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Veerapaneni P, Goo B, Ahmadieh S, Shi H, Kim DS, Ogbi M, Cave S, Chouhaita R, Cyriac N, Fulton DJ, Verin AD, Chen W, Lei Y, Lu XY, Kim HW, Weintraub NL. Transgenic Overexpression of HDAC9 Promotes Adipocyte Hypertrophy, Insulin Resistance and Hepatic Steatosis in Aging Mice. Biomolecules 2024; 14:494. [PMID: 38672510 PMCID: PMC11048560 DOI: 10.3390/biom14040494] [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: 02/13/2024] [Revised: 04/05/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Histone deacetylase (HDAC) 9 is a negative regulator of adipogenic differentiation, which is required for maintenance of healthy adipose tissues. We reported that HDAC9 expression is upregulated in adipose tissues during obesity, in conjunction with impaired adipogenic differentiation, adipocyte hypertrophy, insulin resistance, and hepatic steatosis, all of which were alleviated by global genetic deletion of Hdac9. Here, we developed a novel transgenic (TG) mouse model to test whether overexpression of Hdac9 is sufficient to induce adipocyte hypertrophy, insulin resistance, and hepatic steatosis in the absence of obesity. HDAC9 TG mice gained less body weight than wild-type (WT) mice when fed a standard laboratory diet for up to 40 weeks, which was attributed to reduced fat mass (primarily inguinal adipose tissue). There was no difference in insulin sensitivity or glucose tolerance in 18-week-old WT and HDAC9 TG mice; however, at 40 weeks of age, HDAC9 TG mice exhibited impaired insulin sensitivity and glucose intolerance. Tissue histology demonstrated adipocyte hypertrophy, along with reduced numbers of mature adipocytes and stromovascular cells, in the HDAC9 TG mouse adipose tissue. Moreover, increased lipids were detected in the livers of aging HDAC9 TG mice, as evaluated by oil red O staining. In conclusion, the experimental aging HDAC9 TG mice developed adipocyte hypertrophy, insulin resistance, and hepatic steatosis, independent of obesity. This novel mouse model may be useful in the investigation of the impact of Hdac9 overexpression associated with metabolic and aging-related diseases.
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Affiliation(s)
- Praneet Veerapaneni
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Brandee Goo
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Samah Ahmadieh
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Hong Shi
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
- Department of Medicine, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA
| | - David S. Kim
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Mourad Ogbi
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Stephen Cave
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Ronnie Chouhaita
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - Nicole Cyriac
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
| | - David J. Fulton
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
- Department of Pharmacology and Toxicology, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA
| | - Alexander D. Verin
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
- Department of Medicine, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA
| | - Weiqin Chen
- Department of Physiology, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA;
| | - Yun Lei
- Department of Neuroscience and Regenerative Medicine, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (Y.L.); (X.-Y.L.)
| | - Xin-Yun Lu
- Department of Neuroscience and Regenerative Medicine, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (Y.L.); (X.-Y.L.)
| | - Ha Won Kim
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
- Department of Medicine, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA
| | - Neal L. Weintraub
- Vascular Biology Center, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA; (P.V.); (B.G.); (S.A.); (H.S.); (D.S.K.); (M.O.); (S.C.); (R.C.); (N.C.); (D.J.F.); (A.D.V.); (H.W.K.)
- Department of Medicine, Medical College of Georgia, Augusta University, 1460 Laney Walker Blvd, Augusta, GA 30912, USA
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Jalil JE, Gabrielli L, Ocaranza MP, MacNab P, Fernández R, Grassi B, Jofré P, Verdejo H, Acevedo M, Cordova S, Sanhueza L, Greig D. New Mechanisms to Prevent Heart Failure with Preserved Ejection Fraction Using Glucagon-like Peptide-1 Receptor Agonism (GLP-1 RA) in Metabolic Syndrome and in Type 2 Diabetes: A Review. Int J Mol Sci 2024; 25:4407. [PMID: 38673991 PMCID: PMC11049921 DOI: 10.3390/ijms25084407] [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: 02/07/2024] [Revised: 04/02/2024] [Accepted: 04/07/2024] [Indexed: 04/28/2024] Open
Abstract
This review examines the impact of obesity on the pathophysiology of heart failure with preserved ejection fraction (HFpEF) and focuses on novel mechanisms for HFpEF prevention using a glucagon-like peptide-1 receptor agonism (GLP-1 RA). Obesity can lead to HFpEF through various mechanisms, including low-grade systemic inflammation, adipocyte dysfunction, accumulation of visceral adipose tissue, and increased pericardial/epicardial adipose tissue (contributing to an increase in myocardial fat content and interstitial fibrosis). Glucagon-like peptide 1 (GLP-1) is an incretin hormone that is released from the enteroendocrine L-cells in the gut. GLP-1 reduces blood glucose levels by stimulating insulin synthesis, suppressing islet α-cell function, and promoting the proliferation and differentiation of β-cells. GLP-1 regulates gastric emptying and appetite, and GLP-1 RA is currently indicated for treating type 2 diabetes (T2D), obesity, and metabolic syndrome (MS). Recent evidence indicates that GLP-1 RA may play a significant role in preventing HFpEF in patients with obesity, MS, or obese T2D. This effect may be due to activating cardioprotective mechanisms (the endogenous counter-regulatory renin angiotensin system and the AMPK/mTOR pathway) and by inhibiting deleterious remodeling mechanisms (the PKA/RhoA/ROCK pathway, aldosterone levels, and microinflammation). However, there is still a need for further research to validate the impact of these mechanisms on humans.
