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Remus A, Tadeo X, Kai GNS, Blasiak A, Kee T, Vijayakumar S, Nguyen L, Raczkowska MN, Chai QY, Aliyah F, Rusalovski Y, Teo K, Yeo TT, Wong ALA, Chia D, Asplund CL, Ho D, Vellayappan BA. CURATE.AI COR-Tx platform as a digital therapy and digital diagnostic for cognitive function in patients with brain tumour postradiotherapy treatment: protocol for a prospective mixed-methods feasibility clinical trial. BMJ Open 2023; 13:e077219. [PMID: 37879700 PMCID: PMC10603439 DOI: 10.1136/bmjopen-2023-077219] [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: 06/28/2023] [Accepted: 09/29/2023] [Indexed: 10/27/2023] Open
Abstract
INTRODUCTION Conventional interventional modalities for preserving or improving cognitive function in patients with brain tumour undergoing radiotherapy usually involve pharmacological and/or cognitive rehabilitation therapy administered at fixed doses or intensities, often resulting in suboptimal or no response, due to the dynamically evolving patient state over the course of disease. The personalisation of interventions may result in more effective results for this population. We have developed the CURATE.AI COR-Tx platform, which combines a previously validated, artificial intelligence-derived personalised dosing technology with digital cognitive training. METHODS AND ANALYSIS This is a prospective, single-centre, single-arm, mixed-methods feasibility clinical trial with the primary objective of testing the feasibility of the CURATE.AI COR-Tx platform intervention as both a digital intervention and digital diagnostic for cognitive function. Fifteen patient participants diagnosed with a brain tumour requiring radiotherapy will be recruited. Participants will undergo a remote, home-based 10-week personalised digital intervention using the CURATE.AI COR-Tx platform three times a week. Cognitive function will be assessed via a combined non-digital cognitive evaluation and a digital diagnostic session at five time points: preradiotherapy, preintervention and postintervention and 16-weeks and 32-weeks postintervention. Feasibility outcomes relating to acceptability, demand, implementation, practicality and limited efficacy testing as well as usability and user experience will be assessed at the end of the intervention through semistructured patient interviews and a study team focus group discussion at study completion. All outcomes will be analysed quantitatively and qualitatively. ETHICS AND DISSEMINATION This study has been approved by the National Healthcare Group (NHG) DSRB (DSRB2020/00249). We will report our findings at scientific conferences and/or in peer-reviewed journals. TRIAL REGISTRATION NUMBER NCT04848935.
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Affiliation(s)
- Alexandria Remus
- Heat Resilence and Performance Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore
| | - Xavier Tadeo
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
| | - Grady Ng Shi Kai
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Social Sciences, Yale-NUS College, Singapore
| | - Agata Blasiak
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Theodore Kee
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore
| | - Smrithi Vijayakumar
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
| | - Le Nguyen
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore
| | - Marlena N Raczkowska
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
| | - Qian Yee Chai
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore
| | - Fatin Aliyah
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore
| | - Yaromir Rusalovski
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
| | - Kejia Teo
- Department of Surgery, Division of Neurosurgery, National University Hospital, Singapore
| | - Tseng Tsai Yeo
- Department of Surgery, Division of Neurosurgery, National University Hospital, Singapore
| | - Andrea Li Ann Wong
- Department of Hematology-Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore
| | - David Chia
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Christopher L Asplund
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Social Sciences, Yale-NUS College, Singapore
| | - Dean Ho
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The N.1 Institute for Health (N1), National University of Singapore, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- The Bia-Echo Asia Centre for Reproductive Longevity and Equality, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Balamurugan A Vellayappan
- Department of Radiation Oncology, National University Cancer Institute Singapore, National University Hospital, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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Chotirmall SH, Bogaert D, Chalmers JD, Cox MJ, Hansbro PM, Huang YJ, Molyneaux PL, O’Dwyer DN, Pragman AA, Rogers GB, Segal LN, Dickson RP. Therapeutic Targeting of the Respiratory Microbiome. Am J Respir Crit Care Med 2022; 206:535-544. [PMID: 35549655 PMCID: PMC9716896 DOI: 10.1164/rccm.202112-2704pp] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 05/11/2022] [Indexed: 11/16/2022] Open
Affiliation(s)
- Sanjay H. Chotirmall
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- Department of Respiratory and Critical Care Medicine, Tan Tock Seng Hospital, Singapore
| | - Debby Bogaert
- Center for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom
- Department of Paediatric Immunology and Infectious Diseases, University Medical Center Utrecht, Utrecht, the Netherlands
| | - James D. Chalmers
- Division of Molecular and Clinical Medicine, University of Dundee, Dundee, United Kingdom
| | - Michael J. Cox
- Institute of Microbiology and Infection, University of Birmingham, Birmingham, United Kingdom
| | - Philip M. Hansbro
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, Sydney, New South Wales, Australia
- Priority Research Centre for Healthy Lungs, Hunter Medical Research Institute and University of Newcastle, Newcastle, New South Wales, Australia
