Hamad Bin Khalifa University (HBKU), Doha, Qatar
| | - Heba Hussain Al-Siddiqi
- Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Qatar Foundation (QF), Hamad Bin Khalifa University (HBKU), Doha, Qatar
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3
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Lee J, Yoon KH. Evolving Characteristics of Type 2 Diabetes Mellitus in East Asia. Endocrinol Metab (Seoul) 2025; 40:57-63. [PMID: 39814030 PMCID: PMC11898318 DOI: 10.3803/enm.2024.2193] [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: 10/07/2024] [Revised: 10/15/2024] [Accepted: 10/29/2024] [Indexed: 01/18/2025] Open
Abstract
In East Asians, type 2 diabetes mellitus (T2DM) is primarily characterized by significant defects in insulin secretion and comparatively low insulin resistance. Recently, the prevalence of T2DM has rapidly increased in East Asian countries, including Korea, occurring concurrently with rising obesity rates. This trend has led to an increase in the average body mass index among East Asian T2DM patients, highlighting the influence of insulin resistance in the development of T2DM within this group. Currently, the incidence of T2DM in Korea is declining, which may indicate potential adaptive changes in insulin secretory capacity. This review focuses on the changing epidemiology of T2DM in East Asia, with a particular emphasis on the characteristics of peak functional β-cell mass.
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Affiliation(s)
- Joonyub Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kun-Ho Yoon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
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Balcha SA, Phillips DI, Trimble ER. Type 1 diabetes mellitus in the context of high levels of rural deprivation: differences in demographic and anthropometric characteristics between urban and rural cases in NW Ethiopia. FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2024; 4:1298270. [PMID: 38348016 PMCID: PMC10859451 DOI: 10.3389/fcdhc.2023.1298270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 12/21/2023] [Indexed: 02/15/2024]
Abstract
Background While there is increasing evidence for an altered clinical phenotype of Type 1 diabetes in several low-and middle-income countries, little is known about urban-rural differences and how the greater poverty of rural environments may alter the pattern of disease. Objective Investigation of urban-rural differences in demographic and anthropometric characteristics of type 1 diabetes in a resource-poor setting. Research design and methods Analysis of a unique case register, comprising all patients (rural and urban) presenting with Type 1 diabetes over a 20 yr. period in a poor, geographically defined area in northwest Ethiopia. The records included age, sex, place of residence, together with height and weight at the clinical onset. Results A total of 1682 new cases of Type 1 diabetes were registered with a mean age of onset of 31.2 (SD 13.4) yr. The patients were thin with 1/3 presenting with a body mass index (BMI) <17kg/m2. There was a striking male predominance of cases when clinical onset was between 20 and 35 yr., this was more marked in the very poor rural dwellers compared to the urban population. While most patients with Type 1 diabetes presented with low BMIs and reduced height, stunting preferentially affected rural men. Conclusions These data have led to the hypothesis that complex interactions among poor socioeconomic conditions in early life affect both pancreatic function and the development of autoimmunity and provide a possible explanation of the unusual phenotype of Type 1 diabetes in this very poor community.
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Affiliation(s)
- Shitaye A. Balcha
- Department of Internal Medicine, Gondar University Hospital, Gondar, Ethiopia
| | - David I. Phillips
- Medical Research Council (MRC) Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, United Kingdom
| | - Elisabeth R. Trimble
- Centre for Public Health, Institute of Clinical Science, Queen’s University Belfast, Belfast, United Kingdom
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Santos-Pereira M, Pereira SC, Rebelo I, Spadella MA, Oliveira PF, Alves MG. Decoding the Influence of Obesity on Prostate Cancer and Its Transgenerational Impact. Nutrients 2023; 15:4858. [PMID: 38068717 PMCID: PMC10707940 DOI: 10.3390/nu15234858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 11/12/2023] [Accepted: 11/16/2023] [Indexed: 12/18/2023] Open
Abstract
In recent decades, the escalating prevalence of metabolic disorders, notably obesity and being overweight, has emerged as a pressing concern in public health. Projections for the future indicate a continual upward trajectory in obesity rates, primarily attributable to unhealthy dietary patterns and sedentary lifestyles. The ramifications of obesity extend beyond its visible manifestations, intricately weaving a web of hormonal dysregulation, chronic inflammation, and oxidative stress. This nexus of factors holds particular significance in the context of carcinogenesis, notably in the case of prostate cancer (PCa), which is a pervasive malignancy and a leading cause of mortality among men. A compelling hypothesis arises from the perspective of transgenerational inheritance, wherein genetic and epigenetic imprints associated with obesity may wield influence over the development of PCa. This review proposes a comprehensive exploration of the nuanced mechanisms through which obesity disrupts prostate homeostasis and serves as a catalyst for PCa initiation. Additionally, it delves into the intriguing interplay between the transgenerational transmission of both obesity-related traits and the predisposition to PCa. Drawing insights from a spectrum of sources, ranging from in vitro and animal model research to human studies, this review endeavors to discuss the intricate connections between obesity and PCa. However, the landscape remains partially obscured as the current state of knowledge unveils only fragments of the complex mechanisms linking these phenomena. As research advances, unraveling the associated factors and underlying mechanisms promises to unveil novel avenues for understanding and potentially mitigating the nexus between obesity and the development of PCa.
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Affiliation(s)
- Mariana Santos-Pereira
- iBiMED-Institute of Biomedicine and Department of Medical Science, University of Aveiro, 3810-193 Aveiro, Portugal;
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), School of Medicine and Biomedical Sciences (ICBAS), University of Porto, 4050-313 Porto, Portugal;
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4099-002 Porto, Portugal
| | - Sara C. Pereira
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), School of Medicine and Biomedical Sciences (ICBAS), University of Porto, 4050-313 Porto, Portugal;
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, 4099-002 Porto, Portugal
- LAQV-REQUIMTE and Department of Chemistry, Campus Universitario de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal;
- Department of Pathology, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal
| | - Irene Rebelo
- UCIBIO-REQUIMTE, Laboratory of Biochemistry, Department of Biologic Sciences, Pharmaceutical Faculty, University of Porto, 4050-313 Porto, Portugal;
| | - Maria A. Spadella
- Human Embryology Laboratory, Marília Medical School, Marília 17519-030, SP, Brazil;
| | - Pedro F. Oliveira
- LAQV-REQUIMTE and Department of Chemistry, Campus Universitario de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal;
| | - Marco G. Alves
- iBiMED-Institute of Biomedicine and Department of Medical Science, University of Aveiro, 3810-193 Aveiro, Portugal;
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Schuermans A, Nakao T, Ruan Y, Koyama S, Yu Z, Uddin MM, Haidermota S, Hornsby W, Lewandowski AJ, Bick AG, Niroula A, Jaiswal S, Ebert BL, Natarajan P, Honigberg MC. Birth Weight Is Associated With Clonal Hematopoiesis of Indeterminate Potential and Cardiovascular Outcomes in Adulthood. J Am Heart Assoc 2023; 12:e030220. [PMID: 37345823 PMCID: PMC10356089 DOI: 10.1161/jaha.123.030220] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 05/19/2023] [Indexed: 06/23/2023]
Abstract
Background High and low birth weight are independently associated with increased cardiovascular disease risk in adulthood. Clonal hematopoiesis of indeterminate potential (CHIP), the age-related clonal expansion of hematopoietic cells with preleukemic somatic mutations, predicts incident cardiovascular disease independent of traditional cardiovascular risk factors. Whether birth weight predicts development of CHIP later in life is unknown. Methods and Results A total of 221 047 adults enrolled in the UK Biobank with whole exome sequences and self-reported birth weight were analyzed. Of those, 22 030 (11.5%) had low (<2.5 kg) and 29 292 (14.7%) high birth weight (>4.0 kg). CHIP prevalence was higher among participants with low (6.0%, P=0.049) and high (6.3%, P<0.001) versus normal birth weight (5.7%, ref.). Multivariable-adjusted logistic regression analyses demonstrated that each 1-kg increase in birth weight was associated with a 3% increased risk of CHIP (odds ratio, 1.03 [95% CI, 1.00-1.06]; P=0.04), driven by a stronger association observed between birth weight and DNMT3A CHIP (odds ratio, 1.04 per 1-kg increase [95% CI, 1.01-1.08]; P=0.02). Mendelian randomization analyses supported a causal relationship of longer gestational age at delivery with DNMT3A CHIP. Multivariable Cox regression demonstrated that CHIP was independently and additively associated with incident cardiovascular disease or death across birth weight groups, with highest absolute risks in those with CHIP plus high or low birth weight. Conclusions Higher birth weight is associated with increased risk of developing CHIP in midlife, especially DNMT3A CHIP. These findings identify a novel risk factor for CHIP and provide insights into the relationships among early-life environment, CHIP, cancer, and cardiovascular disease.
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Affiliation(s)
- Art Schuermans
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
- Department of Cardiovascular SciencesKU LeuvenLeuvenBelgium
| | - Tetsushi Nakao
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
- Department of Medical OncologyDana‐Farber Cancer InstituteBostonMAUSA
- Division of Cardiovascular Medicine, Department of MedicineBrigham and Women’s HospitalBostonMAUSA
| | - Yunfeng Ruan
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
| | - Satoshi Koyama
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
| | - Zhi Yu
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
| | - Md Mesbah Uddin
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
| | - Sara Haidermota
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
| | - Whitney Hornsby
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
| | - Adam J. Lewandowski
- Cardiovascular Clinical Research Facility, Division of Cardiovascular MedicineUniversity of OxfordUnited Kingdom
| | - Alexander G. Bick
- Division of Genetic Medicine, Department of MedicineVanderbilt University Medical CenterNashvilleTNUSA
| | - Abhishek Niroula
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Department of Medical OncologyDana‐Farber Cancer InstituteBostonMAUSA
- Department of Laboratory MedicineLund UniversitySweden
| | - Siddhartha Jaiswal
- Department of PathologyStanford University School of MedicineStanfordCAUSA
| | - Benjamin L. Ebert
- Department of Medical OncologyDana‐Farber Cancer InstituteBostonMAUSA
- Howard Hughes Medical InstituteBostonMAUSA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Michael C. Honigberg
- Program in Medical and Population Genetics and Cardiovascular Disease InitiativeBroad Institute of Harvard and MITCambridgeMAUSA
- Cardiovascular Research Center and Center for Genomic MedicineMassachusetts General HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
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7
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, et alBao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Show More Authors] [Citation(s) in RCA: 163] [Impact Index Per Article: 81.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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Beydag-Tasöz BS, Yennek S, Grapin-Botton A. Towards a better understanding of diabetes mellitus using organoid models. Nat Rev Endocrinol 2023; 19:232-248. [PMID: 36670309 PMCID: PMC9857923 DOI: 10.1038/s41574-022-00797-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/19/2022] [Indexed: 01/22/2023]
Abstract
Our understanding of diabetes mellitus has benefited from a combination of clinical investigations and work in model organisms and cell lines. Organoid models for a wide range of tissues are emerging as an additional tool enabling the study of diabetes mellitus. The applications for organoid models include studying human pancreatic cell development, pancreatic physiology, the response of target organs to pancreatic hormones and how glucose toxicity can affect tissues such as the blood vessels, retina, kidney and nerves. Organoids can be derived from human tissue cells or pluripotent stem cells and enable the production of human cell assemblies mimicking human organs. Many organ mimics relevant to diabetes mellitus are already available, but only a few relevant studies have been performed. We discuss the models that have been developed for the pancreas, liver, kidney, nerves and vasculature, how they complement other models, and their limitations. In addition, as diabetes mellitus is a multi-organ disease, we highlight how a merger between the organoid and bioengineering fields will provide integrative models.