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Affiliation(s)
- Jorge E. Jalil
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Luigi Gabrielli
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - María Paz Ocaranza
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Paul MacNab
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Rodrigo Fernández
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Bruno Grassi
- Pontificia Universidad Católica de Chile, School of Medicine, Department of Nutrition and Diabetes, Santiago 8330055, Chile; (B.G.); (P.J.)
| | - Paulina Jofré
- Pontificia Universidad Católica de Chile, School of Medicine, Department of Nutrition and Diabetes, Santiago 8330055, Chile; (B.G.); (P.J.)
| | - Hugo Verdejo
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Monica Acevedo
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Samuel Cordova
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Luis Sanhueza
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
| | - Douglas Greig
- Pontificia Universidad Católica de Chile, School of Medicine, Division of Cardiovascular Diseases, Santiago 8330055, Chile; (L.G.); (P.M.); (R.F.); (H.V.); (M.A.); (S.C.); (L.S.); (D.G.)
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Benchoula K, Serpell CJ, Mediani A, Albogami A, Misnan NM, Ismail NH, Parhar IS, Ogawa S, Hwa WE. 1H NMR metabolomics insights into comparative diabesity in male and female zebrafish and the antidiabetic activity of DL-limonene. Sci Rep 2024; 14:3823. [PMID: 38360784 PMCID: PMC10869695 DOI: 10.1038/s41598-023-45608-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/21/2023] [Indexed: 02/17/2024] Open
Abstract
Zebrafish have been utilized for many years as a model animal for pharmacological studies on diabetes and obesity. High-fat diet (HFD), streptozotocin and alloxan injection, and glucose immersion have all been used to induce diabetes and obesity in zebrafish. Currently, studies commonly used both male and female zebrafish, which may influence the outcomes since male and female zebrafish are biologically different. This study was designed to investigate the difference between the metabolites of male and female diabetic zebrafish, using limonene - a natural product which has shown several promising results in vitro and in vivo in treating diabetes and obesity-and provide new insights into how endogenous metabolites change following limonene treatment. Using HFD-fed male and female zebrafish, we were able to develop an animal model of T2D and identify several endogenous metabolites that might be used as diagnostic biomarkers for diabetes. The endogenous metabolites in males and females were different, even though both genders had high blood glucose levels and a high BMI. Treatment with limonene prevented high blood glucose levels and improved in diabesity zebrafish by limonene, through reversal of the metabolic changes caused by HFD in both genders. In addition, limonene was able to reverse the elevated expression of AKT during HFD.
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Affiliation(s)
- Khaled Benchoula
- School of Medicine, Faculty of Health and Medical Sciences, Taylor's University, 1, Jalan Taylors, 47500, Subang Jaya, Selangor, Malaysia
| | | | - Ahmed Mediani
- Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia
| | - Abdulaziz Albogami
- Biology Department, Faculty of Science, Al-Baha University, 65779-7738, Alaqiq, Saudi Arabia
| | - Norazlan Mohmad Misnan
- Institute for Medical Research Malaysia, No.1, Jalan Setia Murni U13/52, Seksyen U13, Setia Alam, 40170, Shah Alam, Selangor Darul Ehsan, Malaysia
| | - Nor Hadiani Ismail
- Atta-ur-Rahman Institute for Natural Products Discovery, UiTM Puncak Alam Campus, 42300, Puncak Alam, Selangor, Malaysia
| | - Ishwar S Parhar
- Monash University (Malaysia) BRIMS, Jeffrey Cheah School of Medicine and Health Sciences, Jalan Lagoon Selatan, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Satoshi Ogawa
- Monash University (Malaysia) BRIMS, Jeffrey Cheah School of Medicine and Health Sciences, Jalan Lagoon Selatan, Bandar Sunway, 47500, Subang Jaya, Selangor, Malaysia
| | - Wong Eng Hwa
- School of Medicine, Faculty of Health and Medical Sciences, Taylor's University, 1, Jalan Taylors, 47500, Subang Jaya, Selangor, Malaysia.
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Masi D, Zilich R, Candido R, Giancaterini A, Guaita G, Muselli M, Ponzani P, Santin P, Verda D, Musacchio N. Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group. J Clin Med 2023; 12:4095. [PMID: 37373787 DOI: 10.3390/jcm12124095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/25/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023] Open
Abstract
Identifying and treating lipid abnormalities is crucial for preventing cardiovascular disease in diabetic patients, yet only two-thirds of patients reach recommended cholesterol levels. Elucidating the factors associated with lipid goal attainment represents an unmet clinical need. To address this knowledge gap, we conducted a real-world analysis of the lipid profiles of 11.252 patients from the Annals of the Italian Association of Medical Diabetologists (AMD) database from 2005 to 2019. We used a Logic Learning Machine (LLM) to extract and classify the most relevant variables predicting the achievement of a low-density lipoprotein cholesterol (LDL-C) value lower than 100 mg/dL (2.60 mmol/L) within two years of the start of lipid-lowering therapy. Our analysis showed that 61.4% of the patients achieved the treatment goal. The LLM model demonstrated good predictive performance, with a precision of 0.78, accuracy of 0.69, recall of 0.70, F1 Score of 0.74, and ROC-AUC of 0.79. The most significant predictors of achieving the treatment goal were LDL-C values at the start of lipid-lowering therapy and their reduction after six months. Other predictors of a greater likelihood of reaching the target included high-density lipoprotein cholesterol, albuminuria, and body mass index at baseline, as well as younger age, male sex, more follow-up visits, no therapy discontinuation, higher Q-score, lower blood glucose and HbA1c levels, and the use of anti-hypertensive medication. At baseline, for each LDL-C range analysed, the LLM model also provided the minimum reduction that needs to be achieved by the next six-month visit to increase the likelihood of reaching the therapeutic goal within two years. These findings could serve as a useful tool to inform therapeutic decisions and to encourage further in-depth analysis and testing.
