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Maruthur NM, Pilla SJ, White K, Wu B, Maw MTT, Duan D, Turkson-Ocran RA, Zhao D, Charleston J, Peterson CM, Dougherty RJ, Schrack JA, Appel LJ, Guallar E, Clark JM. Effect of Isocaloric, Time-Restricted Eating on Body Weight in Adults With Obesity : A Randomized Controlled Trial. Ann Intern Med 2024. [PMID: 38639542 DOI: 10.7326/m23-3132] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/20/2024] Open
Abstract
BACKGROUND Time-restricted eating (TRE) lowers body weight in many studies. Whether TRE induces weight loss independent of reductions in calorie intake, as seen in rodent studies, is unknown. OBJECTIVE To determine the effect of TRE versus a usual eating pattern (UEP) on body weight in the setting of stable caloric intake. DESIGN Randomized, isocaloric feeding study. (ClinicalTrials.gov: NCT03527368). SETTING Clinical research unit. PARTICIPANTS Adults with obesity and prediabetes or diet-controlled diabetes. INTERVENTION Participants were randomly assigned 1:1 to TRE (10-hour eating window, 80% of calories before 1 p.m.) or UEP (≤16-hour window, ≥50% of calories after 5 p.m.) for 12 weeks. Both groups had the same nutrient content and were isocaloric with total calories determined at baseline. MEASUREMENTS Primary outcome was change in body weight at 12 weeks. Secondary outcomes were fasting glucose, homeostatic model assessment for insulin resistance (HOMA-IR), glucose area under the curve by oral glucose tolerance test, and glycated albumin. We used linear mixed models to evaluate the effect of interventions on outcomes. RESULTS All 41 randomly assigned participants (mean age, 59 years; 93% women; 93% Black race; mean BMI, 36 kg/m2) completed the intervention. Baseline weight was 95.6 kg (95% CI, 89.6 to 101.6 kg) in the TRE group and 103.7 kg (CI, 95.3 to 112.0 kg) in the UEP group. At 12 weeks, weight decreased by 2.3 kg (CI, 1.0 to 3.5 kg) in the TRE group and by 2.6 kg (CI, 1.5 to 3.7 kg) in the UEP group (average difference TRE vs. UEP, 0.3 kg [CI, -1.2 to 1.9 kg]). Change in glycemic measures did not differ between groups. LIMITATION Small, single-site study; baseline differences in weight by group. CONCLUSION In the setting of isocaloric eating, TRE did not decrease weight or improve glucose homeostasis relative to a UEP, suggesting that any effects of TRE on weight in prior studies may be due to reductions in caloric intake. PRIMARY FUNDING SOURCE American Heart Association.
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Affiliation(s)
- Nisa M Maruthur
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore; and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland (N.M.M., L.J.A., E.G., J.M.C.)
| | - Scott J Pilla
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore; Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore; and Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland (S.J.P.)
| | - Karen White
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland (K.W.)
| | - Beiwen Wu
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; and Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada (B.W.)
| | - May Thu Thu Maw
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; and Department of General Internal Medicine, University of Maryland Capital Region Medical Center, Largo, Maryland (M.T.T.M.)
| | - Daisy Duan
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland (D.D.)
| | - Ruth-Alma Turkson-Ocran
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; and General Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts (R.-A.T.)
| | - Di Zhao
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health Baltimore; and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland (D.Z.)
| | - Jeanne Charleston
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore; and Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland (J.C.)
| | - Courtney M Peterson
- Department of Nutrition Sciences, The University of Alabama at Birmingham, Birmingham, Alabama (C.M.P.)
| | - Ryan J Dougherty
- Center on Aging & Health, Johns Hopkins University, Baltimore; and Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland (R.J.D.)
| | - Jennifer A Schrack
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health Baltimore; and Center on Aging & Health, Johns Hopkins University, Baltimore, Maryland (J.A.S.)
| | - Lawrence J Appel
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore; and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland (N.M.M., L.J.A., E.G., J.M.C.)
| | - Eliseo Guallar
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore; and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland (N.M.M., L.J.A., E.G., J.M.C.)
| | - Jeanne M Clark
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore; and Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland (N.M.M., L.J.A., E.G., J.M.C.)
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Liu Y, Cui B, Zhang P, Xiao S, Duan D, Ding Y. Polymicrobial Infection Induces Adipose Tissue Dysfunction via Gingival Extracellular Vesicles. J Dent Res 2024; 103:187-196. [PMID: 38095271 DOI: 10.1177/00220345231211210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2024] Open
Abstract
Recent studies have indicated that periodontitis promotes metabolic dysregulation and insulin resistance by affecting the function of white adipose tissue (WAT). However, the mechanisms linking periodontitis to adipose tissue dysfunction still need to be explored. Extracellular vesicles (EVs) deliver messages to distal sites and regulate their function. Also, recent studies have shown that periodontitis changes the composition of EVs in body fluids and that EVs might be one of the mechanisms underlying the relationship between periodontitis and insulin resistance. Herein, we explored the impact of polymicrobial oral infection with periodontal pathogens on the function of WAT and the role of gingival EVs (gEVs) in the process. Mice were subjected to oral inoculation with 109 Porphyromonas gingivalis and 108 Fusobacterium nucleatum every other day for 14 wk. This prolonged bacterial infection induced WAT dysfunction, characterized by reduced levels of AKT phosphorylation, adiponectin, leptin, and genes associated with adipogenesis and lipogenesis. We successfully isolated gEVs with satisfactory yield and purity. The RNA sequencing results showed that the differentially expressed microRNAs in the gEVs of mice with polymicrobial oral infection were involved in insulin signaling and adipose tissue function. Notably, our in vitro experiments and RNA sequencing results revealed the functional similarities between gEVs and plasma-derived EVs. Furthermore, intraperitoneal injection with gEVs derived from mice with oral infection induced the dysfunction of WAT in healthy mice. Overall, our findings provide evidence for the influence of polymicrobial oral infection on WAT function and propose gEVs as a novel pathway through which periodontal infection may exert its effects on WAT.
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Affiliation(s)
- Y Liu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
- Department of Stomatology, The Third People's Hospital of Chengdu, The Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
| | - B Cui
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - P Zhang
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - S Xiao
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - D Duan
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Y Ding
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Department of Periodontology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China
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Duan D, Lyu W, Chai P, Ma S, Wu K, Wu C, Xiong Y, Sestan N, Zhang K, Koleske AJ. Abl2 repairs microtubules and phase separates with tubulin to promote microtubule nucleation. Curr Biol 2023; 33:4582-4598.e10. [PMID: 37858340 PMCID: PMC10877310 DOI: 10.1016/j.cub.2023.09.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 07/07/2023] [Accepted: 09/06/2023] [Indexed: 10/21/2023]
Abstract
Abl family kinases are evolutionarily conserved regulators of cell migration and morphogenesis. Genetic experiments in Drosophila suggest that Abl family kinases interact functionally with microtubules to regulate axon guidance and neuronal morphogenesis. Vertebrate Abl2 binds to microtubules and promotes their plus-end elongation, both in vitro and in cells, but the molecular mechanisms by which Abl2 regulates microtubule (MT) dynamics are unclear. We report here that Abl2 regulates MT assembly via condensation and direct interactions with both the MT lattice and tubulin dimers. We find that Abl2 promotes MT nucleation, which is further facilitated by the ability of the Abl2 C-terminal half to undergo liquid-liquid phase separation (LLPS) and form co-condensates with tubulin. Abl2 binds to regions adjacent to MT damage, facilitates MT repair via fresh tubulin recruitment, and increases MT rescue frequency and lifetime. Cryo-EM analyses strongly support a model in which Abl2 engages tubulin C-terminal tails along an extended MT lattice conformation at damage sites to facilitate repair via fresh tubulin recruitment. Abl2Δ688-790, which closely mimics a naturally occurring splice isoform, retains binding to the MT lattice but does not bind tubulin, promote MT nucleation, or increase rescue frequency. In COS-7 cells, MT reassembly after nocodazole treatment is greatly slowed in Abl2 knockout COS-7 cells compared with wild-type cells, and these defects are rescued by re-expression of Abl2, but not Abl2Δ688-790. We propose that Abl2 locally concentrates tubulin to promote MT nucleation and recruits it to defects in the MT lattice to enable repair and rescue.
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Affiliation(s)
- Daisy Duan
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Wanqing Lyu
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Pengxin Chai
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Kuanlin Wu
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Chunxiang Wu
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Yong Xiong
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA; Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA; Department of Comparative Medicine, Yale School of Medicine, New Haven, CT 06510, USA; Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale School of Medicine, New Haven, CT 06510, USA; Yale Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
| | - Kai Zhang
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Anthony J Koleske
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA; Department of Neuroscience, Yale University, New Haven, CT 06510, USA.
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Misra S, Wagner R, Ozkan B, Schön M, Sevilla-Gonzalez M, Prystupa K, Wang CC, Kreienkamp RJ, Cromer SJ, Rooney MR, Duan D, Thuesen ACB, Wallace AS, Leong A, Deutsch AJ, Andersen MK, Billings LK, Eckel RH, Sheu WHH, Hansen T, Stefan N, Goodarzi MO, Ray D, Selvin E, Florez JC, Meigs JB, Udler MS. Precision subclassification of type 2 diabetes: a systematic review. Commun Med (Lond) 2023; 3:138. [PMID: 37798471 PMCID: PMC10556101 DOI: 10.1038/s43856-023-00360-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/15/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.
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Affiliation(s)
- Shivani Misra
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- Department of Diabetes and Endocrinology, Imperial College Healthcare NHS Trust, London, UK.
| | - Robert Wagner
- Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Bige Ozkan
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Martin Schön
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Magdalena Sevilla-Gonzalez
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Katsiaryna Prystupa
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Caroline C Wang
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Raymond J Kreienkamp
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
| | - Sara J Cromer
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mary R Rooney
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anne Cathrine Baun Thuesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Amelia S Wallace
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, USA
| | - Aaron J Deutsch
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Mette K Andersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Liana K Billings
- Division of Endocrinology, Diabetes and Metabolism, NorthShore University Health System, Skokie, IL, USA
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Robert H Eckel
- Division of Endocrinology, Metabolism and Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institute, Miaoli County, Taiwan, ROC
- Division of Endocrinology and Metabolism, Taichung Veterans General Hospital, Taichung, Taiwan, ROC
- Division of Endocrinology and Metabolism, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Norbert Stefan
- German Center for Diabetes Research (DZD), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- University Hospital of Tübingen, Tübingen, Germany
- Institute of Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich, Neuherberg, Germany
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jose C Florez
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - James B Meigs
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, USA
| | - Miriam S Udler
- Programs in Metabolism and Medical & Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Division of Endocrinology, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
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Hawkins MS, Pokutnaya DY, Duan D, Coughlin JW, Martin LM, Zhao D, Goheer A, Woolf TB, Holzhauer K, Lehmann HP, Lent MR, McTigue KM, Bennett WL. Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study. Sleep Health 2023; 9:767-773. [PMID: 37268482 DOI: 10.1016/j.sleh.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 03/22/2023] [Accepted: 03/26/2023] [Indexed: 06/04/2023]
Abstract
OBJECTIVES To examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. METHODS We estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of "good" sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. RESULTS The sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. CONCLUSIONS Multidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.