| | - Yvonne J. Huang
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan
| | - Philip L. Molyneaux
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - David N. O’Dwyer
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Alexa A. Pragman
- Department of Medicine, Minneapolis Veterans Affairs Medical Center, Minneapolis, Minnesota
- Department of Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Geraint B. Rogers
- Microbiome and Host Health, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Infection and Immunity, Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Leopoldo N. Segal
- Division of Pulmonary, Critical Care, and Sleep Medicine, New York University Grossman School of Medicine, NYU Langone Health, New York, New York; and
| | - Robert P. Dickson
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan
- Weil Institute for Critical Care Research and Innovation, Ann Arbor, Michigan
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Zhang X, Ng YY, Du Z, Li Z, Chen C, Xiao L, Chng WJ, Wang S. Vγ9Vδ2 T cells expressing a BCMA—Specific chimeric antigen receptor inhibit multiple myeloma xenograft growth. PLoS One 2022; 17:e0267475. [PMID: 35709135 PMCID: PMC9202950 DOI: 10.1371/journal.pone.0267475] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 04/08/2022] [Indexed: 11/19/2022] Open
Abstract
Vγ9Vδ2 T cells are immune effector cells capable of killing multiple myeloma (MM) cells and have been tested in clinical trials to treat MM patients. To enhance the MM cell killing function of Vγ9Vδ2 T cells, we introduced a BCMA-specific CAR into ex vivo expanded Vγ9Vδ2 T cells through electroporation of the CAR-encoding mRNA. The modified Vγ9Vδ2 T cells displayed a high cytolytic activity against BCMA-expressing MM cell lines in vitro, while sparing BCMA-negative cells, including normal B cells and monocytes. Subsequently, we intravenously injected KMS-11 human MM cells to generate a xenograft mouse model. The treatment of the tumor-bearing mice with Zometa and anti-BCMA CAR- Vγ9Vδ2 T cells resulted in a significant reduction of tumor burden in the femur region, as well as the overall tumor burden. In association with the decrease in tumor burden, the survival of the MM cell-inoculated mice was markedly prolonged. Considering the potential of Vγ9Vδ2 T cells to be used as off-the-shelf products, the modification of these cells with a BCMA-specific CAR could be an attractive option for cancer immunotherapy against bone marrow cancer MM.
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Affiliation(s)
- Xi Zhang
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Yu Yang Ng
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Zhicheng Du
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Zhendong Li
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Can Chen
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Lin Xiao
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Wee Joo Chng
- Department of Haematology-Oncology, National University Cancer Institute Singapore, National University Health System, Singapore, Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shu Wang
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
- * E-mail:
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Mathew BK, De Roza JG, Liu C, Goh LJ, Ooi CW, Chen E, Poon S, Tang WE. Which Aspect of Patient-Provider Relationship Affects Acceptance and Adherence of Insulin Therapy in Type 2 Diabetes Mellitus? A Qualitative Study in Primary Care. Diabetes Metab Syndr Obes 2022; 15:235-246. [PMID: 35153494 PMCID: PMC8828446 DOI: 10.2147/dmso.s344607] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/31/2021] [Indexed: 11/23/2022] Open
Abstract
PURPOSE In type 2 diabetes mellitus (T2DM), insulin therapy is often recommended to achieve the optimal control of disease, thereby preventing the onset and progression of diabetes-related complications. Despite knowing about the benefits, it has been reported that 71% of patients refuse insulin and the adherence rate ranges from 30 to 80%. Patient-provider relationship (PPR) may affect such insulin-related behaviours, but little is known about which aspect of PPR affects this. This study aimed to explore the key aspect of the patient-provider relationship that affects the initial insulin acceptance and continued adherence. PATIENTS AND METHODS We used the grounded theory approach in this qualitative research. The study was conducted at two primary care clinics between September 2019 and January 2021. Patients with T2DM on basal or premixed insulin were recruited using maximum variation sampling. Data were collected using semi-structured in-depth interviews and transcribed verbatim for analysis using constant comparison and synthesis. RESULTS Twenty-one participants with different levels of diabetes control and adherence were recruited. Four themes that emerged were 1) patient-provider interaction, 2) addressing the psychological fears, 3) gaining confidence in handling insulin equipment and 4) follow-up after insulin initiation. Among the subthemes, trust in doctors, provider's communication skills, patient-centred decision-making and continuity of care positively influenced insulin acceptance and adherence. Conversely, fear of being judged by the provider hindered open communication around non-adherence. Various aspects of interaction with nurses helped in alleviating patient's fear of injection and gaining confidence with the insulin equipment. CONCLUSION Many aspects of PPR affect insulin acceptance and adherence. Among these, gaining patients' trust, effective patient-provider communication, patient-centred decision-making, and ensuring continuity of care improve both insulin acceptance and treatment adherence. Various interactions with nurses help in addressing fears surrounding injection and gaining acceptance towards insulin therapy. Patients' fear of being blamed or judged by the provider negatively affects open communication around non-adherence.
