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Marais AD, Hoffman A, Blackhurst DM, van der Spuy ZM. Dyslipidaemia in women with polycystic ovary syndrome referred to a teaching hospital in Cape Town, South Africa. J Neuroendocrinol 2024:e13414. [PMID: 38858175 DOI: 10.1111/jne.13414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/02/2024] [Accepted: 05/11/2024] [Indexed: 06/12/2024]
Abstract
The polycystic ovary syndrome (PCOS) imparts health risks including dyslipidaemia, diabetes and cardiovascular disease that are amenable to lifestyle adjustment and/or medication. We describe dyslipidaemia in women referred to a gynaecological endocrine clinic. Clinical data and endocrine and lipoprotein investigations comprising fasting triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDLC) and calculated low density lipoprotein cholesterol (LDLC) were studied along with electrophoresis patterns of apolipoprotein B-containing lipoproteins. The 1721 participants comprised black, mixed ancestry, white and Indian individuals (9.8%, 83.2%, 5.8% and 1.2%, respectively). The mean ± standard deviation of the age, body mass index (BMI) and waist/hip ratio were 26.0 ± 5.9 years, 32.3 ± 8.3 kg/m2 and waist/hip ratio 0.88 ± 0.11, respectively. Overweight status (BMI 26-30 kg/m2) and obesity (BMI >30 kg/m2) involved 272 (15.8%) and 1010 (58.7%) individuals, respectively. Morbid obesity (BMI >40 kg/m2) was present in 309 (17.9%) individuals. The TG, TC, HDLC and LDLC concentrations were 1.22 ± 0.86, 4.77 ± 1.02, 1.3 ± 0.36, 2.94 ± 0.94 mmol/L, respectively. LDL hypercholesterolaemia occurred in 753 (43.7%) and exceeded 5 mmol/L in 39 (2.3%) women. Low HDLC (<0.9 mmol/L) affected 122 (7%), hypertriglyceridaemia (>1.7 mmol/L) affected 265 (15.4%) and exceeded 2.5 mmol/L in 91 (5.3%) women. Mixed hyperlipidaemia (TG >1.7, TC >5.0 mmol/L) occurred in 176 (10.2%). Electrophoresis revealed small LDL particles in 79 (4.6%) and dysbetalipoproteinaemia in 13 (0.76%) of the cohort. Small LDL associated with obesity, blood pressure, TG and glucose concentration and higher androgenic state. Many women with PCOS had unfavourable lipoprotein results: mostly moderate changes in TG, HDLC and LDLC. Small LDL is not rare, may aid risk assessment and is best determined directly. Incidental monogenic disorders of lipoprotein metabolism included dysbetalipoproteinaemia, familial hypercholesterolaemia and severe hypertriglyceridaemia. Dyslipidaemia in PCOS requires more careful diagnosis, individualised management and research.
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Affiliation(s)
- Adrian David Marais
- Chemical Pathology Division of Department of Pathology, University of Cape Town Faculty of Health Sciences, Cape Town, South Africa
| | - Anne Hoffman
- Department of Obstetrics and Gynaecology, University of Cape Town Faculty of Health Sciences, Cape Town, South Africa
| | - Diane Mary Blackhurst
- Chemical Pathology Division of Department of Pathology, University of Cape Town Faculty of Health Sciences, Cape Town, South Africa
| | - Zephne Margeret van der Spuy
- Department of Obstetrics and Gynaecology, University of Cape Town Faculty of Health Sciences, Cape Town, South Africa
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2
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Pan Z, Khatry MA, Yu ML, Choudhury A, Sebastiani G, Alqahtani SA, Eslam M. MAFLD: an ideal framework for understanding disease phenotype in individuals of normal weight. Ther Adv Endocrinol Metab 2024; 15:20420188241252543. [PMID: 38808010 PMCID: PMC11131400 DOI: 10.1177/20420188241252543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/10/2024] [Indexed: 05/30/2024] Open
Abstract
The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) is significant, impacting almost one-third of the global population. MAFLD constitutes a primary cause of end-stage liver disease, liver cancer and the need for liver transplantation. Moreover, it has a strong association with increased mortality rates due to various extrahepatic complications, notably cardiometabolic diseases. While MAFLD is typically correlated with obesity, not all individuals with obesity develop the disease and a significant percentage of MAFLD occurs in patients without obesity, termed lean MAFLD. The clinical features, progression and underlying physiological mechanisms of patients with lean MAFLD remain inadequately characterized. The present review aims to provide a comprehensive summary of current knowledge on lean MAFLD and offer a perspective on defining MAFLD in individuals with normal weight. Key to this process is the concept of metabolic health and flexibility, which links states of dysmetabolism to the development of lean MAFLD. This perspective offers a more nuanced understanding of MAFLD and its underlying mechanisms and highlights the importance of considering the broader metabolic context in which the disease occurs. It also bridges the knowledge gap and offers insights that can inform clinical practice.
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Affiliation(s)
- Ziyan Pan
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, NSW, Australia
| | - Maryam Al Khatry
- Department of Gastroenterology, Obaidullah Hospital, Emirates Health Services, Ministry of Health, Ras Al Khaimah, United Arab Emirates
| | - Ming-Lung Yu
- School of Medicine and Doctoral Program of Clinical and Experimental Medicine, College of Medicine and Center of Excellence for Metabolic Associated Fatty Liver Disease, National Sun Yat-sen University, Kaohsiung, Taiwan
- Hepatobiliary Division, Department of Internal Medicine, Kaohsiung Medical University Hospital, College of Medicine and Center for Liquid Biopsy and Cohort Research, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ashok Choudhury
- Department of Hepatology, Institute of Liver and Biliary Sciences, New Delhi, India
| | - Giada Sebastiani
- Division of Gastroenterology and Hepatology, McGill University Health Centre, Montreal, QC, Canada
| | - Saleh A. Alqahtani
- Organ Transplant Center of Excellence, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
- Division of Gastroenterology and Hepatology, Johns Hopkins University, Baltimore, MD, USA
| | - Mohammed Eslam
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, 176 Hawkesbury Road, Westmead 2145, NSW, Australia
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3
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Peruchet-Noray L, Sedlmeier AM, Dimou N, Baurecht H, Fervers B, Fontvieille E, Konzok J, Tsilidis KK, Christakoudi S, Jansana A, Cordova R, Bohmann P, Stein MJ, Weber A, Bézieau S, Brenner H, Chan AT, Cheng I, Figueiredo JC, Garcia-Etxebarria K, Moreno V, Newton CC, Schmit SL, Song M, Ulrich CM, Ferrari P, Viallon V, Carreras-Torres R, Gunter MJ, Freisling H. Tissue-specific genetic variation suggests distinct molecular pathways between body shape phenotypes and colorectal cancer. SCIENCE ADVANCES 2024; 10:eadj1987. [PMID: 38640244 PMCID: PMC11029802 DOI: 10.1126/sciadv.adj1987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 03/12/2024] [Indexed: 04/21/2024]
Abstract
It remains unknown whether adiposity subtypes are differentially associated with colorectal cancer (CRC). To move beyond single-trait anthropometric indicators, we derived four multi-trait body shape phenotypes reflecting adiposity subtypes from principal components analysis on body mass index, height, weight, waist-to-hip ratio, and waist and hip circumference. A generally obese (PC1) and a tall, centrally obese (PC3) body shape were both positively associated with CRC risk in observational analyses in 329,828 UK Biobank participants (3728 cases). In genome-wide association studies in 460,198 UK Biobank participants, we identified 3414 genetic variants across four body shapes and Mendelian randomization analyses confirmed positive associations of PC1 and PC3 with CRC risk (52,775 cases/45,940 controls from GECCO/CORECT/CCFR). Brain tissue-specific genetic instruments, mapped to PC1 through enrichment analysis, were responsible for the relationship between PC1 and CRC, while the relationship between PC3 and CRC was predominantly driven by adipose tissue-specific genetic instruments. This study suggests distinct putative causal pathways between adiposity subtypes and CRC.
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Affiliation(s)
- Laia Peruchet-Noray
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | - Anja M. Sedlmeier
- Center for Translational Oncology, University Hospital Regensburg, Regensburg, Germany
- Bavarian Cancer Research Center (BZKF), Regensburg, Germany
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Niki Dimou
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Béatrice Fervers
- Département Prévention Cancer Environnement, Centre Léon Bérard, Lyon, France
| | - Emma Fontvieille
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
| | - Julian Konzok
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Kostas K. Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary’s Campus, Norfolk Place, London W2 1PG, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Sofia Christakoudi
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary’s Campus, Norfolk Place, London W2 1PG, UK
- Department of Inflammation Biology, School of Immunology & Microbial Sciences, King’s College London, London, UK
| | - Anna Jansana
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
| | - Reynalda Cordova
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
- Department of Nutritional Sciences, University of Vienna, Vienna, Austria
| | - Patricia Bohmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Michael J. Stein
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Andrea Weber
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Stéphane Bézieau
- Service de Génétique Médicale, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrew T. Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Jane C. Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Koldo Garcia-Etxebarria
- Biodonostia, Gastrointestinal Genetics Group, San Sebastián, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Barcelona, Spain
| | - Victor Moreno
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L’Hospitalet del Llobregat, 08908 Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, 08908 Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
| | | | - Stephanie L. Schmit
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, Cleveland, OH, USA
| | - Mingyang Song
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Departments of Epidemiology and Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Cornelia M. Ulrich
- Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Pietro Ferrari
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
| | - Robert Carreras-Torres
- Digestive Diseases and Microbiota Group, Girona Biomedical Research Institute (IDIBGI), Salt, Girona, Spain
| | - Marc J. Gunter
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary’s Campus, Norfolk Place, London W2 1PG, UK
| | - Heinz Freisling
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 69366 Lyon CEDEX 07, France
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Gruneisen E, Kremer R, Duque G. Fat as a Friend or Foe of the Bone. Curr Osteoporos Rep 2024; 22:245-256. [PMID: 38416274 DOI: 10.1007/s11914-024-00864-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/12/2024] [Indexed: 02/29/2024]
Abstract
PURPOSE OF REVIEW The objective of this review is to summarize the literature on the prevalence and diagnosis of obesity and its metabolic profile, including bone metabolism, focusing on the main inflammatory and turnover bone mediators that better characterize metabolically healthy obesity phenotype, and to summarize the therapeutic interventions for obesity with their effects on bone health. RECENT FINDINGS Osteoporosis and fracture risk not only increase with age and menopause but also with metabolic diseases, such as diabetes mellitus. Thus, patients with high BMI may have a higher bone fragility and fracture risk. However, some obese individuals with healthy metabolic profiles seem to be less at risk of bone fracture. Obesity has become an alarming disease with growing prevalence and multiple metabolic comorbidities, resulting in a significant burden on healthcare and increased mortality. The imbalance between increased food ingestion and decreased energy expenditure leads to pathological adipose tissue distribution and function, with increased secretion of proinflammatory markers and harmful consequences for body tissues, including bone tissue. However, some obese individuals seem to have a healthy metabolic profile and may not develop cardiometabolic disease during their lives. This healthy metabolic profile also benefits bone turnover and is associated with lower fracture risk.
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Affiliation(s)
- Elodie Gruneisen
- Division of Endocrinology & Metabolism, Department of Medicine, McGill University Health Centre, Montréal, QC, Canada
| | - Richard Kremer
- Division of Endocrinology & Metabolism, Department of Medicine, McGill University Health Centre, Montréal, QC, Canada
- Bone, Muscle & Geroscience Group, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Gustavo Duque
- Bone, Muscle & Geroscience Group, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
- Dr. Joseph Kaufmann Chair in Geriatric Medicine, Department of Medicine, McGill University, Montreal, QC, Canada.