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Affiliation(s)
- Marquis S Hawkins
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA.
| | - Darya Y Pokutnaya
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Daisy Duan
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Janelle W Coughlin
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Lindsay M Martin
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Di Zhao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Attia Goheer
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA; Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas B Woolf
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA; Department of Clinical Psychology, School of Professional and Applied Psychology, Philadelphia College of Osteopathic Medicine, Philadelphia, PA, USA
| | - Katherine Holzhauer
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Harold P Lehmann
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Michelle R Lent
- Department of Clinical Psychology, School of Professional and Applied Psychology, Philadelphia College of Osteopathic Medicine, Philadelphia, PA, USA
| | - Kathleen M McTigue
- Division of General Internal Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Wendy L Bennett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Tobias DK, Merino J, Ahmad A, Aiken C, Benham JL, Bodhini D, Clark AL, Colclough K, Corcoy R, Cromer SJ, Duan D, Felton JL, Francis EC, Gillard P, Gingras V, Gaillard R, Haider E, Hughes A, Ikle JM, Jacobsen LM, Kahkoska AR, Kettunen JLT, Kreienkamp RJ, Lim LL, Männistö JME, Massey R, Mclennan NM, Miller RG, Morieri ML, Most J, Naylor RN, Ozkan B, Patel KA, Pilla SJ, Prystupa K, Raghavan S, Rooney MR, Schön M, Semnani-Azad Z, Sevilla-Gonzalez M, Svalastoga P, Takele WW, Tam CHT, Thuesen ACB, Tosur M, Wallace AS, Wang CC, Wong JJ, Yamamoto JM, Young K, Amouyal C, Andersen MK, Bonham MP, Chen M, Cheng F, Chikowore T, Chivers SC, Clemmensen C, Dabelea D, Dawed AY, Deutsch AJ, Dickens LT, DiMeglio LA, Dudenhöffer-Pfeifer M, Evans-Molina C, Fernández-Balsells MM, Fitipaldi H, Fitzpatrick SL, Gitelman SE, Goodarzi MO, Grieger JA, Guasch-Ferré M, Habibi N, Hansen T, Huang C, Harris-Kawano A, Ismail HM, Hoag B, Johnson RK, Jones AG, Koivula RW, Leong A, Leung GKW, Libman IM, Liu K, Long SA, Lowe WL, Morton RW, Motala AA, Onengut-Gumuscu S, Pankow JS, Pathirana M, Pazmino S, Perez D, Petrie JR, Powe CE, Quinteros A, Jain R, Ray D, Ried-Larsen M, Saeed Z, Santhakumar V, Kanbour S, Sarkar S, Monaco GSF, Scholtens DM, Selvin E, Sheu WHH, Speake C, Stanislawski MA, Steenackers N, Steck AK, Stefan N, Støy J, Taylor R, Tye SC, Ukke GG, Urazbayeva M, Van der Schueren B, Vatier C, Wentworth JM, Hannah W, White SL, Yu G, Zhang Y, Zhou SJ, Beltrand J, Polak M, Aukrust I, de Franco E, Flanagan SE, Maloney KA, McGovern A, Molnes J, Nakabuye M, Njølstad PR, Pomares-Millan H, Provenzano M, Saint-Martin C, Zhang C, Zhu Y, Auh S, de Souza R, Fawcett AJ, Gruber C, Mekonnen EG, Mixter E, Sherifali D, Eckel RH, Nolan JJ, Philipson LH, Brown RJ, Billings LK, Boyle K, Costacou T, Dennis JM, Florez JC, Gloyn AL, Gomez MF, Gottlieb PA, Greeley SAW, Griffin K, Hattersley AT, Hirsch IB, Hivert MF, Hood KK, Josefson JL, Kwak SH, Laffel LM, Lim SS, Loos RJF, Ma RCW, Mathieu C, Mathioudakis N, Meigs JB, Misra S, Mohan V, Murphy R, Oram R, Owen KR, Ozanne SE, Pearson ER, Perng W, Pollin TI, Pop-Busui R, Pratley RE, Redman LM, Redondo MJ, Reynolds RM, Semple RK, Sherr JL, Sims EK, Sweeting A, Tuomi T, Udler MS, Vesco KK, Vilsbøll T, Wagner R, Rich SS, Franks PW. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine. Nat Med 2023; 29:2438-2457. [PMID: 37794253 PMCID: PMC10735053 DOI: 10.1038/s41591-023-02502-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 07/14/2023] [Indexed: 10/06/2023]
Abstract
Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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Affiliation(s)
- Deirdre K Tobias
- Division of Preventative Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jordi Merino
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Abrar Ahmad
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Catherine Aiken
- Department of Obstetrics and Gynaecology, The Rosie Hospital, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Jamie L Benham
- Departments of Medicine and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - Amy L Clark
- Division of Pediatric Endocrinology, Department of Pediatrics, Saint Louis University School of Medicine, SSM Health Cardinal Glennon Children's Hospital, St. Louis, MO, USA
| | - Kevin Colclough
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Rosa Corcoy
- CIBER-BBN, ISCIII, Madrid, Spain
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Sara J Cromer
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jamie L Felton
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ellen C Francis
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ, USA
| | | | - Véronique Gingras
- Department of Nutrition, Université de Montréal, Montreal, Quebec, Quebec, Canada
- Research Center, Sainte-Justine University Hospital Center, Montreal, Quebec, Quebec, Canada
| | - Romy Gaillard
- Department of Pediatrics, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Eram Haider
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Alice Hughes
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Jennifer M Ikle
- Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Anna R Kahkoska
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jarno L T Kettunen
- Helsinki University Hospital, Abdominal Centre/Endocrinology, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Raymond J Kreienkamp
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
| | - Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Asia Diabetes Foundation, Hong Kong SAR, China
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jonna M E Männistö
- Departments of Pediatrics and Clinical Genetics, Kuopio University Hospital, Kuopio, Finland
- Department of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Robert Massey
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Niamh-Maire Mclennan
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Rachel G Miller
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mario Luca Morieri
- Metabolic Disease Unit, University Hospital of Padova, Padova, Italy
- Department of Medicine, University of Padova, Padova, Italy
| | - Jasper Most
- Department of Orthopedics, Zuyderland Medical Center, Sittard-Geleen, The Netherlands
| | - Rochelle N Naylor
- Departments of Pediatrics and Medicine, University of Chicago, Chicago, IL, USA
| | - Bige Ozkan
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Kashyap Amratlal Patel
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Scott J Pilla
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Katsiaryna Prystupa
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Sridharan Raghavan
- Section of Academic Primary Care, US Department of Veterans Affairs Eastern Colorado Health Care System, Aurora, CO, USA
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Mary R Rooney
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Martin Schön
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich, Neuherberg, Germany
- Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Magdalena Sevilla-Gonzalez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Pernille Svalastoga
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Wubet Worku Takele
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Claudia Ha-Ting Tam
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Anne Cathrine B Thuesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mustafa Tosur
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Division of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Houston, TX, USA
- Children's Nutrition Research Center, USDA/ARS, Houston, TX, USA
| | - Amelia S Wallace
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Caroline C Wang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jessie J Wong
- Stanford University School of Medicine, Stanford, CA, USA
| | | | - Katherine Young
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Chloé Amouyal
- Department of Diabetology, APHP, Paris, France
- Sorbonne Université, INSERM, NutriOmic team, Paris, France
| | - Mette K Andersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maxine P Bonham
- Department of Nutrition, Dietetics and Food, Monash University, Melbourne, Victoria, Australia
| | - Mingling Chen
- Monash Centre for Health Research and Implementation, Monash University, Clayton, Victoria, Australia
| | - Feifei Cheng
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Tinashe Chikowore
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sian C Chivers
- Department of Women and Children's Health, King's College London, London, UK
| | - Christoffer Clemmensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Adem Y Dawed
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Aaron J Deutsch
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Laura T Dickens
- Section of Adult and Pediatric Endocrinology, Diabetes and Metabolism, Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Linda A DiMeglio
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics, Riley Hospital for Children, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Carmella Evans-Molina
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Richard L. Roudebush VAMC, Indianapolis, IN, USA
| | - María Mercè Fernández-Balsells
- Biomedical Research Institute Girona, IdIBGi, Girona, Spain
- Diabetes, Endocrinology and Nutrition Unit Girona, University Hospital Dr Josep Trueta, Girona, Spain
| | - Hugo Fitipaldi
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Stephanie L Fitzpatrick
- Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Stephen E Gitelman
- University of California at San Francisco, Department of Pediatrics, Diabetes Center, San Francisco, CA, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jessica A Grieger
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nahal Habibi
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Chuiguo Huang
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Arianna Harris-Kawano
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Heba M Ismail
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Benjamin Hoag
- Division of Endocrinology and Diabetes, Department of Pediatrics, Sanford Children's Hospital, Sioux Falls, SD, USA
- University of South Dakota School of Medicine, E Clark St, Vermillion, SD, USA
| | - Randi K Johnson
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Angus G Jones
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Robert W Koivula
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Aaron Leong
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gloria K W Leung
- Department of Nutrition, Dietetics and Food, Monash University, Melbourne, Victoria, Australia
| | | | - Kai Liu
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - S Alice Long
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Robert W Morton
- Department of Pathology & Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Translational Medicine, Medical Science, Novo Nordisk Foundation, Hellerup, Denmark
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Maleesa Pathirana
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
| | - Sofia Pazmino
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinologyó, KU Leuven, Leuven, Belgium
| | - Dianna Perez
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - John R Petrie
- School of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Camille E Powe
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Obstetrics, Gynecology, and Reproductive Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alejandra Quinteros
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Rashmi Jain
- Sanford Children's Specialty Clinic, Sioux Falls, SD, USA
- Department of Pediatrics, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Mathias Ried-Larsen
- Centre for Physical Activity Research, Rigshospitalet, Copenhagen, Denmark
- Institute for Sports and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Zeb Saeed
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Vanessa Santhakumar
- Division of Preventative Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sarah Kanbour
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- AMAN Hospital, Doha, Qatar
| | - Sudipa Sarkar
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Gabriela S F Monaco
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Denise M Scholtens
- Department of Preventive Medicine, Division of Biostatistics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan, Taiwan
- Divsion of Endocrinology and Metabolism, Taichung Veterans General Hospital, Taichung, Taiwan
- Division of Endocrinology and Metabolism, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Cate Speake
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Maggie A Stanislawski
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Nele Steenackers
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinologyó, KU Leuven, Leuven, Belgium
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Norbert Stefan
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich, Neuherberg, Germany
- University Hospital of Tübingen, Tübingen, Germany
| | - Julie Støy
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | | | - Sok Cin Tye
- Sections on Genetics and Epidemiology, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Marzhan Urazbayeva
- Division of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Houston, TX, USA
- Gastroenterology, Baylor College of Medicine, Houston, TX, USA
| | - Bart Van der Schueren
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinologyó, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
| | - Camille Vatier
- Sorbonne University, Inserm U938, Saint-Antoine Research Centre, Institute of Cardiometabolism and Nutrition, Paris, France
- Department of Endocrinology, Diabetology and Reproductive Endocrinology, Assistance Publique-Hôpitaux de Paris, Saint-Antoine University Hospital, National Reference Center for Rare Diseases of Insulin Secretion and Insulin Sensitivity (PRISIS), Paris, France
| | - John M Wentworth
- Royal Melbourne Hospital Department of Diabetes and Endocrinology, Parkville, Victoria, Australia
- Walter and Eliza Hall Institute, Parkville, Victoria, Australia
- University of Melbourne Department of Medicine, Parkville, Victoria, Australia
| | - Wesley Hannah
- Deakin University, Melbourne, Victoria, Australia
- Department of Epidemiology, Madras Diabetes Research Foundation, Chennai, India
| | - Sara L White
- Department of Women and Children's Health, King's College London, London, UK
- Department of Diabetes and Endocrinology, Guy's and St Thomas' Hospitals NHS Foundation Trust, London, UK
| | - Gechang Yu
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yingchai Zhang
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Shao J Zhou
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- School of Agriculture, Food and Wine, University of Adelaide, Adelaide, South Australia, Australia
| | - Jacques Beltrand
- Institut Cochin, Inserm U 10116, Paris, France
- Pediatric Endocrinology and Diabetes, Hopital Necker Enfants Malades, APHP Centre, Université de Paris, Paris, France
| | - Michel Polak
- Institut Cochin, Inserm U 10116, Paris, France
- Pediatric Endocrinology and Diabetes, Hopital Necker Enfants Malades, APHP Centre, Université de Paris, Paris, France
| | - Ingvild Aukrust
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Elisa de Franco
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Sarah E Flanagan
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Kristin A Maloney
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andrew McGovern
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Janne Molnes
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Mariam Nakabuye
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Pål Rasmus Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Hugo Pomares-Millan
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Michele Provenzano
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Cécile Saint-Martin
- Department of Medical Genetics, AP-HP Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
| | - Cuilin Zhang
- Global Center for Asian Women's Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yeyi Zhu
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Sungyoung Auh
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Russell de Souza
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Andrea J Fawcett
- Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Clinical and Organizational Development, Chicago, IL, USA
| | | | - Eskedar Getie Mekonnen
- College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
- Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Emily Mixter
- Department of Medicine and Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Diana Sherifali
- Population Health Research Institute, Hamilton, Ontario, Canada
- School of Nursing, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Robert H Eckel
- Division of Endocrinology, Metabolism, Diabetes, University of Colorado, Aurora, CO, USA
| | - John J Nolan
- Department of Clinical Medicine, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Department of Endocrinology, Wexford General Hospital, Wexford, Ireland
| | - Louis H Philipson
- Department of Medicine and Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Rebecca J Brown
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Liana K Billings
- Division of Endocrinology, NorthShore University HealthSystem, Skokie, IL, USA
- Department of Medicine, Prtizker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Kristen Boyle
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Tina Costacou
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - John M Dennis
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Jose C Florez
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anna L Gloyn
- Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Maria F Gomez
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
- Faculty of Health, Aarhus University, Aarhus, Denmark
| | - Peter A Gottlieb
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Siri Atma W Greeley
- Departments of Pediatrics and Medicine and Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Kurt Griffin
- Department of Pediatrics, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
- Sanford Research, Sioux Falls, SD, USA
| | - Andrew T Hattersley
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Irl B Hirsch
- University of Washington School of Medicine, Seattle, WA, USA
| | - Marie-France Hivert
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Korey K Hood
- Stanford University School of Medicine, Stanford, CA, USA
| | - Jami L Josefson
- Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Lori M Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Siew S Lim
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ronald C W Ma
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | | | | | - James B Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Shivani Misra
- Division of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Diabetes & Endocrinology, Imperial College Healthcare NHS Trust, London, UK
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Rinki Murphy
- Department of Medicine, Faculty of Medicine and Health Sciences, University of Auckland, Auckland, New Zealand
- Auckland Diabetes Centre, Te Whatu Ora Health New Zealand, Auckland, New Zealand
- Medical Bariatric Service, Te Whatu Ora Counties, Health New Zealand, Auckland, New Zealand
| | - Richard Oram
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Katharine R Owen
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Susan E Ozanne
- University of Cambridge, Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, Cambridge, UK
| | - Ewan R Pearson
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Wei Perng
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Toni I Pollin
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rodica Pop-Busui
- Department of Internal Medicine, Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Maria J Redondo
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Division of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Houston, TX, USA
| | - Rebecca M Reynolds
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Robert K Semple
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Emily K Sims
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arianne Sweeting
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Department of Endocrinology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Tiinamaija Tuomi
- Helsinki University Hospital, Abdominal Centre/Endocrinology, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Miriam S Udler
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kimberly K Vesco
- Kaiser Permanente Northwest, Kaiser Permanente Center for Health Research, Portland, OR, USA
| | - Tina Vilsbøll
- Clinial Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Robert Wagner
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Paul W Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
- Department of Translational Medicine, Medical Science, Novo Nordisk Foundation, Hellerup, Denmark.