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Affiliation(s)
- Belin Selcen Beydag-Tasöz
- The Novo Nordisk Foundation Center for Stem Cell Biology, Copenhagen, Denmark
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Siham Yennek
- The Novo Nordisk Foundation Center for Stem Cell Biology, Copenhagen, Denmark
| | - Anne Grapin-Botton
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
- Paul Langerhans Institute Dresden, Dresden, Germany.
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9
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Bele S, Wokasch AS, Gannon M. Epigenetic modulation of cell fate during pancreas development. TRENDS IN DEVELOPMENTAL BIOLOGY 2023; 16:1-27. [PMID: 38873037 PMCID: PMC11173269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/15/2024]
Abstract
Epigenetic modifications to DNA and its associated proteins affect cell plasticity and cell fate restrictions throughout embryonic development. Development of the vertebrate pancreas is characterized by initial is an over-lapping expression of a set of transcriptional regulators in a defined region of the posterior foregut endoderm that collectively promote pancreas progenitor specification and proliferation. As development progresses, these transcription factors segregate into distinct pancreatic lineages, with some being maintained in specific subsets of terminally differentiated pancreas cell types throughout adulthood. Here we describe the progressive stages and cell fate restrictions that occur during pancreas development and the relevant known epigenetic regulatory events that drive the dynamic expression patterns of transcription factors that regulate pancreas development. In addition, we highlight how changes in epigenetic marks can affect susceptibility to pancreas diseases (such as diabetes), adult pancreas cell plasticity, and the ability to derive replacement insulin-producing β cells for the treatment of diabetes.
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Affiliation(s)
- Shilpak Bele
- Department of Medicine, Vanderbilt University Medical Center, 2213 Garland Avenue, Nashville, TN, 37232, USA
| | - Anthony S. Wokasch
- Department of Cell and Developmental Biology, Vanderbilt University, 2213 Garland Avenue, Nashville, TN, 37232, USA
| | - Maureen Gannon
- Department of Medicine, Vanderbilt University Medical Center, 2213 Garland Avenue, Nashville, TN, 37232, USA
- Department of Cell and Developmental Biology, Vanderbilt University, 2213 Garland Avenue, Nashville, TN, 37232, USA
- Department of Veterans Affairs Tennessee Valley Authority, Research Division, 1310 24 Avenue South, Nashville, TN, 37212, USA
- Department of Molecular Physiology and Biophysics, 2213 Garland Avenue, Nashville, TN, 37232, USA
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10
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Chu DT, Bui NL, Vu Thi H, Nguyen Thi YV. Role of DNA methylation in diabetes and obesity. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2023; 197:153-170. [PMID: 37019591 DOI: 10.1016/bs.pmbts.2023.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Due to the fact that the upward trend of several metabolic disorders such as diabetes and obesity, in individuals especially monozygotic twins, who are under the same effects from the environment, are not similar, the role of epigenetic elements like DNA methylation needs taking into account. In this chapter, emerging scientific evidence supporting the strong relationship between changes in DNA methylation and those diseases' development was summarized. Changing in the expression level of diabetes/obesity-related genes through being silenced by methylation can be the underlying mechanism of this phenomenon. Genes with abnormal methylation status are potential biomarkers for early prediction and diagnosis. Moreover, methylation-based molecular targets should be investigated as a new treatment for both T2D and obesity.
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Affiliation(s)
- Dinh-Toi Chu
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam.
| | - Nhat-Le Bui
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
| | - Hue Vu Thi
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
| | - Yen-Vy Nguyen Thi
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
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11
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Salvatore T, Galiero R, Caturano A, Rinaldi L, Criscuolo L, Di Martino A, Albanese G, Vetrano E, Catalini C, Sardu C, Docimo G, Marfella R, Sasso FC. Current Knowledge on the Pathophysiology of Lean/Normal-Weight Type 2 Diabetes. Int J Mol Sci 2022; 24:ijms24010658. [PMID: 36614099 PMCID: PMC9820420 DOI: 10.3390/ijms24010658] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/21/2022] [Accepted: 12/27/2022] [Indexed: 01/03/2023] Open
Abstract
Since early times, being overweight and obesity have been associated with impaired glucose metabolism and type 2 diabetes (T2D). Similarly, a less frequent adult-onset diabetes in low body mass index (BMI) people has been known for many decades. This form is mainly found in developing countries, whereby the largest increase in diabetes incidence is expected in coming years. The number of non-obese patients with T2D is also on the rise among non-white ethnic minorities living in high-income Western countries due to growing migratory flows. A great deal of energy has been spent on understanding the mechanisms that bind obesity to T2D. Conversely, the pathophysiologic features and factors driving the risk of T2D development in non-obese people are still much debated. To reduce the global burden of diabetes, we need to understand why not all obese people develop T2D and not all those with T2D are obese. Moreover, through both an effective prevention and the implementation of an individualized clinical management in all people with diabetes, it is hoped that this will help to reduce this global burden. The purpose of this review is to take stock of current knowledge about the pathophysiology of diabetes not associated to obesity and to highlight which aspects are worthy of future studies.
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Affiliation(s)
- Teresa Salvatore
- Department of Precision Medicine, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Raffaele Galiero
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Alfredo Caturano
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Luca Rinaldi
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Livio Criscuolo
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Anna Di Martino
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Gaetana Albanese
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Erica Vetrano
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Christian Catalini
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Celestino Sardu
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Giovanni Docimo
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
| | - Raffaele Marfella
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
- Mediterrannea Cardiocentro, I–80122 Napoli, Italy
| | - Ferdinando Carlo Sasso
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, I–80138 Naples, Italy
- Correspondence:
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12
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Sarkisova K, van Luijtelaar G. The impact of early-life environment on absence epilepsy and neuropsychiatric comorbidities. IBRO Neurosci Rep 2022; 13:436-468. [PMID: 36386598 PMCID: PMC9649966 DOI: 10.1016/j.ibneur.2022.10.012] [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: 09/30/2022] [Revised: 10/30/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
This review discusses the long-term effects of early-life environment on epileptogenesis, epilepsy, and neuropsychiatric comorbidities with an emphasis on the absence epilepsy. The WAG/Rij rat strain is a well-validated genetic model of absence epilepsy with mild depression-like (dysthymia) comorbidity. Although pathologic phenotype in WAG/Rij rats is genetically determined, convincing evidence presented in this review suggests that the absence epilepsy and depression-like comorbidity in WAG/Rij rats may be governed by early-life events, such as prenatal drug exposure, early-life stress, neonatal maternal separation, neonatal handling, maternal care, environmental enrichment, neonatal sensory impairments, neonatal tactile stimulation, and maternal diet. The data, as presented here, indicate that some early environmental events can promote and accelerate the development of absence seizures and their neuropsychiatric comorbidities, while others may exert anti-epileptogenic and disease-modifying effects. The early environment can lead to phenotypic alterations in offspring due to epigenetic modifications of gene expression, which may have maladaptive consequences or represent a therapeutic value. Targeting DNA methylation with a maternal methyl-enriched diet during the perinatal period appears to be a new preventive epigenetic anti-absence therapy. A number of caveats related to the maternal methyl-enriched diet and prospects for future research are discussed.
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Affiliation(s)
- Karine Sarkisova
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Butlerova str. 5a, Moscow 117485, Russia
| | - Gilles van Luijtelaar
- Donders Institute for Brain, Cognition, and Behavior, Donders Center for Cognition, Radboud University, Nijmegen, PO Box 9104, 6500 HE Nijmegen, the Netherlands
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13
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Dicer1 deficient mice exhibit premature aging and metabolic perturbations in adipocytes. iScience 2022; 25:105149. [PMID: 36185376 PMCID: PMC9523393 DOI: 10.1016/j.isci.2022.105149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 08/12/2022] [Accepted: 09/13/2022] [Indexed: 11/26/2022] Open
Abstract
Age-related diseases are major concern in developed countries. To avoid disabilities that accompany increased lifespan, pharmaceutical approaches are considered. Therefore, appropriate animal models are required for a better understanding of aging processes and potential in vivo assays to evaluate the impact of molecules that may delay the occurrence of age-related diseases. Few mouse models exhibiting pathological aging exist, but currently, none of them reproducibly mimics human diseases like osteoporosis, cognitive dysfunctions or sarcopenia that can be seen in some, but not all, elders. Here, we describe the premature aging phenotypes of Dicer-deficient mature animals, which exhibit an overall deterioration of many organs and tissues (skin, heart, and adipose tissue) ultimately leading to a significant reduction of their lifespan. Molecular characterization of transcriptional responses focused on the adipose tissue suggested that both canonical and non-canonical functions of DICER are involved in this process and highlight potential actionable pathways to revert it. Dicer1-deficient mice have a reduced lifespan with early age-related symptoms Mutant mice are resistant to high fat diet-induced disorders Myokines FGF21 and GDF15 are likely key regulators of adipocytes metabolism
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14
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Gardner DS, Gray C. Development and the art of nutritional maintenance. Br J Nutr 2022; 128:828-834. [PMID: 35587048 PMCID: PMC9361123 DOI: 10.1017/s0007114522001490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 04/25/2022] [Accepted: 04/29/2022] [Indexed: 12/24/2022]
Abstract
Development from early conceptus to a complex, multi-cellular organism is a highly ordered process that is dependent on an adequate supply of nutrients. During this process, the pattern of organ growth is robust, driven by a genetic blueprint and matched to anticipated body mass with high precision and with built-in physiological reserve capacity. This apparent canalisation of the developmental process is particularly sensitive to variation in environmental stimuli, such as inappropriate drug or hormone exposure, or pattern of nutrient delivery. Significant variation in any of these factors can profoundly affect fetal and neonatal growth patterns, with later detriment for physiological function and/or reserve capacity of the resultant adult, with potential health impact. This paradigm shift in science has become known as the Developmental Origins of Health and Disease (DOHaD). Over the last 30 years, many animal and clinical studies have vastly expanded our fundamental knowledge of developmental biology, particularly in the context of later effects on health. In this horizons article, we discuss DOHaD through the lens of nutritional quality (e.g. micronutrient, amino acid, NSP intake). The concept of ‘Quality’ was considered undefinable by Robert Persig in his book, ‘Zen and the Art of Motorcycle Maintenance’. Here, development and the art of nutritional maintenance will define quality in terms of the pattern of nutrient intake, the quality of development and how each interact to influence later health outcomes.
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Affiliation(s)
- David S. Gardner
- School of Veterinary Medicine & Science, University of Nottingham, Sutton Bonington, LE12 5RDLoughborough, UK
| | - Clint Gray
- Gillies McIndoe Research Institute, Wellington, New Zealand
- University of Otago, Wellington, New Zealand
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15
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Todtenhaupt P, van Pel M, Roest AAW, Heijmans BT. Mesenchymal stromal cells as a tool to unravel the developmental origins of disease. Trends Endocrinol Metab 2022; 33:614-627. [PMID: 35902331 DOI: 10.1016/j.tem.2022.06.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/09/2022] [Accepted: 06/26/2022] [Indexed: 10/16/2022]
Abstract
The intrauterine environment can induce alterations of the epigenome that have a lasting impact on disease risk. Current human studies in the field focus on a single epigenetic mark, DNA methylation, measured in blood. For in-depth mechanistic insight into the developmental origins of disease, it will be crucial to consider innovative tissue types. Mesenchymal stromal cells (MSCs) may serve as a novel tool to investigate the full epigenome beyond DNA methylation, to explore other omics levels, and to perform functional assays. Moreover, MSCs can be differentiated into multiple cell types and thereby mimic otherwise inaccessible cell types. A first wave of studies supports the potential of MSCs and illustrates how the innovative use of this cell type may be incorporated in birth cohorts.