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5
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Wang M, Ou Y, Yuan XL, Zhu XF, Niu B, Kang Z, Zhang B, Ahmed A, Xing GQ, Su H. Heterogeneously elevated branched-chain/aromatic amino acids among new-onset type-2 diabetes mellitus patients are potentially skewed diabetes predictors. World J Diabetes 2024; 15:53-71. [PMID: 38313852 PMCID: PMC10835491 DOI: 10.4239/wjd.v15.i1.53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/03/2023] [Accepted: 12/13/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND The lack of specific predictors for type-2 diabetes mellitus (T2DM) severely impacts early intervention/prevention efforts. Elevated branched-chain amino acids (BCAAs: Isoleucine, leucine, valine) and aromatic amino acids (AAAs: Tyrosine, tryptophan, phenylalanine)) show high sensitivity and specificity in predicting diabetes in animals and predict T2DM 10-19 years before T2DM onset in clinical studies. However, improvement is needed to support its clinical utility. AIM To evaluate the effects of body mass index (BMI) and sex on BCAAs/AAAs in new-onset T2DM individuals with varying body weight. METHODS Ninety-seven new-onset T2DM patients (< 12 mo) differing in BMI [normal weight (NW), n = 33, BMI = 22.23 ± 1.60; overweight, n = 42, BMI = 25.9 ± 1.07; obesity (OB), n = 22, BMI = 31.23 ± 2.31] from the First People's Hospital of Yunnan Province, Kunming, China, were studied. One-way and 2-way ANOVAs were conducted to determine the effects of BMI and sex on BCAAs/AAAs. RESULTS Fasting serum AAAs, BCAAs, glutamate, and alanine were greater and high-density lipoprotein (HDL) was lower (P < 0.05, each) in OB-T2DM patients than in NW-T2DM patients, especially in male OB-T2DM patients. Arginine, histidine, leucine, methionine, and lysine were greater in male patients than in female patients. Moreover, histidine, alanine, glutamate, lysine, valine, methionine, leucine, isoleucine, tyrosine, phenylalanine, and tryptophan were significantly correlated with abdominal adiposity, body weight and BMI, whereas isoleucine, leucine and phenylalanine were negatively correlated with HDL. CONCLUSION Heterogeneously elevated amino acids, especially BCAAs/AAAs, across new-onset T2DM patients in differing BMI categories revealed a potentially skewed prediction of T2DM development. The higher BCAA/AAA levels in obese T2DM patients would support T2DM prediction in obese individuals, whereas the lower levels of BCAAs/AAAs in NW-T2DM individuals may underestimate T2DM risk in NW individuals. This potentially skewed T2DM prediction should be considered when BCAAs/AAAs are to be used as the T2DM predictor.
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Affiliation(s)
- Min Wang
- School of Chemical Science and Technology, Yunnan University, Kunming 650091, Yunnan Province, China
| | - Yang Ou
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Xiang-Lian Yuan
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Xiu-Fang Zhu
- School of Chemical Science and Technology, Yunnan University, Kunming 650091, Yunnan Province, China
| | - Ben Niu
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Zhuang Kang
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
| | - Bing Zhang
- Clinical Laboratory, Nanchong Central Hospital & The Second Clinical Medical College of North Sichuan Medical University, Nanchong 637000, Sichuan Province, China
| | - Anwar Ahmed
- Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, United States
| | - Guo-Qiang Xing
- The Affiliated Hospital and Second Clinical Medical College, North Sichuan Medical University, Nanchong 637000, Sichuan Province, China
- Department of Research and Development, Lotus Biotech.com LLC, Gaithersburg, MD 20878, United States
| | - Heng Su
- Department of Endocrinology, The First People’s Hospital of Yunnan Province, Kunming 650032, Yunnan Province, China
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6
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Ghatan S, van Rooij J, van Hoek M, Boer CG, Felix JF, Kavousi M, Jaddoe VW, Sijbrands EJG, Medina-Gomez C, Rivadeneira F, Oei L. Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations. Genome Med 2024; 16:10. [PMID: 38200577 PMCID: PMC10777532 DOI: 10.1186/s13073-023-01255-7] [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: 06/01/2023] [Accepted: 11/08/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations. METHODS We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger's Z-test and further validated in a pediatric cohort without diabetes (aged 9-12 years old, n = 3866). RESULTS We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta - 0.08 SD, 95% CI [- 0.10-0.07], p = 6.50 × 10-32) and beta-cell dysfunction (Beta - 0.10 SD, 95% CI [- 0.12, - 0.08], p = 1.46 × 10-47) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06-0.10, p = 8.0 × 10-33). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02-1.62, p = 0.03). CONCLUSIONS We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.
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Affiliation(s)
- Samuel Ghatan
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jeroen van Rooij
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Mandy van Hoek
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Cindy G Boer
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Vincent W Jaddoe
- The Generation R Study Group, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Eric J G Sijbrands
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Ling Oei
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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7
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Chen F, Sarver DC, Saqib M, Velez LM, Aja S, Seldin MM, Wong GW. Loss of CTRP10 results in female obesity with preserved metabolic health. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.01.565163. [PMID: 37961647 PMCID: PMC10635050 DOI: 10.1101/2023.11.01.565163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Obesity is a major risk factor for type 2 diabetes, dyslipidemia, cardiovascular disease, and hypertension. Intriguingly, there is a subset of metabolically healthy obese (MHO) individuals who are seemingly able to maintain a healthy metabolic profile free of metabolic syndrome. The molecular underpinnings of MHO, however, are not well understood. Here, we report that CTRP10/C1QL2-deficient mice represent a unique female model of MHO. CTRP10 modulates weight gain in a striking and sexually dimorphic manner. Female, but not male, mice lacking CTRP10 develop obesity with age on a low-fat diet while maintaining an otherwise healthy metabolic profile. When fed an obesogenic diet, female Ctrp10 knockout (KO) mice show rapid weight gain. Despite pronounced obesity, Ctrp10 KO female mice do not develop steatosis, dyslipidemia, glucose intolerance, insulin resistance, oxidative stress, or low-grade inflammation. Obesity is largely uncoupled from metabolic dysregulation in female KO mice. Multi-tissue transcriptomic analyses highlighted gene expression changes and pathways associated with insulin-sensitive obesity. Transcriptional correlation of the differentially expressed gene (DEG) orthologous in humans also show sex differences in gene connectivity within and across metabolic tissues, underscoring the conserved sex-dependent function of CTRP10. Collectively, our findings suggest that CTRP10 negatively regulates body weight in females, and that loss of CTRP10 results in benign obesity with largely preserved insulin sensitivity and metabolic health. This female MHO mouse model is valuable for understanding sex-biased mechanisms that uncouple obesity from metabolic dysfunction.
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Affiliation(s)
- Fangluo Chen
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Center for Metabolism and Obesity Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Dylan C. Sarver
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Center for Metabolism and Obesity Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Muzna Saqib
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Center for Metabolism and Obesity Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Leandro M Velez
- Department of Biological Chemistry, University of California, Irvine, Irvine, USA
- Center for Epigenetics and Metabolism, University of California Irvine, Irvine, USA
| | - Susan Aja
- Center for Metabolism and Obesity Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marcus M. Seldin
- Department of Biological Chemistry, University of California, Irvine, Irvine, USA
- Center for Epigenetics and Metabolism, University of California Irvine, Irvine, USA
| | - G. William Wong
- Department of Physiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Center for Metabolism and Obesity Research, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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8
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Salmón-Gómez L, Catalán V, Frühbeck G, Gómez-Ambrosi J. Relevance of body composition in phenotyping the obesities. Rev Endocr Metab Disord 2023; 24:809-823. [PMID: 36928809 PMCID: PMC10492885 DOI: 10.1007/s11154-023-09796-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/08/2023] [Indexed: 03/18/2023]
Abstract
Obesity is the most extended metabolic alteration worldwide increasing the risk for the development of cardiometabolic alterations such as type 2 diabetes, hypertension, and dyslipidemia. Body mass index (BMI) remains the most frequently used tool for classifying patients with obesity, but it does not accurately reflect body adiposity. In this document we review classical and new classification systems for phenotyping the obesities. Greater accuracy of and accessibility to body composition techniques at the same time as increased knowledge and use of cardiometabolic risk factors is leading to a more refined phenotyping of patients with obesity. It is time to incorporate these advances into routine clinical practice to better diagnose overweight and obesity, and to optimize the treatment of patients living with obesity.
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Affiliation(s)
- Laura Salmón-Gómez
- Metabolic Research Laboratory, Clínica Universidad de Navarra, Irunlarrea 1, Pamplona, 31008, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain
| | - Victoria Catalán
- Metabolic Research Laboratory, Clínica Universidad de Navarra, Irunlarrea 1, Pamplona, 31008, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain
- Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA) Pamplona, Pamplona, Spain
| | - Gema Frühbeck
- Metabolic Research Laboratory, Clínica Universidad de Navarra, Irunlarrea 1, Pamplona, 31008, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain
- Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA) Pamplona, Pamplona, Spain
- Department of Endocrinology & Nutrition, Clínica Universidad de Navarra, Pamplona, Spain
| | - Javier Gómez-Ambrosi
- Metabolic Research Laboratory, Clínica Universidad de Navarra, Irunlarrea 1, Pamplona, 31008, Spain.
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain.
- Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA) Pamplona, Pamplona, Spain.
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9
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Aberra YT, Ma L, Björkegren JLM, Civelek M. Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation. eLife 2023; 12:e79834. [PMID: 37326626 PMCID: PMC10275637 DOI: 10.7554/elife.79834] [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: 04/28/2022] [Accepted: 05/31/2023] [Indexed: 06/17/2023] Open
Abstract
Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.
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Affiliation(s)
- Yonathan Tamrat Aberra
- Department of Biomedical Engineering, University of VirginiaCharlottesvilleUnited States
- Center for Public Health Genomics, University of VirginiaCharlottesvilleUnited States
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount SinaiNew YorkUnited States
| | - Johan LM Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount SinaiNew YorkUnited States
- Department of Medicine, Karolinska Institutet, HuddingeStockholmSweden
| | - Mete Civelek
- Department of Biomedical Engineering, University of VirginiaCharlottesvilleUnited States
- Center for Public Health Genomics, University of VirginiaCharlottesvilleUnited States
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10
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Glunk V, Laber S, Sinnott-Armstrong N, Sobreira DR, Strobel SM, Batista TM, Kubitz P, Moud BN, Ebert H, Huang Y, Brandl B, Garbo G, Honecker J, Stirling DR, Abdennur N, Calabuig-Navarro V, Skurk T, Ocvirk S, Stemmer K, Cimini BA, Carpenter AE, Dankel SN, Lindgren CM, Hauner H, Nobrega MA, Claussnitzer M. A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes. Nat Metab 2023; 5:861-879. [PMID: 37253881 DOI: 10.1038/s42255-023-00807-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 04/12/2023] [Indexed: 06/01/2023]
Abstract
Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.
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Affiliation(s)
- Viktoria Glunk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Samantha Laber
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Nasa Sinnott-Armstrong
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
- Herbold Computational Biology Program, Publich Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Debora R Sobreira
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Sophie M Strobel
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Thiago M Batista
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Phil Kubitz
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bahareh Nemati Moud
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Hannah Ebert
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Yi Huang
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Beate Brandl
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Garrett Garbo
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
| | - Julius Honecker
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - David R Stirling
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nezar Abdennur
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Virtu Calabuig-Navarro
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | - Thomas Skurk
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Soeren Ocvirk
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Intestinal Microbiology Research Group, Department of Molecular Toxicology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Kerstin Stemmer
- Molecular Cell Biology, Institute for Theoretical Medicine, University of Augsburg, Augsburg, Germany
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anne E Carpenter
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Simon N Dankel
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Cecilia M Lindgren
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Hans Hauner
- Institute of Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
- ZIEL Institute for Food & Health, Else Kröner-Fresenius-Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Marcelo A Nobrega
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Medical and Population Genetics Program & Type 2 Diabetes Systems Genomics Initiative, Cambridge, MA, USA.