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Cadena MA, Amaya C, Duan D, Rico CA, García-Bayona L, Blanco AT, Agreda YS, Villegas Rodríguez GJ, Ceja A, Martinez VG, Goldman OV, Fernandez RW. Insights and strategies for improving equity in graduate school admissions. Cell 2023; 186:3529-3547. [PMID: 37595563 PMCID: PMC10512701 DOI: 10.1016/j.cell.2023.07.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 05/12/2023] [Accepted: 07/18/2023] [Indexed: 08/20/2023]
Abstract
Applying to graduate school can be particularly challenging for students from historically minoritized backgrounds due to a hidden curriculum in the graduate admissions process. To address this issue, a team of volunteer STEM trainees established the Científico Latino Graduate Student Mentorship Initiative (CL-GSMI) in 2019 to support applicants from historically minoritized backgrounds. CL-GSMI is designed to improve access to critical resources, including information, mentorship, and financial support, and has assisted 443 students in applying and matriculating to graduate school. Using program evaluation data from 2020 to 2021, we highlight areas in graduate school admissions that can be improved to promote equity and inclusion.
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Affiliation(s)
- Melissa Andrea Cadena
- Department of Biomedical Engineering, Emory University School of Medicine and Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Cathy Amaya
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | - Daisy Duan
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06510, USA
| | | | | | - Aníbal Tornes Blanco
- Department of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yessica Santana Agreda
- Neuroscience Graduate Program, Vollum Institute, Oregon Health & Science University, Portland, OR 97239, USA
| | | | - Alexis Ceja
- Department of Community Health Systems, School of Nursing, University of California, San Francisco, 2 Koret Way, N505, San Francisco, CA 94143, USA
| | - Vianna G Martinez
- Department of Pathology, Duke University School of Medicine, Durham, NC 27708, USA
| | - Olivia V Goldman
- Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY 10065, USA; Kavli Neural Systems Institute, New York, NY 10065, USA.
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8
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Osman A, Gu C, Kim DE, Duan D, Barron B, Pham LV, Polotsky VY, Jun JC. Ketogenic diet acutely improves gas exchange and sleep apnoea in obesity hypoventilation syndrome: A non-randomized crossover study. Respirology 2023; 28:784-793. [PMID: 37246156 DOI: 10.1111/resp.14526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 05/17/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND AND OBJECTIVE Obesity hypoventilation syndrome (OHS) causes hypercapnia which is often refractory to current therapies. We examine whether hypercapnia in OHS can be improved by a ketogenic dietary intervention. METHODS We conducted a single-arm crossover clinical trial to examine the impact of a ketogenic diet on CO2 levels in patients with OHS. Patients were instructed to adhere to 1 week of regular diet, 2 weeks of ketogenic diet, followed by 1 week of regular diet in an ambulatory setting. Adherence was assessed with capillary ketone levels and continuous glucose monitors. At weekly visits, we measured blood gases, calorimetry, body composition, metabolic profiles, and sleep studies. Outcomes were assessed with linear mixed models. RESULTS A total of 20 subjects completed the study. Blood ketones increased from 0.14 ± 0.08 during regular diet to 1.99 ± 1.11 mmol/L (p < 0.001) after 2 weeks of ketogenic diet. Ketogenic diet decreased venous CO2 by 3.0 mm Hg (p = 0.008), bicarbonate by 1.8 mmol/L (p = 0.001), and weight by 3.4 kg (p < 0.001). Sleep apnoea severity and nocturnal oxygen levels significantly improved. Ketogenic diet lowered respiratory quotient, fat mass, body water, glucose, insulin, triglycerides, leptin, and insulin-like growth factor 1. Rebound hypercapnia was observed after resuming regular diet. CO2 lowering was dependent on baseline hypercapnia, and associated with circulating ketone levels and respiratory quotient. The ketogenic diet was well tolerated. CONCLUSION This study demonstrates for the first time that a ketogenic diet may be useful for control of hypercapnia and sleep apnoea in patients with obesity hypoventilation syndrome.
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Affiliation(s)
- Adam Osman
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Chenjuan Gu
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - David E Kim
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Daisy Duan
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University, Baltimore, Maryland, USA
| | - Bobbie Barron
- Institute for Clinical and Translational Research, Johns Hopkins University, Baltimore, Maryland, USA
| | - Luu V Pham
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Vsevolod Y Polotsky
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jonathan C Jun
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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9
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Duan D, Perin J, Osman A, Sgambati F, Kim LJ, Pham LV, Polotsky VY, Jun JC. Effects of sex, age, and body mass index on serum bicarbonate. Front Sleep 2023; 2:1195823. [PMID: 37736141 PMCID: PMC10512520 DOI: 10.3389/frsle.2023.1195823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
Rationale Obesity hypoventilation syndrome (OHS) is often underdiagnosed, with significant morbidity and mortality. Bicarbonate, as a surrogate of arterial carbon dioxide, has been proposed as a screening tool for OHS. Understanding the predictors of serum bicarbonate could provide insights into risk factors for OHS. We hypothesized that the bicarbonate levels would increase with an increase in body mass index (BMI), since the prevalence of OHS increases with obesity. Methods We used the TriNetX Research Network, an electronic health record database with de-identified clinical data from participating healthcare organizations across the United States, to identify 93,320 adults without pulmonary or advanced renal diseases who had serum bicarbonate and BMI measurements within 6 months of each other between 2017 and 2022. We used linear regression analysis to examine the associations between bicarbonate and BMI, age, and their interactions for the entire cohort and stratified by sex. We also applied a non-linear machine learning algorithm (XGBoost) to examine the relative importance of age, BMI, sex, race/ethnicity, and obstructive sleep apnea (OSA) status on bicarbonate. Results This cohort population was 56% women and 72% white and 80% non-Hispanic individuals, with an average (SD) age of 49.4 (17.9) years and a BMI of 29.1 (6.1) kg/m2. The mean bicarbonate was 24.8 (2.8) mmol/L, with higher levels in men (mean 25.2 mmol/L) than in women (mean 24.4 mmol/L). We found a small negative association between bicarbonate and BMI, with an expected change of -0.03 mmol/L in bicarbonate for each 1 kg/m2 increase in BMI (p < 0.001), in the entire cohort and both sexes. We found sex differences in the bicarbonate trajectory with age, with women exhibiting lower bicarbonate values than men until age 50, after which the bicarbonate levels were modestly higher. The non-linear machine learning algorithm similarly revealed that age and sex played larger roles in determining bicarbonate levels than the BMI or OSA status. Conclusion Contrary to our hypothesis, BMI is not associated with elevated bicarbonate levels, and age modifies the impact of sex on bicarbonate.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Jamie Perin
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Adam Osman
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Francis Sgambati
- Center for Interdisciplinary Sleep Research and Education, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Lenise J. Kim
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Luu V. Pham
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Vsevolod Y. Polotsky
- Departments of Anesthesiology and Critical Care Medicine and Pharmacology and Physiology, George Washington University School of Medicine and Health Sciences, Washington, DC, United States
| | - Jonathan C. Jun
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Misra S, Wagner R, Ozkan B, Schön M, Sevilla-Gonzalez M, Prystupa K, Wang CC, Kreienkamp RJ, Cromer SJ, Rooney MR, Duan D, Thuesen ACB, Wallace AS, Leong A, Deutsch AJ, Andersen MK, Billings LK, Eckel RH, Sheu WHH, Hansen T, Stefan N, Goodarzi MO, Ray D, Selvin E, Florez JC, Meigs JB, Udler MS. Systematic review of precision subclassification of type 2 diabetes. medRxiv 2023:2023.04.19.23288577. [PMID: 37131632 PMCID: PMC10153304 DOI: 10.1101/2023.04.19.23288577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.
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Columbus A, Goheer A, Yanek L, Zhao D, Woolf TB, Martin L, Guallar E, Lehmann H, Coughlin JW, Holzhauer K, Duan D, Hawkins M, Pokutnaya D, Clark J, McTigue KM, Lent M, Bennett W. Abstract P401: Circadian Dietary Patterns and Weight Trajectories in Adults Using the Daily24 Mobile Application. Circulation 2023. [DOI: 10.1161/circ.147.suppl_1.p401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
Introduction:
It is unclear whether the timing of meals relative to sleep impacts cardiometabolic risk factors (e.g., weight gain). This cohort study aimed to detect and describe the association of the timing of caloric intake and dietary patterns (e.g., skipping breakfast) with weight trajectory over 2 years among participants who used the Daily24 mobile application to record their timing of eating and sleeping.
Hypothesis:
We hypothesized that skipping breakfast or consuming 50% or more of daily calories in the latter half of the day is associated with greater weight gain over 2 years.
Methods:
We conducted a secondary data analysis from a multi-site, electronic health record-based cohort study of adults from 3 healthcare systems in PCORnet’s PaTH Clinical Research Network. Of the 1017 participants enrolled in the study, N=407 patients downloaded and used the Daily24 mobile application for at least 2 weekdays and 1 weekend day over 6 months. We calculated the median of each participant’s daily eating and sleeping intervals. Participants’ weights were extracted from electronic health records available for up to 10 years prior to until 10 months after baseline. Weight trajectories were calculated over 2 years of this data. Participants completed online surveys about demographics and behavioral characteristics at baseline and after 4 months. We constructed multivariate linear regression models with weight trajectory as the dependent variable and breakfast skipping (i.e., not eating anything within 3 hours of waking), having a medium or large meal within 3 hours of sleep, ≥50% caloric consumption in the latter half of the day (after 12 pm), and ≥90% caloric consumption after 7 pm as independent variables. Additional independent variables included age, sex, race, days of application use, and body mass index (BMI) category.
Results:
Mean (SD) baseline age was 50.8 (15.0) years, 75.7% had a BMI≥25 kg/m
2
, 78.1% were women, and 84.0% were white. The average number of recorded Daily24 application days was 55.9 (53.5), significantly greater than the 3-day minimum inclusion criterion. The mean of participants’ median intervals from first to last meal was 11.2 (2.0) hours. Although not statistically significant, consuming 50% of daily calories in the latter half of the day and skipping breakfast were associated with an increasing weight trajectory (0.03 and 0.25 kg/year; 95% CI -0.39 to 0.45 and -0.32 to 0.82, respectively).
Conclusions:
Timing of eating (e.g., skipping breakfast or eating most calories later in the day) may be associated with very small weight increases over time. Our app-based approach may not have had enough observations to establish this association. Further research is needed to understand the clinical importance of circadian dietary patterns related to cardiometabolic health.