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Affiliation(s)
- Pia Todtenhaupt
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands; Neonatology, Department of Pediatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Melissa van Pel
- NecstGen, Leiden, The Netherlands; Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Arno A W Roest
- Pediatric Cardiology, Department of Pediatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
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16
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Reale A, Tagliatesta S, Zardo G, Zampieri M. Counteracting aged DNA methylation states to combat ageing and age-related diseases. Mech Ageing Dev 2022; 206:111695. [PMID: 35760211 DOI: 10.1016/j.mad.2022.111695] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/09/2022] [Accepted: 06/22/2022] [Indexed: 12/18/2022]
Abstract
DNA methylation (DNAm) overwrites information about multiple extrinsic factors on the genome. Age is one of these factors. Age causes characteristic DNAm changes that are thought to be not only major drivers of normal ageing but also precursors to diseases, cancer being one of these. Although there is still much to learn about the relationship between ageing, age-related diseases and DNAm, we now know how to interpret some of the effects caused by age in the form of changes in methylation marks at specific loci. In fact, these changes form the basis of the so called "epigenetic clocks", which translate the genomic methylation profile into an "epigenetic age". Epigenetic age does not only estimate chronological age but can also predict the risk of chronic diseases and mortality. Epigenetic age is believed to be one of the most accurate metrics of biological age. Initial evidence has recently been gathered pointing to the possibility that the rate of epigenetic ageing can be slowed down or even reversed. In this review, we discuss some of the most relevant advances in this field. Expected outcome is that this approach can provide insights into how to preserve health and reduce the impact of ageing diseases in humans.
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Affiliation(s)
- Anna Reale
- Department of Experimental Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Stefano Tagliatesta
- Department of Biology and Biotechnology "Charles Darwin", Sapienza University of Rome, 00161 Rome, Italy.
| | - Giuseppe Zardo
- Department of Experimental Medicine, Sapienza University of Rome, 00161 Rome, Italy.
| | - Michele Zampieri
- Department of Experimental Medicine, Sapienza University of Rome, 00161 Rome, Italy.
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17
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Abstract
Lipids are a major source of energy during the fetal/neonatal period. Most are received from the mother, transplacentally during the intrauterine period or via maternal milk after birth. However, in addition to the known nutritional roles, lipids are now known to bind a variety of cellular receptors to regulate specific patterns in metabolism and gene expression. The expression of these receptors is regulated by various genetic and environmental stimuli, and ligation can activate positive-feedback loops in the expression and the activity of downstream signaling pathways. The authors summarize the role of lipid ligands, cognate receptors, epigenetic regulation, and downstream signaling.
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Affiliation(s)
- Keyur Donda
- Department of Pediatrics, University of South Florida Health Morsani College of Medicine, Tampa, FL, USA
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18
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Simões-Alves AC, Arcoverde-Mello APFC, Campos JDO, Wanderley AG, Leandro CVG, da Costa-Silva JH, de Oliveira Nogueira Souza V. Cardiometabolic Effects of Postnatal High-Fat Diet Consumption in Offspring Exposed to Maternal Protein Restriction In Utero. Front Physiol 2022; 13:829920. [PMID: 35620602 PMCID: PMC9127546 DOI: 10.3389/fphys.2022.829920] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/29/2022] [Indexed: 01/01/2023] Open
Abstract
In recent decades, the high incidence of infectious and parasitic diseases has been replaced by a high prevalence of chronic and degenerative diseases. Concomitantly, there have been profound changes in the behavior and eating habits of families around the world, characterizing a "nutritional transition" phenomenon, which refers to a shift in diet in response to modernization, urbanization, or economic development from undernutrition to the excessive consumption of hypercaloric and ultra-processed foods. Protein malnutrition that was a health problem in the first half of the 20th century has now been replaced by high-fat diets, especially diets high in saturated fat, predisposing consumers to overweight and obesity. This panorama points us to the alarming coexistence of both malnutrition and obesity in the same population. In this way, individuals whose mothers were undernourished early in pregnancy and then exposed to postnatal hyperlipidic nutrition have increased risk factors for developing metabolic dysfunction and cardiovascular diseases in adulthood. Thus, our major aim was to review the cardiometabolic effects resulting from postnatal hyperlipidic diets in protein-restricted subjects, as well as to examine the epigenetic repercussions occasioned by the nutritional transition.
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Affiliation(s)
- Aiany Cibelle Simões-Alves
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Department of Physical Education and Sport Sciences, Universidade Federal de Pernambuco UFPE, Vitória de Santo Antão, Brazil
| | - Ana Paula Fonseca Cabral Arcoverde-Mello
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Department of Physical Education and Sport Sciences, Universidade Federal de Pernambuco UFPE, Vitória de Santo Antão, Brazil
| | - Jéssica de Oliveira Campos
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Department of Physical Education and Sport Sciences, Universidade Federal de Pernambuco UFPE, Vitória de Santo Antão, Brazil
| | | | - Carol Virginia Gois Leandro
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Department of Physical Education and Sport Sciences, Universidade Federal de Pernambuco UFPE, Vitória de Santo Antão, Brazil
| | - João Henrique da Costa-Silva
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Department of Physical Education and Sport Sciences, Universidade Federal de Pernambuco UFPE, Vitória de Santo Antão, Brazil
| | - Viviane de Oliveira Nogueira Souza
- Laboratory of Nutrition, Physical Activity and Phenotypic Plasticity, Department of Physical Education and Sport Sciences, Universidade Federal de Pernambuco UFPE, Vitória de Santo Antão, Brazil
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Vipin VA, Blesson CS, Yallampalli C. Maternal low protein diet and fetal programming of lean type 2 diabetes. World J Diabetes 2022; 13:185-202. [PMID: 35432755 PMCID: PMC8984567 DOI: 10.4239/wjd.v13.i3.185] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 12/30/2021] [Accepted: 02/10/2022] [Indexed: 02/06/2023] Open
Abstract
Maternal nutrition is found to be the key factor that determines fetal health in utero and metabolic health during adulthood. Metabolic diseases have been primarily attributed to impaired maternal nutrition during pregnancy, and impaired nutrition has been an immense issue across the globe. In recent years, type 2 diabetes (T2D) has reached epidemic proportion and is a severe public health problem in many countries. Although plenty of research has already been conducted to tackle T2D which is associated with obesity, little is known regarding the etiology and pathophysiology of lean T2D, a variant of T2D. Recent studies have focused on the effects of epigenetic variation on the contribution of in utero origins of lean T2D, although other mechanisms might also contribute to the pathology. Observational studies in humans and experiments in animals strongly suggest an association between maternal low protein diet and lean T2D phenotype. In addition, clear sex-specific disease prevalence was observed in different studies. Consequently, more research is essential for the understanding of the etiology and pathophysiology of lean T2D, which might help to develop better disease prevention and treatment strategies. This review examines the role of protein insufficiency in the maternal diet as the central driver of the developmental programming of lean T2D.
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Affiliation(s)
- Vidyadharan Alukkal Vipin
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX 77030, United States
| | - Chellakkan Selvanesan Blesson
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX 77030, United States
- Family Fertility Center, Texas Children's Hospital, Houston, TX 77030, United States
| | - Chandra Yallampalli
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX 77030, United States
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20
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Habash NW, Sehrawat TS, Shah VH, Cao S. Epigenetics of alcohol-related liver diseases. JHEP REPORTS : INNOVATION IN HEPATOLOGY 2022; 4:100466. [PMID: 35462859 PMCID: PMC9018389 DOI: 10.1016/j.jhepr.2022.100466] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 02/14/2022] [Accepted: 02/22/2022] [Indexed: 02/07/2023]
Abstract
Alcohol-related liver disease (ARLD) is a primary cause of chronic liver disease in the United States. Despite advances in the diagnosis and management of ARLD, it remains a major public health problem associated with significant morbidity and mortality, emphasising the need to adopt novel approaches to the study of ARLD and its complications. Epigenetic changes are increasingly being recognised as contributing to the pathogenesis of multiple disease states. Harnessing the power of innovative technologies for the study of epigenetics (e.g., next-generation sequencing, DNA methylation assays, histone modification profiling and computational techniques like machine learning) has resulted in a seismic shift in our understanding of the pathophysiology of ARLD. Knowledge of these techniques and advances is of paramount importance for the practicing hepatologist and researchers alike. Accordingly, in this review article we will summarise the current knowledge about alcohol-induced epigenetic alterations in the context of ARLD, including but not limited to, DNA hyper/hypo methylation, histone modifications, changes in non-coding RNA, 3D chromatin architecture and enhancer-promoter interactions. Additionally, we will discuss the state-of-the-art techniques used in the study of ARLD (e.g. single-cell sequencing). We will also highlight the epigenetic regulation of chemokines and their proinflammatory role in the context of ARLD. Lastly, we will examine the clinical applications of epigenetics in the diagnosis and management of ARLD.
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Key Words
- 3C, chromosome conformation capture
- 4C, chromosome conformation capture-on-chip
- AH, alcohol-related hepatitis
- ARLD, alcohol-related liver disease
- ASH, alcohol-related steatohepatitis
- ATAC, assay for transposase-accessible chromatin
- Acetylation
- Alcohol liver disease
- BET, bromodomain and extraterminal motif
- BETi, BET inhibitor
- BRD, bromodomain
- CCL2, C-C motif chemokine ligand 2
- CTCF, CCCTC-binding factor
- CXCL, C-X-C motif chemokine ligand
- Chromatin architecture
- Computational biology
- DNA methylation
- DNMT, DNA methyltransferase
- E-P, enhancer-promoter
- Epidrugs
- Epigenetics
- FKBP5, FK506-binding protein 5
- HCC, hepatocellular carcinoma
- HDAC, histone deacetylase
- HIF1α, hypoxia inducible factor-1α
- HMGB1, high-mobility group box protein 1
- HNF4α, hepatocyte nuclear factor 4α
- HSC, hepatic stellate cell
- Hi-C, chromosome capture followed by high-throughput sequencing
- Histones
- IL, interleukin
- LPS, lipopolysaccharide
- MALAT1, metastasis-associated lung adenocarcinoma transcript 1
- MECP2, methyl-CpG binding protein 2
- NAFLD, non-alcohol-related fatty liver disease
- PPARG, peroxisome proliferator activated receptor-γ
- SAA, salvianolic acid A
- SIRT, sirtuin
- SREBPs, sterol regulatory element-binding proteins
- Single cell epigenome
- TAD, topologically associating domain
- TEAD, TEA domain transcription factor
- TLR, Toll-like receptor
- TNF, tumour necrosis factor
- YAP, Yes-associated protein
- lncRNA, long non-coding RNA
- miRNA, microRNA
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Affiliation(s)
| | | | - Vijay H. Shah
- Corresponding authors. Address: Division of Gastroenterology and Hepatology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. Tel. 507-255-6028, fax: 507-255-6318.
| | - Sheng Cao
- Corresponding authors. Address: Division of Gastroenterology and Hepatology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. Tel. 507-255-6028, fax: 507-255-6318.