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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11
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Sanchez-Lastra MA, Ding D, Dalene KE, Del Pozo Cruz B, Ekelund U, Tarp J. Body composition and mortality from middle to old age: a prospective cohort study from the UK Biobank. Int J Obes (Lond) 2023:10.1038/s41366-023-01314-4. [PMID: 37087469 DOI: 10.1038/s41366-023-01314-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 04/12/2023] [Accepted: 04/13/2023] [Indexed: 04/24/2023]
Abstract
BACKGROUND How the association between adiposity and the risk of death changes with age, and which is the optimal level of adiposity to reduce mortality in older ages, is still not completely understood. We aimed to ascertain the age-specific risks of mortality associated with different measures of adiposity. METHODS This was a prospective UK Biobank cohort study. Participants were categorized based on five different adiposity and body composition metrics. We explored the age-varying associations between body composition indices and all-cause mortality from 45 to 85 years of age at follow-up using hazard ratios (HR) from flexible parametric survival models with multivariable adjustment and age as timescale. Participants were followed from baseline (2006-2010) through 31 March 2020. RESULTS We included 369,752 participants (mean baseline age = 56.3 ± 8.1 years; range 38.9-73.7 years; 54.1% women) and 10,660 deaths during a median follow-up of 11.4 years. Associations between body mass index and mortality were similar when using the fat mass index in magnitude and shape. Compared to participants with normal weight, overweight was not associated with the risk of death regardless of age and the adiposity measure used. Participants with obesity class I showed an HR of 1.20 (95% confidence interval [CI]: 1.08, 1.33) and 1.14 (95%CI: 0.98, 1.30) at ages 60 and 80, respectively, and participants with obesity class II an HR about 1.55 across all age. More attenuated associations with higher age were found in individuals with the highest obesity using the fat mass index. Very high lean mass was associated with an increased risk of mortality in those aged 55-75 years (HR about 1.20 across all ages). CONCLUSION Obesity should be prevented at any age. Attenuated associations with older age were observed only among the individuals with the highest obesity, but the risk remained higher compared to normal-weight participants. Lean mass did not reduce mortality risk at any age.
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Affiliation(s)
- Miguel Adriano Sanchez-Lastra
- Department of Special Didactics, University of Vigo, 36005, Pontevedra, Spain.
- Wellness and Movement Research Group (WellMove), Galicia-Sur Health Research Institute (IIS Galicia Sur). SERGAS-UVIGO, Vigo, Spain.
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway.
| | - Ding Ding
- Prevention Research Collaboration, Sydney School of Public Health, The University of Sydney, Camperdown, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Camperdown, NSW, Australia
| | - Knut Eirik Dalene
- Department of Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway
| | - Borja Del Pozo Cruz
- Centre for Active and Healthy Ageing, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
- Faculty of Education, University of Cádiz, Cádiz, Spain
- Biomedical Research and Innovation Institute of Cádiz (INiBICA) Research Unit, Puerta del Mar University Hospital, University of Cádiz, Cádiz, Spain
| | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
- Department of Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway
| | - Jakob Tarp
- Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
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12
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Coral DE, Fernandez-Tajes J, Tsereteli N, Pomares-Millan H, Fitipaldi H, Mutie PM, Atabaki-Pasdar N, Kalamajski S, Poveda A, Miller-Fleming TW, Zhong X, Giordano GN, Pearson ER, Cox NJ, Franks PW. A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes. Nat Metab 2023; 5:237-247. [PMID: 36703017 PMCID: PMC9970876 DOI: 10.1038/s42255-022-00731-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 12/20/2022] [Indexed: 01/27/2023]
Abstract
Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.
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Affiliation(s)
- Daniel E Coral
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
| | - Juan Fernandez-Tajes
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Neli Tsereteli
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Hugo Pomares-Millan
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Hugo Fitipaldi
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Pascal M Mutie
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Naeimeh Atabaki-Pasdar
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Sebastian Kalamajski
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Alaitz Poveda
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Tyne W Miller-Fleming
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xue Zhong
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Giuseppe N Giordano
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Ewan R Pearson
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden
- Population Health and Genomics, University of Dundee, Dundee, UK
| | - Nancy J Cox
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Paul W Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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13
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Leyden GM, Greenwood MP, Gaborieau V, Han Y, Amos CI, Brennan P, Murphy D, Davey Smith G, Richardson TG. Disentangling the aetiological pathways between body mass index and site-specific cancer risk using tissue-partitioned Mendelian randomisation. Br J Cancer 2023; 128:618-625. [PMID: 36434155 PMCID: PMC9938133 DOI: 10.1038/s41416-022-02060-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 10/30/2022] [Accepted: 11/02/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Body mass index (BMI) is known to influence the risk of various site-specific cancers, however, dissecting which subcomponents of this heterogenous risk factor are predominantly responsible for driving disease effects has proven difficult to establish. We have leveraged tissue-specific gene expression to separate the effects of distinct phenotypes underlying BMI on the risk of seven site-specific cancers. METHODS SNP-exposure estimates were weighted in a multivariable Mendelian randomisation analysis by their evidence for colocalization with subcutaneous adipose- and brain-tissue-derived gene expression using a recently developed methodology. RESULTS Our results provide evidence that brain-tissue-derived BMI variants are predominantly responsible for driving the genetically predicted effect of BMI on lung cancer (OR: 1.17; 95% CI: 1.01-1.36; P = 0.03). Similar findings were identified when analysing cigarettes per day as an outcome (Beta = 0.44; 95% CI: 0.26-0.61; P = 1.62 × 10-6), highlighting a possible shared aetiology or mediator effect between brain-tissue BMI, smoking and lung cancer. Our results additionally suggest that adipose-tissue-derived BMI variants may predominantly drive the effect of BMI and increased risk for endometrial cancer (OR: 1.71; 95% CI: 1.07-2.74; P = 0.02), highlighting a putatively important role in the aetiology of endometrial cancer. CONCLUSIONS The study provides valuable insight into the divergent underlying pathways between BMI and the risk of site-specific cancers.
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Affiliation(s)
- Genevieve M Leyden
- MRC Integrative Epidemiology Unit, Bristol Population Health Science Institute, University of Bristol, Bristol, BS8 2BN, UK.
- Bristol Medical School: Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, BS1 3NY, UK.
| | - Michael P Greenwood
- Bristol Medical School: Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, BS1 3NY, UK
| | - Valérie Gaborieau
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Paul Brennan
- Bristol Medical School: Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, BS1 3NY, UK
| | - David Murphy
- Bristol Medical School: Translational Health Sciences, Dorothy Hodgkin Building, University of Bristol, Bristol, BS1 3NY, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Bristol Population Health Science Institute, University of Bristol, Bristol, BS8 2BN, UK
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit, Bristol Population Health Science Institute, University of Bristol, Bristol, BS8 2BN, UK.
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14
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Association of dietary patterns with obesity and metabolically healthy obesity phenotype in Chinese population: a cross-sectional analysis of China Multi-Ethnic Cohort Study. Br J Nutr 2022; 128:2230-2240. [PMID: 35000632 DOI: 10.1017/s0007114521005158] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Metabolically healthy obesity (MHO) might be an alternative valuable target in obesity treatment. We aimed to assess whether alternative Mediterranean (aMED) diet and Dietary Approaches to Stop Hypertension (DASH) diet were favourably associated with obesity and MHO phenotype in a Chinese multi-ethnic population. We conducted this cross-sectional analysis using the baseline data of the China Multi-Ethnic Cohort study that enrolled 99 556 participants from seven diverse ethnic groups. Participants with self-reported cardiometabolic diseases were excluded to eliminate possible reverse causality. Marginal structural logistic models were used to estimate the associations, with confounders determined by directed acyclic graph (DAG). Among 65 699 included participants, 11·2 % were with obesity. MHO phenotype was present in 5·7 % of total population and 52·7 % of population with obesity. Compared with the lowest quintile, the highest quintile of DASH diet score had 23 % decreased odds of obesity (OR = 0·77, 95 % CI 0·71, 0·83, Ptrend < 0·001) and 27 % increased odds of MHO (OR = 1·27, 95 % CI 1·10, 1·48, Ptrend = 0·001) in population with obesity. However, aMED diet showed no obvious favourable associations. Further adjusting for BMI did not change the associations between diet scores and MHO. Results were robust to various sensitivity analyses. In conclusion, DASH diet rather than aMED diet is associated with reduced risk of obesity and presents BMI-independent metabolic benefits in this large population-based study. Recommendation for adhering to DASH diet may benefit the prevention of obesity and related metabolic disorders in Chinese population.
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15
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Bell JA, Richardson TG, Wang Q, Sanderson E, Palmer T, Walker V, O'Keeffe LM, Timpson NJ, Cichonska A, Julkunen H, Würtz P, Holmes MV, Davey Smith G. Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study. THE LANCET REGIONAL HEALTH. EUROPE 2022; 21:100457. [PMID: 35832062 PMCID: PMC9272390 DOI: 10.1016/j.lanepe.2022.100457] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Background The direct effects of general adiposity (body mass index (BMI)) and central adiposity (waist-to-hip-ratio (WHR)) on circulating lipoproteins, lipids, and metabolites are unknown. Methods We used new metabolic data from UK Biobank (N=109,532, a five-fold higher N over previous studies). EDTA-plasma was used to quantify 249 traits with nuclear-magnetic-resonance spectroscopy including subclass-specific lipoprotein concentrations and lipid content, plus pre-glycemic and inflammatory metabolites. We used univariable and multivariable two-stage least-squares regression models with genetic risk scores for BMI and WHR as instruments to estimate total (unadjusted) and direct (mutually-adjusted) effects of BMI and WHR on metabolic traits; plus effects on statin use and interaction by sex, statin use, and age (proxy for medication use). Findings Higher BMI decreased apolipoprotein B and low-density lipoprotein cholesterol (LDL-C) before and after WHR-adjustment, whilst BMI increased triglycerides only before WHR-adjustment. These effects of WHR were larger and BMI-independent. Direct effects differed markedly by sex, e.g., triglycerides increased only with BMI among men, and only with WHR among women. Adiposity measures increased statin use and showed metabolic effects which differed by statin use and age. Among the youngest (38-53y, statins-5%), BMI and WHR (per-SD) increased LDL-C (total effects: 0.04-SD, 95%CI=-0.01,0.08 and 0.10-SD, 95%CI=0.02,0.17 respectively), but only WHR directly. Among the oldest (63-73y, statins-29%), BMI and WHR directly lowered LDL-C (-0.19-SD, 95%CI=-0.27,-0.11 and -0.05-SD, 95%CI=-0.16,0.06 respectively). Interpretation Excess adiposity likely raises atherogenic lipid and metabolite levels exclusively via adiposity stored centrally, particularly among women. Apparent effects of adiposity on lowering LDL-C are likely explained by an effect of adiposity on statin use. Funding UK Medical Research Council; British Heart Foundation; Novo Nordisk; National Institute for Health Research; Wellcome Trust; Cancer Research UK.
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Affiliation(s)
- Joshua A. Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom G. Richardson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK
| | - Qin Wang
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom Palmer
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Venexia Walker
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Linda M. O'Keeffe
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Public Health, Western Gateway Building, University College Cork, Ireland
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | | | | | - Michael V. Holmes
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit at the University of Oxford, Oxford, UK
- National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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16
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Eslam M, El-Serag HB, Francque S, Sarin SK, Wei L, Bugianesi E, George J. Metabolic (dysfunction)-associated fatty liver disease in individuals of normal weight. Nat Rev Gastroenterol Hepatol 2022; 19:638-651. [PMID: 35710982 DOI: 10.1038/s41575-022-00635-5] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/13/2022] [Indexed: 12/12/2022]
Abstract
Metabolic (dysfunction)-associated fatty liver disease (MAFLD) affects up to a third of the global population; its burden has grown in parallel with rising rates of type 2 diabetes mellitus and obesity. MAFLD increases the risk of end-stage liver disease, hepatocellular carcinoma, death and liver transplantation and has extrahepatic consequences, including cardiometabolic disease and cancers. Although typically associated with obesity, there is accumulating evidence that not all people with overweight or obesity develop fatty liver disease. On the other hand, a considerable proportion of patients with MAFLD are of normal weight, indicating the importance of metabolic health in the pathogenesis of the disease regardless of body mass index. The clinical profile, natural history and pathophysiology of patients with so-called lean MAFLD are not well characterized. In this Review, we provide epidemiological data on this group of patients and consider overall metabolic health and metabolic adaptation as a framework to best explain the pathogenesis of MAFLD and its heterogeneity in individuals of normal weight and in those who are above normal weight. This framework provides a conceptual schema for interrogating the MAFLD phenotype in individuals of normal weight that can translate to novel approaches for diagnosis and patient care.