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Affiliation(s)
| | | | | | - Di Zhao
- Johns Hopkins Univ, Baltimore, MD
| | | | | | | | | | | | | | | | | | | | | | | | - Michelle Lent
- Philadelphia College of Osteopathic Medicine, Philadelphia, PA
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Duan D, Lyu W, Wu K, Wu C, Xiong Y, Koleske AJ. Abl2 mediates microtubule nucleation and repair via tubulin co-condensation. Biophys J 2023; 122:124a. [PMID: 36782548 DOI: 10.1016/j.bpj.2022.11.839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023] Open
Affiliation(s)
- Daisy Duan
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Wanqing Lyu
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Kuanlin Wu
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Chunxiang Wu
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Yong Xiong
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Anthony J Koleske
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
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Duan D, Kim LJ, Jun JC, Polotsky VY. Connecting insufficient sleep and insomnia with metabolic dysfunction. Ann N Y Acad Sci 2023; 1519:94-117. [PMID: 36373239 PMCID: PMC9839511 DOI: 10.1111/nyas.14926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The global epidemic of obesity and type 2 diabetes parallels the rampant state of sleep deprivation in our society. Epidemiological studies consistently show an association between insufficient sleep and metabolic dysfunction. Mechanistically, sleep and circadian rhythm exert considerable influences on hormones involved in appetite regulation and energy metabolism. As such, data from experimental sleep deprivation in humans demonstrate that insufficient sleep induces a positive energy balance with resultant weight gain, due to increased energy intake that far exceeds the additional energy expenditure of nocturnal wakefulness, and adversely impacts glucose metabolism. Conversely, animal models have found that sleep loss-induced energy expenditure exceeds caloric intake resulting in net weight loss. However, animal models have significant limitations, which may diminish the clinical relevance of their metabolic findings. Clinically, insomnia disorder and insomnia symptoms are associated with adverse glucose outcomes, though it remains challenging to isolate the effects of insomnia on metabolic outcomes independent of comorbidities and insufficient sleep durations. Furthermore, both pharmacological and behavioral interventions for insomnia may have direct metabolic effects. The goal of this review is to establish an updated framework for the causal links between insufficient sleep and insomnia and risks for type 2 diabetes and obesity.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes, and Metabolism; Department of Medicine; Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Lenise J. Kim
- Division of Pulmonary and Critical Care; Department of Medicine; Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jonathan C. Jun
- Division of Pulmonary and Critical Care; Department of Medicine; Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Vsevolod Y. Polotsky
- Division of Pulmonary and Critical Care; Department of Medicine; Johns Hopkins University School of Medicine, Baltimore, Maryland
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14
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Duan D, Gu C, Jun J, Mavronis A, Pham L, Polotsky V. PSUN111 Rationale and Design of the Dinner Time 2 Trial: A Randomized, Crossover Trial to Compare the Effects of Delayed Eating vs Delayed Sleeping on Overnight Metabolism in Healthy Volunteers. J Endocr Soc 2022. [PMCID: PMC9624900 DOI: 10.1210/jendso/bvac150.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Background Obesity and its associated metabolic complications are leading causes of morbidity and mortality worldwide. Recent studies suggest that the timing of meals may be critically important for weight control and metabolic health. Consuming calories later in the day is associated with greater risks of obesity and metabolic syndrome. Interventional diet studies show more weight loss with early, rather than later, eating. Our team conducted a randomized, crossover study ("Dinner Time Study") that compared the metabolic effects of routine dinner (6pm) vs late dinner (10pm) with a fixed sleep period (11pm-7am) in young, healthy adults. We found that late dinner caused an 18% increase in post-prandial glucose and a 10% decrease in dietary fat oxidation. These metabolic consequences in the long term may lead to the development of obesity and type 2 diabetes. However, it remains unclear whether the adverse metabolic effects of late dinner are mediated by circadian misalignment (eating at the "wrong" time relative to the body's central circadian clock) or mediated by sleep (eating too close to bedtime, coinciding with the fall in metabolic rate induced by sleep). To address this question, we aim to examine the metabolic effects of early dinner, late dinner, and late dinner followed by delayed sleep, in healthy adults. Methods Dinner Time 2 Study is a randomized crossover trial with 3 treatment arms with a 3-4-week washout period: (1) early dinner + routine sleep; (2) late dinner + routine sleep; (3) late dinner + late sleep. Dinner times and bedtimes will be customized to each participant's central circadian rhythm (assessed by dim light melatonin onset, DLMO). The primary objectives of this study are to (1) examine the metabolic effects of early dinner (DLMO-3h) vs late dinner (DLMO+1h) with a fixed routine bedtime (DLMO+2h); (2) examine the metabolic effects of routine bedtime (DLMO+2h) vs delayed bedtime (DLMO+6h) with a fixed late dinner time (DLMO+1h). We will examine 24-h profiles of glucose, insulin, free fatty acids, triglycerides, and dietary fat oxidation using serial blood sampling and an ingested stable isotope ([2H31] palmitate) tracer. We aim to recruit 20 healthy adults, age 18-30 years old, with a BMI 18-29.9 kg/m2. Participants who perform night shift work or have any sleep disorders or metabolic diseases including diabetes are ineligible. Each participant will have 4 overnight admissions to our Clinical Research Unit (1 DLMO visit and 3 metabolic visits). A total of 3 participants have successfully completed the protocol since recruitment started in 2021. Conclusion Dinner Time 2 will greatly advance our understanding of the interactions between meal timing, sleep timing, and metabolism, which could inform the design and implementation of future studies that leverage chronobiology to combat diabetes and obesity. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.
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Harrington YA, Parisi JM, Duan D, Rojo-Wissar DM, Holingue C, Spira AP. Sex Hormones, Sleep, and Memory: Interrelationships Across the Adult Female Lifespan. Front Aging Neurosci 2022; 14:800278. [PMID: 35912083 PMCID: PMC9331168 DOI: 10.3389/fnagi.2022.800278] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 06/09/2022] [Indexed: 01/26/2023] Open
Abstract
As the population of older adults grows, so will the prevalence of aging-related conditions, including memory impairments and sleep disturbances, both of which are more common among women. Compared to older men, older women are up to twice as likely to experience sleep disturbances and are at a higher risk of cognitive decline and Alzheimer's disease and related dementias (ADRD). These sex differences may be attributed in part to fluctuations in levels of female sex hormones (i.e., estrogen and progesterone) that occur across the adult female lifespan. Though women tend to experience the most significant sleep and memory problems during the peri-menopausal period, changes in memory and sleep have also been observed across the menstrual cycle and during pregnancy. Here, we review current knowledge on the interrelationships among female sex hormones, sleep, and memory across the female lifespan, propose possible mediating and moderating mechanisms linking these variables and describe implications for ADRD risk in later life.
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Affiliation(s)
- Yasmin A. Harrington
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Jeanine M. Parisi
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Darlynn M. Rojo-Wissar
- The Initiative on Stress, Trauma, and Resilience (STAR), Department of Psychiatry and Human Behavior, Center for Behavioral and Preventive Medicine, The Miriam Hospital, Warren Alpert Medical School of Brown University, Providence, RI, United States
| | - Calliope Holingue
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Adam P. Spira
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, United States
- Johns Hopkins Center on Aging and Health, Baltimore, MD, United States
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16
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Duan D, Hanson M, Holland DO, Johnson ME. Integrating protein copy numbers with interaction networks to quantify stoichiometry in clathrin-mediated endocytosis. Sci Rep 2022; 12:5413. [PMID: 35354856 PMCID: PMC8967901 DOI: 10.1038/s41598-022-09259-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 03/21/2022] [Indexed: 11/25/2022] Open
Abstract
Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at copy numbers within a cell and across cell types varying from hundreds (e.g. auxilin) to millions (e.g. clathrin). These variations contain important information about function, but without integration with the interaction network, they cannot capture how supply and demand for each protein depends on binding to shared and distinct partners. Here we construct the interface-resolved network of 82 proteins involved in CME and establish a metric, a stoichiometric balance ratio (SBR), that quantifies whether each protein in the network has an abundance that is sub- or super-stoichiometric dependent on the global competition for binding. We find that highly abundant proteins (like clathrin) are super-stoichiometric, but that not all super-stoichiometric proteins are highly abundant, across three cell populations (HeLa, fibroblast, and neuronal synaptosomes). Most strikingly, within all cells there is significant competition to bind shared sites on clathrin and the central AP-2 adaptor by other adaptor proteins, resulting in most being in excess supply. Our network and systematic analysis, including response to perturbations of network components, show how competition for shared binding sites results in functionally similar proteins having widely varying stoichiometries, due to variations in both abundance and their unique network of binding partners.
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Affiliation(s)
- Daisy Duan
- TC Jenkins Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | - Meretta Hanson
- TC Jenkins Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA
| | | | - Margaret E Johnson
- TC Jenkins Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD, 21218, USA.
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17
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Duan D, Pilla SJ, Michalski K, Laferrère B, Clark JM, Maruthur NM. Eating breakfast is associated with weight loss during an intensive lifestyle intervention for overweight/obesity. Obesity (Silver Spring) 2022; 30:378-388. [PMID: 35048528 PMCID: PMC8820381 DOI: 10.1002/oby.23340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 10/02/2021] [Accepted: 10/28/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE This study examined whether breakfast consumption frequency (BCF) is associated with weight-loss outcomes in the Look AHEAD (Action for Health in Diabetes) trial. METHODS Data from a subset of participants (n = 3,915) from Look AHEAD, a randomized trial comparing intensive lifestyle intervention (ILI) to diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, were analyzed. BCF was collected by yearly questionnaire. Multivariable linear regression models were used to estimate the association between average BCF and percentage weight change over 4 years, controlling for baseline sociodemographic, anthropometric, and diabetes-related variables. In separate models, adjustment for diet (n = 915) and physical activity level (n = 837) was performed in a subset of participants. RESULTS Four-year average BCF was similar in DSE (n = 1,916) and ILI (n = 1,999) arms (p = 0.14). Each 1-day higher average BCF was associated with an additional 0.5% weight loss in the ILI arm (p < 0.0001) but not in the DSE arm (p = 0.58). This association in the ILI arm remained significant after adjustment for diet (p = 0.02) but not after adjustment for physical activity (p = 0.36). CONCLUSIONS Breakfast consumption was associated with greater weight loss in the active treatment group of an ILI, which may be mediated by increased physical activity.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes & Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Scott J. Pilla
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Kathy Michalski
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Blandine Laferrère
- New York Nutrition Obesity Research Center, Division of Endocrinology, Columbia University Irving Medical Center, New York, NY
| | - Jeanne M. Clark
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Nisa M. Maruthur
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Welch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
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18
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Duan D, Lyu W, Koleske T. Elucidating how Abl2 tyrosine kinase regulates microtubule dynamics. Biophys J 2022. [DOI: 10.1016/j.bpj.2021.11.2155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Abstract
Overt type 2 diabetes mellitus (T2DM) is preceded by prediabetes and latent diabetes (lasts 9-12 years). Key dysglycemia screening tests are fasting plasma glucose and hemoglobin A1C. Screen-detected T2DM benefits from multifactorial management of cardiovascular risk beyond glycemia. Prediabetes is best addressed by lifestyle modification, with the goal of preventing T2DM. Although there is no trial evidence of prediabetes/T2DM screening effectiveness, simulations suggest that clinic-based opportunistic screening of high-risk individuals is cost-effective. The most rigorous extant recommendations are those of the American Diabetes Association and US Preventive Services Task Force, which advise opportunistic 3-yearly screening.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Circle, Baltimore, MD 21224, USA
| | - Andre P Kengne
- Non-Communicable Diseases Research Unit, South African Medical Research Council, Francie van Zijl Drive Parowvallei, PO Box 19070, Tygerberg, Cape Town 7505, South Africa
| | - Justin B Echouffo-Tcheugui
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Circle, Baltimore, MD 21224, USA; Welch Prevention Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
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Turkson-Ocran RAN, Miller ER, Zhao D, Pilla S, Duan D, Jaeger B, Muntner P, Clark J, Maruthur N. Abstract MP14: The Effect Of Time-restricted Feeding On 24-hour Ambulatory Blood Pressure: Results From The Time-restricted Intake Of Meals (TRIM) Study. Circulation 2021. [DOI: 10.1161/circ.143.suppl_1.mp14] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Some studies suggest that time-restricted feeding may decrease blood pressure (BP), but the current evidence is inconclusive.
Objective:
To determine the effect of a time-restricted feeding pattern compared to a usual feeding pattern on ambulatory 24-hour BP in adults.
Hypothesis:
An isocaloric, time-restricted feeding pattern will lower 24-hour BP more than an isocaloric usual feeding pattern over 12 weeks.
Methods:
Forty-one persons with prediabetes (HbA1c 5.7-6.9%) and obesity (BMI 30-50 kg/m
2
) were randomized to consume 80% of their total calories before 1 pm (i.e., time-restricted feeding) or more than 50% of their calories after 5 pm (i.e., usual feeding) with identical macronutrient content. We used ambulatory BP monitoring to measure BP over 24-hours at baseline and 12-weeks. Outcomes of interest were mean systolic and diastolic 24-hr, daytime (7 am - 11 pm), and nighttime (11 pm - 7 am) BP. To examine the difference in BP patterns between time-restricted feeding and usual feeding pattern groups in change in BP outcomes from baseline to 12 weeks, we used linear mixed-effects regression models with participant-specific random intercepts and fixed effects for visit and intervention group. To assess whether feeding patterns affected BP levels over the 12 week intervention period, we tested whether there was an intervention-by-time interaction.
Results:
Thirty-five adults (mean age 60.4 years; 91% female, 91% African American) had sufficient data. We found reductions from baseline in systolic and diastolic BP for both groups for the 24-hour, daytime, and nighttime periods. The decrease in BP was larger in the usual feeding pattern group compared to the time-restricted feeding group (Table).
Conclusion:
Time-restricted feeding may attenuate the effect of a healthy isocaloric diet on BP compared to typical feeding patterns, and at this time, should not be recommended as a way to lower BP more than simply adopting a healthy diet.