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Affiliation(s)
- Blessy Koottappal Mathew
- National Healthcare Group Polyclinics, Toa Payoh Polyclinic, National Healthcare Group, Singapore
- Correspondence: Blessy Koottappal Mathew, National Healthcare Group Polyclinic, 2003 Toa Payoh Polyclinic, Lorong 8, Toa Payoh, 319260, Singapore, Email
| | | | - Changwei Liu
- National Healthcare Group Polyclinics, Geylang Polyclinic, National Healthcare Group, Singapore
| | - Ling Jia Goh
- National Healthcare Group Polyclinics, Hougang Polyclinic, National Healthcare Group, Singapore
| | - Chai Wah Ooi
- National Healthcare Group Polyclinics, Geylang Polyclinic, National Healthcare Group, Singapore
| | - Elya Chen
- National Healthcare Group Polyclinics, Clinical Research Unit, National Healthcare Group, Singapore
| | - Shixuan Poon
- National Healthcare Group Polyclinics, Toa Payoh Polyclinic, National Healthcare Group, Singapore
| | - Wern Ee Tang
- National Healthcare Group Polyclinics, Clinical Research Unit, National Healthcare Group, Singapore
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Kwon J, Liu YV, Gao C, Bassal MA, Jones AI, Yang J, Chen Z, Li Y, Yang H, Chen L, Di Ruscio A, Tay Y, Chai L, Tenen DG. Pseudogene-mediated DNA demethylation leads to oncogene activation. Sci Adv 2021; 7:eabg1695. [PMID: 34597139 PMCID: PMC10938534 DOI: 10.1126/sciadv.abg1695] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 08/10/2021] [Indexed: 06/13/2023]
Abstract
Pseudogenes, noncoding homologs of protein-coding genes, once considered nonfunctional evolutionary relics, have recently been linked to patient prognoses and cancer subtypes. Despite this potential clinical importance, only a handful of >12,000 pseudogenes in humans have been characterized in cancers to date. Here, we describe a previously unrecognized role for pseudogenes as potent epigenetic regulators that can demethylate and activate oncogenes. We focused on SALL4, a known oncogene in hepatocellular carcinoma (HCC) with eight pseudogenes. Using a locus-specific demethylating technology, we identified the critical CpG region for SALL4 expression. We demonstrated that SALL4 pseudogene 5 hypomethylates this region through interaction with DNMT1, resulting in SALL4 up-regulation. Intriguingly, pseudogene 5 is significantly up-regulated in a hepatitis B virus model before SALL4 induction, and both are increased in patients with HBV-HCC. Our results suggest that pseudogene-mediated demethylation represents a novel mechanism of oncogene activation in cancer.
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Affiliation(s)
- Junsu Kwon
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Yanjing V. Liu
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Chong Gao
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Mahmoud A. Bassal
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
- Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115 USA
| | - Adrianna I. Jones
- Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115 USA
| | - Junyu Yang
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Zhiyuan Chen
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Ying Li
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Henry Yang
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Leilei Chen
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
| | - Annalisa Di Ruscio
- Harvard Medical School Initiative for RNA Medicine, Harvard Medical School, Boston, MA 02115, USA
- Department of Translational Medicine, University of Eastern Piedmont, Novara 28100, Italy
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02214, USA
| | - Yvonne Tay
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117599, Singapore
| | - Li Chai
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Daniel G. Tenen
- Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore
- Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115 USA
- Harvard Medical School Initiative for RNA Medicine, Harvard Medical School, Boston, MA 02115, USA
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Fadil H, Totman JJ, Hausenloy DJ, Ho HH, Joseph P, Low AFH, Richards AM, Chan MY, Marchesseau S. A deep learning pipeline for automatic analysis of multi-scan cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2021; 23:47. [PMID: 33896419 PMCID: PMC8074440 DOI: 10.1186/s12968-020-00695-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 12/09/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance (CMR) sequences are commonly used to obtain a complete description of the function and structure of the heart, provided that accurate measurements are extracted from images. New methods of extraction of information are being developed, among them, deep neural networks are powerful tools that showed the ability to perform fast and accurate segmentation. Iq1n order to reduce the time spent by reading physicians to