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Affiliation(s)
- Mohammed Eslam
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, New South Wales, Australia.
| | - Hashem B El-Serag
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Sven Francque
- Department of Gastroenterology and Hepatology, Antwerp University Hospital, Antwerp, Belgium.,Laboratory of Experimental Medicine and Paediatrics (LEMP), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Shiv K Sarin
- Department of Hepatology, Institute of Liver and Biliary Sciences, New Delhi, India
| | - Lai Wei
- Hepatopancreatobiliary Center, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China
| | - Elisabetta Bugianesi
- Department of Medical Sciences, Division of Gastroenterology and Hepatology, A.O. Città della Salute e della Scienza di Torino, University of Turin, Turin, Italy
| | - Jacob George
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, New South Wales, Australia.
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17
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Szalanczy AM, Goff E, Seshie O, Deal A, Grzybowski M, Klotz J, Chuang Key CC, Geurts AM, Solberg Woods LC. Keratinocyte-associated protein 3 plays a role in body weight and adiposity with differential effects in males and females. Front Genet 2022; 13:942574. [PMID: 36212147 PMCID: PMC9535360 DOI: 10.3389/fgene.2022.942574] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/26/2022] [Indexed: 11/26/2022] Open
Abstract
Despite the obesity crisis in the United States, the underlying genetics are poorly understood. Our lab previously identified Keratinocyte-associated protein 3, Krtcap3, as a candidate gene for adiposity through a genome-wide association study in outbred rats, where increased liver expression of Krtcap3 correlated with decreased fat mass. Here we seek to confirm that Krtcap3 expression affects adiposity traits. To do so, we developed an in vivo whole-body Krtcap3 knock-out (KO) rat model. Wild-type (WT) and KO rats were placed onto a high-fat (HFD) or low-fat diet (LFD) at 6 weeks of age and were maintained on diet for 13 weeks, followed by assessments of metabolic health. We hypothesized that Krtcap3-KO rats will have increased adiposity and a worsened metabolic phenotype relative to WT. We found that KO male and female rats have significantly increased body weight versus WT, with the largest effect in females on a HFD. KO females also ate more and had greater adiposity, but were more insulin sensitive than WT regardless of diet condition. Although KO males weighed more than WT under both diet conditions, there were no differences in eating behavior or fat mass. Interestingly, KO males on a HFD were more insulin resistant than WT. This study confirms that Krtcap3 plays a role in body weight regulation and demonstrates genotype- and sex-specific effects on food intake, adiposity, and insulin sensitivity. Future studies will seek to better understand these sex differences, the role of diet, and establish a mechanism for Krtcap3 in obesity.
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Affiliation(s)
- Alexandria M. Szalanczy
- Department of Internal Medicine, School of Medicine, Wake Forest University, Winston Salem, NC, United States
| | - Emily Goff
- Department of Internal Medicine, School of Medicine, Wake Forest University, Winston Salem, NC, United States
| | - Osborne Seshie
- Department of Internal Medicine, School of Medicine, Wake Forest University, Winston Salem, NC, United States
| | - Aaron Deal
- Department of Internal Medicine, School of Medicine, Wake Forest University, Winston Salem, NC, United States
| | - Michael Grzybowski
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jason Klotz
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Chia-Chi Chuang Key
- Department of Internal Medicine, School of Medicine, Wake Forest University, Winston Salem, NC, United States
| | - Aron M. Geurts
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Leah C. Solberg Woods
- Department of Internal Medicine, School of Medicine, Wake Forest University, Winston Salem, NC, United States
- *Correspondence: Leah C. Solberg Woods,
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18
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Qi L. Nutrition for precision health: The time is now. Obesity (Silver Spring) 2022; 30:1335-1344. [PMID: 35785484 DOI: 10.1002/oby.23448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/13/2022] [Accepted: 03/21/2022] [Indexed: 11/11/2022]
Abstract
Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi-tiered "omics" makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene-diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.
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Affiliation(s)
- Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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19
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Agrawal S, Wang M, Klarqvist MDR, Smith K, Shin J, Dashti H, Diamant N, Choi SH, Jurgens SJ, Ellinor PT, Philippakis A, Claussnitzer M, Ng K, Udler MS, Batra P, Khera AV. Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots. Nat Commun 2022; 13:3771. [PMID: 35773277 PMCID: PMC9247093 DOI: 10.1038/s41467-022-30931-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/25/2022] [Indexed: 12/11/2022] Open
Abstract
For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not fully understood. Here, we study up to 38,965 UK Biobank participants with MRI-derived visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes. Because these fat depot volumes are highly correlated with BMI, we additionally study six local adiposity traits: VAT adjusted for BMI and height (VATadj), ASATadj, GFATadj, VAT/ASAT, VAT/GFAT, and ASAT/GFAT. We identify 250 independent common variants (39 newly-identified) associated with at least one trait, with many associations more pronounced in female participants. Rare variant association studies extend prior evidence for PDE3B as an important modulator of fat distribution. Local adiposity traits (1) highlight depot-specific genetic architecture and (2) enable construction of depot-specific polygenic scores that have divergent associations with type 2 diabetes and coronary artery disease. These results - using MRI-derived, BMI-independent measures of local adiposity - confirm fat distribution as a highly heritable trait with important implications for cardiometabolic health outcomes.
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Affiliation(s)
- Saaket Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Minxian Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | | | - Kirk Smith
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Joseph Shin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hesam Dashti
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nathaniel Diamant
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Seung Hoan Choi
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Sean J Jurgens
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Experimental Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anthony Philippakis
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Melina Claussnitzer
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kenney Ng
- Center for Computational Health, IBM Research, Cambridge, MA, USA
| | - Miriam S Udler
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Puneet Batra
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Verve Therapeutics, Cambridge, MA, USA.
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20
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Vabistsevits M, Davey Smith G, Sanderson E, Richardson TG, Lloyd-Lewis B, Richmond RC. Deciphering how early life adiposity influences breast cancer risk using Mendelian randomization. Commun Biol 2022; 5:337. [PMID: 35396499 PMCID: PMC8993830 DOI: 10.1038/s42003-022-03272-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 03/14/2022] [Indexed: 12/17/2022] Open
Abstract
Studies suggest that adiposity in childhood may reduce the risk of breast cancer in later life. The biological mechanism underlying this effect is unclear but is likely to be independent of body size in adulthood. Using a Mendelian randomization framework, we investigate 18 hypothesised mediators of the protective effect of childhood adiposity on later-life breast cancer, including hormonal, reproductive, physical, and glycaemic traits. Our results indicate that, while most of the hypothesised mediators are affected by childhood adiposity, only IGF-1 (OR: 1.08 [1.03: 1.15]), testosterone (total/free/bioavailable ~ OR: 1.12 [1.05: 1.20]), age at menopause (OR: 1.05 [1.03: 1.07]), and age at menarche (OR: 0.92 [0.86: 0.99], direct effect) influence breast cancer risk. However, multivariable Mendelian randomization analysis shows that the protective effect of childhood body size remains unaffected when accounting for these traits (ORs: 0.59-0.67). This suggests that none of the investigated potential mediators strongly contribute to the protective effect of childhood adiposity on breast cancer risk individually. It is plausible, however, that several related traits could collectively mediate the effect when analysed together, and this work provides a compelling foundation for investigating other mediating pathways in future studies.
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Affiliation(s)
- Marina Vabistsevits
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Eleanor Sanderson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Tom G Richardson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Novo Nordisk Research Centre, Headington, Oxford, OX3 7FZ, UK
| | - Bethan Lloyd-Lewis
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, Bristol, BS8 1TD, UK
| | - Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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21
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Wood AC, Arora A, Newell M, Bland VL, Zhou J, Pirastu N, Ordovas JM, Klimentidis YC. Identification of genetic loci simultaneously associated with multiple cardiometabolic traits. Nutr Metab Cardiovasc Dis 2022; 32:1027-1034. [PMID: 35168826 PMCID: PMC9275655 DOI: 10.1016/j.numecd.2022.01.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 12/09/2021] [Accepted: 01/04/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Cardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits. METHODS AND RESULTS We conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N = 356,574-456,823). Multiple loci reached genome-wide levels of significance (N = 145-333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P < 5 × 10-8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses. GRB14-COBLL1 showed the most consistent replication, revealing nominally significant associations (P < 0.05) with all traits except DBP. CONCLUSIONS Our analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.
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Affiliation(s)
- Alexis C Wood
- USDA/ARS Children's Nutrition Research Center, 1100 Bates Avenue, Houston, TX, USA.
| | - Amit Arora
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Michelle Newell
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Victoria L Bland
- Division of Geriatric Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jin Zhou
- Department of Biostatistics, University of California, Los Angeles, CA, USA
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, UK
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA; IMDEA-Food, Madrid, Spain
| | - Yann C Klimentidis
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA; BIO5 Institute, University of Arizona, Tucson, AZ, USA
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22
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Leyden GM, Shapland CY, Davey Smith G, Sanderson E, Greenwood MP, Murphy D, Richardson TG. Harnessing tissue-specific genetic variation to dissect putative causal pathways between body mass index and cardiometabolic phenotypes. Am J Hum Genet 2022; 109:240-252. [PMID: 35090585 DOI: 10.1016/j.ajhg.2021.12.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 12/14/2021] [Indexed: 12/11/2022] Open
Abstract
Body mass index (BMI) is a complex disease risk factor known to be influenced by genes acting via both metabolic pathways and appetite regulation. In this study, we aimed to gain insight into the phenotypic consequences of BMI-associated genetic variants, which may be mediated by their expression in different tissues. First, we harnessed meta-analyzed gene expression datasets derived from subcutaneous adipose (n = 1257) and brain (n = 1194) tissue to identify 86 and 140 loci, respectively, which provided evidence of genetic colocalization with BMI. These two sets of tissue-partitioned loci had differential effects with respect to waist-to-hip ratio, suggesting that the way they influence fat distribution might vary despite their having very similar average magnitudes of effect on BMI itself (adipose = 0.0148 and brain = 0.0149 standard deviation change in BMI per effect allele). For instance, BMI-associated variants colocalized with TBX15 expression in adipose tissue (posterior probability [PPA] = 0.97), but not when we used TBX15 expression data derived from brain tissue (PPA = 0.04) This gene putatively influences BMI via its role in skeletal development. Conversely, there were loci where BMI-associated variants provided evidence of colocalization with gene expression in brain tissue (e.g., NEGR1, PPA = 0.93), but not when we used data derived from adipose tissue, suggesting that these genes might be more likely to influence BMI via energy balance. Leveraging these tissue-partitioned variant sets through a multivariable Mendelian randomization framework provided strong evidence that the brain-tissue-derived variants are predominantly responsible for driving the genetically predicted effects of BMI on cardiovascular-disease endpoints (e.g., coronary artery disease: odds ratio = 1.05, 95% confidence interval = 1.04-1.07, p = 4.67 × 10-14). In contrast, our analyses suggested that the adipose tissue variants might predominantly be responsible for the underlying relationship between BMI and measures of cardiac function, such as left ventricular stroke volume (beta = 0.21, 95% confidence interval = 0.09-0.32, p = 6.43 × 10-4).