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Affiliation(s)
| | | | - Di Zhao
- Johns Hopkins Univ, Baltimore, MD
| | | | - Daisy Duan
- Johns Hopkins Sch of Medicnie, Baltimore, MD
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Duan D, Gu C, Polotsky VY, Jun JC, Pham LV. Effects of Dinner Timing on Sleep Stage Distribution and EEG Power Spectrum in Healthy Volunteers. Nat Sci Sleep 2021; 13:601-612. [PMID: 34017207 PMCID: PMC8131073 DOI: 10.2147/nss.s301113] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 04/13/2021] [Indexed: 02/05/2023] Open
Abstract
PURPOSE Eating time and sleep habits are important modifiable behaviors that affect metabolic health, but the relationship between food intake and sleep remains incompletely understood. Observational data suggest that late food intake is associated with impaired sleep quality. We examined the effect of routine dinner (RD, 5 hours before bedtime) vs late dinner (LD, 1 hour before bedtime) on sleep architecture in healthy volunteers. PARTICIPANTS AND METHODS This was a post hoc analysis of a randomized crossover study of RD vs LD with a fixed sleep opportunity in a laboratory setting. On each of the two visits, 20 healthy adult volunteers (10 women) received an isocaloric meal followed by overnight polysomnography. Sleep architecture over the course of the night was assessed using visual sleep staging and EEG spectral power analysis and was compared between RD and LD. We modeled the proportions of spectral power in alpha, beta, delta, and theta bands as functions of dinner timing, time of night, and their interaction with mixed-effect spline regression. RESULTS Conventional sleep stages were similar between the 2 visits. LD caused a 2.5% initial increase in delta power and a reciprocal 2.7% decrease in combined alpha and beta power (p<0.0001). These effects diminished as sleep continued with a reversal of these patterns in the latter part of the night. CONCLUSION Contrary to the existing literature, shifting dinner timing from 5 hours before sleep to 1 hour before sleep in healthy volunteers did not result in significant adverse changes in overnight sleep architecture. In fact, LD was associated with deeper sleep in the beginning of the night and lighter sleep in the latter part of the night in healthy volunteers. This novel manifestation of postprandial hypersomnia may have therapeutic potential in patients with sleep disorders.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chenjuan Gu
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Vsevolod Y Polotsky
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jonathan C Jun
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Luu V Pham
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Duan D, Wehbeh L, Mukherjee D, Hamrahian AH, Rodriguez FJ, Gujar S, Khalafallah AM, Hage C, Caturegli P, Gallia GL, Ahima RS, Maruthur NM, Salvatori R. Preoperative BMI Predicts Postoperative Weight Gain in Adult-onset Craniopharyngioma. J Clin Endocrinol Metab 2021; 106:e1603-e1617. [PMID: 33417676 PMCID: PMC7993568 DOI: 10.1210/clinem/dgaa985] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Indexed: 02/07/2023]
Abstract
CONTEXT Craniopharyngiomas, while benign, have the highest morbidity of all nonmalignant sellar tumors. Studies on weight and metabolic outcomes in adult-onset craniopharyngioma (AOCP) remain sparse. OBJECTIVE To examine postsurgical weight and metabolic outcomes in AOCP and to identify any clinical predictors of weight gain. METHODS Retrospective chart review of patients with AOCP who underwent surgery between January 2014 and May 2019 in a single pituitary center. The study included 45 patients with AOCP with a minimum follow-up of 3 months. Median follow-up time was 26 months (interquartile range [IQR] 10-44). Main outcome measures were the changes in weight/body mass index (BMI), metabolic comorbidities, and pituitary deficiencies between preoperative and last follow-up. RESULTS Both weight and BMI were higher at last follow-up, with a mean increase of 3.4 kg for weight (P = .015) and 1.15 kg/m2 for BMI (P = .0095). Median % weight change was 2.7% (IQR -1.1%, 8.8%). Obesity rate increased from 37.8% at baseline to 55.6% at last follow-up. One-third of patients had ~15% median weight gain. The prevalence of metabolic comorbidities at last follow-up was not different from baseline. Pituitary deficiencies increased postoperatively, with 58% of patients having ≥3 hormonal deficiencies. Preoperative BMI was inversely associated with postoperative weight gain, which remained significant after adjusting for age, sex, race, tumor, and treatment characteristics. Patients with ≥3 hormonal deficiencies at last follow-up also had higher postoperative weight gain. CONCLUSION In this AOCP cohort, those with a lower BMI at the preoperative visit had higher postoperative weight gain. Our finding may help physicians better counsel patients and provide anticipatory guidance on postoperative expectations and management.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Leen Wehbeh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Debraj Mukherjee
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Amir H Hamrahian
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fausto J Rodriguez
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sachin Gujar
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Adham M Khalafallah
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Camille Hage
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Patrizio Caturegli
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gary L Gallia
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Rexford S Ahima
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nisa M Maruthur
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Roberto Salvatori
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Correspondence: Roberto Salvatori, Division of Endocrinology, Diabetes & Metabolism, Johns Hopkins University School of Medicine, 1830 E. Monument St, Ste 333, Baltimore, MD 21287, USA.
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Kopparapu S, Khalafallah AM, Botros D, Carey AR, Rodriguez FJ, Duan D, Rowan NR, Mukherjee D. Predictors of Postoperative Visual Outcome After Surgical Intervention for Craniopharyngiomas. World Neurosurg 2021; 148:e589-e599. [PMID: 33482413 DOI: 10.1016/j.wneu.2021.01.044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 01/10/2021] [Accepted: 01/10/2021] [Indexed: 11/20/2022]
Abstract
BACKGROUND Because of involvement of the optic apparatus, craniopharyngiomas frequently present with visual deterioration. Although visual improvement is a primary goal of surgical intervention, prediction models are lacking. METHODS We retrospectively reviewed all patients undergoing craniopharyngioma surgery at a single institution (2014-2019). Preoperative, intraoperative, and postoperative variables of interest were collected. Visual acuity and visual fields (VFs) were standardized into Visual Impairment Scores (VISs), defined by the German Ophthalmological Society. VIS ranged from 0 (normal vision) to 100 (complete bilateral blindness). Visual improvement/deterioration was defined as a postsurgical decrease/increase of ≥5 VIS points, respectively. RESULTS Complete ophthalmologic assessments were available for 61 operations, corresponding to 41 patients (age, 4-73 years). Vision improved after 28 operations (46%), remained stable after 27 (44%), and deteriorated after 6 (10%). In bivariate analysis, significant predictors of visual improvement included worse preoperative VIS (odds ratio [OR], 1.058; P < 0.001), worse preoperative VF mean deviation (OR, 1.107; P = 0.032), preoperative vision deficits presenting for longer than 1 month (OR, 6.050; P = 0.010), radiographic involvement of the anterior cerebral arteries (OR, 3.555; P = 0.019), and gross total resection (OR, 4.529; P = 0.022). The translaminar surgical approach was associated with visual deterioration (OR, 6.857; P = 0.035). In multivariate analysis, worse preoperative VIS remained significantly associated with postoperative visual improvement (OR, 1.060; P = 0.011). Simple linear correlation (R2=0.398; P < 0.001) suggests prediction of postoperative VIS improvement via preoperative VIS. CONCLUSIONS Patients with reduced preoperative vision, specific radiographic vascular involvement, and gross total resection showed increased odds of visual improvement, whereas the translaminar approach was associated with visual deterioration. Such characteristics may facilitate patient-surgeon counseling and surgical decision making.
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Affiliation(s)
- Srujan Kopparapu
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Adham M Khalafallah
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - David Botros
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Andrew R Carey
- Department of Neuro-Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Fausto J Rodriguez
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Daisy Duan
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nicholas R Rowan
- Department of Otolaryngology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Debraj Mukherjee
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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Xue Y, Li C, Duan D, Wang M, Han X, Wang K, Qiao R, Li XJ, Li XL. Genome-wide association studies for growth-related traits in a crossbreed pig population. Anim Genet 2020; 52:217-222. [PMID: 33372713 DOI: 10.1111/age.13032] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2020] [Indexed: 12/24/2022]
Abstract
Growth-related traits are important economic traits in the pig industry that directly influence pork production efficiency. To detect quantitative trait loci and candidate genes affecting growth traits, genome-wide association studies were performed for backfat thickness (BF) and loin muscle depth (LMD) in 370 Chuying-black pigs using Illumina PorcineSNP50 BeadChip array. We totally identified 14 BF-associated SNPs, which included 11 genome-wide SNPs (P < 1.39E-06) and 3 chromosome-wide suggestive SNPs (P < 2.79E-05) and for LMD, 9 SNPs surpassed the genome-wide significant threshold (P < 1.39E-06). These SNPs explained 30.33 and 27.51% phenotypic variance for BF and LMD respectively. Furthermore, 14 and 9 genes nearest to the significant SNPs were selected to be candidate genes, including MAGED1, GPHN, CCSER1, and GUCY2D for BF and PARM1, COL18A1, HSF5, and SCML2 genes for LMD. One significant SNP, which explained 6.07% of phenotypic variance for BF, mapped to a pleiotropic quantitative trait locus with a 494-kb interval. Together, the SNPs and candidate genes identified in this study will advance our understanding of the complex genetic architecture of BF and LMD traits, and they will also provide important clues for future implementation of a genomic selection program in Chuying-black pigs.
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Affiliation(s)
- Y Xue
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - C Li
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - D Duan
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - M Wang
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - X Han
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - K Wang
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - R Qiao
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - X-J Li
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - X-L Li
- College of Animal Sciences and Technology, Henan Agricultural University, Zhengzhou, Henan, 450046, China
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Gu C, Brereton N, Schweitzer A, Cotter M, Duan D, Børsheim E, Wolfe RR, Pham LV, Polotsky VY, Jun JC. Metabolic Effects of Late Dinner in Healthy Volunteers-A Randomized Crossover Clinical Trial. J Clin Endocrinol Metab 2020; 105:5855227. [PMID: 32525525 PMCID: PMC7337187 DOI: 10.1210/clinem/dgaa354] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 05/07/2020] [Accepted: 06/05/2020] [Indexed: 01/25/2023]
Abstract
CONTEXT Consuming calories later in the day is associated with obesity and metabolic syndrome. We hypothesized that eating a late dinner alters substrate metabolism during sleep in a manner that promotes obesity. OBJECTIVE The objective of this work is to examine the impact of late dinner on nocturnal metabolism in healthy volunteers. DESIGN AND SETTING This is a randomized crossover trial of late dinner (LD, 22:00) vs routine dinner (RD, 18:00), with a fixed sleep period (23:00-07:00) in a laboratory setting. PARTICIPANTS Participants comprised 20 healthy volunteers (10 male, 10 female), age 26.0 ± 0.6 years, body mass index 23.2 ± 0.7 kg/m2, accustomed to a bedtime between 22:00 and 01:00. INTERVENTIONS An isocaloric macronutrient diet was administered on both visits. Dinner (35% daily kcal, 50% carbohydrate, 35% fat) with an oral lipid tracer ([2H31] palmitate, 15 mg/kg) was given at 18:00 with RD and 22:00 with LD. MAIN OUTCOME MEASURES Measurements included nocturnal and next-morning hourly plasma glucose, insulin, triglycerides, free fatty acids (FFAs), cortisol, dietary fatty acid oxidation, and overnight polysomnography. RESULTS LD caused a 4-hour shift in the postprandial period, overlapping with the sleep phase. Independent of this shift, the postprandial period following LD was characterized by higher glucose, a triglyceride peak delay, and lower FFA and dietary fatty acid oxidation. LD did not affect sleep architecture, but increased plasma cortisol. These metabolic changes were most pronounced in habitual earlier sleepers determined by actigraphy monitoring. CONCLUSION LD induces nocturnal glucose intolerance, and reduces fatty acid oxidation and mobilization, particularly in earlier sleepers. These effects might promote obesity if they recur chronically.