process data and minimize intra- and inter-observer variability, we propose a fully automatic multi-scan CMR image analysis pipeline. METHODS Sequence specific U-Net 2D models were trained to perform the segmentation of the left ventricle (LV), right ventricle (RV) and aorta in cine short-axis, late gadolinium enhancement (LGE), native T1 map, post-contrast T1, native T2 map and aortic flow sequences depending on the need. The models were trained and tested on a set of data manually segmented by experts using semi-automatic and manual tools. A set of parameters were computed from the resulting segmentations such as the left ventricular and right ventricular ejection fraction (EF), LGE scar percentage, the mean T1, T1 post, T2 values within the myocardium, and aortic flow. The Dice similarity coefficient, Hausdorff distance, mean surface distance, and Pearson correlation coefficient R were used to assess and compare the results of the U-Net based pipeline with intra-observer variability. Additionally, the pipeline was validated on two clinical studies. RESULTS The sequence specific U-Net 2D models trained achieved fast (≤ 0.2 s/image on GPU) and precise segmentation over all the targeted region of interest with high Dice scores (= 0.91 for LV, = 0.92 for RV, = 0.93 for Aorta in average) comparable to intra-observer Dice scores (= 0.86 for LV, = 0.87 for RV, = 0.95 for aorta flow in average). The automatically and manually computed parameters were highly correlated (R = 0.91 in average) showing results superior to the intra-observer variability (R = 0.85 in average) for every sequence presented here. CONCLUSION The proposed pipeline allows for fast and robust analysis of large CMR studies while guaranteeing reproducibility, hence potentially improving patient's diagnosis as well as clinical studies outcome.
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Affiliation(s)
- Hakim Fadil
- Centre for Translational MR Research (TMR), National University of Singapore, Singapore, 117549, Singapore.
| | - John J Totman
- Centre for Translational MR Research (TMR), National University of Singapore, Singapore, 117549, Singapore
| | - Derek J Hausenloy
- Cardiovascular & Metabolic Disorders Program, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore
- National Heart Research Institute Singapore, National Heart Centre, Singapore, Singapore
- Department of Medicine, Yong Loo Lin SoM, National University of Singapore, Singapore, 117597, Singapore
- The Hatter Cardiovascular Institute, University College London, London, UK
- Cardiovascular Research Center, College of Medical and Health Sciences, Asia University, Taichung, Taiwan
| | - Hee-Hwa Ho
- Tan Tock Seng Hospital, Singapore, 308433, Singapore
| | | | | | - A Mark Richards
- Cardiovascular Research Institute, National University of Singapore, Singapore, 119228, Singapore
- Christchurch Heart Institute, University of Otago, 8140, Christchurch, New Zealand
| | - Mark Y Chan
- Department of Medicine, Yong Loo Lin SoM, National University of Singapore, Singapore, 117597, Singapore
| | - Stephanie Marchesseau
- Centre for Translational MR Research (TMR), National University of Singapore, Singapore, 117549, Singapore
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Jeitany M, Prabhu A, Dakle P, Pathak E, Madan V, Kanojia D, Mukundan V, Jiang YY, Landesman Y, Tam WL, Kappei D, Koeffler HP. Novel carfilzomib-based combinations as potential therapeutic strategies for liposarcomas. Cell Mol Life Sci 2021; 78:1837-1851. [PMID: 32851475 PMCID: PMC7904719 DOI: 10.1007/s00018-020-03620-w] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 07/19/2020] [Accepted: 08/07/2020] [Indexed: 01/09/2023]
Abstract
Proteasome inhibitors, such as bortezomib and carfilzomib, have shown efficacy in anti-cancer therapy in hematological diseases but not in solid cancers. Here, we found that liposarcomas (LPS) are susceptible to proteasome inhibition, and identified drugs that synergize with carfilzomib, such as selinexor, an inhibitor of XPO1-mediated nuclear export. Through quantitative nuclear protein profiling and phospho-kinase arrays, we identified potential mode of actions of this combination, including interference with ribosome biogenesis and inhibition of pro-survival kinase PRAS40. Furthermore, by assessing global protein levels changes, FADS2, a key enzyme regulating fatty acids synthesis, was found down-regulated after proteasome inhibition. Interestingly, SC26196, an inhibitor of FADS2, synergized with carfilzomib. Finally, to identify further combinational options, we performed high-throughput drug screening and uncovered novel drug interactions with carfilzomib. For instance, cyclosporin A, a known immunosuppressive agent, enhanced carfilzomib's efficacy in vitro and in vivo. Altogether, these results demonstrate that carfilzomib and its combinations could be repurposed for LPS clinical management.