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23
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Altun I, Yan X, Ussar S. Immune Cell Regulation of White Adipose Progenitor Cell Fate. Front Endocrinol (Lausanne) 2022; 13:859044. [PMID: 35422761 PMCID: PMC9001836 DOI: 10.3389/fendo.2022.859044] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 02/28/2022] [Indexed: 02/03/2023] Open
Abstract
Adipose tissue is essential for energy storage and endocrine regulation of metabolism. Imbalance in energy intake and expenditure result in obesity causing adipose tissue dysfunction. This alters cellular composition of the stromal cell populations and their function. Moreover, the individual cellular composition of each adipose tissue depot, regulated by environmental factors and genetics, determines the ability of the depots to expand and maintain its endocrine and storage function. Thus, stromal cells modulate adipocyte function and vice versa. In this mini-review we discuss heterogeneity in terms of composition and fate of adipose progenitor subtypes and their interactions with and regulation by different immune cell populations. Immune cells are the most diverse cell populations in adipose tissue and play essential roles in regulating adipose tissue function via interaction with adipocytes but also with adipocyte progenitors. We specifically discuss the role of macrophages, mast cells, innate lymphoid cells and T cells in the regulation of adipocyte progenitor proliferation, differentiation and lineage commitment. Understanding the factors and cellular interactions regulating preadipocyte expansion and fate decision will allow the identification of novel mechanisms and therapeutic strategies to promote healthy adipose tissue expansion without systemic metabolic impairment.
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Affiliation(s)
- Irem Altun
- Research Group Adipocytes and Metabolism, Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Xiaocheng Yan
- Research Group Adipocytes and Metabolism, Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Siegfried Ussar
- Research Group Adipocytes and Metabolism, Institute for Diabetes and Obesity, Helmholtz Diabetes Center, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Department of Medicine, Technische Universität München, Munich, Germany
- *Correspondence: Siegfried Ussar,
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24
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Pal P, Palui R, Ray S. Heterogeneity of non-alcoholic fatty liver disease: Implications for clinical practice and research activity. World J Hepatol 2021; 13:1584-1610. [PMID: 34904031 PMCID: PMC8637673 DOI: 10.4254/wjh.v13.i11.1584] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 07/29/2021] [Accepted: 10/14/2021] [Indexed: 02/06/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a heterogeneous condition with a wide spectrum of clinical presentations and natural history and disease severity. There is also substantial inter-individual variation and variable response to a different therapy. This heterogeneity of NAFLD is in turn influenced by various factors primarily demographic/dietary factors, metabolic status, gut microbiome, genetic predisposition together with epigenetic factors. The differential impact of these factors over a variable period of time influences the clinical phenotype and natural history. Failure to address heterogeneity partly explains the sub-optimal response to current and emerging therapies for fatty liver disease. Consequently, leading experts across the globe have recently suggested a change in nomenclature of NAFLD to metabolic-associated fatty liver disease (MAFLD) which can better reflect current knowledge of heterogeneity and does not exclude concomitant factors for fatty liver disease (e.g. alcohol, viral hepatitis, etc.). Precise identification of disease phenotypes is likely to facilitate clinical trial recruitment and expedite translational research for the development of novel and effective therapies for NAFLD/MAFLD.
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Affiliation(s)
- Partha Pal
- Department of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad 500082, India
| | - Rajan Palui
- Department of Endocrinology, The Mission Hospital, Durgapur 713212, West Bengal, India
| | - Sayantan Ray
- Department of Endocrinology, Jagannath Gupta Institute of Medical Sciences and Hospital, Kolkata 700137, West Bengal, India
- Diabetes and Endocrinology, Apollo Clinic, Ballygunge, Kolkata 700019, West Bengal, India
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25
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Kim HS, Jung CH. Metabolically Healthy Obesity: Is It Really a Benign Condition? J Obes Metab Syndr 2021; 30:1-3. [PMID: 33653972 PMCID: PMC8017328 DOI: 10.7570/jomes21011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/11/2021] [Accepted: 02/18/2021] [Indexed: 11/05/2022] Open
Affiliation(s)
- Hwi Seung Kim
- Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.,Asan Diabetes Center, Asan Medical Center, Seoul, Korea
| | - Chang Hee Jung
- Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.,Asan Diabetes Center, Asan Medical Center, Seoul, Korea
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26
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Park JM, Park DH, Song Y, Kim JO, Choi JE, Kwon YJ, Kim SJ, Lee JW, Hong KW. Understanding the genetic architecture of the metabolically unhealthy normal weight and metabolically healthy obese phenotypes in a Korean population. Sci Rep 2021; 11:2279. [PMID: 33500527 PMCID: PMC7838176 DOI: 10.1038/s41598-021-81940-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/14/2021] [Indexed: 01/30/2023] Open
Abstract
Understanding the mechanisms underlying the metabolically unhealthy normal weight (MUHNW) and metabolically healthy obese (MHO) phenotypes is important for developing strategies to prevent cardiometabolic diseases. Here, we conducted genome-wide association studies (GWASs) to identify the MUHNW and MHO genetic indices. The study dataset comprised genome-wide single-nucleotide polymorphism genotypes and epidemiological data from 49,915 subjects categorised into four phenotypes-metabolically healthy normal weight (MHNW), MUHNW, MHO, and metabolically unhealthy obese (MUHO). We conducted two GWASs using logistic regression analyses and adjustments for confounding variables (model 1: MHNW versus MUHNW and model 2: MHO versus MUHO). GCKR, ABCB11, CDKAL1, LPL, CDKN2B, NT5C2, APOA5, CETP, and APOC1 were associated with metabolically unhealthy phenotypes among normal weight individuals (model 1). LPL, APOA5, and CETP were associated with metabolically unhealthy phenotypes among obese individuals (model 2). The genes common to both models are related to lipid metabolism (LPL, APOA5, and CETP), and those associated with model 1 are related to insulin or glucose metabolism (GCKR, CDKAL1, and CDKN2B). This study reveals the genetic architecture of the MUHNW and MHO phenotypes in a Korean population-based cohort. These findings could help identify individuals at a high metabolic risk in normal weight and obese populations and provide potential novel targets for the management of metabolically unhealthy phenotypes.
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Affiliation(s)
- Jae-Min Park
- grid.15444.300000 0004 0470 5454Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju‐ro, Gangnam-gu, Seoul, 06273 Korea ,grid.15444.300000 0004 0470 5454Department of Medicine, Graduate School of Medicine, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722 Korea
| | - Da-Hyun Park
- Theragen Bio Co., Ltd., 145 Gwanggyo-ro, Suwon-si, Gyeonggi-do 16229 Korea
| | - Youhyun Song
- grid.15444.300000 0004 0470 5454Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju‐ro, Gangnam-gu, Seoul, 06273 Korea
| | - Jung Oh Kim
- Theragen Bio Co., Ltd., 145 Gwanggyo-ro, Suwon-si, Gyeonggi-do 16229 Korea
| | - Ja-Eun Choi
- Theragen Bio Co., Ltd., 145 Gwanggyo-ro, Suwon-si, Gyeonggi-do 16229 Korea
| | - Yu-Jin Kwon
- grid.15444.300000 0004 0470 5454Department of Family Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, 363 Dongbaekjukjeon-daero, Giheung-gu, Yongin-si, Gyeonggi-do 16995 Korea
| | - Seong-Jin Kim
- Theragen Bio Co., Ltd., 145 Gwanggyo-ro, Suwon-si, Gyeonggi-do 16229 Korea
| | - Ji-Won Lee
- grid.15444.300000 0004 0470 5454Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju‐ro, Gangnam-gu, Seoul, 06273 Korea
| | - Kyung-Won Hong
- Theragen Bio Co., Ltd., 145 Gwanggyo-ro, Suwon-si, Gyeonggi-do 16229 Korea
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Andrade S, Morais T, Sandovici I, Seabra AL, Constância M, Monteiro MP. Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review. Front Endocrinol (Lausanne) 2021; 12:681649. [PMID: 34290669 PMCID: PMC8288106 DOI: 10.3389/fendo.2021.681649] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 05/26/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Obesity is a major risk factor for dysglycemic disorders, including type 2 diabetes (T2D). However, there is wide phenotypic variation in metabolic profiles. Tissue-specific epigenetic modifications could be partially accountable for the observed phenotypic variability. SCOPE The aim of this systematic review was to summarize the available data on epigenetic signatures in human adipose tissue (AT) that characterize overweight or obesity-related insulin resistance (IR) and dysglycemia states and to identify potential underlying mechanisms through the use of unbiased bioinformatics approaches. METHODS Original data published in the last decade concerning the comparison of epigenetic marks in human AT of individuals with metabolically unhealthy overweight/obesity (MUHO) versus normal weight individuals or individuals with metabolically healthy overweight/obesity (MHO) was assessed. Furthermore, association of these epigenetic marks with IR/dysglycemic traits, including T2D, was compiled. RESULTS We catalogued more than two thousand differentially methylated regions (DMRs; above the cut-off of 5%) in the AT of individuals with MUHO compared to individuals with MHO. These DNA methylation changes were less likely to occur around the promoter regions and were enriched at loci implicated in intracellular signaling (signal transduction mediated by small GTPases, ERK1/2 signaling and intracellular trafficking). We also identified a network of seven transcription factors that may play an important role in targeting DNA methylation changes to specific genes in the AT of subjects with MUHO, contributing to the pathogeny of obesity-related IR/T2D. Furthermore, we found differentially methylated CpG sites at 8 genes that were present in AT and whole blood, suggesting that DMRs in whole blood could be potentially used as accessible biomarkers of MUHO. CONCLUSIONS The overall evidence linking epigenetic alterations in key tissues such AT to metabolic complications in human obesity is still very limited, highlighting the need for further studies, particularly those focusing on epigenetic marks other than DNA methylation. Our initial analysis suggests that DNA methylation patterns can potentially discriminate between MUHO from MHO and provide new clues into why some people with obesity are less susceptible to dysglycemia. Identifying AT-specific epigenetic targets could also lead to novel approaches to modify the progression of individuals with obesity towards metabolic disease. SYSTEMATIC REVIEW REGISTRATION PROSPERO, identifier CRD42021227237.
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Affiliation(s)
- Sara Andrade
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Tiago Morais
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Ionel Sandovici
- University of Cambridge Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Institute of Metabolic Science, Addenbrookes Hospital, Cambridge, United Kingdom
- Department of Obstetrics and Gynaecology and National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, United Kingdom
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
| | - Alexandre L. Seabra
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Miguel Constância
- University of Cambridge Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Institute of Metabolic Science, Addenbrookes Hospital, Cambridge, United Kingdom
- Department of Obstetrics and Gynaecology and National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, United Kingdom
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
- National Institute of Health Research, Cambridge Biomedical Research Centre, Cambridge, United Kingdom
| | - Mariana P. Monteiro
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
- *Correspondence: Mariana P. Monteiro,
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Liao C, Gao W, Cao W, Lv J, Yu C, Wang S, Pang Z, Cong L, Wang H, Wu X, Li L. Associations of Metabolic/Obesity Phenotypes with Insulin Resistance and C-Reactive Protein: Results from the CNTR Study. Diabetes Metab Syndr Obes 2021; 14:1141-1151. [PMID: 33758523 PMCID: PMC7979357 DOI: 10.2147/dmso.s298499] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 02/17/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Obesity is a heterogeneous condition in terms of metabolic status. Different obesity phenotypes have various health risks. The aim of this work was to define different subtypes of obesity and investigate their relationship with inflammatory-cardiometabolic abnormalities among Chinese adult twins. METHODS The analyses used data from 1113 adult twins in 4 provinces (Shandong, Zhejiang, Jiangsu and Sichuan) from Chinese National Twin Registry (CNTR) which collected detailed information. We defined those with 0 or 1 metabolic syndrome (MetS) components excluding waist circumference as metabolically healthy, and those with waist circumference ≥90 cm (for men) and ≥85 cm (for women) as obese. The two-category obesity status and metabolic states are combined to generate four metabolic/obesity phenotypes. High sensitivity C reactive protein (hsCRP) was measured to assess underlying inflammation and homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as surrogate measure of insulin resistance. Mixed-effect linear regression models and fixed-effect linear regression models were used to analyse the correlation between HOMA-IR, hsCRP and different metabolic/obesity phenotypes. RESULTS In cross-sectional analyses of 1113 individuals (mean [SD] age, 46.6 [12.9] years; 463 obese [41.6%]), 20.3% obese twins were metabolic healthy and 64.2% non-obese twins were metabolic unhealthy. Serum HOMA-IR level was higher in metabolically unhealthy non-obesity (MUNO) (β=0.42, 95% CI: 0.21-0.64), metabolically healthy obesity (MHO) (β=0.68, 95% CI: 0.36-1.00) and metabolically unhealthy obesity (MUO) (β=0.69, 95% CI: 0.46-0.91) twins, compared with their metabolically healthy non-obesity (MHNO) counterparts. HsCRP was similar between MHO and MUO, which differed significantly to metabolic healthy non-obesity (MHNO). CONCLUSION MHO and MUNO phenotypes were common in Chinese twin population. Both phenotypes were associated with elevated IR and hsCRP which may not be benign and need to be concerned.