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Affiliation(s)
- Davide Masi
- Department of Experimental Medicine, Section of Medical Pathophysiology, Food Science and Endocrinology, Sapienza University of Rome, 00161 Rome, Italy
| | | | - Riccardo Candido
- Associazione Medici Diabetologi, Giuliano Isontina University Health Service, 34149 Trieste, Italy
| | - Annalisa Giancaterini
- UOSD Diabetology, Department of Exchange and Nutrition Diseases, Brianza Health Service, Pio XI Hospital, 20833 Desio, Italy
| | - Giacomo Guaita
- Diabetes and Endocrinology Unit, ASL SULCIS, 9016 Iglesias, Italy
| | - Marco Muselli
- Rulex Innovation Labs, Rulex Inc., 16122 Genoa, Italy
| | - Paola Ponzani
- Diabetes and Metabolic Disease Unit, ASL 4 Liguria, 16043 Chiavari, Italy
| | | | - Damiano Verda
- Rulex Innovation Labs, Rulex Inc., 16122 Genoa, Italy
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Honda M, Tsuboi A, Minato-Inokawa S, Takeuchi M, Kurata M, Wu B, Kazumi T, Fukuo K. Reduced gluteofemoral (subcutaneous) fat mass in young Japanese women with family history of type 2 diabetes: an exploratory analysis. Sci Rep 2022; 12:12579. [PMID: 35869280 PMCID: PMC9307820 DOI: 10.1038/s41598-022-16890-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 07/18/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractLimited expandability of subcutaneous adipose tissue may be characteristics of first-degree relatives of type 2 diabetes. We tested the hypothesis that family history of type 2 diabetes (FHD) may be associated with reduced peripheral fat mass. Body composition and metabolic variables were compared between 18 and 111 Japanese female collegiate athletes, and between 55 and 148 nonathletes with positive (FHD +) and negative FHD (FHD-), respectively. We had multivariate logistic regression analyses for FHD + as dependent variable in a total population.BMI averaged < 21 kg/m2 and did not differ between FHD + and FHD- nonathletes. Despite comparable BMI, body fat percentage and serum leptin were lower in FHD + nonathletes. This was due to lower arm and gluteofemoral fat percentage (both p = 0.02) whereas the difference in trunk fat percentage was not significant (p = 0.08). These differences were not found between two groups of athletes. FHD + women had lower HDL cholesterol despite lower BMI in a total population. Fasting insulin, serum adiponectin and high-sensitivity C-reactive protein did not differ between FHD + and FHD- athletes or nonathletes. Multivariate logistic regression analyses revealed independent associations of FHD + with BMI (odds ratio, 0.869; 95% confidential interval, 0.768–0.984; p = 0.02) and HDL cholesterol (odds ratio, 0.977; 95% confidential interval, 0.957–0.997, p = 0.02). In conclusion, FHD may be associated with reduced subcutaneous fat mass in young Japanese women, suggesting impaired adipose tissue expandability.
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Börgeson E, Boucher J, Hagberg CE. Of mice and men: Pinpointing species differences in adipose tissue biology. Front Cell Dev Biol 2022; 10:1003118. [PMID: 36187476 PMCID: PMC9521710 DOI: 10.3389/fcell.2022.1003118] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
The prevalence of obesity and metabolic diseases continues to rise, which has led to an increased interest in studying adipose tissue to elucidate underlying disease mechanisms. The use of genetic mouse models has been critical for understanding the role of specific genes for adipose tissue function and the tissue’s impact on other organs. However, mouse adipose tissue displays key differences to human fat, which has led, in some cases, to the emergence of some confounding concepts in the adipose field. Such differences include the depot-specific characteristics of visceral and subcutaneous fat, and divergences in thermogenic fat phenotype between the species. Adipose tissue characteristics may therefore not always be directly compared between species, which is important to consider when setting up new studies or interpreting results. This mini review outlines our current knowledge about the cell biological differences between human and mouse adipocytes and fat depots, highlighting some examples where inadequate knowledge of species-specific differences can lead to confounding results, and presenting plausible anatomic explanations that may underlie the differences. The article thus provides critical insights and guidance for researchers working primarily with only human or mouse fat tissue, and may contribute to new ideas or concepts in the important and evolving field of adipose biology.
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Affiliation(s)
- Emma Börgeson
- Department of Molecular and Clinical Medicine, Wallenberg Laboratory, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Region Vaestra Goetaland, Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jeremie Boucher
- The Lundberg Laboratory for Diabetes Research, Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Metabolic Disease, Evotec International GmbH, Göttingen, Germany
| | - Carolina E. Hagberg
- Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Carolina E. Hagberg,
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Yanina IY, Tanikawa Y, Genina EA, Dyachenko PA, Tuchina DK, Bashkatov AN, Dolotov LE, Tarakanchikova YV, Terentuk GS, Navolokin NA, Bucharskaya AB, Maslyakova GN, Iga Y, Takimoto S, Tuchin VV. Immersion optical clearing of adipose tissue in rats: ex vivo and in vivo studies. JOURNAL OF BIOPHOTONICS 2022; 15:e202100393. [PMID: 35340116 DOI: 10.1002/jbio.202100393] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/24/2022] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
Optical clearing (OC) of adipose tissue has not been studied enough, although it can be promising in medical applications, including surgery and cosmetology, for example, to visualize blood vessels or increase the permeability of tissues to laser beams. The main objective of this work is to develop technology for OC of abdominal adipose tissue in vivo using hyperosmotic optical clearing agents (OCAs). The maximum OC effect (77%) was observed for ex vivo rat adipose tissue samples exposed to OCA on fructose basis for 90 minutes. For in vivo studies, the maximum effect of OC (65%) was observed when using OCA based on diatrizoic acid and dimethylsulfoxide for 120 minutes. Histological analysis showed that in vivo application of OCAs may induce a limited local necrosis of fat cells. The efficiency of OC correlated with local tissue damage through cell necrosis due to accompanied cell lipolysis.