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Affiliation(s)
- Maya Jeitany
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore.
| | - Aishvaryaa Prabhu
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Pushkar Dakle
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Elina Pathak
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Vikas Madan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Deepika Kanojia
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Vineeth Mukundan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Yan Yi Jiang
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | | | - Wai Leong Tam
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Dennis Kappei
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Phillip Koeffler
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Cedars-Sinai Medical Center, Division of Hematology/Oncology, UCLA School of Medicine, Los Angeles, CA, USA
- Department of Hematology-Oncology, National University Cancer Institute of Singapore (NCIS), National University Hospital, Singapore, Singapore
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Shafie S, Samari E, Jeyagurunathan A, Abdin E, Chang S, Chong SA, Subramaniam M. Gender difference in quality of life (QoL) among outpatients with schizophrenia in a tertiary care setting. BMC Psychiatry 2021; 21:61. [PMID: 33509142 PMCID: PMC7842069 DOI: 10.1186/s12888-021-03051-2] [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] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 01/13/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Patients with mental illness report lower quality of life (QoL) compared to the general population. Prior research has found several differences in clinical features and experiences of male and female patients with schizophrenia. Given these differences, it is also important to explore if there are any gender differences in terms of their QoL. This study aimed to investigate differences in QoL between and within each gender among outpatients with schizophrenia in Singapore. METHODS A total of 140 outpatients were recruited through convenience sampling at the Institute of Mental Health, Singapore. QoL was measured using the brief version of World Health Organization Quality of Life (WHOQOL-BREF) which consists of four domains: physical health, psychological health, social relationships, and environment. QoL scores of males and females were compared using independent t-tests, and multiple linear regressions were used to examine sociodemographic correlates of QoL in the overall sample and within each gender. RESULTS There was no significant difference in QoL domain scores between genders. Among males, Indian ethnicity (versus Chinese ethnicity) was positively associated with physical health (β=3.03, p=0.018) while males having Technical Education/ Diploma/ A level education (versus Degree and above) were positively associated with social relationships domain (β=2.46, p=0.047). Among females, Malay ethnicity (versus Chinese ethnicity) was positively associated with physical health (β=1.95, p=0.026) psychological health (β=3.21, p=0.001) social relationships (β=2.17, p=0.048) and environment (β=2.69, p=0.006) domains, while females who were separated/divorced (versus single) were inversely associated with psychological health (β=- 2.80, p=0.044) and social relationships domains (β=- 4.33, p=0.011). Females who had Secondary and below education (versus Degree and above) were inversely associated with social relationships (β=- 2.29, p=0.028) and environment domains (β=- 1.79, p=0.048). CONCLUSIONS The findings show the importance of treatments targeting QoL to attend to both the clinical features of the illness as well patient's sociodemographic characteristics.
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Affiliation(s)
- Saleha Shafie
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore.
| | - Ellaisha Samari
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore
| | - Anitha Jeyagurunathan
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore
| | - Edimansyah Abdin
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore
| | - Sherilyn Chang
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore
| | - Siow Ann Chong
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore
| | - Mythily Subramaniam
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore, 539747, Singapore
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9
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Silvain J, Zeitouni M, Paradies V, Zheng HL, Ndrepepa G, Cavallini C, Feldman DN, Sharma SK, Mehilli J, Gili S, Barbato E, Tarantini G, Ooi SY, von Birgelen C, Jaffe AS, Thygesen K, Montalescot G, Bulluck H, Hausenloy DJ. Procedural myocardial injury, infarction and mortality in patients undergoing elective PCI: a pooled analysis of patient-level data. Eur Heart J 2021; 42:323-334. [PMID: 33257958 PMCID: PMC7850039 DOI: 10.1093/eurheartj/ehaa885] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [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: 02/28/2020] [Revised: 05/10/2020] [Accepted: 10/14/2020] [Indexed: 12/28/2022] Open
Abstract
AIMS The prognostic importance of cardiac procedural myocardial injury and myocardial infarction (MI) in chronic coronary syndrome (CCS) patients undergoing elective percutaneous coronary intervention (PCI) is still debated. METHODS AND RESULTS We analysed individual data of 9081 patients undergoing elective PCI with normal pre-PCI baseline cardiac troponin (cTn) levels. Multivariate models evaluated the association between post-PCI elevations in cTn and 1-year mortality, while an interval analysis evaluated the impact of the size of the myocardial injury on mortality. Our analysis was performed in the overall population and also according to the type of cTn used [52.0% had high-sensitivity cTn (hs-cTn)]. Procedural myocardial injury, as defined by the Fourth Universal Definition of MI (UDMI) [post-PCI cTn elevation ≥1 × 99th percentile upper reference limit (URL)], occurred in 52.8% of patients and was not associated with 1-year mortality [adj odds ratio (OR), 1.35, 95% confidence interval (CI) (0.84-1.77), P = 0.21]. The association between post-PCI cTn elevation and 1-year mortality was significant starting ≥3 × 99th percentile URL. Major myocardial injury defined by post-PCI ≥5 × 99th percentile URL occurred in 18.2% of patients and was associated with a two-fold increase in the adjusted odds of 1-year mortality [2.29, 95% CI (1.32-3.97), P = 0.004]. In the subset of patients for whom periprocedural evidence of ischaemia was collected (n = 2316), Type 4a MI defined by the Fourth UDMI occurred in 12.7% of patients and was strongly associated with 1-year mortality [adj OR 3.21, 95% CI (1.42-7.27), P = 0.005]. We also present our results according to the type of troponin used (hs-cTn or conventional troponin). CONCLUSION Our analysis has demonstrated that in CCS patients with normal baseline cTn levels, the post-PCI cTn elevation of ≥5 × 99th percentile URL used to define Type 4a MI is associated with 1-year mortality and could be used to detect 'major' procedural myocardial injury in the absence of procedural complications or evidence of new myocardial ischaemia.