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21
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Nema J, Joshi N, Sundrani D, Joshi S. Influence of maternal one carbon metabolites on placental programming and long term health. Placenta 2022; 125:20-28. [DOI: 10.1016/j.placenta.2022.02.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 02/12/2022] [Accepted: 02/24/2022] [Indexed: 10/18/2022]
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22
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Mechanisms Underlying the Expansion and Functional Maturation of β-Cells in Newborns: Impact of the Nutritional Environment. Int J Mol Sci 2022; 23:ijms23042096. [PMID: 35216239 PMCID: PMC8877060 DOI: 10.3390/ijms23042096] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/04/2022] [Accepted: 02/09/2022] [Indexed: 12/24/2022] Open
Abstract
The functional maturation of insulin-secreting β-cells is initiated before birth and is completed in early postnatal life. This process has a critical impact on the acquisition of an adequate functional β-cell mass and on the capacity to meet and adapt to insulin needs later in life. Many cellular pathways playing a role in postnatal β-cell development have already been identified. However, single-cell transcriptomic and proteomic analyses continue to reveal new players contributing to the acquisition of β-cell identity. In this review, we provide an updated picture of the mechanisms governing postnatal β-cell mass expansion and the transition of insulin-secreting cells from an immature to a mature state. We then highlight the contribution of the environment to β-cell maturation and discuss the adverse impact of an in utero and neonatal environment characterized by calorie and fat overload or by protein deficiency and undernutrition. Inappropriate nutrition early in life constitutes a risk factor for developing diabetes in adulthood and can affect the β-cells of the offspring over two generations. A better understanding of these events occurring in the neonatal period will help developing better strategies to produce functional β-cells and to design novel therapeutic approaches for the prevention and treatment of diabetes.
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Andrés S, Madsen O, Montero O, Martín A, Giráldez FJ. The Role of Feed Restriction on DNA Methylation, Feed Efficiency, Metabolome, Biochemical Profile, and Progesterone Patterns in the Female Filial Generation (F1) Obtained From Early Feed Restricted Ewes (F0). Front Physiol 2022; 12:779054. [PMID: 35024036 PMCID: PMC8745145 DOI: 10.3389/fphys.2021.779054] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/18/2021] [Indexed: 12/24/2022] Open
Abstract
Deficient management of replacement animals in the farm during early developmental windows may promote adverse programming effects on reproductive traits and subsequent transmission to the next generation. In this sense, DNA methylation profiles allow researchers to decode epigenetic regulation mechanisms in mammals and identify novel candidate genes correlated with phenotype differences in both dams and offspring. Therefore, improving knowledge in the field of epigenetics and intergenerational effects caused by prenatal and postnatal early nutritional events (e.g., feed restriction) is crucial for refining strategies dedicated to animal breeding. In this study, we determined differences in the global blood methylation patterns, biochemical profile, and metabolome of ewe lambs (F1) born from either early feed restricted dams (F0-RES) or fed ad libitum (F0-ADL). Our data show that functional categories such as those related to cellular processes, phosphorylation, nervous system, immunity response, or reproductive function were enriched significantly in the F1-RES lambs due to differences in the methylation of genes in these categories. These F1-RES lambs did not show differences in feed efficiency during the replacement period but presented higher levels of insulin and triglycerides and reduced concentration of progesterone, whereas the metabolome profile demonstrated variations in the bile acid composition when compared with the F1-ADL lambs. Taken together, all these results suggest that intergenerational effects caused by early feed restriction of dams (F0) may persist in the F1 female lambs with negative consequences on genes involved in cellular processes and reproductive traits.
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Affiliation(s)
- Sonia Andrés
- Instituto de Ganadería de Montaña, CSIC-Universidad de León, León, Spain
| | - Ole Madsen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, Netherlands
| | - Olimpio Montero
- Instituto de Biología y Genética Molecular, CSIC, Valladolid, Spain
| | - Alba Martín
- Instituto de Ganadería de Montaña, CSIC-Universidad de León, León, Spain
| | - F Javier Giráldez
- Instituto de Ganadería de Montaña, CSIC-Universidad de León, León, Spain
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Asahara SI, Inoue H, Kido Y. Regulation of Pancreatic β-Cell Mass by Gene-Environment Interaction. Diabetes Metab J 2022; 46:38-48. [PMID: 35135077 PMCID: PMC8831821 DOI: 10.4093/dmj.2021.0045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/28/2021] [Indexed: 11/15/2022] Open
Abstract
The main pathogenic mechanism of diabetes consists of an increase in insulin resistance and a decrease in insulin secretion from pancreatic β-cells. The number of diabetic patients has been increasing dramatically worldwide, especially in Asian people whose capacity for insulin secretion is inherently lower than that of other ethnic populations. Causally, changes of environmental factors in addition to intrinsic genetic factors have been considered to have an influence on the increased prevalence of diabetes. Particular focus has been placed on "gene-environment interactions" in the development of a reduced pancreatic β-cell mass, as well as type 1 and type 2 diabetes mellitus. Changes in the intrauterine environment, such as intrauterine growth restriction, contribute to alterations of gene expression in pancreatic β-cells, ultimately resulting in the development of pancreatic β-cell failure and diabetes. As a molecular mechanism underlying the effect of the intrauterine environment, epigenetic modifications have been widely investigated. The association of diabetes susceptibility genes or dietary habits with gene-environment interactions has been reported. In this review, we provide an overview of the role of gene-environment interactions in pancreatic β-cell failure as revealed by previous reports and data from experiments.
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Affiliation(s)
- Shun-ichiro Asahara
- Division of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Hiroyuki Inoue
- Division of Medical Chemistry, Department of Metabolism and Diseases, Kobe University Graduate School of Health Sciences, Kobe, Japan
| | - Yoshiaki Kido
- Division of Diabetes and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
- Division of Medical Chemistry, Department of Metabolism and Diseases, Kobe University Graduate School of Health Sciences, Kobe, Japan
- Corresponding author: Yoshiaki Kido https://orcid.org/0000-0003-2433-5799 Department of Metabolism and Diseases, Kobe University Graduate School of Health Sciences, 7-10-2 Tomogaoka, Suma-ku, Kobe 654-0142, Japan E-mail:
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25
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Dietary Protein Modulates the Efficacy of Taurine Supplementation on Adaptive Islet Function and Morphology in Obesity. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1370:267-278. [DOI: 10.1007/978-3-030-93337-1_26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Mishra P, Beura S, Ghosh R, Modak R. Nutritional Epigenetics: How Metabolism Epigenetically Controls Cellular Physiology, Gene Expression and Disease. Subcell Biochem 2022; 100:239-267. [PMID: 36301497 DOI: 10.1007/978-3-031-07634-3_8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The regulation of gene expression is a dynamic process that is influenced by both internal and external factors. Alteration in the epigenetic profile is a key mechanism in the regulation process. Epigenetic regulators, such as enzymes and proteins involved in posttranslational modification (PTM), use different cofactors and substrates derived from dietary sources. For example, glucose metabolism provides acetyl CoA, S-adenosylmethionine (SAM), α- ketoglutarate, uridine diphosphate (UDP)-glucose, adenosine triphosphate (ATP), nicotinamide adenine dinucleotide (NAD+), and fatty acid desaturase (FAD), which are utilized by chromatin-modifying enzymes in many intermediary metabolic pathways. Any alteration in the metabolic status of the cell results in the alteration of these metabolites, which causes dysregulation in the activity of chromatin regulators, resulting in the alteration of the epigenetic profile. Such long-term or repeated alteration of epigenetic profile can lead to several diseases, like cancer, insulin resistance and diabetes, cognitive impairment, neurodegenerative disease, and metabolic syndromes. Here we discuss the functions of key nutrients that contribute to epigenetic regulation and their role in pathophysiological conditions.
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Affiliation(s)
- Pragyan Mishra
- Infection and Epigenetics Group, School of Biotechnology, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India
| | - Shibangini Beura
- Infection and Epigenetics Group, School of Biotechnology, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India
| | - Ritu Ghosh
- Infection and Epigenetics Group, School of Biotechnology, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India
| | - Rahul Modak
- Infection and Epigenetics Group, School of Biotechnology, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India.
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Abstract
The intestinal tract is the entry gate for nutrients and symbiotic organisms, being in constant contact with external environment. DNA methylation is one of the keys to how environmental conditions, diet and nutritional status included, shape functionality in the gut and systemically. This review aims to summarise findings on the importance of methylation to gut development, differentiation and function. Evidence to date on how external factors such as diet, dietary supplements, nutritional status and microbiota modifications modulate intestinal function through DNA methylation is also presented.
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Zambrano E, Lomas-Soria C, Nathanielsz PW. Rodent studies of developmental programming and ageing mechanisms: Special issue: In utero and early life programming of ageing and disease. Eur J Clin Invest 2021; 51:e13631. [PMID: 34061987 DOI: 10.1111/eci.13631] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 05/30/2021] [Accepted: 05/30/2021] [Indexed: 12/31/2022]
Abstract
Compelling evidence exists indicating that developmental programming influences ageing. Programming alters life-course phenotype in multiple organs, predisposing to diseases such as diabetes, obesity and cardiovascular disease that shorten lifespan. This review describes studies in rodents, the most commonly studied species, addressing interactions of programming challenges with ageing. We first consider ageing and programming of insulin function that has been clearly shown to decrease with age. It is important to evaluate ageing in pancreatic islets isolated from other systems. Studies discussed show premature pancreatic islet ageing resulting from both maternal under- and overnutrition. New ways to determine programming of adipose tissue and effects on fat storage are explored. Oxidative stress is a major factor that regulates ageing in tissues. Oxidative stress is discussed in relation to reproductive and cardiovascular ageing. Premature ageing is associated with both low and high glucocorticoid function. Both over and undernutrition have offspring sex-specific programming effects on life-course glucocorticoid concentrations. Evidence is provided that maternal age at conception affects offspring endocrine and metabolism ageing. Finally, the importance of matching foetal nutrition and energy availability with composition and energy content in the post-weaning diet is demonstrated. This mismatch can lead to a greatly shortened lifespan. General principles are discussed throughout. For example, sexual dimorphism of age-related outcomes can be marked. Accelerated ageing occurs early in life. Improving knowledge on programming ageing interactions will improve health span as well as lifespan. Finally, there are considerable similarities in outcomes programmed by maternal undernutrition and overnutrition.