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Affiliation(s)
- Irina Yu Yanina
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | | | - Elina A Genina
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Polina A Dyachenko
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Daria K Tuchina
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Alexey N Bashkatov
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
| | - Leonid E Dolotov
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
| | | | | | - Nikita A Navolokin
- Science Medical Center, Saratov State University, Saratov, Russia
- Research-Scientific Institute of Fundamental and Clinic Uronephrology, Saratov State Medical University, Saratov, Russia
| | - Alla B Bucharskaya
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
- Science Medical Center, Saratov State University, Saratov, Russia
- Research-Scientific Institute of Fundamental and Clinic Uronephrology, Saratov State Medical University, Saratov, Russia
| | - Galina N Maslyakova
- Science Medical Center, Saratov State University, Saratov, Russia
- Research-Scientific Institute of Fundamental and Clinic Uronephrology, Saratov State Medical University, Saratov, Russia
| | | | | | - Valery V Tuchin
- Research-Educational Institute of Optics and Biophotonics, Saratov State University, Saratov, Russia
- Laboratory of Laser Molecular Imaging and Machine Learning, Tomsk State University, Tomsk, Russia
- Science Medical Center, Saratov State University, Saratov, Russia
- Laboratory of Laser Diagnostics of Technical and Living Systems, Institute of Precision Mechanics and Control, FRC "Saratov Scientific Centre of the Russian Academy of Sciences", Saratov, Russia
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Dhore-Patil A, Thannoun T, Samson R, Le Jemtel TH. Diabetes Mellitus and Heart Failure With Preserved Ejection Fraction: Role of Obesity. Front Physiol 2022; 12:785879. [PMID: 35242044 PMCID: PMC8886215 DOI: 10.3389/fphys.2021.785879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/03/2021] [Indexed: 12/15/2022] Open
Abstract
Heart failure with preserved ejection fraction is a growing epidemic and accounts for half of all patients with heart failure. Increasing prevalence, morbidity, and clinical inertia have spurred a rethinking of the pathophysiology of heart failure with preserved ejection fraction. Unlike heart failure with reduced ejection fraction, heart failure with preserved ejection fraction has distinct clinical phenotypes. The obese-diabetic phenotype is the most often encountered phenotype in clinical practice and shares the greatest burden of morbidity and mortality. Left ventricular remodeling plays a major role in its pathophysiology. Understanding the interplay of obesity, diabetes mellitus, and inflammation in the pathophysiology of left ventricular remodeling may help in the discovery of new therapeutic targets to improve clinical outcomes in heart failure with preserved ejection fraction. Anti-diabetic agents like glucagon-like-peptide 1 analogs and sodium-glucose co-transporter 2 are promising therapeutic modalities for the obese-diabetic phenotype of heart failure with preserved ejection fraction and aggressive weight loss via lifestyle or bariatric surgery is still key to reverse adverse left ventricular remodeling. This review focuses on the obese-diabetic phenotype of heart failure with preserved ejection fraction highlighting the interaction between obesity, diabetes, and coronary microvascular dysfunction in the development and progression of left ventricular remodeling. Recent therapeutic advances are reviewed.
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Affiliation(s)
- Aneesh Dhore-Patil
- Section of Cardiology, Department of Medicine, Tulane University School of Medicine, New Orleans, LA, United States.,Tulane University Heart and Vascular Institute, New Orleans, LA, United States
| | - Tariq Thannoun
- Section of Cardiology, Department of Medicine, Tulane University School of Medicine, New Orleans, LA, United States.,Tulane University Heart and Vascular Institute, New Orleans, LA, United States
| | - Rohan Samson
- Section of Cardiology, Department of Medicine, Tulane University School of Medicine, New Orleans, LA, United States.,Tulane University Heart and Vascular Institute, New Orleans, LA, United States
| | - Thierry H Le Jemtel
- Section of Cardiology, Department of Medicine, Tulane University School of Medicine, New Orleans, LA, United States.,Tulane University Heart and Vascular Institute, New Orleans, LA, United States
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9
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Camastra S, Ferrannini E. Role of anatomical location, cellular phenotype and perfusion of adipose tissue in intermediary metabolism: A narrative review. Rev Endocr Metab Disord 2022; 23:43-50. [PMID: 35031911 PMCID: PMC8873050 DOI: 10.1007/s11154-021-09708-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/22/2021] [Indexed: 02/07/2023]
Abstract
It is well-established that adipose tissue accumulation is associated with insulin resistance through multiple mechanisms. One major metabolic link is the classical Randle cycle: enhanced release of free fatty acids (FFA) from hydrolysis of adipose tissue triglycerides impedes insulin-mediated glucose uptake in muscle tissues. Less well studied are the different routes of this communication. First, white adipose tissue depots may be regionally distant from muscle (i.e., gluteal fat and diaphragm muscle) or contiguous to muscle but separated by a fascia (Scarpa's fascia in the abdomen, fascia lata in the thigh). In this case, released FFA outflow through the venous drainage and merge into arterial plasma to be transported to muscle tissues. Next, cytosolic triglycerides can directly, i.e., within the cell, provide FFA to myocytes (but also pancreatic ß-cells, renal tubular cells, etc.). Finally, adipocyte layers or lumps may be adjacent to, but not anatomically segregated, from muscle, as is typically the case for epicardial fat and cardiomyocytes. As regulation of these three main delivery paths is different, their separate contribution to substrate competition at the whole-body level is uncertain. Another important link between fat and muscle is vascular. In the resting state, blood flow is generally higher in adipose tissue than in muscle. In the insulinized state, fat blood flow is directly related to whole-body insulin resistance whereas muscle blood flow is not; consequently, fractional (i.e., flow-adjusted) glucose uptake is stimulated in muscle but not fat. Thus, reduced blood supply is a major factor for the impairment of in vivo insulin-mediated glucose uptake in both subcutaneous and visceral fat. In contrast, the insulin resistance of glucose uptake in resting skeletal muscle is predominantly a cellular defect.