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Affiliation(s)
- Johanne Silvain
- Corresponding author. Tel: +33 142162961, Fax: +33 142162931,
| | - Michel Zeitouni
- Sorbonne Université, ACTION Study Group, Institut de Cardiologie, Hôpital Pitié-Salpêtrière (AP-HP), INSERM UMRS 1166, 47-83 bld de l’Hôpital, 75013 Paris, France
| | - Valeria Paradies
- Cardiology Department, Maasstad Hospital, Rotterdam, Netherlands
| | - Huili L Zheng
- Health Promotion Board, National Registry of Diseases Office, Singapore, Singapore
| | - Gjin Ndrepepa
- Department of Adult Cardiology, Deutsches Herzzentrum München, Technische Universität, Munich, Germany
| | - Claudio Cavallini
- Division of Cardiology, Ospedale S Maria della Misericordia, Piazzale Meneghini 1, Perugia 06100, Italy
| | - Dimitri N Feldman
- Division of Cardiology, Weill Cornell Medical College, New York, NY, USA
| | - Samin K Sharma
- Cardiac Catheterization Laboratory, Cardiovascular Institute, Mount Sinai Hospital, New York, NY, USA
| | - Julinda Mehilli
- Munich University Clinic, Ludwig-Maximilians University, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | | | - Emanuele Barbato
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Napoli, Italy
| | - Giuseppe Tarantini
- Department of Cardiac, Thoracic and Vascular Sciences, University of Padua Medical School, Padua, Italy
| | - Sze Y Ooi
- Eastern Heart Clinic, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Clemens von Birgelen
- Department of Cardiology, Thoraxcentrum Twente, Medisch Spectrum Twente, Enschede, Netherlands
- Department of Health Technology and Services Research, Faculty of Behavioural, Management and Social Sciences, Technical Medical Centre, University of Twente, Enschede, Netherlands
| | - Allan S Jaffe
- Department of Cardiology, Mayo Clinic, Rochester, MN, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Kristian Thygesen
- Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark
| | - Gilles Montalescot
- Sorbonne Université, ACTION Study Group, Institut de Cardiologie, Hôpital Pitié-Salpêtrière (AP-HP), INSERM UMRS 1166, 47-83 bld de l’Hôpital, 75013 Paris, France
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10
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Gomez-Alonso MDC, Kretschmer A, Wilson R, Pfeiffer L, Karhunen V, Seppälä I, Zhang W, Mittelstraß K, Wahl S, Matias-Garcia PR, Prokisch H, Horn S, Meitinger T, Serrano-Garcia LR, Sebert S, Raitakari O, Loh M, Rathmann W, Müller-Nurasyid M, Herder C, Roden M, Hurme M, Jarvelin MR, Ala-Korpela M, Kooner JS, Peters A, Lehtimäki T, Chambers JC, Gieger C, Kettunen J, Waldenberger M. DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures. Clin Epigenetics 2021; 13:7. [PMID: 33413638 PMCID: PMC7789600 DOI: 10.1186/s13148-020-00957-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 10/22/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances. RESULTS We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations. CONCLUSION Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.
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Affiliation(s)
- Monica Del C Gomez-Alonso
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Anja Kretschmer
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Liliane Pfeiffer
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
| | - Kirstin Mittelstraß
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Pamela R Matias-Garcia
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany
| | - Sacha Horn
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Luis R Serrano-Garcia
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Microbiology, Technical University of Munich, Freising, Germany
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku, Turku University Hospital, Turku, Finland
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55101, Mainz, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- UKMRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Mika Ala-Korpela
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
- National Heart and Lung Institute, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Johannes Kettunen
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany.
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.