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Affiliation(s)
- Chenjuan Gu
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Nga Brereton
- Institute for Clinical and Translational Research, Johns Hopkins University, Baltimore, Maryland
| | - Amy Schweitzer
- Institute for Clinical and Translational Research, Johns Hopkins University, Baltimore, Maryland
| | - Matthew Cotter
- Arkansas Children’s Nutrition Center, Arkansas Children’s Research Institute, Little Rock, Arkansas
| | - Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Elisabet Børsheim
- Arkansas Children’s Nutrition Center, Arkansas Children’s Research Institute, Little Rock, Arkansas
- Department of Pediatrics, The University of Arkansas for Medical Sciences, Little Rock, Arkansas
- Department of Geriatrics, Center for Translational Research in Aging and Longevity, The University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Robert R Wolfe
- Department of Pediatrics, The University of Arkansas for Medical Sciences, Little Rock, Arkansas
- Department of Geriatrics, Center for Translational Research in Aging and Longevity, The University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Luu V Pham
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Vsevolod Y Polotsky
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Jonathan C Jun
- Division of Pulmonary and Critical Care, Department of Medicine, Johns Hopkins University, Baltimore, Maryland
- Correspondence and Reprint Requests: Jonathan C. Jun, MD, Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Circle, Room 5A50.B, Baltimore, MD 21224. E-mail:
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Chen Cardenas SM, Duan D, Rooper LM, Santhanam P, Cooper DS, Ladenson PW. Misdiagnosis of Paraganglioma by 123I-mIBG Without Stable Iodine Blockade of Thyroidal Radioiodine Uptake. J Endocr Soc 2020; 4:bvaa099. [PMID: 32793847 PMCID: PMC7414919 DOI: 10.1210/jendso/bvaa099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 07/13/2020] [Indexed: 01/02/2023] Open
Abstract
Iodine-123/iodine-131 (123I/131I)-metaiodobenzylguanidine (mIBG) scan is an established tool for the localization and treatment of neuroendocrine tumors such as paragangliomas (PGL). To minimize thyroid irradiation by the radioactive iodine in the mIBG preparation, blockade of thyroidal iodine uptake with high doses of stable iodine used to be given routinely as part of all mIBG protocols. As 123I is now more frequently utilized than 131I, concern about thyroid radiation has lessened and thyroid blockade is often considered unnecessary. However, in certain situations, the lack of thyroid blockade can significantly impact treatment decisions. This report describes 2 patients who had mediastinal masses incidentally discovered on CT scans, and on further evaluation were found to have symptoms suggesting catecholamine excess with mildly elevated plasma normetanephrine levels. 123I-mIBG scans were performed without thyroid blockade, which demonstrated accumulation of tracer in the masses that were therefore deemed positive for PGL. Both patients underwent surgical resection of the masses with their surgical pathology revealing ectopic thyroid tissue (ETT). These cases illustrate that if appropriate thyroid blockade is not performed, ETT concentrating radioiodine from mIBG can lead to falsely positive mIBG scans and unnecessary surgical procedures. We conclude that in the setting of a mass suspicious for PGL in a location potentially representing ETT, such as the mediastinum, thyroid blockade should be employed for mIBG protocols to avoid false positive scans caused by ETT.
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Affiliation(s)
- Stanley M Chen Cardenas
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Daisy Duan
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Lisa M Rooper
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Prasanna Santhanam
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - David S Cooper
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Paul W Ladenson
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland
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Duan D, Wehbeh L, Mukherjee D, Hamrahian AH, Ahima RS, Maruthur NM, Salvatori R. MON-276 Post-Surgical Metabolic Outcomes in Adult-Onset Craniopharyngioma: A Single Pituitary Center Experience. J Endocr Soc 2020. [PMCID: PMC7207351 DOI: 10.1210/jendso/bvaa046.1168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Background: Craniopharyngiomas, while benign, have the highest morbidity of all pituitary tumors. Hypothalamic obesity (HO), one of the most devastating consequences, is commonly studied in the pediatric population, but few data are available on weight and other metabolic outcomes in adult-onset craniopharyngiomas (AOCP). Methods: We conducted a retrospective chart review of 49 adult patients with AOCP who underwent surgery between 1/2014 and 5/2019 at an academic pituitary center. Weight, BMI, metabolic diseases (type 2 diabetes, hypertension, hyperlipidemia, cardiovascular disease, OSA), and pituitary hormone deficiencies were recorded pre-surgery and at last follow up and analyzed using paired t-tests or McNemar’s test. Results: Median age was 56 years (51% women), 45% had >1 surgery (range 1-5), and 49% had radiotherapy. Of 72 total surgeries, 54% were craniotomies and 68% of surgeries resulted in subtotal resections. Median follow up was 25 months. Median BMI was 29.2 and 30.5 kg/m2 at baseline and at last follow up, respectively. Weight was higher at last follow up (mean increase 2.7 kg; p=0.043), with an average of 4% weight gain. Patients with baseline normal and overweight BMI had significant weight gain (mean increase 5.1 kg, p=0.045; mean increase 5.5 kg, p=0.015 respectively), while those who were obese at baseline did not (mean increase 2.0 kg, p=0.302). The proportion of patients with obesity (BMI>30) increased from 37% to 53% (p=0.008). 31% of patients had >5% weight gain, with mean increase in BMI of 4.1 kg/m2 (p<0.0001) and mean weight gain of 13.1 kg (p<0.0001). 24.5% had an increase in the total number of metabolic diseases (p=0.07). Of 43 patients who were overweight or obese at last follow up, obesity was addressed in 51%, most commonly through lifestyle counseling (49%) and adjustment of hormone replacement in response to weight gain (23%). Two patients had bariatric surgery within one year of pituitary surgery. The proportion of patients with ≥3 hormone deficiencies increased from 18% to 55% (p=0.0003). At last follow-up, only one patient had GHD, diagnosed by low age-adjusted IGF-1 level. 14 of 15 patients with ≥3 hormone deficiencies had normal age-adjusted IGF-1 levels and one patient had normal GH provocative testing. Conclusion: Weight significantly increased after surgery for AOCP, with mean weight gain of 4%. 31% of patients had a marked increase in BMI and weight, suggesting possible HO. GHD is likely under-diagnosed in AOCP, and IGF-1 may not be a sensitive tool. Obesity-directed treatment is under-utilized in this patient population.
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Leen Wehbeh
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Debraj Mukherjee
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Amir H Hamrahian
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Rexford S Ahima
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nisa M Maruthur
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Roberto Salvatori
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chenjuan Gu
- Division of Pulmonary and Critical Care Medicine, Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jonathan C Jun
- Division of Pulmonary and Critical Care Medicine, Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Duan D, Wehbeh L, Cimino-Mathews A, Mukherjee D, Rowan N, Shanbhag S, Salvatori R, Hamrahian A. MON-419 Sellar Plasmacytoma: A Commonly Misdiagnosed Sellar Mass. J Endocr Soc 2019. [PMCID: PMC6551133 DOI: 10.1210/js.2019-mon-419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Background: Plasmacytoma, defined as neoplastic proliferation of a clone of plasma cells, is a rare presentation of multiple myeloma (MM). Plasmacytomas very rarely present in the sellar/parasellar region, with a reported prevalence of < 0.1%. Case: 51-year-old man with no past medical history presented with a 3-month history of severe headache, fatigue, and back pain. Brain MRI showed a large sellar mass 34 x 25 x 25 mm eroding the clivus and extending into the sphenoid sinus, with bilateral cavernous sinus invasion but no optic chiasm compression. Endocrine evaluation showed central hypogonadism and hypothyroidism: TSH 2.62 uIU/mL (0.45-4.5); free T4 0.8 ng/dL (0.82-1.77); total testosterone 229.3 ng/dL (264-916); LH 4.8 mIU/mL (1.7-8.6). Prolactin and AM cortisol levels were normal. Total protein and gamma gap were elevated. Patient endorsed 2 years of low libido and difficulty with erections. Physical exam showed no visual field deficit or cranial nerve palsies. Patient was presumptively diagnosed with an invasive non-functioning pituitary adenoma and underwent endoscopic endonasal trans-sphenoidal debulking of the mass. Intraoperatively, the mass was found to be fibrous and friable. Frozen pathology revealed a plasma cell neoplasm, and accordingly only a subtotal resection was performed. Final surgical pathology confirmed plasmacytoma with lambda light-chain restriction on immunostains. Post-op CT scan revealed multiple lytic lesions in the pelvis, spine, and bilateral hips. Oncologic evaluation confirmed the diagnosis of IgG lambda MM. Given evidence of systemic MM, patient was initiated on systemic chemotherapy within 20 days of surgery. Discussion: Sellar plasmacytoma is a diagnostic challenge, as preoperative imaging and clinical features may be indistinguishable from those of invasive pituitary adenoma. It often presents with mass effect symptoms such as headache, as seen in this case. However, this patient did not have visual disturbances or cranial nerve palsies (reported in 80% and 65% of cases, respectively). This patient's partial hypopituitarism is also atypical, as hypopituitarism is reported in 15% of cases. Misdiagnosis may potentially lead to inappropriate surgical approach and delay in therapy. Upon diagnosis, complete assessment for MM must be performed, as it is diagnosed concurrently with or during workup of plasmacytoma in 53% and 37% of cases, respectively. Conclusion: This case illustrates the importance of close attention to lab parameters such as gamma gap and total protein and to musculoskeletal symptoms in patients presenting with a sellar mass that were later found to be secondary to MM. Reference: (1) Lee J, Kulubya E, Pressman B, Mamelak A, Bannykh S, Zada G, and Cooper O. Sellar and clival plasmacytomas: case series of 5 patients with systematic review of 65 published cases. Pituitary. 2017 Jun;20(3):381-392
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Affiliation(s)
- Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Leen Wehbeh
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ashley Cimino-Mathews
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Debraj Mukherjee
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Nicholas Rowan
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Satish Shanbhag
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Roberto Salvatori
- Department of Medicine, Division of Endo, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Amir Hamrahian
- Medical Subspecialties Institute, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Duan D, Du GX, Kavatamane VK, Arumugam S, Tzeng YK, Chang HC, Balasubramanian G. Efficient nitrogen-vacancy centers' fluorescence excitation and collection from micrometer-sized diamond by a tapered optical fiber in endoscope-type configuration. Opt Express 2019; 27:6734-6745. [PMID: 30876253 DOI: 10.1364/oe.27.006734] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 12/27/2018] [Indexed: 06/09/2023]
Abstract
Using an optical fiber to both excite the nitrogen-vacancy (NV) center in diamond and collect its fluorescence is essential to build NV-based endoscope-type sensor. Such endoscope-type sensor can reach inaccessible fields for traditional NV-based sensors built by bulky optical components and extend the application areas. Since single NV's fluorescence is weak and can easily be buried in fluorescence from optical fiber core's oxide defects excited by the green laser, fixing a micrometer size diamond containing high-density NVs rather than a nanodiamond containing single NV or several NVs on the apex of an optical fiber to build an endoscope-type sensor is more implementable. Unfortunately, due to small numerical aperture (NA), most of the optical fibers have a low fluorescence collection efficiency, which limits the sensitivity and spatial resolution of the NV-based endoscope-type sensor. Here, using a tapered optical fiber (TOF) tip, we significantly improve the efficiency of the laser excitation and fluorescence collection of the NV ensembles in diamond. This could potentially enhance the sensitivity and spatial resolution of the NV-based endoscope-type sensor. Numerical calculations show that the TOF tip delivers a high NA and has a high NV excitation and fluorescence collection efficiency. Experiments demonstrate that such TOF tip can obtain up to over 7-fold excitation efficiency and over 15-fold fluorescence collection efficiency of that from a flat-ended fiber (non-TOF) tip.
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Abstract
Cushing's syndrome is associated with increased morbidity and mortality. Cardiovascular events, sepsis, and thromboembolism are the leading causes of mortality. Patient's with Cushing's due to a pituitary adenoma and those with Cushing's due to benign adrenal adenoma have relatively good survival outcomes often mirroring that of the general population. Persistent or recurrent disease is associated with high mortality risk. Ectopic Cushing's syndrome and Cushing's due to adrenocortical carcinoma confer the highest mortality risk among Cushing's etiologies. Prompt diagnosis and treatment, and specific monitoring for and treatment of associated comorbidities are essential to decrease the burden of mortality from Cushing's.
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Affiliation(s)
- Pedram Javanmard
- Department of Medicine, Division of Endocrinology, Diabetes, and Bone Disease, Icahn School of Medicine, The Mount Sinai Hospital, 1 Gustave L Levy Place, Box 1055, New York, NY 10029, USA
| | - Daisy Duan
- Department of Medicine, Division of Endocrinology, Diabetes, and Bone Disease, Icahn School of Medicine, The Mount Sinai Hospital, 1 Gustave L Levy Place, Box 1055, New York, NY 10029, USA
| | - Eliza B Geer
- Division of Endocrinology, Department of Medicine, Multidisciplinary Pituitary and Skull Base Tumor Center, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 419, New York, NY 10065, USA.
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Duan D, Gong X, Yuan G, Zhai F. Right linear map preserving the left spectrum of 2x2 quaternion matrices. Proc Estonian Acad Sci 2018. [DOI: 10.3176/proc.2018.4.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Sun Y, Liu C, Bo Y, You J, Zhu Y, Duan D, Cui H, Lu Q. Dietary vitamin C intake and the risk of hip fracture: a dose-response meta-analysis. Osteoporos Int 2018; 29:79-87. [PMID: 29101410 DOI: 10.1007/s00198-017-4284-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 10/20/2017] [Indexed: 12/31/2022]
Abstract
UNLABELLED The meta-analysis suggested that dietary vitamin C was statistically inversely associated with the risk of hip fracture (overall OR = 0.73, 95% CI = 0.55-0.97, I 2 = 69.1%) and with the increase of 50 mg/day vitamin C intake, the risk of hip fracture will reduce by 5% (OR = 0.95, 95% CI 0.91-1.00, P = 0.05). INTRODUCTION Previous studies had inconsistent findings regarding the association between vitamin C intake and the risk of hip fracture. Therefore, we conducted a meta-analysis to evaluate the association of dietary vitamin C intake and the risk of hip fracture. METHODS Relevant studies were identified by searching PubMed, Embase, and Web of Science up to December 2016. Additional articles were identified from reviewing the reference lists of relevant articles. The summary relative risks (RRs) or odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by random effects model. Funnel plot and Egger's test were used to test publication bias. RESULTS The total six articles containing 7908 controls and 2899 cases of hip fracture were included in this meta-analysis. By comparing the highest versus the lowest categories of vitamin C intake, we found that dietary vitamin C was statistically correlated with the risk of hip fracture [overall OR = 0.73, 95% CI = 0.55-0.97, I 2 = 69.1%]. A linear dose-response association showed that the increase with vitamin C intake of 50 mg/day statistically reduced by 5% (OR = 0.95, 95% CI 0.91-1.00, P = 0.05) the risk of hip fracture. CONCLUSIONS In conclusion, the results of current meta-analysis strongly support that increasing dietary vitamin C intake can decrease the risk of hip fracture. In order to verify the association of vitamin C intake and hip fracture risk, further well-designed largely randomized controlled trials (RCTs) are needed.