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Affiliation(s)
- Stefania Camastra
- Department of Clinical & Experimental Medicine, University of Pisa, Pisa, Italy.
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10
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Ye RZ, Richard G, Gévry N, Tchernof A, Carpentier AC. Fat Cell Size: Measurement Methods, Pathophysiological Origins, and Relationships With Metabolic Dysregulations. Endocr Rev 2022; 43:35-60. [PMID: 34100954 PMCID: PMC8755996 DOI: 10.1210/endrev/bnab018] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Indexed: 11/19/2022]
Abstract
The obesity pandemic increasingly causes morbidity and mortality from type 2 diabetes, cardiovascular diseases and many other chronic diseases. Fat cell size (FCS) predicts numerous obesity-related complications such as lipid dysmetabolism, ectopic fat accumulation, insulin resistance, and cardiovascular disorders. Nevertheless, the scarcity of systematic literature reviews on this subject is compounded by the use of different methods by which FCS measurements are determined and reported. In this paper, we provide a systematic review of the current literature on the relationship between adipocyte hypertrophy and obesity-related glucose and lipid dysmetabolism, ectopic fat accumulation, and cardiovascular disorders. We also review the numerous mechanistic origins of adipocyte hypertrophy and its relationship with metabolic dysregulation, including changes in adipogenesis, cell senescence, collagen deposition, systemic inflammation, adipokine secretion, and energy balance. To quantify the effect of different FCS measurement methods, we performed statistical analyses across published data while controlling for body mass index, age, and sex.
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Affiliation(s)
- Run Zhou Ye
- Division of Endocrinology, Department of Medicine, Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Gabriel Richard
- Division of Endocrinology, Department of Medicine, Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Nicolas Gévry
- Department of Biology, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - André Tchernof
- Québec Heart and Lung Research Institute, Laval University, Québec, Québec, Canada
| | - André C Carpentier
- Division of Endocrinology, Department of Medicine, Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Université de Sherbrooke, Sherbrooke, Québec, Canada
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11
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Honda M, Tsuboi A, Minato-Inokawa S, Takeuchi M, Kurata M, Takayoshi T, Hirota Y, Wu B, Kazumi T, Fukuo K. Serum Orosomucoid Is Associated with Serum Adiponectin, Adipose Tissue Insulin Resistance Index, and a Family History of Type 2 Diabetes in Young Normal Weight Japanese Women. J Diabetes Res 2022; 2022:7153238. [PMID: 35103244 PMCID: PMC8800618 DOI: 10.1155/2022/7153238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 11/03/2021] [Accepted: 12/24/2021] [Indexed: 11/17/2022] Open
Abstract
INTRODUCTION Adipose tissue (AT) expandability may be facilitated by adiponectin and suppressed by orosomucoid, and reduced AT expandability may be associated with first-degree relatives of type 2 diabetes. We tested the hypothesis that orosomucoid may be associated not only with adiponectin and adipose tissue insulin resistance but also with a family history of type 2 diabetes (FHD). Research Design and Methods. Anthropometric and metabolic variables, adipokines, and measures of inflammatory and insulin resistance were cross-sectionally investigated in 153 young normal weight Japanese women. Stepwise multivariate linear regression analyses were used to identify the most important determinants of orosomucoid. RESULTS Orosomucoid was higher in women with positive (n = 57) compared to women with negative FHD and was associated positively with FHD (both p = 0.01). Orosomucoid also showed positive associations with fasting glucose (p < 0.001), free fatty acids (p = 0.001), and HbA1c (p = 0.007), whereas there was no association with fasting insulin and serum lipids. In addition, orosomucoid was associated inversely with adiponectin (p = 0.02) and positively with adipose tissue-insulin resistance index (AT-IR, the product of fasting insulin and free fatty acids; p = 0.001) but not with homeostasis model assessment-insulin resistance, leptin, and high-sensitivity C-reactive protein. In multivariate analyses, AT-IR (standardized β, 0.22; p = 0.003), serum adiponectin (standardized β, -0.163; p = 0.032), FHD+ (standardized β, 0.178; p = 0.029), and HbA1c (standardized β, 0.213; p = 0.005) emerged as independent determinants of orosomucoid and explained 15.2% of its variability. CONCLUSIONS These results are the first to demonstrate that orosomucoid is associated not only with adipose tissue-insulin resistance and adiponectin but also with FHD.