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11
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Lee YAJ, Xie Y, Lee PSS, Lee ES. Comparing the prevalence of multimorbidity using different operational definitions in primary care in Singapore based on a cross-sectional study using retrospective, large administrative data. BMJ Open 2020; 10:e039440. [PMID: 33318111 PMCID: PMC7737073 DOI: 10.1136/bmjopen-2020-039440] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 11/18/2020] [Accepted: 11/19/2020] [Indexed: 01/15/2023] Open
Abstract
OBJECTIVES Multimorbidity is a norm in primary care. A consensus on its operational definition remains lacking especially in the list of chronic conditions considered. This study aimed to compare six different operational definitions of multimorbidity previously reported in the literature for the context of primary care in Singapore. DESIGN, SETTING AND PARTICIPANTS This is a retrospective study using anonymised primary care data from a study population of 787 446 patients. We defined multimorbidity as having three or more chronic conditions in an individual. The prevalence of single conditions and multimorbidity with each operational definition was tabulated and standardised prevalence rates (SPRs) were obtained by adjusting for age, sex and ethnicity. We compared the operational definitions based on (1) number of chronic diseases, (2) presence of chronic diseases of high burden and (3) relevance in primary care in Singapore. IBM SPSS V.23 and Microsoft Office Excel 2019 were used for all statistical calculations and analyses. RESULTS The SPRs of multimorbidity in primary care in Singapore varied from 5.7% to 17.2%. The lists by Fortin et al, Ge et al, Low et al and Quah et al included at least 12 chronic conditions, the recommended minimal number of conditions. Quah et al considered the highest proportion of chronic diseases (92.3%) of high burden in primary care in Singapore, with SPRs of at least 1.0%. Picco et al and Subramaniam et al considered the fewest number of conditions of high relevance in primary care in Singapore. CONCLUSIONS Fortin et al's list of conditions is most suitable for describing multimorbidity in the Singapore primary care setting. Prediabetes and 'physical disability' should be added to Fortin et al's list to augment its comprehensiveness. We propose a similar study methodology be performed in other countries to identify the most suitable operational definition in their own context.
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Affiliation(s)
- Yi An Janis Lee
- National Healthcare Group Polyclinics, Clinical Research Unit, National Healthcare Group, Singapore
| | - Ying Xie
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | | | - Eng Sing Lee
- National Healthcare Group Polyclinics, Clinical Research Unit, National Healthcare Group, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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12
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Xing QR, El Farran CA, Gautam P, Chuah YS, Warrier T, Toh CXD, Kang NY, Sugii S, Chang YT, Xu J, Collins JJ, Daley GQ, Li H, Zhang LF, Loh YH. Diversification of reprogramming trajectories revealed by parallel single-cell transcriptome and chromatin accessibility sequencing. Sci Adv 2020; 6:eaba1190. [PMID: 32917699 PMCID: PMC7486102 DOI: 10.1126/sciadv.aba1190] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 07/30/2020] [Indexed: 05/16/2023]
Abstract
Cellular reprogramming suffers from low efficiency especially for the human cells. To deconstruct the heterogeneity and unravel the mechanisms for successful reprogramming, we adopted single-cell RNA sequencing (scRNA-Seq) and single-cell assay for transposase-accessible chromatin (scATAC-Seq) to profile reprogramming cells across various time points. Our analysis revealed that reprogramming cells proceed in an asynchronous trajectory and diversify into heterogeneous subpopulations. We identified fluorescent probes and surface markers to enrich for the early reprogrammed human cells. Furthermore, combinatory usage of the surface markers enabled the fine segregation of the early-intermediate cells with diverse reprogramming propensities. scATAC-Seq analysis further uncovered the genomic partitions and transcription factors responsible for the regulatory phasing of reprogramming process. Binary choice between a FOSL1 and a TEAD4-centric regulatory network determines the outcome of a successful reprogramming. Together, our study illuminates the multitude of diverse routes transversed by individual reprogramming cells and presents an integrative roadmap for identifying the mechanistic part list of the reprogramming machinery.
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Affiliation(s)
- Q R Xing
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore 637551, Singapore
| | - Chadi A El Farran
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | - Pradeep Gautam
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | - Yu Song Chuah
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore
| | - Tushar Warrier
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | - Cheng-Xu Delon Toh
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore
| | - Nam-Young Kang
- Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, A*STAR, Singapore 138667, Singapore
- Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Republic of Korea
| | - Shigeki Sugii
- Institute of Bioengineering and Nanotechnology, A*STAR, Singapore 138669, Singapore
- Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Young-Tae Chang
- Laboratory of Bioimaging Probe Development, Singapore Bioimaging Consortium, A*STAR, Singapore 138667, Singapore
- Department of Chemistry, National University of Singapore, Singapore 117543, Singapore
- Center for Self-assembly and Complexity, Institute for Basic Science (IBS), Pohang 37673, Republic of Korea
- Department of Chemistry, Pohang University of Science and Technology (POSTECH), Pohang 37673, Republic of Korea
| | - Jian Xu
- Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
- Department of Plant Systems Physiology, Institute for Water and Wetland Research, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, Netherlands
| | - James J Collins
- Institute for Medical Engineering and Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
| | - George Q Daley
- Stem Cell Program, Division of Pediatric Hematology and Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA
- Harvard Stem Cell Institute, Cambridge, MA 02138, USA
- Manton Center for Orphan Disease Research, Boston, MA 02115, USA
| | - Hu Li
- Center for Individualized Medicine, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905, USA.