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Affiliation(s)
- Y Sun
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - C Liu
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Y Bo
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - J You
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Y Zhu
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - D Duan
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - H Cui
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Q Lu
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, China.
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Wang Y, Zhang K, Duan D, Yao G. Heart structural remodeling in a mouse model of Duchenne cardiomyopathy revealed using optical polarization tractography [Invited]. Biomed Opt Express 2017; 8:1271-1276. [PMID: 28663827 PMCID: PMC5480542 DOI: 10.1364/boe.8.001271] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 01/27/2017] [Accepted: 01/28/2017] [Indexed: 05/10/2023]
Abstract
We investigated the heart structural remodeling in the mdx4cv mouse model of Duchenne cardiomyopathy using optical polarization tractography. Whole heart tractography was obtained in freshly dissected hearts from six mdx4cv mice. Six hearts from C57BL/6J mice were also imaged as the normal control. The mdx4cv hearts were significantly larger than the control hearts and had significantly higher between-subject variations in myofiber organization. While both strains showed classic cross-helical fiber organization in the left ventricle, the rate of the myocardial fiber orientation change across the heart wall was significantly altered in the right ventricle of the mdx4cv heart.
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Affiliation(s)
- Y. Wang
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
| | - K. Zhang
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211, USA
| | - D. Duan
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211, USA
| | - G. Yao
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
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Wang Y, Ravanfar M, Zhang K, Duan D, Yao G. Mapping 3D fiber orientation in tissue using dual-angle optical polarization tractography. Biomed Opt Express 2016; 7:3855-3870. [PMID: 27867698 PMCID: PMC5102555 DOI: 10.1364/boe.7.003855] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Revised: 08/28/2016] [Accepted: 08/29/2016] [Indexed: 05/07/2023]
Abstract
Optical polarization tractography (OPT) has recently been applied to map fiber organization in the heart, skeletal muscle, and arterial vessel wall with high resolution. The fiber orientation measured in OPT represents the 2D projected fiber angle in a plane that is perpendicular to the incident light. We report here a dual-angle extension of the OPT technology to measure the actual 3D fiber orientation in tissue. This method was first verified by imaging the murine extensor digitorum muscle placed at various known orientations in space. The accuracy of the method was further studied by analyzing the 3D fiber orientation of the mouse tibialis anterior muscle. Finally we showed that dual-angle OPT successfully revealed the unique 3D "arcade" fiber structure in the bovine articular cartilage.
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Affiliation(s)
- Y. Wang
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
| | - M. Ravanfar
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
| | - K. Zhang
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211, USA
| | - D. Duan
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211, USA
| | - G. Yao
- Department of Bioengineering, University of Missouri, Columbia, MO 65211, USA
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Narula A, Benenstein RJ, Duan D, Zagha D, Li L, Choy-Shan A, Konigsberg MW, Lau G, Phillips LM, Saric M, Vreeland L, Reynolds HR. Ankle-Brachial Index Testing at the Time of Stress Testing in Patients Without Known Atherosclerosis. Clin Cardiol 2015; 39:24-9. [PMID: 26694882 DOI: 10.1002/clc.22487] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 10/18/2015] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Individuals referred for stress testing to identify coronary artery disease may have nonobstructive atherosclerosis, which is not detected by stress tests. Identification of increased risk despite a negative stress test could inform prevention efforts. Abnormal ankle-brachial index (ABI) is associated with increased cardiovascular risk. HYPOTHESIS Routine ABI testing in the stress laboratory will identify unrecognized peripheral arterial disease in some patients. METHODS Participants referred for stress testing without known history of atherosclerotic disease underwent ABI testing (n = 451). Ankle-brachial index was assessed via simultaneous arm and leg pressure using standard measurement, automated blood-pressure cuffs at rest. Ankle-brachial index was measured after exercise in 296 patients and 30 healthy controls. Abnormal postexercise ABI was defined as a >20% drop in ABI or fall in ankle pressure by >30 mm Hg. RESULTS Overall, 2.0% of participants had resting ABI ≤0.90, 3.1% had ABI ≥1.40, and 5.5% had borderline ABI. No patient with abnormal or borderline ABI had an abnormal stress test. Participants who met peripheral arterial disease screening criteria (age ≥65 or 50-64 with diabetes or smoking) tended toward greater frequency of low ABI (2.9% vs 1.0%; P = 0.06) and were more likely to have borderline ABI (0.91 to 0.99; 7.8% vs 2.9%; P = 0.006). Postexercise ABI was abnormal in 29.4% of patients and 30.0% of controls (P not significant). CONCLUSIONS Ankle-brachial index screening at rest just before stress testing detected low ABI in 2.0% of participants, all of whom had negative stress tests.
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Affiliation(s)
- Amar Narula
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Ricardo J Benenstein
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Daisy Duan
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - David Zagha
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Lilun Li
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Alana Choy-Shan
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Matthew W Konigsberg
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Ginger Lau
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Lawrence M Phillips
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | - Muhamed Saric
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
| | | | - Harmony R Reynolds
- Division of Cardiology Department of Medicine, New York University School of Medicine, New York, NY
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Wang Y, Zhang K, Wasala NB, Duan D, Yao G. Optical polarization tractography revealed significant fiber disarray in skeletal muscles of a mouse model for Duchenne muscular dystrophy. Biomed Opt Express 2015; 6:347-52. [PMID: 25780728 PMCID: PMC4354596 DOI: 10.1364/boe.6.000347] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2014] [Revised: 01/03/2015] [Accepted: 01/03/2015] [Indexed: 05/14/2023]
Abstract
Optical polarization tractography (OPT) was recently developed to visualize tissue fiber architecture with cellular-level resolution and accuracy. In this study, we explored the feasibility of using OPT to study muscle disease in the mdx4cv mouse model of Duchenne muscular dystrophy. The freshly dissected tibialis anterior muscles of mdx4cv and normal mice were imaged. A "fiber disarray index" (FDI) was developed to quantify the myofiber disorganization. In necrotic muscle regions of the mdx4cv mice, the FDI was significantly elevated and can be used to segment the 3D necrotic regions for assessing the overall muscle damage. These results demonstrated the OPT's capability for imaging microscopic fiber alternations in muscle research.
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Zi W, Duan D, Zheng J. Cognitive impairments associated with periventricular white matter hyperintensities are mediated by cortical atrophy. Acta Neurol Scand 2014; 130:178-87. [PMID: 24838230 DOI: 10.1111/ane.12262] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/16/2014] [Indexed: 11/29/2022]
Abstract
BACKGROUND Previous studies have shown that white matter lesions (WMLs) is an important risk factor for cognitive impairment, but the underlying mechanisms have not been clarified. OBJECTIVE We tested the hypothesis that the cognitive impairments associated with periventricular white matter hyperintensities (PWMHs) on magnetic resonance imaging (MRI) would be mediated by the cortical thinning of corresponding area. METHOD Sixteen stroke- and dementia-free subjects with PWMHs and 16 healthy control subjects were enrolled in this study. All participants underwent an examination of cognition, MRI-based cortical thickness measurement and a MRI-DTI scan. Then, the possible relationships among cognitive impairments, PWMHs and the topography of cortical thinning were analyzed. RESULTS Comparing with the controls, the cognitive tests of the subjects with PWMHs showed significant decline in the domains of verbal fluency and executive function. After accounting for age, gender, years of education, and treatable vascular risk factors related to cognitive performance, cortical thickness had an independent influence on the cognitive impairments, especially in the frontal pole, orbitofrontal cortex, superior and middle frontal gyrus, superior and middle temporal gyrus, insula, and cuneus. CONCLUSIONS Our results suggest that the association between PWMHs and cognitive impairments is mediated by cortical thinning.
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Affiliation(s)
- W. Zi
- Department of Neurology; Xinqiao Hospital; Third Military Medical University; Chongqing China
| | - D. Duan
- Department of Neurology; Xinqiao Hospital; Third Military Medical University; Chongqing China
| | - J. Zheng
- Department of Neurology; Xinqiao Hospital; Third Military Medical University; Chongqing China
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Wang Y, Zhang K, Wasala NB, Yao X, Duan D, Yao G. Histology validation of mapping depth-resolved cardiac fiber orientation in fresh mouse heart using optical polarization tractography. Biomed Opt Express 2014; 5:2843-55. [PMID: 25136507 PMCID: PMC4133011 DOI: 10.1364/boe.5.002843] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 07/24/2014] [Accepted: 07/24/2014] [Indexed: 05/18/2023]
Abstract
Myofiber organization in cardiac muscle plays an important role in achieving normal mechanical and electrical heart functions. An imaging tool that can reveal microstructural details of myofiber organization is valuable for both basic research and clinical applications. A high-resolution optical polarization tractography (OPT) was recently developed based on Jones matrix optical coherence tomography (JMOCT). In this study, we validated the accuracy of using OPT for measuring depth-resolved fiber orientation in fresh heart samples by comparing directly with histology images. Systematic image processing algorithms were developed to register OPT with histology images. The pixel-wise differences between the two tractographic results were analyzed in details. The results indicate that OPT can accurately image depth-resolved fiber orientation in fresh heart tissues and reveal microstructural details at the histological level.
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Affiliation(s)
- Y. Wang
- Department of Bioengineering, University of Missouri, Columbia, MO 65211 USA
| | - K. Zhang
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211 USA
| | - N. B. Wasala
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211 USA
| | - X. Yao
- Department of Bioengineering, University of Missouri, Columbia, MO 65211 USA
| | - D. Duan
- Department of Molecular Microbiology & Immunology, University of Missouri, Columbia, MO 65211 USA
| | - G. Yao
- Department of Bioengineering, University of Missouri, Columbia, MO 65211 USA
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Wang P, Duan D, Zhou X, Li X, Yang J, Deng M, Xu Y. Relationship between expression of human gingival beta-defensins and levels of periodontopathogens in subgingival plaque. J Periodontal Res 2014; 50:113-22. [PMID: 24814979 DOI: 10.1111/jre.12187] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/11/2014] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND OBJECTIVE Human beta-defensins (hBDs) are a group of antimicrobial peptides important in epithelial innate immunity, and their differential expression is associated with periodontal diseases. The aim of this study was to explore relationships among hBDs, total subgingival bacteria and periodontopathogens in healthy subjects and in patients with chronic periodontitis. MATERIAL AND METHODS The periodontal clinical parameters of 29 healthy subjects and 25 patients with chronic periodontitis were recorded. The relative expression of hBD1, hBD2 and hBD3 genes in gingival biopsies was measured using real-time PCR. The numbers of total bacteria and of Treponema denticola, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Fusobacterium nucleatum and Tannerella forsythia in subgingival plaque were quantified by real-time PCR. Data were analyzed using the Mann-Whitney U-test and Spearman's rank correlation test. RESULTS No significant differences in expression of the hBD genes were found between the group of healthy subjects and the group of patients with chronic periodontitis. Total bacteria and T. denticola were detected in all participants. F. nucleatum and T. forsythia were detected in all patients with chronic periodontitis and in 86.21% and 51.72%, respectively, of healthy volunteers. P. gingivalis and A. actinomycetemcomitans were detected in 24.14% and 17.24%, respectively, of the healthy group and in 84.00% and 12.00%, respectively, of the chronic periodontitis group. The prevalence of all bacteria, except A. actinomycetemcomitans, was significantly higher in the group of patients with chronic periodontitis than in the group of healthy subjects (p < 0.05). A significant, negative correlation was observed between total bacteria and hBD-2 (r = -0.384, p = 0.011). Upon analyzing the data in different groups, total bacteria and hBD-2 were significantly correlated (r = -0.492, p = 0.026) only in the group of healthy subjects. CONCLUSION The negative correlations between hBD-2 and total bacteria, especially in the group of healthy subjects, indicate that hBDs may play an important role by limiting an increase of bacterial load at the initial stage of periodontitis.