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Affiliation(s)
- Mari Honda
- Open Research Center for Studying of Lifestyle-Related Diseases, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Department of Health, Sports, and Nutrition, Faculty of Health and Welfare, Kobe Women's University, Kobe, Hyogo, Japan
| | - Ayaka Tsuboi
- Research Institute for Nutrition Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Department of Nutrition, Osaka City Juso Hospital, Osaka, Japan
| | - Satomi Minato-Inokawa
- Research Institute for Nutrition Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Laboratory of Community Health and Nutrition, Department of Bioscience, Graduate School of Agriculture, Ehime University, Matsuyama, Ehime, Japan
| | - Mika Takeuchi
- Research Institute for Nutrition Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
| | - Miki Kurata
- Research Institute for Nutrition Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Department of Food Sciences and Nutrition, School of Food Sciences and Nutrition, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
| | - Tomofumi Takayoshi
- Division of Diabetes and Endocrinology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Yushi Hirota
- Division of Diabetes and Endocrinology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Bin Wu
- Open Research Center for Studying of Lifestyle-Related Diseases, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Department of Endocrinology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Tsutomu Kazumi
- Open Research Center for Studying of Lifestyle-Related Diseases, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Research Institute for Nutrition Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Department of Medicine, Kohnan Kakogawa Hospital, Kakogawa, Hyogo, Japan
| | - Keisuke Fukuo
- Open Research Center for Studying of Lifestyle-Related Diseases, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Research Institute for Nutrition Sciences, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
- Department of Food Sciences and Nutrition, School of Food Sciences and Nutrition, Mukogawa Women's University, Nishinomiya, Hyogo, Japan
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12
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Greco F, Mallio CA. Artificial intelligence and abdominal adipose tissue analysis: a literature review. Quant Imaging Med Surg 2021; 11:4461-4474. [PMID: 34603998 DOI: 10.21037/qims-21-370] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 06/01/2021] [Indexed: 12/12/2022]
Abstract
Body composition imaging relies on assessment of tissues composition and distribution. Quantitative data provided by body composition imaging analysis have been linked to pathogenesis, risk, and clinical outcomes of a wide spectrum of diseases, including cardiovascular and oncologic. Manual segmentation of imaging data allows to obtain information on abdominal adipose tissue; however, this procedure can be cumbersome and time-consuming. On the other hand, quantitative imaging analysis based on artificial intelligence (AI) has been proposed as a fast and reliable automatic technique for segmentation of abdominal adipose tissue compartments, possibly improving the current standard of care. AI holds the potential to extract quantitative data from computed tomography (CT) and magnetic resonance (MR) images, which in most of the cases are acquired for other purposes. This information is of great importance for physicians dealing with a wide spectrum of diseases, including cardiovascular and oncologic, for the assessment of risk, pathogenesis, clinical outcomes, response to treatments, and complications. In this review we summarize the available evidence on AI algorithms aimed to the segmentation of visceral and subcutaneous adipose tissue compartments on CT and MR images.
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Affiliation(s)
- Federico Greco
- U.O.C. Diagnostica per Immagini Territoriale Aziendale, Cittadella della Salute Azienda Sanitaria Locale di Lecce, Piazza Filippo Bottazzi, Lecce, Italy
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13
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Identification of markers that distinguish adipose tissue and glucose and insulin metabolism using a multi-modal machine learning approach. Sci Rep 2021; 11:17050. [PMID: 34426590 PMCID: PMC8382765 DOI: 10.1038/s41598-021-95688-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/21/2021] [Indexed: 01/04/2023] Open
Abstract
The study of metabolomics has improved our knowledge of the biology behind type 2 diabetes and its related metabolic physiology. We aimed to investigate markers of adipose tissue morphology, as well as insulin and glucose metabolism in 53 non-obese male individuals. The participants underwent extensive clinical, biochemical and magnetic resonance imaging phenotyping, and we also investigated non-targeted serum metabolites. We used a multi-modal machine learning approach to evaluate which serum metabolomic compounds predicted markers of glucose and insulin metabolism, adipose tissue morphology and distribution. Fasting glucose was associated with metabolites of intracellular insulin action and beta-cell dysfunction, namely cysteine-s-sulphate and n-acetylgarginine, whereas fasting insulin was predicted by myristoleoylcarnitine, propionylcarnitine and other metabolites of beta-oxidation of fatty acids. OGTT-glucose levels at 30 min were predicted by 7-Hoca, a microbiota derived metabolite, as well as eugenol, a fatty acid. Both insulin clamp and HOMA-IR were predicted by metabolites involved in beta-oxidation of fatty acids and biodegradation of triacylglycerol, namely tartrate and 3-phosphoglycerate, as well as pyruvate, xanthine and liver fat. OGTT glucose area under curve (AUC) and OGTT insulin AUC, was associated with bile acid metabolites, subcutaneous adipocyte cell size, liver fat and fatty chain acids and derivates, such as isovalerylcarnitine. Finally, subcutaneous adipocyte size was associated with long chain fatty acids, markers of sphingolipid metabolism, increasing liver fat and dopamine-sulfate 1. Ectopic liver fat was predicted by methylmalonate, adipocyte cell size, glutathione derived metabolites and fatty chain acids. Ectopic heart fat was predicted visceral fat, gamma-glutamyl tyrosine and 2-acetamidophenol sulfate. Adipocyte cell size, age, alpha-tocopherol and blood pressure were associated with visceral fat. We identified several biomarkers associated with adipose tissue pathophysiology and insulin and glucose metabolism using a multi-modal machine learning approach. Our approach demonstrated the relative importance of serum metabolites and they outperformed traditional clinical and biochemical variables for most endpoints.
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14
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Mann M, Kumar C, Zeng WF, Strauss MT. Artificial intelligence for proteomics and biomarker discovery. Cell Syst 2021; 12:759-770. [PMID: 34411543 DOI: 10.1016/j.cels.2021.06.006] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 05/07/2021] [Accepted: 06/28/2021] [Indexed: 12/14/2022]
Abstract
There is an avalanche of biomedical data generation and a parallel expansion in computational capabilities to analyze and make sense of these data. Starting with genome sequencing and widely employed deep sequencing technologies, these trends have now taken hold in all omics disciplines and increasingly call for multi-omics integration as well as data interpretation by artificial intelligence technologies. Here, we focus on mass spectrometry (MS)-based proteomics and describe how machine learning and, in particular, deep learning now predicts experimental peptide measurements from amino acid sequences alone. This will dramatically improve the quality and reliability of analytical workflows because experimental results should agree with predictions in a multi-dimensional data landscape. Machine learning has also become central to biomarker discovery from proteomics data, which now starts to outperform existing best-in-class assays. Finally, we discuss model transparency and explainability and data privacy that are required to deploy MS-based biomarkers in clinical settings.