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Affiliation(s)
- Elena Zambrano
- Reproductive Biology Department, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, México
| | - Consuelo Lomas-Soria
- Reproductive Biology Department, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, México.,Reproductive Biology Department, CONACyT-Cátedras, Instituto Nacional de Ciencias Médicas y Nutrición SZ, Mexico City, México
| | - Peter W Nathanielsz
- Department of Animal Science, Texas Pregnancy and Life-course Health Center, University of Wyoming, Laramie, WY, USA
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Dos Santos C, Rafacho A, Ferreira SM, Vettorazzi JF, Dos Reis Araújo T, Mateus Gonçalves L, Ruhrmann S, Bacos K, Ling C, Boschero AC, Jorge Dos Santos G. Excess of glucocorticoids during late gestation impairs the recovery of offspring's β-cell function after a postnatal injury. FASEB J 2021; 35:e21828. [PMID: 34325494 DOI: 10.1096/fj.202100841r] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 07/05/2021] [Accepted: 07/15/2021] [Indexed: 11/11/2022]
Abstract
Since prenatal glucocorticoids (GC) excess increases the risk of metabolic dysfunctions in the offspring and its effect on β-cell recovery capacity remains unknown we investigated these aspects in offspring from mice treated with dexamethasone (DEX) in the late pregnancy. Half of the pups were treated with streptozotocin (STZ) on the sixth postnatal day (PN). Functional and molecular analyses were performed in male offspring on PN25 and PN225. Prenatal DEX treatment resulted in low birth weight. At PN25, both the STZ-treated offspring developed hyperglycemia and had lower β-cell mass, in parallel with higher α-cell mass and glucose intolerance, with no impact of prenatal DEX on such parameters. At PN225, the β-cell mass was partially recovered in the STZ-treated mice, but they remained glucose-intolerant, irrespective of being insulin sensitive. Prenatal exposition to DEX predisposed adult offspring to sustained hyperglycemia and perturbed islet function (lower insulin and higher glucagon response to glucose) in parallel with exacerbated glucose intolerance. β-cell-specific knockdown of the Hnf4α in mice from the DS group resulted in exacerbated glucose intolerance. We conclude that high GC exposure during the prenatal period exacerbates the metabolic dysfunctions in adult life of mice exposed to STZ early in life, resulting in a lesser ability to recover the islets' function over time. This study alerts to the importance of proper management of exogenous GCs during pregnancy and a healthy postnatal lifestyle since the combination of adverse factors during the prenatal and postnatal period accentuates the predisposition to metabolic disorders in adult life.
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Affiliation(s)
- Cristiane Dos Santos
- Laboratory of Endocrine Pancreas and Metabolism - LAPEM, Department of Structural and Functional Biology, Institute of Biology, Campinas State University - UNICAMP, Campinas, Brazil
| | - Alex Rafacho
- Laboratory of Investigation in Chronic Diseases - LIDoC, Department of Physiological Sciences, Center of Biological Sciences, Federal University of Santa Catarina - UFSC, Florianópolis, Brazil
| | - Sandra Mara Ferreira
- Laboratory of Endocrine Pancreas and Metabolism - LAPEM, Department of Structural and Functional Biology, Institute of Biology, Campinas State University - UNICAMP, Campinas, Brazil
| | - Jean Franciesco Vettorazzi
- Laboratory of Endocrine Pancreas and Metabolism - LAPEM, Department of Structural and Functional Biology, Institute of Biology, Campinas State University - UNICAMP, Campinas, Brazil
| | - Thiago Dos Reis Araújo
- Laboratory of Endocrine Pancreas and Metabolism - LAPEM, Department of Structural and Functional Biology, Institute of Biology, Campinas State University - UNICAMP, Campinas, Brazil
| | - Luciana Mateus Gonçalves
- Laboratory of Endocrine Pancreas and Metabolism - LAPEM, Department of Structural and Functional Biology, Institute of Biology, Campinas State University - UNICAMP, Campinas, Brazil
| | - Sabrina Ruhrmann
- Epigenetics and Diabetes Unit, Department of Clinical Sciences Malmö, Lund University Diabetes Center, Scania University Hospital, Malmö, Sweden
| | - Karl Bacos
- Epigenetics and Diabetes Unit, Department of Clinical Sciences Malmö, Lund University Diabetes Center, Scania University Hospital, Malmö, Sweden
| | - Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences Malmö, Lund University Diabetes Center, Scania University Hospital, Malmö, Sweden
| | - Antônio Carlos Boschero
- Laboratory of Endocrine Pancreas and Metabolism - LAPEM, Department of Structural and Functional Biology, Institute of Biology, Campinas State University - UNICAMP, Campinas, Brazil
| | - Gustavo Jorge Dos Santos
- Laboratory of Investigation in Chronic Diseases - LIDoC, Department of Physiological Sciences, Center of Biological Sciences, Federal University of Santa Catarina - UFSC, Florianópolis, Brazil
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Understanding the Long-Lasting Effects of Fetal Nutrient Restriction versus Exposure to an Obesogenic Diet on Islet-Cell Mass and Function. Metabolites 2021; 11:metabo11080514. [PMID: 34436455 PMCID: PMC8401811 DOI: 10.3390/metabo11080514] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 07/28/2021] [Accepted: 07/29/2021] [Indexed: 12/14/2022] Open
Abstract
Early life represents a window of phenotypic plasticity. Thus, exposure of the developing fetus to a compromised nutritional environment can have long term consequences for their health. Indeed, undernutrition or maternal intake of an obesogenic diet during pregnancy leads to a heightened risk of type 2 diabetes (T2D) and obesity in her offspring in adult life. Given that abnormalities in beta-cell function are crucial in delineating the risk of T2D, studies have investigated the impact of these exposures on islet morphology and beta-cell function in the offspring in a bid to understand why they are more at risk of T2D. Interestingly, despite the contrasting maternal metabolic phenotype and, therefore, intrauterine environment associated with undernutrition versus high-fat feeding, there are a number of similarities in the genes/biological pathways that are disrupted in offspring islets leading to changes in function. Looking to the future, it will be important to define the exact mechanisms involved in mediating changes in the gene expression landscape in islet cells to determine whether the road to T2D development is the same or different in those exposed to different ends of the nutritional spectrum.
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Effects of early life adversity on maternal effort and glucocorticoids in wild olive baboons. Behav Ecol Sociobiol 2021. [DOI: 10.1007/s00265-021-03056-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Kim K, Joyce BT, Zheng Y, Schreiner PJ, Jacobs DR, Catov JM, Shikany JM, Carnethon MR, Greenland P, Van Horn LV, Allen NB, Lloyd-Jones DM, Gunderson EP, Hou L. DNA Methylation GrimAge and Incident Diabetes: The Coronary Artery Risk Development in Young Adults (CARDIA) Study. Diabetes 2021; 70:1404-1413. [PMID: 33820761 PMCID: PMC8275890 DOI: 10.2337/db20-1167] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 03/27/2021] [Indexed: 12/21/2022]
Abstract
DNA methylation (DNAm)-based biological age (epigenetic age) has been suggested as a useful biomarker of age-related conditions including type 2 diabetes (T2D), and its newest iterations (GrimAge measurements) have shown early promise. In this study, we explored the association between epigenetic age and incident T2D in the context of their relationships with obesity. A total of 1,057 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study were included in the current analyses. We stratified the participants into three groups: normal weight, overweight, and obese. A 1-year increase of GrimAge was associated with higher 10-year (study years 15-25) incidence of T2D (odds ratio [OR] 1.06, 95% CI 1.01-1.11). GrimAge acceleration, which represents the deviation of GrimAge from chronological age, was derived from the residuals of a model of GrimAge and chronological age, and any GrimAge acceleration (positive GrimAA: having GrimAge older than chronological age) was associated with significantly higher odds of 10-year incidence of T2D in obese participants (OR 2.57, 95% CI 1.61-4.11). Cumulative obesity was estimated by years since obesity onset, and GrimAge partially mediated the statistical association between cumulative obesity and incident diabetes or prediabetes (proportion mediated = 8.0%). In conclusion, both older and accelerated GrimAge were associated with higher risk of T2D, particularly among obese participants. GrimAge also statistically mediated the associations between cumulative obesity and T2D. Our findings suggest that epigenetic age measurements with DNAm can potentially be used as a risk factor or biomarker associated with T2D development.
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Affiliation(s)
- Kyeezu Kim
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
- Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL
| | - Brian T Joyce
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Yinan Zheng
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Janet M Catov
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA
| | - James M Shikany
- Division of Preventive Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Mercedes R Carnethon
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Linda V Van Horn
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Norrina B Allen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Donald M Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Erica P Gunderson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Lifang Hou
- Center for Global Oncology, Institute for Global Health, Northwestern University Feinberg School of Medicine, Chicago, IL
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
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Parveen N, Dhawan S. DNA Methylation Patterning and the Regulation of Beta Cell Homeostasis. Front Endocrinol (Lausanne) 2021; 12:651258. [PMID: 34025578 PMCID: PMC8137853 DOI: 10.3389/fendo.2021.651258] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 04/21/2021] [Indexed: 12/14/2022] Open
Abstract
Pancreatic beta cells play a central role in regulating glucose homeostasis by secreting the hormone insulin. Failure of beta cells due to reduced function and mass and the resulting insulin insufficiency can drive the dysregulation of glycemic control, causing diabetes. Epigenetic regulation by DNA methylation is central to shaping the gene expression patterns that define the fully functional beta cell phenotype and regulate beta cell growth. Establishment of stage-specific DNA methylation guides beta cell differentiation during fetal development, while faithful restoration of these signatures during DNA replication ensures the maintenance of beta cell identity and function in postnatal life. Lineage-specific transcription factor networks interact with methylated DNA at specific genomic regions to enhance the regulatory specificity and ensure the stability of gene expression patterns. Recent genome-wide DNA methylation profiling studies comparing islets from diabetic and non-diabetic human subjects demonstrate the perturbation of beta cell DNA methylation patterns, corresponding to the dysregulation of gene expression associated with mature beta cell state in diabetes. This article will discuss the molecular underpinnings of shaping the islet DNA methylation landscape, its mechanistic role in the specification and maintenance of the functional beta cell phenotype, and its dysregulation in diabetes. We will also review recent advances in utilizing beta cell specific DNA methylation patterns for the development of biomarkers for diabetes, and targeting DNA methylation to develop translational approaches for supplementing the functional beta cell mass deficit in diabetes.
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Affiliation(s)
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, United States
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Lecoutre S, Maqdasy S, Breton C. Maternal obesity as a risk factor for developing diabetes in offspring: An epigenetic point of view. World J Diabetes 2021; 12:366-382. [PMID: 33889285 PMCID: PMC8040079 DOI: 10.4239/wjd.v12.i4.366] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Revised: 01/30/2021] [Accepted: 02/19/2021] [Indexed: 02/06/2023] Open
Abstract
According to the developmental origin of health and disease concept, the risk of many age-related diseases is not only determined by genetic and adult lifestyle factors but also by factors acting during early development. In particular, maternal obesity and neonatal accelerated growth predispose offspring to overweight and type 2 diabetes (T2D) in adulthood. This concept mainly relies on the developmental plasticity of adipose tissue and pancreatic β-cell programming in response to suboptimal milieu during the perinatal period. These changes result in unhealthy hypertrophic adipocytes with decreased capacity to store fat, low-grade inflammation and loss of insulin-producing pancreatic β-cells. Over the past years, many efforts have been made to understand how maternal obesity induces long-lasting adipose tissue and pancreatic β-cell dysfunction in offspring and what are the molecular basis of the transgenerational inheritance of T2D. In particular, rodent studies have shed light on the role of epigenetic mechanisms in linking maternal nutritional manipulations to the risk for T2D in adulthood. In this review, we discuss epigenetic adipocyte and β-cell remodeling during development in the progeny of obese mothers and the persistence of these marks as a basis of obesity and T2D predisposition.