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Affiliation(s)
- Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
- Correspondence: Liming Li; Wenjing Gao Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 XueYuan Road, HaiDian District, Beijing, 100191, People’s Republic of ChinaTel +86 10 82801528Fax +86 10 82801528 Ext. 322 Email ;
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
| | - Shengfeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
| | - Zengchang Pang
- Qingdao Center for Diseases Control and Prevention, Qingdao, 266033, People’s Republic of China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, People’s Republic of China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, 210009, People’s Republic of China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, People’s Republic of China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, People’s Republic of China
- Correspondence: Liming Li; Wenjing Gao Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 XueYuan Road, HaiDian District, Beijing, 100191, People’s Republic of ChinaTel +86 10 82801528Fax +86 10 82801528 Ext. 322 Email ;
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English J, Son JM, Cardamone MD, Lee C, Perissi V. Decoding the rosetta stone of mitonuclear communication. Pharmacol Res 2020; 161:105161. [PMID: 32846213 PMCID: PMC7755734 DOI: 10.1016/j.phrs.2020.105161] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 08/04/2020] [Accepted: 08/14/2020] [Indexed: 12/12/2022]
Abstract
Cellular homeostasis in eukaryotic cells requires synchronized coordination of multiple organelles. A key role in this stage is played by mitochondria, which have recently emerged as highly interconnected and multifunctional hubs that process and coordinate diverse cellular functions. Beyond producing ATP, mitochondria generate key metabolites and are central to apoptotic and metabolic signaling pathways. Because most mitochondrial proteins are encoded in the nuclear genome, the biogenesis of new mitochondria and the maintenance of mitochondrial functions and flexibility critically depend upon effective mitonuclear communication. This review addresses the complex network of signaling molecules and pathways allowing mitochondria-nuclear communication and coordinated regulation of their independent but interconnected genomes, and discusses the extent to which dynamic communication between the two organelles has evolved for mutual benefit and for the overall maintenance of cellular and organismal fitness.
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Affiliation(s)
- Justin English
- Department of Biochemistry, Boston University, Boston, MA, 02115, USA; Graduate Program in Biomolecular Pharmacology, Department of Pharmacology and Experimental Therapeutics, Boston University, Boston, MA, 02115, USA
| | - Jyung Mean Son
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | | | - Changhan Lee
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA; USC Norris Comprehensive Cancer Center, Los Angeles, CA, 90089, USA; Biomedical Sciences, Graduate School, Ajou University, Suwon, 16499, South Korea
| | - Valentina Perissi
- Department of Biochemistry, Boston University, Boston, MA, 02115, USA.
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30
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Krishnan M, Murphy R, Okesene-Gafa KAM, Ji M, Thompson JMD, Taylor RS, Merriman TR, McCowan LME, McKinlay CJD. The Pacific-specific CREBRF rs373863828 allele protects against gestational diabetes mellitus in Māori and Pacific women with obesity. Diabetologia 2020; 63:2169-2176. [PMID: 32654027 DOI: 10.1007/s00125-020-05202-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 05/06/2020] [Indexed: 01/13/2023]
Abstract
AIMS/HYPOTHESIS The CREBRF rs373863828 minor (A) allele is associated with increased BMI but reduced prevalence of type 2 diabetes in Māori and Pacific people. Given the shared aetiology of type 2 diabetes and gestational diabetes mellitus (GDM), we tested for an association between the CREBRF rs373863828 variant and GDM. METHODS We conducted a prospective cohort study of Māori and Pacific women nested within a nutritional intervention study for pregnant women with obesity. Women were enrolled at 12-17 weeks' gestation and underwent anthropometry and collection of buffy coats for later genetic testing. GDM was diagnosed by 75 g OGTT at 24-28 weeks' gestation using the International Association of Diabetes and Pregnancy Study Groups criteria. Genotyping was performed by real-time PCR with a custom CREBRF rs373863828 probe-set. The association between CREBRF rs373863828 and GDM was analysed separately by ethnic group using logistic regression, with effect estimates combined in a meta-analysis. RESULTS Of 112 Māori and Pacific pregnant women with obesity, 31 (28%) carried the CREBRF rs373863828 A allele (A/G or A/A) and 35 (31%) developed GDM. Women who carried the CREBRF rs373863828 A allele did not differ in BMI when compared with non-carriers (G/G). There was a fivefold reduction in the likelihood of GDM per CREBRF rs373863828 A allele (OR 0.19 [95% CI 0.05, 0.69], p = 0.01), independent of age, BMI and family history of diabetes (adjusted OR 0.13 [95% CI 0.03, 0.53], p = 0.004). GDM was diagnosed in 10% and 40% of women with and without the CREBRF rs373863828 A allele, respectively (no woman with the A/A genotype developed GDM). CONCLUSIONS/INTERPRETATION The CREBRF rs373863828 (A) allele is associated with reduced likelihood of GDM in Māori and Pacific women with obesity and may improve GDM risk prediction. Graphical abstract.
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Affiliation(s)
- Mohanraj Krishnan
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
| | - Rinki Murphy
- Department of Medicine, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
- Counties Manukau Health, Auckland, New Zealand.
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand.
| | - Karaponi A M Okesene-Gafa
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Counties Manukau Health, Auckland, New Zealand
| | - Maria Ji
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - John M D Thompson
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Department of Paediatrics, University of Auckland, Auckland, New Zealand
| | - Rennae S Taylor
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
| | - Tony R Merriman
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Lesley M E McCowan
- Department of Obstetrics and Gynaecology, University of Auckland, Auckland, New Zealand
- Counties Manukau Health, Auckland, New Zealand
| | - Christopher J D McKinlay
- Counties Manukau Health, Auckland, New Zealand.
- Liggins Institute, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
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31
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Smith GI, Mittendorfer B, Klein S. Metabolically healthy obesity: facts and fantasies. J Clin Invest 2020; 129:3978-3989. [PMID: 31524630 DOI: 10.1172/jci129186] [Citation(s) in RCA: 326] [Impact Index Per Article: 81.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Although obesity is typically associated with metabolic dysfunction and cardiometabolic diseases, some people with obesity are protected from many of the adverse metabolic effects of excess body fat and are considered "metabolically healthy." However, there is no universally accepted definition of metabolically healthy obesity (MHO). Most studies define MHO as having either 0, 1, or 2 metabolic syndrome components, whereas many others define MHO using the homeostasis model assessment of insulin resistance (HOMA-IR). Therefore, numerous people reported as having MHO are not metabolically healthy, but simply have fewer metabolic abnormalities than those with metabolically unhealthy obesity (MUO). Nonetheless, a small subset of people with obesity have a normal HOMA-IR and no metabolic syndrome components. The mechanism(s) responsible for the divergent effects of obesity on metabolic health is not clear, but studies conducted in rodent models suggest that differences in adipose tissue biology in response to weight gain can cause or prevent systemic metabolic dysfunction. In this article, we review the definition, stability over time, and clinical outcomes of MHO, and discuss the potential factors that could explain differences in metabolic health in people with MHO and MUO - specifically, modifiable lifestyle factors and adipose tissue biology. Better understanding of the factors that distinguish people with MHO and MUO can produce new insights into mechanism(s) responsible for obesity-related metabolic dysfunction and disease.
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Abstract
This review addresses the interplay between obesity, type 2 diabetes mellitus, and cardiovascular diseases. It is proposed that obesity, generally defined by an excess of body fat causing prejudice to health, can no longer be evaluated solely by the body mass index (expressed in kg/m2) because it represents a heterogeneous entity. For instance, several cardiometabolic imaging studies have shown that some individuals who have a normal weight or who are overweight are at high risk if they have an excess of visceral adipose tissue-a condition often accompanied by accumulation of fat in normally lean tissues (ectopic fat deposition in liver, heart, skeletal muscle, etc). On the other hand, individuals who are overweight or obese can nevertheless be at much lower risk than expected when faced with excess energy intake if they have the ability to expand their subcutaneous adipose tissue mass, particularly in the gluteal-femoral area. Hence, excessive amounts of visceral adipose tissue and of ectopic fat largely define the cardiovascular disease risk of overweight and moderate obesity. There is also a rapidly expanding subgroup of patients characterized by a high accumulation of body fat (severe obesity). Severe obesity is characterized by specific additional cardiovascular health issues that should receive attention. Because of the difficulties of normalizing body fat content in patients with severe obesity, more aggressive treatments have been studied in this subgroup of individuals such as obesity surgery, also referred to as metabolic surgery. On the basis of the above, we propose that we should refer to obesities rather than obesity.
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Affiliation(s)
- Marie-Eve Piché
- From the Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval (M.-E.P., A.T., J.-P.D.), Université Laval, Québec, QC, Canada.,Department of Medicine, Faculty of Medicine (M.-E.P.), Université Laval, Québec, QC, Canada
| | - André Tchernof
- From the Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval (M.-E.P., A.T., J.-P.D.), Université Laval, Québec, QC, Canada.,School of Nutrition (A.T.), Université Laval, Québec, QC, Canada
| | - Jean-Pierre Després
- From the Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval (M.-E.P., A.T., J.-P.D.), Université Laval, Québec, QC, Canada.,Vitam - Centre de recherche en santé durable, CIUSSS - Capitale-Nationale (J.-P.D.), Université Laval, Québec, QC, Canada.,Department of Kinesiology, Faculty of Medicine (J.-P.D.), Université Laval, Québec, QC, Canada
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Eslam M, Sanyal AJ, George J, Neuschwander-Tetri B, Tiribelli C, Kleiner DE, Brunt E, Bugianesi E, Yki-Järvinen H, Grønbæk H, Cortez-Pinto H, George J, Fan J, Valenti L, Abdelmalek M, Romero-Gomez M, Rinella M, Arrese M, Eslam M, Bedossa P, Newsome PN, Anstee QM, Jalan R, Bataller R, Loomba R, Sookoian S, Sarin SK, Harrison S, Kawaguchi T, Wong VWS, Ratziu V, Yilmaz Y, Younossi Z. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology 2020; 158:1999-2014.e1. [PMID: 32044314 DOI: 10.1053/j.gastro.2019.11.312] [Citation(s) in RCA: 1726] [Impact Index Per Article: 431.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 10/27/2019] [Accepted: 11/05/2019] [Indexed: 12/02/2022]
Abstract
Fatty liver associated with metabolic dysfunction is common, affects a quarter of the population, and has no approved drug therapy. Although pharmacotherapies are in development, response rates appear modest. The heterogeneous pathogenesis of metabolic fatty liver diseases and inaccuracies in terminology and definitions necessitate a reappraisal of nomenclature to inform clinical trial design and drug development. A group of experts sought to integrate current understanding of patient heterogeneity captured under the acronym nonalcoholic fatty liver disease (NAFLD) and provide suggestions on terminology that more accurately reflects pathogenesis and can help in patient stratification for management. Experts reached consensus that NAFLD does not reflect current knowledge, and metabolic (dysfunction) associated fatty liver disease "MAFLD" was suggested as a more appropriate overarching term. This opens the door for efforts from the research community to update the nomenclature and subphenotype the disease to accelerate the translational path to new treatments.
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Affiliation(s)
- Mohammed Eslam
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, NSW, Australia.
| | - Arun J Sanyal
- Virginia Commonwealth University School of Medicine, Richmond, Virginia.
| | - Jacob George
- Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, NSW, Australia.