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Affiliation(s)
- Matthias Mann
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
| | - Chanchal Kumar
- Translational Science & Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
| | - Wen-Feng Zeng
- Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
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15
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Edqvist J, Rawshani A, Rawshani A, Adiels M, Franzén S, Bjorck L, Svensson AM, Lind M, Sattar N, Rosengren A. Trajectories in HbA1c and other risk factors among adults with type 1 diabetes by age at onset. BMJ Open Diabetes Res Care 2021; 9:9/1/e002187. [PMID: 34059526 PMCID: PMC8169495 DOI: 10.1136/bmjdrc-2021-002187] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/18/2021] [Indexed: 11/08/2022] Open
Abstract
INTRODUCTION In type 1 diabetes, potential loss of life-years is greatest in those who are youngest at the time of onset. Using data from a nationwide cohort of patients with type 1 diabetes, we aimed to study risk factor trajectories by age at diagnosis. RESEARCH DESIGN AND METHODS We stratified 30 005 patients with type 1 diabetes aged 18-75 years into categories based on age at onset: 0-10, 11-15, 16-20, 21-25, and 26-30 years. HbA1c, albuminuria, estimated glomerular filtration rate (eGFR), body mass index (BMI), low-denisty lipoprotein (LDL)-cholesterol, systolic blood pressure (SBP), and diastolic blood pressure trends were analyzed using mixed models. Variable importance for baseline HbA1c was analyzed using conditional random forest and gradient boosting machine approaches. RESULTS Individuals aged ≥16 years at onset displayed a relatively low mean HbA1c level (~55-57 mmol/mol) that gradually increased. In contrast, individuals diagnosed at ≤15 years old entered adulthood with a mean HbA1c of approximately 70 mmol/mol. For all groups, HbA1c levels stabilized at a mean of approximately 65 mmol/mol by about 40 years old. In patients who were young at the time of onset, albuminuria appeared at an earlier age, suggesting a more rapid decrease in eGFR, while there were no distinct differences in BMI, SBP, and LDL-cholesterol trajectories between groups. Low education, higher age, and poor risk factor control were associated with higher HbA1c levels. CONCLUSIONS Young age at the diabetes onset plays a substantial role in subsequent glycemic control and the presence of albuminuria, where patients with early onset may accrue a substantial glycemic load during this period.
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Affiliation(s)
- Jon Edqvist
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Araz Rawshani
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Aidin Rawshani
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Martin Adiels
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Department of Public Health and Community Medicine, University of Gothenburg Health Metrics Unit, Gothenburg, Sweden
| | - Stefan Franzén
- National Diabetes Register, Centre of Registers, Gothenburg, Sweden
| | - Lena Bjorck
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Goteborg, Sweden
| | | | - Marcus Lind
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Medicine, Uddevalla Hospital, Uddevalia, Region of Vastra Gotaland, Sweden
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, Scotland, UK
| | - Annika Rosengren
- Department of Molecular and Clinical Medicine, Institute of Medicine, Gothenburg, Västra Götaland, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Goteborg, Sweden
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16
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Liu RK, Lin X, Wang Z, Greenbaum J, Qiu C, Zeng CP, Zhu YY, Shen J, Deng HW. Identification of novel functional CpG-SNPs associated with Type 2 diabetes and birth weight. Aging (Albany NY) 2021; 13:10619-10658. [PMID: 33835050 PMCID: PMC8064204 DOI: 10.18632/aging.202828] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 03/04/2021] [Indexed: 12/18/2022]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of genetic loci for type 2 diabetes (T2D) and birth weight (BW); however, a large proportion of the total trait heritability remains unexplained. The previous studies were generally focused on individual traits and largely failed to identify the majority of the variants that play key functional roles in the etiology of the disease. Here, we aim to identify novel functional loci for T2D, BW and the pleiotropic variants shared between them by performing a targeted conditional false discovery rate (cFDR) analysis that integrates two independent GWASs with summary statistics for T2D (n = 26,676 cases and 132,532 controls) and BW (n = 153,781) which entails greater statistical power than individual trait analyses. In this analysis, we considered CpG-SNPs, which are SNPs that may influence DNA methylation status, and are therefore considered to be functionally important. We identified 103 novel CpG-SNPs for T2D, 182 novel CpG-SNPs for BW (cFDR < 0.05), and 52 novel pleiotropic loci for both (conjunction cFDR [ccFDR] < 0.05). Among the identified novel CpG-SNPs, 33 were annotated as methylation quantitative trait loci (meQTLs) in whole blood, and 145 displayed at least some effects on meQTL, metabolic QTL (metaQTL), and/or expression QTL (eQTL). These findings may provide further insights into the shared biological mechanisms and functional genetic determinants that overlap between T2D and BW, thereby providing novel potential targets for treatment/intervention development.
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Affiliation(s)
- Rui-Ke Liu
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
- Department of Endocrinology and Metabolism, SSL Central Hospital of Dongguan City, Dongguan 523326, China
| | - Xu Lin
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Zun Wang
- Xiangya Nursing School, Central South University, Changsha 410013, China
| | - Jonathan Greenbaum
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chuan Qiu
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chun-Ping Zeng
- Department of Endocrinology and metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510330, China
| | - Yong-Yao Zhu
- Department of Endocrinology and Metabolism, SSL Central Hospital of Dongguan City, Dongguan 523326, China
| | - Jie Shen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Hong-Wen Deng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
- School of Basic Medical Sciences, Central South University, Changsha 410000, China
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17
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Carpentier AC. 100 th anniversary of the discovery of insulin perspective: insulin and adipose tissue fatty acid metabolism. Am J Physiol Endocrinol Metab 2021; 320:E653-E670. [PMID: 33522398 DOI: 10.1152/ajpendo.00620.2020] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Insulin inhibits systemic nonesterified fatty acid (NEFA) flux to a greater degree than glucose or any other metabolite. This remarkable effect is mainly due to insulin-mediated inhibition of intracellular triglyceride (TG) lipolysis in adipose tissues and is essential to prevent diabetic ketoacidosis, but also to limit the potential lipotoxic effects of NEFA in lean tissues that contribute to the development of diabetes complications. Insulin also regulates adipose tissue fatty acid esterification, glycerol and TG synthesis, lipogenesis, and possibly oxidation, contributing to the trapping of dietary fatty acids in the postprandial state. Excess NEFA flux at a given insulin level has been used to define in vivo adipose tissue insulin resistance. Adipose tissue insulin resistance defined in this fashion has been associated with several dysmetabolic features and complications of diabetes, but the mechanistic significance of this concept is not fully understood. This review focusses on the in vivo regulation of adipose tissue fatty acid metabolism by insulin and the mechanistic significance of the current definition of adipose tissue insulin resistance. One hundred years after the discovery of insulin and despite decades of investigations, much is still to be understood about the multifaceted in vivo actions of this hormone on adipose tissue fatty acid metabolism.