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Affiliation(s)
- Simon Lecoutre
- Department of Medicine (H7), Karolinska Institutet, Stockholm 141-86, Sweden
- University of Lille, EA4489, Maternal Malnutrition and Programming of Metabolic Diseases, Lille 59000, France
| | - Salwan Maqdasy
- Department of Medicine (H7), Karolinska Institutet, Stockholm 141-86, Sweden
- Clermont-Ferrand CHU, Department of Endocrinology, Diabetology and Metabolic Diseases, Clermont-Ferrand 63003, France
| | - Christophe Breton
- University of Lille, EA4489, Maternal Malnutrition and Programming of Metabolic Diseases, Lille 59000, France
- U1283-UMR8199-EGID, University of Lille, Institut National de la Santé Et de la Recherche Médicale, Centre National de la Recherche Scientifique, Lille 59000, France
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Associations Between Physical Effort and DNA Methylation in the Promotor Region of the Dopamine Transporter Gene (DAT1). J Hum Kinet 2021; 77:125-133. [PMID: 34168698 PMCID: PMC8008309 DOI: 10.2478/hukin-2021-0041] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The purpose of this study was to investigate the association between physical effort and DNA methylation in the promoter region of the dopamine transporter gene (DAT1). The research group included 100 athletes (mean age = 22.88, SD = 6.35), whereas the control group were 239 healthy male volunteers matched for age (mean age = 21.69, SD = 3.39). Both, the control and the research group, included individuals with Caucasian origin from the same region of Poland. DNA was extracted from peripheral blood leukocytes using a DNA isolation kit (A&A Biotechnology, Gdynia, Poland). Bisulfite modification of 250 ng DNA was performed using the EZ DNA Methylation Kit (Zymo Research, Orange, CA, USA), according to manufacturer's instructions. The methylation-specific PCR assay was carried out in a Mastercycler epgradient S (Eppendorf, Germany). We observed that the level of general methylation of the CpG island was similar for both groups. Further exploration of individual CpG sites allowed to notice that there were significant differences in methylation status in specific positions. Nonetheless, there was no rule that would indicate either higher or lower methylation of individual sites, four of them were methylated at a higher level (positions 1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 23, 25, 26, 27, 29 and 30), while one showed an inverse trend (position 3). More precise analysis with the usage of Bonferroni correction for multiple tests indicated that differences in CpG site methylation were mainly increased in several positions and decreased in position 3.
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Zhang Q, Xiao X, Zheng J, Li M, Yu M, Ping F, Wang T, Wang X. Maternal High-Fat Diet Disturbs the DNA Methylation Profile in the Brown Adipose Tissue of Offspring Mice. Front Endocrinol (Lausanne) 2021; 12:705827. [PMID: 34690924 PMCID: PMC8531551 DOI: 10.3389/fendo.2021.705827] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/30/2021] [Indexed: 12/18/2022] Open
Abstract
The prevalence of obesity has become a threatening global public health issue. The consequence of obesity is abnormal energy metabolism. Unlike white adipose tissue (WAT), brown adipose tissue (BAT) has a unique role in nonshivering thermogenesis. Lipids and glucose are consumed to maintain energy and metabolic homeostasis in BAT. Recently, accumulating evidence has indicated that exposure to excess maternal energy intake affects energy metabolism in offspring throughout their life. However, whether excess intrauterine energy intake influences BAT metabolism in adulthood is not clear. In this study, mouse dams were exposed to excess energy intake by feeding a high-fat diet (HFD) before and during pregnancy and lactation. The histology of BAT was assessed by hematoxylin and eosin staining. The genome-wide methylation profile of BAT was determined by a DNA methylation array, and specific site DNA methylation was quantitatively analyzed by methylated DNA immunoprecipitation (MeDIP) qPCR. We found that intrauterine exposure to a high-energy diet resulted in blood lipid panel disorders and impaired the BAT structure. Higher methylation levels of genes involved in thermogenesis and fatty acid oxidation (FAO) in BAT, such as Acaa2, Acsl1, and Cox7a1, were found in 16-week-old offspring from mothers fed with HFD. Furthermore, the expression of Acaa2, Acsl1, and Cox7a1 was down-regulated by intrauterine exposure to excess energy intake. In summary, our results reveal that excess maternal energy leads to a long-term disorder of BAT in offspring that involves the activation of DNA methylation of BAT-specific genes involved in fatty acid oxidation and thermogenesis.
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Christoforou ER, Sferruzzi-Perri AN. Molecular mechanisms governing offspring metabolic programming in rodent models of in utero stress. Cell Mol Life Sci 2020; 77:4861-4898. [PMID: 32494846 PMCID: PMC7658077 DOI: 10.1007/s00018-020-03566-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 05/23/2020] [Accepted: 05/27/2020] [Indexed: 12/13/2022]
Abstract
The results of different human epidemiological datasets provided the impetus to introduce the now commonly accepted theory coined as 'developmental programming', whereby the presence of a stressor during gestation predisposes the growing fetus to develop diseases, such as metabolic dysfunction in later postnatal life. However, in a clinical setting, human lifespan and inaccessibility to tissue for analysis are major limitations to study the molecular mechanisms governing developmental programming. Subsequently, studies using animal models have proved indispensable to the identification of key molecular pathways and epigenetic mechanisms that are dysregulated in metabolic organs of the fetus and adult programmed due to an adverse gestational environment. Rodents such as mice and rats are the most used experimental animals in the study of developmental programming. This review summarises the molecular pathways and epigenetic mechanisms influencing alterations in metabolic tissues of rodent offspring exposed to in utero stress and subsequently programmed for metabolic dysfunction. By comparing molecular mechanisms in a variety of rodent models of in utero stress, we hope to summarise common themes and pathways governing later metabolic dysfunction in the offspring whilst identifying reasons for incongruencies between models so to inform future work. With the continued use and refinement of such models of developmental programming, the scientific community may gain the knowledge required for the targeted treatment of metabolic diseases that have intrauterine origins.
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Affiliation(s)
- Efthimia R Christoforou
- Department of Physiology, Development and Neuroscience, Centre for Trophoblast Research, University of Cambridge, Downing Site, Cambridge, UK
| | - Amanda N Sferruzzi-Perri
- Department of Physiology, Development and Neuroscience, Centre for Trophoblast Research, University of Cambridge, Downing Site, Cambridge, UK.
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Maternal Malnutrition Affects Hepatic Metabolism through Decreased Hepatic Taurine Levels and Changes in HNF4A Methylation. Int J Mol Sci 2020; 21:ijms21239060. [PMID: 33260590 PMCID: PMC7729756 DOI: 10.3390/ijms21239060] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 11/22/2020] [Accepted: 11/25/2020] [Indexed: 12/16/2022] Open
Abstract
Fetal programming implies that the maternal diet during pregnancy affects the long-term health of offspring. Although maternal diet influences metabolic disorders and non-alcoholic fatty liver disease in offspring, the hepatic mechanisms related to metabolites are still unknown. Here, we investigated the maternal diet-related alterations in metabolites and the biological pathway in male offspring at three months of age. Pregnant rats were exposed to 50% food restriction during the prenatal period or a 45% high-fat diet during the prenatal and postnatal periods. The male offspring exposed to food restriction and high-fat diets had lower birth weights than controls, but had a catch-up growth spurt at three months of age. Hepatic taurine levels decreased in both groups compared to controls. The decreased hepatic taurine levels in offspring affected excessive lipid accumulation through changes in hepatocyte nuclear factor 4 A methylation. Moreover, the alteration of gluconeogenesis in offspring exposed to food restriction was observed to a similar extent as that of offspring exposed to a high fat diet. These results indicate that maternal diet affects the dysregulation in hepatic metabolism through changes in taurine levels and HNF4A methylation, and predisposes the offspring to Type 2 diabetes and non-alcoholic fatty liver disease in later life.
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de Toro-Martín J, Fernández-Marcelo T, González-Rodríguez Á, Escrivá F, Valverde ÁM, Álvarez C, Fernández-Millán E. Defective liver glycogen autophagy related to hyperinsulinemia in intrauterine growth-restricted newborn wistar rats. Sci Rep 2020; 10:17651. [PMID: 33077861 PMCID: PMC7573689 DOI: 10.1038/s41598-020-74702-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 10/01/2020] [Indexed: 02/07/2023] Open
Abstract
Maternal malnutrition plays a critical role in the developmental programming of later metabolic diseases susceptibility in the offspring, such as obesity and type 2 diabetes. Because the liver is the major organ that produces and supplies blood glucose, we aimed at defining the potential role of liver glycogen autophagy in the programming of glucose metabolism disturbances. To this end, newborns were obtained from pregnant Wistar rats fed ad libitum with a standard diet or 65% food-restricted during the last week of gestation. We found that newborns from undernourished mothers showed markedly high basal insulin levels whereas those of glucagon were decreased. This unbalance led to activation of the mTORC1 pathway and inhibition of hepatic autophagy compromising the adequate handling of glycogen in the very early hours of extrauterine life. Restoration of autophagy with rapamycin but not with glucagon, indicated no defect in autophagy machinery per se, but in signals triggered by glucagon. Taken together, these results support the notion that hyperinsulinemia is an important mechanism by which mobilization of liver glycogen by autophagy is defective in food-restricted animals. This early alteration in the hormonal control of liver glycogen autophagy may influence the risk of developing metabolic diseases later in life.
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Affiliation(s)
- Juan de Toro-Martín
- Centre Nutrition, Santé et Société (NUTRISS)-Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec City, QC, Canada
| | - Tamara Fernández-Marcelo
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), ISCIII, 28029, Madrid, Spain
| | - Águeda González-Rodríguez
- Hospital Universitario Santa Cristina, Instituto de Investigación Sanitaria Princesa, Madrid, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), ISCIII, Madrid, Spain
| | - Fernando Escrivá
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), ISCIII, 28029, Madrid, Spain.,Departamento de Bioquímica y Biología Molecular, Facultad de Farmacia, UCM, Ciudad Universitaria s/n, 28040, Madrid, Spain
| | - Ángela M Valverde
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), ISCIII, 28029, Madrid, Spain.,Instituto de Investigaciones Biomédicas Alberto Sols (IIBm) (CSIC/UAM), C/ Arturo Duperier 4, 28029, Madrid, Spain
| | - Carmen Álvarez
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), ISCIII, 28029, Madrid, Spain. .,Departamento de Bioquímica y Biología Molecular, Facultad de Farmacia, UCM, Ciudad Universitaria s/n, 28040, Madrid, Spain.
| | - Elisa Fernández-Millán
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERdem), ISCIII, 28029, Madrid, Spain. .,Departamento de Bioquímica y Biología Molecular, Facultad de Farmacia, UCM, Ciudad Universitaria s/n, 28040, Madrid, Spain.