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34
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Yeh HC, Li CC, Chien TM, Li CY, Cheng YC, Woldu SL, Robyak H, Huang CN, Ke HL, Li WM, Lee HY, Yeh BW, Yang SF, Tu HP, Sagalowsky AI, Raman JD, Singla N, Margulis V, Lotan Y, Hsieh JT, Wu WJ. Interethnic differences in the impact of body mass index on upper tract urothelial carcinoma following radical nephroureterectomy. World J Urol 2020; 39:491-500. [PMID: 32318857 DOI: 10.1007/s00345-020-03204-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 04/08/2020] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Inconsistent prognostic implications of body mass index (BMI) in upper tract urothelial carcinoma (UTUC) have been reported across different ethnicities. In this study, we aimed to analyze the oncologic role of BMI in Asian and Caucasian patients with UTUC. METHODS We retrospectively collected data from 648 Asian Taiwanese and 213 Caucasian American patients who underwent radical nephroureterectomy for UTUC. We compared clinicopathologic features among groups categorized by different BMI. Kaplan-Meier method and Cox regression model were used to examine the impact of BMI on recurrence and survival by ethnicity. RESULTS According to ethnicity-specific criteria, overweight and obesity were found in 151 (23.2%) and 215 (33.2%) Asians, and 79 (37.1%) and 78 (36.6%) Caucasians, respectively. No significant association between BMI and disease characteristics was detected in both ethnicities. On multivariate analysis, overweight and obese Asians had significantly lower recurrence than those with normal weight (HR 0.631, 95% CI 0.413-0.966; HR 0.695, 95% CI 0.493-0.981, respectively), and obesity was an independent prognostic factor for favorable cancer-specific and overall survival (HR 0.521, 95% CI 0.342-0.794; HR 0.545, 95% CI 0.386-0.769, respectively). There was no significant difference in outcomes among normal, overweight and obese Caucasians, but obese patients had a relatively poorer 5-year RFS, CSS, and OS rates of 52.8%, 60.5%, and 47.2%, compared to 54.9%, 69.1%, and 54.9% for normal weight patients. CONCLUSION Higher BMI was associated with improved outcomes in Asian patients with UTUC. Interethnic differences could influence preoperative counseling or prediction modeling in patients with UTUC.
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Affiliation(s)
- Hsin-Chih Yeh
- Department of Urology, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan.,Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Ching-Chia Li
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Tsu-Ming Chien
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Chia-Yang Li
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No. 100 Tzyou 1st Road, Kaohsiung, 807, Taiwan
| | - Yen-Chen Cheng
- Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
| | - Solomon L Woldu
- Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Haley Robyak
- Division of Urology, Department of Surgery, Penn State Health Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Chun-Nung Huang
- Department of Urology, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan.,Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hung-Lung Ke
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Wei-Ming Li
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hsiang-Ying Lee
- Department of Urology, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan.,Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.,Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No. 100 Tzyou 1st Road, Kaohsiung, 807, Taiwan
| | - Bi-Wen Yeh
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Sheau-Fang Yang
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No. 100 Tzyou 1st Road, Kaohsiung, 807, Taiwan.,Department of Pathology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hung-Pin Tu
- Department of Public Health and Environmental Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Arthur I Sagalowsky
- Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Jay D Raman
- Division of Urology, Department of Surgery, Penn State Health Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Nirmish Singla
- Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA.
| | - Vitaly Margulis
- Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Yair Lotan
- Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Jer-Tsong Hsieh
- Department of Urology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA. .,Department of Biotechnology, College of Life Science, Kaohsiung Medical University, Kaohsiung, Taiwan.
| | - Wen-Jeng Wu
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan. .,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. .,Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No. 100 Tzyou 1st Road, Kaohsiung, 807, Taiwan.
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Cirera S, Taşöz E, Juul Jacobsen M, Schumacher-Petersen C, Østergaard Christoffersen B, Kaae Kirk R, Pagh Ludvigsen T, Hvid H, Duelund Pedersen H, Høier Olsen L, Fredholm M. The expression signatures in liver and adipose tissue from obese Göttingen Minipigs reveal a predisposition for healthy fat accumulation. Nutr Diabetes 2020; 10:9. [PMID: 32205840 PMCID: PMC7090036 DOI: 10.1038/s41387-020-0112-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 01/14/2020] [Accepted: 01/20/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Model animals are valuable resources for dissecting basic aspects of the regulation of obesity and metabolism. The translatability of results relies on understanding comparative aspects of molecular pathophysiology. Several studies have shown that despite the presence of overt obesity and dyslipidemia in the pig key human pathological hepatic findings such as hepatocellular ballooning and abundant steatosis are lacking in the model. OBJECTIVES The aim of this study was to elucidate why these histopathological characteristics did not occur in a high fat, fructose and cholesterol (FFC) diet-induced obese Göttingen Minipig model. METHODS High-throughput expression profiling of more than 90 metabolically relevant genes was performed in liver, subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) of male minipigs diet fed: standard chow (SD, n = 7); FFC diet (n = 14); FFC diet in streptozotocin-induced diabetic pigs (FFCDIA, n = 8). Moreover, histopathological assessment of SAT and VAT was performed. RESULTS 12, 4 and 1 genes were highly significantly differentially expressed in liver, SAT and VAT when comparing the FFC and SD groups whereas the corresponding numbers were 15, 2, and 1 when comparing the FFCDIA and SD groups. Although the minipigs in both FFC groups developed sever obesity and dyslipidemia, the insulin-signaling pathways were not affected. Notably, four genes involved in lipid acquisition and removal, were highly deregulated in the liver: PPARG, LPL, CD36 and FABP4. These genes have been reported to play a major role in promoting hepatic steatosis in rodents and humans. Since very little macrophage-associated pro-inflammatory response was detected in the adipose tissues the expansion appears to have no adverse impact on adipose tissue metabolism. CONCLUSION The study shows that morbidly obese Göttingen Minipigs are protected against many of the metabolic and hepatic abnormalities associated with obesity due to a remarkable ability to expand the adipose compartments to accommodate excess calories.
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Affiliation(s)
- Susanna Cirera
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark
| | - Emirhan Taşöz
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark
| | - Mette Juul Jacobsen
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark
| | - Camilla Schumacher-Petersen
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark
| | | | - Rikke Kaae Kirk
- Global Drug Discovery, Novo Nordisk A/S, Novo Nordisk Park, Måløv, Denmark
| | | | - Henning Hvid
- Global Drug Discovery, Novo Nordisk A/S, Novo Nordisk Park, Måløv, Denmark
| | - Henrik Duelund Pedersen
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark
- Ellegaard Gottingen Minipigs A/S, Sorø Landevej 302, 4261, Dalmose, Denmark
| | - Lisbeth Høier Olsen
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark
| | - Merete Fredholm
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, 1870, Frederiksberg, Denmark.
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Fathzadeh M, Li J, Rao A, Cook N, Chennamsetty I, Seldin M, Zhou X, Sangwung P, Gloudemans MJ, Keller M, Attie A, Yang J, Wabitsch M, Carcamo-Orive I, Tada Y, Lusis AJ, Shin MK, Molony CM, McLaughlin T, Reaven G, Montgomery SB, Reilly D, Quertermous T, Ingelsson E, Knowles JW. FAM13A affects body fat distribution and adipocyte function. Nat Commun 2020; 11:1465. [PMID: 32193374 PMCID: PMC7081215 DOI: 10.1038/s41467-020-15291-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 02/20/2020] [Indexed: 02/06/2023] Open
Abstract
Genetic variation in the FAM13A (Family with Sequence Similarity 13 Member A) locus has been associated with several glycemic and metabolic traits in genome-wide association studies (GWAS). Here, we demonstrate that in humans, FAM13A alleles are associated with increased FAM13A expression in subcutaneous adipose tissue (SAT) and an insulin resistance-related phenotype (e.g. higher waist-to-hip ratio and fasting insulin levels, but lower body fat). In human adipocyte models, knockdown of FAM13A in preadipocytes accelerates adipocyte differentiation. In mice, Fam13a knockout (KO) have a lower visceral to subcutaneous fat (VAT/SAT) ratio after high-fat diet challenge, in comparison to their wild-type counterparts. Subcutaneous adipocytes in KO mice show a size distribution shift toward an increased number of smaller adipocytes, along with an improved adipogenic potential. Our results indicate that GWAS-associated variants within the FAM13A locus alter adipose FAM13A expression, which in turn, regulates adipocyte differentiation and contribute to changes in body fat distribution.
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Affiliation(s)
- Mohsen Fathzadeh
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Jiehan Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Abhiram Rao
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Bioengineering Department, School of Engineering and Medicine, Stanford, CA, USA
| | - Naomi Cook
- Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Indumathi Chennamsetty
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Marcus Seldin
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Xiang Zhou
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Panjamaporn Sangwung
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | | | - Mark Keller
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA
| | - Allan Attie
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA
| | - Jing Yang
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Martin Wabitsch
- Division of Paediatric Endocrinology and Diabetes, Department of Paediatrics and Adolescent Medicine, University of Ulm, Ulm, Germany
| | - Ivan Carcamo-Orive
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Yuko Tada
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Aldons J Lusis
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Myung Kyun Shin
- Genetics and Pharmacogenomics, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Cliona M Molony
- Genetics and Pharmacogenomics, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Tracey McLaughlin
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Endocrinology, Stanford University School of Medicine, Stanford, CA, USA
| | - Gerald Reaven
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Stephen B Montgomery
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University, California, CA, USA
- Department of Medicine, Division of Endocrinology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University, California, CA, USA
| | - Dermot Reilly
- Genetics and Pharmacogenomics, Merck & Co., Inc., Kenilworth, NJ, USA
| | - Thomas Quertermous
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA.
| | - Joshua W Knowles
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA.
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Baranowska-Bik A, Bik W. The Association of Obesity with Autoimmune Thyroiditis and Thyroid Function-Possible Mechanisms of Bilateral Interaction. Int J Endocrinol 2020; 2020:8894792. [PMID: 33381173 PMCID: PMC7755496 DOI: 10.1155/2020/8894792] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 11/28/2020] [Accepted: 12/04/2020] [Indexed: 12/17/2022] Open
Abstract
A growing number of patients suffer from autoimmune diseases, including autoimmune thyroid disease. There has simultaneously been a significant increase in the prevalence of obesity worldwide. It is still an open question whether adiposity can directly influence activation of inflammatory processes affecting the thyroid in genetically predisposed individuals. Adipokines, biologically active substances derived from the adipocytes, belong to a heterogenic group of compounds involved in numerous physiological functions, including the maintenance of metabolism, hormonal balance, and immune response. Notably, the presence of obesity worsens the course of selected autoimmune diseases and impairs response to treatment. Moreover, the excess of body fat may result in the progression of autoimmune diseases. Nutritional status, body weight, and energy expenditure may influence thyroid hormone secretion. Interestingly, thyroid hormones might influence the activity of adipose tissue as metabolic alterations related to fat tissue are observed under pathological conditions in which there are deficits or overproduction of thyroid hormones. Functioning TSH receptors are expressed on adipocytes. Thermogenesis may presumably be stimulated by TSH binding to its receptor on brown adipocytes. There could be a bilateral interaction between the thyroid and adipose. Obesity may influence the onset and course of autoimmune disease.
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Affiliation(s)
- Agnieszka Baranowska-Bik
- Department of Endocrinology, Centre of Postgraduate Medical Education, Ceglowska 80, Warsaw 01-809, Poland
| | - Wojciech Bik
- Department of Neuroendocrinology, Centre of Postgraduate Medical Education, Marymoncka 99/103, Warsaw 01-813, Poland
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Genetic contributions to NAFLD: leveraging shared genetics to uncover systems biology. Nat Rev Gastroenterol Hepatol 2020; 17:40-52. [PMID: 31641249 DOI: 10.1038/s41575-019-0212-0] [Citation(s) in RCA: 186] [Impact Index Per Article: 46.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/05/2019] [Indexed: 12/14/2022]
Abstract
Nonalcoholic fatty liver disease (NAFLD) affects around a quarter of the global population, paralleling worldwide increases in obesity and metabolic syndrome. NAFLD arises in the context of systemic metabolic dysfunction that concomitantly amplifies the risk of cardiovascular disease and diabetes. These interrelated conditions have long been recognized to have a heritable component, and advances using unbiased association studies followed by functional characterization have created a paradigm for unravelling the genetic architecture of these conditions. A novel perspective is to characterize the shared genetic basis of NAFLD and other related disorders. This information on shared genetic risks and their biological overlap should in future enable the development of precision medicine approaches through better patient stratification, and enable the identification of preventive and therapeutic strategies. In this Review, we discuss current knowledge of the genetic basis of NAFLD and of possible pleiotropy between NAFLD and other liver diseases as well as other related metabolic disorders. We also discuss evidence of causality in NAFLD and other related diseases and the translational significance of such evidence, and future challenges from the study of genetic pleiotropy.