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Affiliation(s)
- André C Carpentier
- Division of Endocrinology, Department of Medicine, Centre de recherche du CHUS, Université de Sherbrooke, Sherbrooke, Quebec, Canada
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18
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Piccialli F, Calabrò F, Crisci D, Cuomo S, Prezioso E, Mandile R, Troncone R, Greco L, Auricchio R. Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease. Sci Rep 2021; 11:5683. [PMID: 33707543 PMCID: PMC7952550 DOI: 10.1038/s41598-021-84951-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 02/23/2021] [Indexed: 02/07/2023] Open
Abstract
Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic predisposition, a significant production of antihuman transglutaminase antibodies, but no morphological changes in the small bowel mucosa. A minority of patients (17%) showed clinical symptoms and need a gluten free diet at time of diagnosis, while the majority progress over several years (up to a decade) without any clinical problem neither a progression of the small intestine mucosal damage even when they continued to assume gluten in their diet. Recently we developed a traditional multivariate approach to predict the natural history, on the base of the information at enrolment (time 0) by a discriminant analysis model. Still, the traditional multivariate model requires stringent assumptions that may not be answered in the clinical setting. Starting from a follow-up dataset available for PCD, we propose the application of Machine Learning (ML) methodologies to extend the analysis on available clinical data and to detect most influent features predicting the outcome. These features, collected at time of diagnosis, should be capable to classify patients who will develop duodenal atrophy from those who will remain potential. Four ML methods were adopted to select features predictive of the outcome; the feature selection procedure was indeed capable to reduce the number of overall features from 85 to 19. ML methodologies (Random Forests, Extremely Randomized Trees, and Boosted Trees, Logistic Regression) were adopted, obtaining high values of accuracy: all report an accuracy above 75%. The specificity score was always more than 75% also, with two of the considered methods over 98%, while the best performance of sensitivity was 60%. The best model, optimized Boosted Trees, was able to classify PCD starting from the selected 19 features with an accuracy of 0.80, sensitivity of 0.58 and specificity of 0.84. Finally, with this work, we are able to categorize PCD patients that can more likely develop overt CD using ML. ML techniques appear to be an innovative approach to predict the outcome of PCD, since they provide a step forward in the direction of precision medicine aimed to customize healthcare, medical therapies, decisions, and practices tailoring the clinical management of PCD children.
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Affiliation(s)
- Francesco Piccialli
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples "Federico II", Via Cintia, Monte S. Angelo, 80126, Naples, Italy
| | - Francesco Calabrò
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples "Federico II", Via Cintia, Monte S. Angelo, 80126, Naples, Italy.
| | - Danilo Crisci
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples "Federico II", Via Cintia, Monte S. Angelo, 80126, Naples, Italy
| | - Salvatore Cuomo
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples "Federico II", Via Cintia, Monte S. Angelo, 80126, Naples, Italy
| | - Edoardo Prezioso
- Department of Mathematics and Applications "Renato Caccioppoli", University of Naples "Federico II", Via Cintia, Monte S. Angelo, 80126, Naples, Italy
| | - Roberta Mandile
- Department of Translational Medical Sciences, University of Naples "Federico II", Naples, Italy
| | - Riccardo Troncone
- Department of Translational Medical Sciences, University of Naples "Federico II", Naples, Italy.,European Laboratory for the Investigation of Food Induced Diseases (ELFID), University of Naples "Federico II", Naples, Italy
| | - Luigi Greco
- Department of Translational Medical Sciences, University of Naples "Federico II", Naples, Italy.,European Laboratory for the Investigation of Food Induced Diseases (ELFID), University of Naples "Federico II", Naples, Italy
| | - Renata Auricchio
- Department of Translational Medical Sciences, University of Naples "Federico II", Naples, Italy.,European Laboratory for the Investigation of Food Induced Diseases (ELFID), University of Naples "Federico II", Naples, Italy
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Lipid Traffic Analysis reveals the impact of high paternal carbohydrate intake on offsprings' lipid metabolism. Commun Biol 2021; 4:163. [PMID: 33547386 PMCID: PMC7864968 DOI: 10.1038/s42003-021-01686-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 01/08/2021] [Indexed: 12/12/2022] Open
Abstract
In this paper we present an investigation of parental-diet-driven metabolic programming in offspring using a novel computational network analysis tool. The impact of high paternal carbohydrate intake on offsprings’ phospholipid and triglyceride metabolism in F1 and F2 generations is described. Detailed lipid profiles were acquired from F1 neonate (3 weeks), F1 adult (16 weeks) and F2 neonate offspring in serum, liver, brain, heart and abdominal adipose tissues by MS and NMR. Using a purpose-built computational tool for analysing both phospholipid and fat metabolism as a network, we characterised the number, type and abundance of lipid variables in and between tissues (Lipid Traffic Analysis), finding a variety of reprogrammings associated with paternal diet. These results are important because they describe the long-term metabolic result of dietary intake by fathers. This analytical approach is important because it offers unparalleled insight into possible mechanisms for alterations in lipid metabolism throughout organisms. Furse et al. use a purpose-built computational tool called Lipid Traffic Analysis to determine the spatial distribution of lipids throughout an organism. They use it to show that high paternal carbohydrate intake influences lipid metabolism in offspring two generations hence.
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