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Affiliation(s)
- P Wang
- State Key Laboratory of Oral Diseases, Chengdu, China; Department of Applied Oral Sciences, Center for Periodontology, The Forsyth Institute, Cambridge, MA, USA
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Talhelm T, Zhang X, Oishi S, Shimin C, Duan D, Lan X, Kitayama S. Large-Scale Psychological Differences Within China Explained by Rice Versus Wheat Agriculture. Science 2014; 344:603-8. [DOI: 10.1126/science.1246850] [Citation(s) in RCA: 554] [Impact Index Per Article: 55.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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Affiliation(s)
- Daisy Duan
- New York University School of Medicine, New York, New York, USA
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Wells RG, Lockwood J, Wei L, Duan D, Fernando P, Bensimon C, Ruddy TD. Sci-Fri AM: Imaging - 09: Serial estimation of cross-talk for correction in dual-isotope imaging with dynamic tracers. Med Phys 2012; 39:4642. [PMID: 28516654 DOI: 10.1118/1.4740195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
The recent radioisotope shortage has led to interest in non-Tc99m-based tracers. We have developed a novel I-123-labelled myocardial perfusion imaging tracer. We compare the I123-tracer to the clinical standard of Tc99m tetrofosmin in vivo in a rat model using a small-animal SPECT/CT camera. SPECT distinguishes different isotopes based on the different energies of the emitted gamma rays and thus allows simultaneous comparison of two tracer distributions in the same animal. Dual-isotope imaging is complicated by cross-talk between the energy windows of the isotopes. Standard energy-window-based correction methods are difficult to employ because of the proximity in energy of Tc99m (140keV) and I123 (159keV). Imaging the second tracer's energy window prior to its injection provides an estimate of the cross-talk. However, this estimate is only accurate if the tracer distribution is static. We use serial imaging prior to the introduction of the second tracer to estimate the dynamics of the first tracer and interpolate the cross-talk images to provide a more accurate correction. We used rat models of myocardial disease (n=3). I123 tracer was injected and imaged for one hour at 20min intervals. The Tc99m tetrofosmin was then injected and 30min later, a dual-isotope image was obtained. The impact of this approach is assessed by comparing the differences in the Tc99m-tetrofosmin image using this method with correction by simple correction for physical decay. The interpolative approach improves the accuracy of the correction by 2%-5% and thereby enhances the comparison of the two tracers.
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Affiliation(s)
- R G Wells
- Cardiology, The University of Ottawa Heart Institute, Ottawa, ON
| | - J Lockwood
- Cardiology, The University of Ottawa Heart Institute, Ottawa, ON
| | | | | | | | | | - T D Ruddy
- Cardiology, The University of Ottawa Heart Institute, Ottawa, ON
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Abstract
The retrosplenial cortex (RSP) is highly interconnected with medial temporal lobe structures, yet relatively little is known about its specific contributions to learning and memory. One possibility is that RSP is involved in forming associations between multiple sensory stimuli. Indeed, damage to RSP disrupts learning about spatial or contextual cues and also impairs learning about co-occurring conditioned stimuli (CSs). Two experiments were conducted to test this notion more rigorously. In Experiment 1, rats were trained in a serial feature negative discrimination task consisting of reinforced presentations of a tone alone and nonreinforced serial presentations of a light followed by the tone. Thus, in contrast to prior studies, this paradigm involved serial presentation of conditioned stimuli (CS), rather than simultaneous presentation. Rats with damage to RSP failed to acquire the discrimination, indicating that RSP is required for forming associations between sensory stimuli regardless of whether they occur serially or simultaneously. In Experiment 2, a sensory preconditioning task was used to determine if RSP was necessary for forming associations between stimuli even in the absence of reinforcement. During the first phase of this procedure, one auditory stimulus was paired with a light while a second auditory stimulus was presented alone. In the next phase of training, the same light was paired with food. During the final phase of the procedure both auditory stimuli were presented alone during a single session. Control, but not RSP-lesioned rats, exhibited more food cup behavior following presentation of the auditory cue that was previously paired with light compared with the unpaired auditory stimulus, indicating that a stimulus-stimulus association was formed during the first phase of training. These results support the idea that RSP has a fundamental role in forming associations between environmental stimuli.
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Affiliation(s)
- Siobhan Robinson
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
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Moe SM, Seifert MF, Chen NX, Sinders RM, Chen X, Duan D, Henley C, Martin D, Gattone VH. R-568 reduces ectopic calcification in a rat model of chronic kidney disease-mineral bone disorder (CKD-MBD). Nephrol Dial Transplant 2009; 24:2371-7. [DOI: 10.1093/ndt/gfp078] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Cheng Y, Wu J, Hertervig E, Lindgren S, Duan D, Nilsson A, Duan RD. Identification of aberrant forms of alkaline sphingomyelinase (NPP7) associated with human liver tumorigenesis. Br J Cancer 2007; 97:1441-8. [PMID: 17923876 PMCID: PMC2360232 DOI: 10.1038/sj.bjc.6604013] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Alkaline sphingomyelinase (alk-SMase) is expressed in the intestine and human liver. It may inhibit colonic tumorigenesis, and loss of function mutations have been identified in human colon cancer. The present study investigates its expression in human liver cancer. In HepG2 liver cancer cells, RT–PCR identified three transcripts with 1.4, 1.2 and 0.4 kb, respectively. The 1.4 kb form is the wild-type cDNA with five translated exons, the 1.2 kb product lacks exon 4 and the 0.4 kb form is a combination of exons 1 and 5. Genomic sequence showed that these aberrant transcripts were products of alternative splicing. Transient expression of the 1.2 kb form showed no alk-SMase activity. In HepG2 cells, the alk-SMase activity is low in monolayer condition and increased with cell polarisation. Coexistence of 1.4 and 1.2 kb forms was also identified in one hepatoma biopsy. GenBank search identified a cDNA clone from human liver tumour, which codes a protein containing full length of alk-SMase plus a 73-amino-acid tag at the N terminus. The aberrant form was translated by an alternative starting codon upstream of the wild-type mRNA. Expression study showed that linking the tag markedly reduced the enzyme activity. We also analysed human liver biopsy samples and found relatively low alk-SMase activity in diseases with increased risk of liver tumorigenesis. In conclusion, expression of alk-SMase is changed in hepatic tumorigenesis, resulting in loss or marked reduction of the enzyme function.
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Affiliation(s)
- Y Cheng
- Gastroenterology Lab, Biomedical Centre, B11, Institute of Clinical Sciences, Lund University, Lund S-221 84, Sweden
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Abstract
Adeno-associated virus (AAV) serotype-9 (AAV-9) has attracted great attention as an optimal vehicle for body-wide gene delivery. Here we examined the effect of animal age (newborn vs adult) and the route of administration (intravenous vs intra-arterial) on systemic AAV-9 transduction. We delivered an alkaline phosphatase (AP) reporter gene AAV vector (AV.RSV.AP) to either newborn (via either the facial vein or the left ventricular cavity) or adult (via tail vein) C57Bl/10 mice. At 12 weeks' postinfection, we examined the AP expression. We observed efficient transduction in multiple skeletal muscles and the heart, irrespective of the age or delivery route. However, the soleus muscle, which consists mainly of slow-twitch myofibers, was poorly transduced. Besides striated muscle, we also found consistent high-level transduction in the lung. Abundant AP-positive cells were seen in alveolar cells and vasculature, but not in bronchioles. Interestingly, several organs demonstrated an age-dependent profile. In particular, the aorta, liver and kidney were preferentially transduced in adult mice while the inner layer of retina was strongly transduced only following the neonatal administration. Taken together, our results demonstrate the robustness of intravascular AAV-9 delivery for muscle and lung gene therapy applications. The unique expression patterns in the aorta, liver, kidney and retina call for special attention when designing AAV-9 gene therapy applications for these organs.
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Affiliation(s)
- B Bostick
- Department of Molecular Microbiology and Immunology, University of Missouri, Columbia, MO, USA
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Chen NX, Duan D, O'Neill KD, Wolisi GO, Koczman JJ, Laclair R, Moe SM. The mechanisms of uremic serum-induced expression of bone matrix proteins in bovine vascular smooth muscle cells. Kidney Int 2006; 70:1046-53. [PMID: 16837922 DOI: 10.1038/sj.ki.5001663] [Citation(s) in RCA: 99] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We have previously found that uremic human serum upregulates RUNX2 in vascular smooth muscle cells (VSMCs), and that RUNX2 is upregulated in areas of vascular calcification in vivo. To confirm the role of RUNX2, we transiently transfected a dominant-negative RUNX2 (DeltaRUNX2) construct in bovine vascular smooth muscle cells (BVSMCs). Blocking RUNX2 transcriptional activity significantly decreased uremic serum induced alkaline phosphatase (ALP) activity (268+/-34 vs 188+/-9.5 U/g protein, P<0.05) and osteocalcin expression (172+/-17 vs 125+/-9 ODU, P<0.05). To determine the mechanism by which uremic serum upregulates RUNX2, we examined cell signaling pathways. BVSMCs were incubated in the presence or absence of inhibitors and RUNX2 expression and ALP activity were determined. The results demonstrate that the cyclic AMP (cAMP)/protein kinase A (PKA), but not protein kinase C, signaling pathway is involved in uremic serum-induced RUNX2 expression and ALP activity in BVSMCs. To examine potential uremic 'toxins', we measured bone morphogenetic protein (BMP)-2 concentration and found that uremic serum contained increased BMP-2 (uremic serum=169+/-33 pg/ml, normal serum=117+/-15 pg/ml, P<0.05). The incubation of BVSMCs with noggin, an inhibitor of BMP, decreased RUNX2 expression. In addition, BMP-2 secretion progressively increased during calcification and uremic serum enhanced its secretion compared to normal serum. In conclusion, this study demonstrates that RUNX2 transcriptional activity is critical in uremic serum-induced bone matrix protein expression in BVSMCs and that the cAMP/PKA pathway is involved. BMP-2 is also increased in uremic serum and can upregulate RUNX2 and calcification in vitro in VSMCs.
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Affiliation(s)
- N X Chen
- Indiana University School of Medicine, Indianapolis, Indiana, USA
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Rossow CF, Duan D, Hatton WJ, Britton F, Hume JR, Horowitz B. Functional role of amino terminus in ClC-3 chloride channel regulation by phosphorylation and cell volume. Acta Physiol (Oxf) 2006; 187:5-19. [PMID: 16734738 DOI: 10.1111/j.1748-1716.2006.01550.x] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
AIM This study investigated the functional role of the ClC-3 amino-terminus in channel regulation in response to changes in cell volume. METHODS Wild-type sClC-3 tagged with a green fluorescence protein (GFP) at the C-terminus was used as a template to construct a number of deletion mutants which were functionally expressed in NIH-3T3 cells. Whole cell and single channel patch-clamp electrophysiology was used to determine the functional properties of heterologously expressed channels. RESULTS The first 100 amino acids of the ClC-3 N-terminus were removed and the truncated channel (sClC-3DeltaNT) was functionally expressed. Immunocytochemistry confirmed membrane expression of both wtsClC-3 and sClC-3DeltaNT channels in NIH/3T3 cells. sClC-3DeltaNT yielded constitutively active functional channels, which showed no response to protein kinase C or changes in cell volume. Deletion of a cluster of negatively charged amino acids 16-21 (sClC-3Delta16-21) within the N-terminus also yielded a constitutively active open channel phenotype, indicating these amino acids are involved in the N-type regulation. Intracellular delivery of a thiol-phosphorylated peptide corresponding to N-terminal residues 12-61 (NT peptide) markedly inhibited sClC-3DeltaNT whole-cell and single-channel currents, further confirming the essential role of the N-terminus in volume regulation of channel activity. CONCLUSIONS These data strongly suggest the N-terminus of sClC-3 channels acts as a blocking particle inhibiting the flow of anions through the channel pore. This 'N-type' regulation of sClC-3 channels may be an important transducing mechanism linking changes in cell volume and channel protein phosphorylation to channel gating.
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Affiliation(s)
- C F Rossow
- Department of Physiology and Cell Biology, University of Nevada School of Medicine, Reno, NV 89557, USA
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Abstract
NVT molecular dynamics simulations were performed on liquid o-terphenyl as a function of temperature in the range 320-480 K. Computed translational diffusion coefficients displayed the non-Arrhenius behavior expected of a fragile glass-forming liquid and were in good, semiquantitative agreement with experimental results. Rotational correlation functions calculated for various vectors within the molecule exhibited a very short time (0-1 ps) initial decay, followed by a reversal, which corresponds to free reorientation within the "solvent" cage prior to collision with a wall. Rotational correlation times of three orthogonal vectors fixed on the central benzene were close to equal at all temperatures, indicating nearly isotropic overall molecular reorientation. The average correlation times exhibited a non-Arrhenius temperature dependence and were in very good agreement with experimental values derived from 2D and 1H NMR relaxation times. Correlation times of vectors located on the lateral phenyl rings were used to calculate the "spinning" internal rotation diffusion coefficients, which were approximately twice as great as the overall rotational diffusion constants, indicating rapid internal rotation of the phenyl side groups over wide ranges of angle in the liquid.
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Affiliation(s)
- R J Berry
- Air Force Research Laboratory, Materials and Manufacturing Directorate, Wright-Patterson AFB, Ohio 45433, USA
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