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Efremov L, Lacruz ME, Tiller D, Medenwald D, Greiser KH, Kluttig A, Wienke A, Nuding S, Mikolajczyk R. Metabolically Healthy, but Obese Individuals and Associations with Echocardiographic Parameters and Inflammatory Biomarkers: Results from the CARLA Study. Diabetes Metab Syndr Obes 2020; 13:2653-2665. [PMID: 32821138 PMCID: PMC7419616 DOI: 10.2147/dmso.s263727] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 07/02/2020] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION The research on heterogeneity among obese individuals has identified the metabolically healthy, but obese (MHO) phenotype as a distinct group that does not experience the typical cardiovascular-related diseases (CVD). It is unclear if this group differs with regard to preconditions for CVDs. Our aim was to assess differences in echocardiographic parameters and inflammatory biomarkers between MHO and metabolically healthy, normal weight individuals (MHNW). METHODS The analyses used data from 1412 elderly participants from a German population-based cohort study (CARLA), which collected detailed information on demographic, biochemical, and echocardiographic variables. Participants were subdivided into four groups (MHNW, MHO, MUNW (metabolically unhealthy, normal weight) and MUO (metabolically unhealthy, obese)) based on BMI≥30 kg/m2 (obese or normal weight) and presence of components of the metabolic syndrome. The clinical characteristics of the 4 groups were compared with ANOVA or Chi-Square test, in addition to two linear regression models for 16 echocardiographic parameters. The difference in inflammatory biomarkers (hsCRP, IL-6 and sTNF-RI) between the groups was examined with a multinomial logistic regression model. RESULTS The MHO individuals were on average 64.2±8.4 years old, with a higher proportion of women (71.6%), low percentage of smokers, larger waist circumference (109.3±10.5 cm vs 89.1±10.8 cm, p<0.0001) and higher odds ratios for hsCRP, IL-6 and sTNF-RI compared to MHNW individuals. Linear regression models revealed greater left atrial (LA) diameter (2.73 (95% CI: 1.35-4.11) mm), LA volume (7.86 (95% CI: 2.88-12.83) mL), and left ventricular mass index (LVMI) (11.82 (95% CI: 4.43-19.22) g/m1.7) in the MHO group compared to the MHNW group. CONCLUSION The MHO phenotype is associated with echocardiographic markers of cardiac remodeling (LA diameter, volume and LVMI) and higher odds ratios for inflammatory biomarkers.
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Affiliation(s)
- Ljupcho Efremov
- Institute of Medical Epidemiology, Biostatistics, and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | | | - Daniel Tiller
- IT Department, Data Integration Center, University Hospital Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Daniel Medenwald
- Institute of Medical Epidemiology, Biostatistics, and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Karin Halina Greiser
- Division of Cancer Epidemiology, German Cancer Research Centre, Heidelberg, Germany
| | - Alexander Kluttig
- Institute of Medical Epidemiology, Biostatistics, and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Sebastian Nuding
- Department of Internal Medicine III, University Hospital Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Rafael Mikolajczyk
- Institute of Medical Epidemiology, Biostatistics, and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Correspondence: Rafael Mikolajczyk Institute of Medical Epidemiology, Biostatistics, and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther-University Halle-Wittenberg, Magdeburger Str. 8, Halle (Saale)06112, Germany Email
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Lumish HS, O'Reilly M, Reilly MP. Sex Differences in Genomic Drivers of Adipose Distribution and Related Cardiometabolic Disorders: Opportunities for Precision Medicine. Arterioscler Thromb Vasc Biol 2019; 40:45-60. [PMID: 31747800 DOI: 10.1161/atvbaha.119.313154] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
This review focuses on the human genetics, epidemiology, and molecular pathophysiology of sex differences in central obesity, adipose distribution, and related cardiometabolic disorders. Distribution of fat is important for cardiometabolic health, with peripheral fat depots having a protective effect and central visceral fat depots conferring a detrimental effect on health. There are important sex differences in fat distribution that are masked when studying body mass index as a measure of obesity. From epidemiological, murine, and in vitro studies, several mechanisms have been proposed to explain the sex differences in adipose distribution, including sex hormonal effects, cell-intrinsic properties, and the microenvironment in fat depots. More recently, human genetics have revealed hundreds of loci for central obesity providing disruptive opportunities for mechanistic discoveries and clinical translation. A striking feature is that over one-third of these loci have reproducible but poorly understood sexual dimorphic associations with central obesity, most having stronger effects in women. Understanding the genetic and molecular mechanisms of adipose distribution and its sexual dimorphism in humans provides a unique opportunity to promote the use of precision medicine for early identification of at-risk individuals, and the development of novel therapeutic strategies for central obesity and related cardiometabolic disorders.
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Affiliation(s)
- Heidi S Lumish
- From the Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY (H.S.L., M.O., M.P.R.)
| | - Marcella O'Reilly
- From the Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY (H.S.L., M.O., M.P.R.)
| | - Muredach P Reilly
- From the Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY (H.S.L., M.O., M.P.R.).,Irving Institute for Clinical and Translational Research, Columbia University, New York, NY (M.P.R.)
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Ramos-Lopez O, Riezu-Boj JI, Milagro FI, Cuervo M, Goni L, Martinez JA. Genetic and nongenetic factors explaining metabolically healthy and unhealthy phenotypes in participants with excessive adiposity: relevance for personalized nutrition. Ther Adv Endocrinol Metab 2019; 10:2042018819877303. [PMID: 31555433 PMCID: PMC6751528 DOI: 10.1177/2042018819877303] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 08/29/2019] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Different genetic and environmental factors can explain the heterogeneity of obesity-induced metabolic alterations between individuals. In this study, we aimed to screen factors that predict metabolically healthy (MHP) and unhealthy (MUP) phenotypes using genetic and lifestyle data in overweight/obese participants. METHODS In this cross-sectional study we enrolled 298 overweight/obese Spanish adults. The Adult Treatment Panel III criteria for metabolic syndrome were used to categorize MHP (at most, one trait) and MUP (more than one feature). Blood lipid and inflammatory profiles were measured by standardized methods. Body composition was determined by dual-energy X-ray absorptiometry. A total of 95 obesity-predisposing single-nucleotide polymorphisms (SNPs) were genotyped by a predesigned next-generation sequencing system. SNPs associated with a MUP were used to compute a weighted genetic-risk score (wGRS). Information concerning lifestyle (dietary intake and physical activity level) was collected using validated questionnaires. RESULTS The prevalence of MHP and MUP was 44.3% and 55.7%, respectively, in this sample. Overall, 12 obesity-related genetic variants were associated with the MUP. Multiple logistic regression analyses revealed that wGRS (OR = 4.133, p < 0.001), total dietary fat [odds ratio (OR) = 1.105, p = 0.002], age (OR = 1.064, p = 0.001), and BMI (OR = 1.408, p < 0.001) positively explained the MUP, whereas female sex (OR = 0.330, p = 0.009) produced a protective effect. The area under the receiver operating characteristic curve using the multivariable model was high (0.8820). Interestingly, the wGRS was the greatest contributor to the MUP (squared partial correlation = 0.3816, p < 0.001). CONCLUSIONS The genetic background is an important factor explaining MHP and MUP related to obesity, in addition to lifestyle variables. This information could be useful to metabolically categorize individuals, as well as for the design/implementation of personalized nutrition interventions aimed at promoting metabolic health and nutritional wellbeing.
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Affiliation(s)
- Omar Ramos-Lopez
- Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain
- Medicine and Psychology School, Autonomous University of Baja California, Tijuana, Baja California, Mexico
| | - Jose I. Riezu-Boj
- Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Fermin I. Milagro
- Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- CIBERobn, Fisiopatología de la Obesidad y la Nutrición; Carlos III Health Institute, Madrid, Spain
| | - Marta Cuervo
- Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- CIBERobn, Fisiopatología de la Obesidad y la Nutrición; Carlos III Health Institute, Madrid, Spain
| | - Leticia Goni
- Department of Nutrition, Food Science and Physiology, and Center for Nutrition Research, University of Navarra, Pamplona, Spain
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Vukovic R, Dos Santos TJ, Ybarra M, Atar M. Children With Metabolically Healthy Obesity: A Review. Front Endocrinol (Lausanne) 2019; 10:865. [PMID: 31920976 PMCID: PMC6914809 DOI: 10.3389/fendo.2019.00865] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 11/26/2019] [Indexed: 02/06/2023] Open
Abstract
Children with "metabolically healthy obesity" (MHO) are a distinct subgroup of youth with obesity, who are less prone to the clustering of cardiometabolic risk factors. Although this phenotype, frequently defined by the absence of metabolic syndrome components or insulin resistance, was first described during the early 1980s, a consensus-based definition of pediatric MHO was introduced only recently, in 2018. The purpose of this review was to concisely summarize current knowledge regarding the MHO phenomenon in youth. The prevalence of MHO in children varies from 3 to 87%, depending on the definition used and the parameters evaluated, as well as the ethnicity and the pubertal status of the sample. The most consistent predictors of MHO in youth include younger age, lower body mass index, lower waist circumference, and lower body fat measurements. Various hypotheses have been proposed to elucidate the underlying factors maintaining the favorable MHO phenotype. While preserved insulin sensitivity and lack of inflammation were previously considered to be the main etiological factors, the most recent findings have implicated adipokine levels, the number of inflammatory immune cells in the adipose tissue, and the reduction of visceral adiposity due to adipose tissue expandability. Physical activity and genetic factors also contribute to the MHO phenotype. Obesity constitutes a continuum-increased risk for cardiometabolic complications, which is less evident in children with MHO. However, some findings have highlighted the emergence of hepatic steatosis, increased carotid intima-media thickness and inflammatory biomarkers in the MHO group compared to peers without obesity. Screening should be directed at those more likely to develop clustering of cardiometabolic risk factors. Lifestyle modifications should include behavioral changes focusing on sleep duration, screen time, diet, physical activity, and tobacco smoke exposure. Weight loss has also been associated with the improvement of insulin sensitivity and inflammation. Further investigative efforts are needed in order to elucidate the mechanisms which protect against the clustering of cardiometabolic risk factors in pediatric obesity, to provide more efficient, targeted treatment approaches for children with obesity, and to identify the protective factors preserving the MHO profile, avoiding the crossover of MHO to the phenotype with metabolically unhealthy obesity.
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Affiliation(s)
- Rade Vukovic
- Department of Pediatric Endocrinology, Mother and Child Healthcare Institute of Serbia “Dr Vukan Cupic”, Belgrade, Serbia
- School of Medicine, University of Belgrade, Belgrade, Serbia
- *Correspondence: Rade Vukovic
| | | | - Marina Ybarra
- Research Center of Sainte Justine University Hospital, Université de Montréal, Montreal, QC, Canada
- Centre Armand-Frappier, Institut National de la Recherche Scientifique, Université du Québec, Laval, QC, Canada
| | - Muge Atar
- Department of Pediatric Endocrinology, School of Medicine, Demirel University, Isparta, Turkey
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Vidal-Puig A, Enerback S. "Obesity-associated metabolic complications, the second wave of the tsunami" 14th Key Symposium. J Intern Med 2018; 284:447-449. [PMID: 30141829 DOI: 10.1111/joim.12828] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- A Vidal-Puig
- Department of Clinical Biochemistry, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
| | - S Enerback
- Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden
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