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Balcha SA, Demisse AG, Mishra R, Vartak T, Cousminer DL, Hodge KM, Voight BF, Lorenz K, Schwartz S, Jerram ST, Gamper A, Holmes A, Wilson HF, Williams AJK, Grant SFA, Leslie RD, Phillips DIW, Trimble ER. Type 1 diabetes in Africa: an immunogenetic study in the Amhara of North-West Ethiopia. Diabetologia 2020; 63:2158-2168. [PMID: 32705316 PMCID: PMC7476916 DOI: 10.1007/s00125-020-05229-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 06/01/2020] [Indexed: 12/12/2022]
Abstract
AIMS/HYPOTHESIS We aimed to characterise the immunogenic background of insulin-dependent diabetes in a resource-poor rural African community. The study was initiated because reports of low autoantibody prevalence and phenotypic differences from European-origin cases with type 1 diabetes have raised doubts as to the role of autoimmunity in this and similar populations. METHODS A study of consecutive, unselected cases of recently diagnosed, insulin-dependent diabetes (n = 236, ≤35 years) and control participants (n = 200) was carried out in the ethnic Amhara of rural North-West Ethiopia. We assessed their demographic and socioeconomic characteristics, and measured non-fasting C-peptide, diabetes-associated autoantibodies and HLA-DRB1 alleles. Leveraging genome-wide genotyping, we performed both a principal component analysis and, given the relatively modest sample size, a provisional genome-wide association study. Type 1 diabetes genetic risk scores were calculated to compare their genetic background with known European type 1 diabetes determinants. RESULTS Patients presented with stunted growth and low BMI, and were insulin sensitive; only 15.3% had diabetes onset at ≤15 years. C-peptide levels were low but not absent. With clinical diabetes onset at ≤15, 16-25 and 26-35 years, 86.1%, 59.7% and 50.0% were autoantibody positive, respectively. Most had autoantibodies to GAD (GADA) as a single antibody; the prevalence of positivity for autoantibodies to IA-2 (IA-2A) and ZnT8 (ZnT8A) was low in all age groups. Principal component analysis showed that the Amhara genomes were distinct from modern European and other African genomes. HLA-DRB1*03:01 (p = 0.0014) and HLA-DRB1*04 (p = 0.0001) were positively associated with this form of diabetes, while HLA-DRB1*15 was protective (p < 0.0001). The mean type 1 diabetes genetic risk score (derived from European data) was higher in patients than control participants (p = 1.60 × 10-7). Interestingly, despite the modest sample size, autoantibody-positive patients revealed evidence of association with SNPs in the well-characterised MHC region, already known to explain half of type 1 diabetes heritability in Europeans. CONCLUSIONS/INTERPRETATION The majority of patients with insulin-dependent diabetes in rural North-West Ethiopia have the immunogenetic characteristics of autoimmune type 1 diabetes. Phenotypic differences between type 1 diabetes in rural North-West Ethiopia and the industrialised world remain unexplained.
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Affiliation(s)
- Shitaye A Balcha
- Department of Internal Medicine, Gondar University Hospital, Gondar, Ethiopia
| | - Abayneh G Demisse
- Department of Pediatrics and Child Health, School of Medicine, University of Gondar, Gondar, Ethiopia
| | - Rajashree Mishra
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Tanwi Vartak
- Blizard Institute, Queen Mary University of London, London, UK
| | - Diana L Cousminer
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kenyaita M Hodge
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Benjamin F Voight
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kim Lorenz
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Samuel T Jerram
- Blizard Institute, Queen Mary University of London, London, UK
| | - Arla Gamper
- Severn Postgraduate School of Primary Care, Health Education England, Bristol, UK
| | - Alice Holmes
- Avon and Wiltshire Mental Health Partnership NHS Trust, Clevedon, UK
| | - Hannah F Wilson
- Diabetes and Metabolism, Translational Health Sciences, University of Bristol, Southmead Hospital, Bristol, UK
| | - Alistair J K Williams
- Diabetes and Metabolism, Translational Health Sciences, University of Bristol, Southmead Hospital, Bristol, UK
| | - Struan F A Grant
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - R David Leslie
- Blizard Institute, Queen Mary University of London, London, UK
| | - David I W Phillips
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
| | - Elisabeth R Trimble
- Centre for Public Health, Institute of Clinical Science, Queen's University Belfast, Grosvenor Road, Belfast, BT12 6BA, UK.
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Chen YT, Lin WD, Liao WL, Tsai YC, Liao JW, Tsai FJ. NT5C2 methylation regulatory interplay between DNMT1 and insulin receptor in type 2 diabetes. Sci Rep 2020; 10:16087. [PMID: 32999320 PMCID: PMC7527562 DOI: 10.1038/s41598-020-71336-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 08/12/2020] [Indexed: 11/29/2022] Open
Abstract
Epigenetics alternation of non-genetic variation and genome-wide association study proven allelic variants may associate with insulin secretion in type 2 diabetes (T2D) development. We analyzed promoter DNA methylation array to evaluate the associated with increased susceptibility to T2D (30 cases, 10 controls) and found 1,091 gene hypermethylated in promoter regions. We performed the association study of T2D and found 698 single nucleotide polymorphisms in exon and promoter sites by using 2,270 subjects (560 cases, 1,710 controls). A comparison of DNA hypermethylation and gene silencing of mouse T2D results in our T2D patients' results showed that the 5'-nucleotidase, cytosolic II (NT5C2) and fucosyltransferase 8 (FUT8) genes were strongly associated with increased susceptibility to T2D. DNA hypermethylation in promoter regions reduced NT5C2 gene expression, but not FUT8 in T2D patients. NT5C2 protein expression was decreased in pancreatic β-cells from T2D mice. Transient transfection NT5C2 into RIN-m5F cells down-regulated DNA methyltransferase I (DNMT1) expression and up-regulation of the insulin receptor. Moreover, NT5C2 knockdown induced in DNMT1 overexpression and insulin receptor inhibition. Taken together, these results showed that NT5C2 epigenetically regulated insulin receptor in patients and mice with T2D, and maybe provide for T2D therapy strategy.
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Affiliation(s)
- Yng-Tay Chen
- Graduate Institute of Food Safety, College of Agriculture and Natural Resources, National Chung Hsing University, Taichung, Taiwan.
| | - Wei-De Lin
- Human Genetic Center, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
- School of Post Baccalaureate Chinese Medicine, China Medical University, Taichung, Taiwan
| | - Wen-Ling Liao
- Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan
- Center for Personalized Medicine, China Medical University Hospital, Taichung, Taiwan
| | - Ya-Ching Tsai
- Human Genetic Center, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Jiunn-Wang Liao
- Graduate Institute of Veterinary Pathobiology, National Chung Hsing University, Taichung, Taiwan
| | - Fuu-Jen Tsai
- Human Genetic Center, Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.
- School of Chinese Medicine, China Medical University, Taichung, Taiwan.
- Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan.
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Control of Cell Identity by the Nuclear Receptor HNF4 in Organ Pathophysiology. Cells 2020; 9:cells9102185. [PMID: 32998360 PMCID: PMC7600215 DOI: 10.3390/cells9102185] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 09/25/2020] [Accepted: 09/26/2020] [Indexed: 12/14/2022] Open
Abstract
Hepatocyte Nuclear Factor 4 (HNF4) is a transcription factor (TF) belonging to the nuclear receptor family whose expression and activities are restricted to a limited number of organs including the liver and gastrointestinal tract. In this review, we present robust evidence pointing to HNF4 as a master regulator of cellular differentiation during development and a safekeeper of acquired cell identity in adult organs. Importantly, we discuss that transient loss of HNF4 may represent a protective mechanism upon acute organ injury, while prolonged impairment of HNF4 activities could contribute to organ dysfunction. In this context, we describe in detail mechanisms involved in the pathophysiological control of cell identity by HNF4, including how HNF4 works as part of cell-specific TF networks and how its expression/activities are disrupted in injured organs.
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Altered Transcription Factor Binding and Gene Bivalency in Islets of Intrauterine Growth Retarded Rats. Cells 2020; 9:cells9061435. [PMID: 32527043 PMCID: PMC7348746 DOI: 10.3390/cells9061435] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 05/30/2020] [Accepted: 06/04/2020] [Indexed: 12/16/2022] Open
Abstract
Intrauterine growth retardation (IUGR), which induces epigenetic modifications and permanent changes in gene expression, has been associated with the development of type 2 diabetes. Using a rat model of IUGR, we performed ChIP-Seq to identify and map genome-wide histone modifications and gene dysregulation in islets from 2- and 10-week rats. IUGR induced significant changes in the enrichment of H3K4me3, H3K27me3, and H3K27Ac marks in both 2-wk and 10-wk islets, which were correlated with expression changes of multiple genes critical for islet function in IUGR islets. ChIP-Seq analysis showed that IUGR-induced histone mark changes were enriched at critical transcription factor binding motifs, such as C/EBPs, Ets1, Bcl6, Thrb, Ebf1, Sox9, and Mitf. These transcription factors were also identified as top upstream regulators in our previously published transcriptome study. In addition, our ChIP-seq data revealed more than 1000 potential bivalent genes as identified by enrichment of both H3K4me3 and H3K27me3. The poised state of many potential bivalent genes was altered by IUGR, particularly Acod1, Fgf21, Serpina11, Cdh16, Lrrc27, and Lrrc66, key islet genes. Collectively, our findings suggest alterations of histone modification in key transcription factors and genes that may contribute to long-term gene dysregulation and an abnormal islet phenotype in IUGR rats.
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Franzago M, Santurbano D, Vitacolonna E, Stuppia L. Genes and Diet in the Prevention of Chronic Diseases in Future Generations. Int J Mol Sci 2020; 21:ijms21072633. [PMID: 32290086 PMCID: PMC7178197 DOI: 10.3390/ijms21072633] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 03/30/2020] [Accepted: 04/08/2020] [Indexed: 12/21/2022] Open
Abstract
Nutrition is a modifiable key factor that is able to interact with both the genome and epigenome to influence human health and fertility. In particular, specific genetic variants can influence the response to dietary components and nutrient requirements, and conversely, the diet itself is able to modulate gene expression. In this context and the era of precision medicine, nutrigenetic and nutrigenomic studies offer significant opportunities to improve the prevention of metabolic disturbances, such as Type 2 diabetes, gestational diabetes, hypertension, and cardiovascular diseases, even with transgenerational effects. The present review takes into account the interactions between diet, genes and human health, and provides an overview of the role of nutrigenetics, nutrigenomics and epigenetics in the prevention of non-communicable diseases. Moreover, we focus our attention on the mechanism of intergenerational or transgenerational transmission of the susceptibility to metabolic disturbances, and underline that the reversibility of epigenetic modifications through dietary intervention could counteract perturbations induced by lifestyle and environmental factors.
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Affiliation(s)
- Marica Franzago
- Department of Medicine and Aging, School of Medicine and Health Sciences, ‘G. d’Annunzio’ University of Chieti-Pescara, 66100 Chieti, Italy
- Center for Advanced Studies and Technology (CAST), ‘G. d’Annunzio’ University of Chieti-Pescara, 66100 Chieti, Italy
| | | | - Ester Vitacolonna
- Department of Medicine and Aging, School of Medicine and Health Sciences, ‘G. d’Annunzio’ University of Chieti-Pescara, 66100 Chieti, Italy
- Center for Advanced Studies and Technology (CAST), ‘G. d’Annunzio’ University of Chieti-Pescara, 66100 Chieti, Italy
- Correspondence:
| | - Liborio Stuppia
- Center for Advanced Studies and Technology (CAST), ‘G. d’Annunzio’ University of Chieti-Pescara, 66100 Chieti, Italy
- Department of Psychological, Health and Territorial Sciences, School of Medicine and Health Sciences, ‘G. d’Annunzio’ University of Chieti-Pescara, 66100 Chieti, Italy
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Deng YN, Xia Z, Zhang P, Ejaz S, Liang S. Transcription Factor RREB1: from Target Genes towards Biological Functions. Int J Biol Sci 2020; 16:1463-1473. [PMID: 32210733 PMCID: PMC7085234 DOI: 10.7150/ijbs.40834] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 02/06/2020] [Indexed: 02/05/2023] Open
Abstract
The Ras-responsive element binding protein 1(RREB1) is a member of zinc finger transcription factors, which is widely involved in biological processes including cell proliferation, transcriptional regulation and DNA damage repair. New findings reveal RREB1 functions as both transcriptional repressors and transcriptional activators for transcriptional regulation of target genes. The activation of RREB1 is regulated by MAPK pathway. We have summarized the target genes of RREB1 and discussed RREB1 roles in the cancer development. In addition, increasing evidences suggest that RREB1 is a potential risk gene for type 2 diabetes and obesity. We also review the current clinical application of RREB1 as a biomarker for melanoma detection. In conclusion, RREB1 is a promising diagnostic biomarker or new drug target for cancers and metabolic diseases.
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Affiliation(s)
- Ya-Nan Deng
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center for Biotherapy, No.17, 3rd Section of People's South Road, Chengdu, 610041, P.R. China
| | - Zijing Xia
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center for Biotherapy, No.17, 3rd Section of People's South Road, Chengdu, 610041, P.R. China
- Department of Rheumatology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, P. R. China
| | - Peng Zhang
- Department of Urinary Surgery, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, P. R. China
| | - Samina Ejaz
- Department of Biochemistry and Biotechnology, Baghdad Campus, The Islamia University of Bahawalpur, Pakistan
| | - Shufang Liang
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center for Biotherapy, No.17, 3rd Section of People's South Road, Chengdu, 610041, P.R. China
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Zhang W, Qu J, Liu GH, Belmonte JCI. The ageing epigenome and its rejuvenation. Nat Rev Mol Cell Biol 2020; 21:137-150. [PMID: 32020082 DOI: 10.1038/s41580-019-0204-5] [Citation(s) in RCA: 288] [Impact Index Per Article: 57.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2019] [Indexed: 02/07/2023]
Abstract
Ageing is characterized by the functional decline of tissues and organs and the increased risk of ageing-associated disorders. Several 'rejuvenating' interventions have been proposed to delay ageing and the onset of age-associated decline and disease to extend healthspan and lifespan. These interventions include metabolic manipulation, partial reprogramming, heterochronic parabiosis, pharmaceutical administration and senescent cell ablation. As the ageing process is associated with altered epigenetic mechanisms of gene regulation, such as DNA methylation, histone modification and chromatin remodelling, and non-coding RNAs, the manipulation of these mechanisms is central to the effectiveness of age-delaying interventions. This Review discusses the epigenetic changes that occur during ageing and the rapidly increasing knowledge of how these epigenetic mechanisms have an effect on healthspan and lifespan extension, and outlines questions to guide future research on interventions to rejuvenate the epigenome and delay ageing processes.
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Affiliation(s)
- Weiqi Zhang
- Beijing Institute for Brain Disorders, Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China.,Key Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China.,Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
| | - Jing Qu
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.,State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Guang-Hui Liu
- Beijing Institute for Brain Disorders, Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China. .,University of Chinese Academy of Sciences, Beijing, China. .,Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China. .,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
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Dalfrà MG, Burlina S, Del Vescovo GG, Lapolla A. Genetics and Epigenetics: New Insight on Gestational Diabetes Mellitus. Front Endocrinol (Lausanne) 2020; 11:602477. [PMID: 33335512 PMCID: PMC7736606 DOI: 10.3389/fendo.2020.602477] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 11/02/2020] [Indexed: 12/11/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is the most common metabolic complication of pregnancy, with a prevalence that has increased significantly in the last decade, coming to affect 12-18% of all pregnancies. GDM is believed to be the result of a combination of genetic, epigenetic and environmental factors. Following the identification of susceptibility genes for type 2 diabetes by means of genome-wide association studies, an association has also been demonstrated between some type 2 diabetes susceptibility genes and GDM, suggesting a partial similarity of the genetic architecture behind the two forms of diabetes. More recent genome-wide association studies, focusing on maternal metabolism during pregnancy, have demonstrated an overlap in the genes associated with metabolic traits in gravid and non-gravid populations, as well as in genes apparently unique to pregnancy. Epigenetic changes-such as DNA methylation, histone modifications and microRNA gene silencing-have also been identified in GDM patients. Metabolomics has been used to profile the metabolic state of women during pregnancy, based on the measurement of numerous low-molecular-weight metabolites. Measuring amino acids and conventional metabolites has revealed changes in pregnant women with a higher insulin resistance and high blood glucose levels that resemble the changes seen in non-gravid, insulin-resistant populations. This would suggest similarities in the metabolic profiles typical of insulin resistance and hyperglycemia whether individuals are pregnant or not. Future studies combining data obtained using multiple technologies will enable an integrated systems biology approach to maternal metabolism during a pregnancy complicated by GDM. This review highlights the recent knowledge on the impact of genetics and epigenetics in the pathophysiology of GDM and the maternal and fetal complications associated with this pathology condition.
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Shufang C, Yinan Z, Huilin L, Hengxia Z, Deliang L, Xuemei L. Effect of He Qi San on DNA Methylation in Type 2 Diabetes Mellitus Patients with Phlegm-blood Stasis Syndrome. OPEN CHEM 2019. [DOI: 10.1515/chem-2019-0130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
AbstractThis study was performed to elucidate the potential influence of He Qi San (HQS) on glucose and lipid metabolism in type 2 diabetes mellitus (T2DM) patients with phlegm-blood stasis syndrome (PBSS), and to determine DNA methylation changes. Sixty T2DM patients with PBSS were randomly divided into control and HQS groups. The control group received conventional treatments, and the HQS group received conventional treatments plus HQS. Glucose metabolism (FPG, 2hPG, FINS, and HbA1c) and lipid metabolism indexes (TG, TC and LDL-C) were determined. Genes with differential DNA methylation were subjected to GO and KEGG analyses. Glucose and lipid metabolism indexes in both groups were reduced, but were much more pronounced in the HQS group. Differential promoter CpG methylation regions were identified in 682 genes, including 426 genes with high-CpG promoters, 150 genes with intermediate CpG promoters, and 106 genes with low CpG promoters. Genes with differential DNA methylation were mainly enriched in the AMPK and insulin signaling pathways, terpenoid backbone biosynthesis, and renin secretion. We concluded that HQS remarkably improved indexes of glucose and lipid metabolism in T2DM patients with PBSS through regulating the DNA methylation of genes in the AMPK and insulin signaling pathways and terpenoid backbone biosynthesis.
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Affiliation(s)
- Chu Shufang
- Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China, 518033
| | - Zhou Yinan
- Department of Internal Medicine, Beijing University of Chinese Medicine Shenzhen Hospital (Longgang), China, 518172
| | - Li Huilin
- Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China, 518033
| | - Zhao Hengxia
- Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China, 518033
| | - Liu Deliang
- Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China, 518033
| | - Liu Xuemei
- Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China, 518033
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Pullar J, Wickramasinghe K, Demaio AR, Roberts N, Perez-Blanco KM, Noonan K, Townsend N. The impact of maternal nutrition on offspring's risk of non-communicable diseases in adulthood: a systematic review. J Glob Health 2019; 9:020405. [PMID: 31656604 PMCID: PMC6790233 DOI: 10.7189/jogh.09.020405] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background A growing body of evidence suggests the impact of maternal nutrition plays a role in determining offspring's risk of non-communicable diseases (NCDs), including heart disease (CVD), type 2 diabetes (T2DM), cancer and chronic obstructive pulmonary diseases (COPD). We conducted a systematic review to investigate this relationship. Methods We systematically searched CINAHL, Cochrane Database of Systematic Reviews, Cochrane Register of Controlled Trials, Database of Abstracts of Reviews of Effects, MEDLINE, EMBASE, Web of Science Core Collection and Global Health for papers published before May 2016 (PROSPERO: CRD42016039244, CRD42016039247). Included studies examined the impact of maternal nutrition (diet, vitamin status and weight) on adult offspring's NCD outcomes. Results Of 23 501 identified citations, 20 met our inclusion criteria. Heterogeneity of papers required narrative synthesis. Included studies involved 1 939 786 participants. CVD: Four papers examined maternal exposure to famine during gestation, 3 identified a resulting increased risk of CVD in offspring. Five identified an increased risk of offspring CVD with increasing maternal weight. T2DM: Six studies investigated maternal exposure to famine during gestation; three identified an increase in offspring's T2DM risk. Three found no increased risk; two of these were in circumstances where famine states persisted beyond pregnancy. Three papers found an increased risk of T2DM in offspring with increasing maternal BMI. CANCER: Four papers investigated maternal famine exposure during pregnancy - two identified a reduced risk of cancer in male offspring, and two an increased risk in female offspring. COPD: One study found low maternal vitamin D status was associated with reduced use of asthma medication. Conclusions While there are indications that exposure to both famine (particularly when coupled with exposure to nutritional excess after birth) and maternal overweight during pregnancy is associated with offspring's risk of CVD, T2DM and cancer, currently there is a lack of evidence to confirm this relationship. Despite the lack of conclusive evidence, these finding hold important research and policy implications for a lifecycle approach to the prevention of NCDs.
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Affiliation(s)
- Jessie Pullar
- Centre on Population Approaches for NCD Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kremlin Wickramasinghe
- Centre on Population Approaches for NCD Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Alessandro R Demaio
- Evidence and Programme Guidance, Department of Nutrition for Health and Development, World Health Organisation, Geneva, Switzerland
| | - Nia Roberts
- Health Library, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Karla-Maria Perez-Blanco
- Centre on Population Approaches for NCD Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Katharine Noonan
- Centre on Population Approaches for NCD Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Nick Townsend
- Centre on Population Approaches for NCD Prevention, Nuffield Department of Population Health, University of Oxford, Oxford, UK
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50
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Vaiserman A, Lushchak O. Developmental origins of type 2 diabetes: Focus on epigenetics. Ageing Res Rev 2019; 55:100957. [PMID: 31473332 DOI: 10.1016/j.arr.2019.100957] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 08/19/2019] [Accepted: 08/28/2019] [Indexed: 12/15/2022]
Abstract
Traditionally, genetics and lifestyle are considered as main determinants of aging-associated pathological conditions. Accumulating evidence, however, suggests that risk of many age-related diseases is not only determined by genetic and adult lifestyle factors but also by factors acting during early development. Type 2 diabetes (T2D), an age-related disease generally manifested after the age of 40, is among such disorders. Since several age-related conditions, such as pro-inflammatory states, are characteristic of both T2D and aging, this disease is conceptualized by many authors as a kind of premature or accelerated aging. There is substantial evidence that intrauterine growth restriction (IUGR), induced by poor or unbalanced nutrient intake, exposure to xenobiotics, maternal substance abuse etc., may impair fetal development, thereby causing the fetal adipose tissue and pancreatic beta cell dysfunction. Consequently, persisting adaptive changes may occur in the glucose-insulin metabolism, including reduced capacity for insulin secretion and insulin resistance. These changes can lead to an improved ability to store fat, thus predisposing to T2D development in later life. The modulation of epigenetic regulation of gene expression likely plays a central role in linking the adverse environmental conditions early in life to the risk of T2D in adulthood. In animal models of IUGR, long-term persistent changes in both DNA methylation and expression of genes implicated in metabolic processes have been repeatedly reported. Findings from human studies confirming the role of epigenetic mechanisms in linking early-life adverse experiences to the risk for T2D in adult life are scarce compared to data from animal studies, mainly because of limited access to suitable biological samples. It is, however, convincing evidence that these mechanisms may also operate in human beings. In this review, theoretical models and research findings evidencing the role of developmental epigenetic variation in the pathogenesis of T2D are summarized and discussed.
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Affiliation(s)
| | - Oleh Lushchak
- Vasyl Stefanyk Precarpathian National University, Ivano-Frankivsk, Ukraine
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