| | - Li-Feng Zhang
- School of Biological Sciences, Nanyang Technological University, Singapore 637551, Singapore.
| | - Yuin-Han Loh
- Epigenetics and Cell Fates Laboratory, Programme in Stem Cell, Regenerative Medicine and Aging, Institute of Molecular and Cell Biology, A*STAR, Singapore 138673, Singapore.
- Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore 119077, Singapore
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
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13
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Thumboo J, Ow MYL, Uy EJB, Xin X, Chan ZYC, Sung SC, Bautista DC, Cheung YB. Developing a comprehensive, culturally sensitive conceptual framework of health domains in Singapore. PLoS One 2018; 13:e0199881. [PMID: 29953526 PMCID: PMC6023157 DOI: 10.1371/journal.pone.0199881] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 06/16/2018] [Indexed: 11/18/2022] Open
Abstract
The increasing focus of healthcare systems worldwide on long-term care highlights the need for culturally sensitive Health-Related Quality of Life instruments to accurately capture perceived health of various populations. Such instruments require a contextualized conceptual framework of health domains, which is lacking in some socio-cultural contexts. We developed a comprehensive and culturally sensitive conceptual framework of health domains relevant to the Singaporean population. We recruited Singaporeans/ permanent residents, English/ Chinese-speaking, with/ without chronic illnesses to participate in focus group discussions (FGDs) and in-depth interviews (IDIs). We elicited health areas participants perceived to be important for them to be happy and satisfied with life. To encourage spontaneous emergence of themes, we did not specify any aspect beyond the broad domains of Physical, Mental, and Social health so as not to limit the emergence of new themes. Themes from the transcripts were distilled through open coding (two independent coders), then classified into more abstract domains (each transcript coded independently by two coders from a pool of six coders). From October 2013 to August 2014, 121 members of the general public participated in 18 FGDs and 13 IDIs (44.6% males, mean age: 53.3 years 77% Chinese, 9% Malay, 12% Indian, 63% with chronic illness) while 13 healthcare workers participated as patient-proxies in three FGDs. Thematic analysis identified 27 domains. The 15 physical domains included physical appearance, energy, physical fitness, and health and resistance to illness. The nine mental domains included emotions, self-esteem, and personal freedom. The three social domains were social contact, social relationships, and social roles. This conceptual framework reflected physical, mental, and social dimensions of well-being, suggesting that the Singapore population's views on health support the World Health Organization's definition of health as "a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity".
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Affiliation(s)
- Julian Thumboo
- Department of Rheumatology & Immunology, Singapore General Hospital, Singapore, Singapore
- Office of Clinical, Academic & Faculty Affairs, Duke-NUS Medical School, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Mandy Y. L. Ow
- Academic Medicine Research Institute, Duke-NUS Medical School, Singapore, Singapore
| | - Elenore Judy B. Uy
- Department of Rheumatology & Immunology, Singapore General Hospital, Singapore, Singapore
| | - Xiaohui Xin
- Academic Clinical Programme for Medicine, Singapore General Hospital, Singapore, Singapore
| | - Zi Ying Clarice Chan
- Department of Rheumatology & Immunology, Singapore General Hospital, Singapore, Singapore
| | - Sharon C. Sung
- Office of Clinical Sciences, Duke-NUS Medical School, Singapore, Singapore
- Department of Child and Adolescent Psychiatry, Institute of Mental Health, Singapore, Singapore
| | - Dianne Carrol Bautista
- Singapore Clinical Research Institute, Singapore, Singapore
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
| | - Yin Bun Cheung
- Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
- Tampere Center for Child Health Research, University of Tampere and Tampere University Hospital, Tampere, Finland
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14
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Abstract
γ-Aminobutyric acid (GABA), the primary inhibitory neurotransmitter, has often been studied in relation to its role in the pathophysiology of schizophrenia. GABA is synthesized from glutamate by glutamic acid decarboxylase (GAD), derived from two genes, GAD1 and GAD2. GAD1 is expressed as both GAD67 and GAD25 mRNA transcripts with the former reported to have a lower expression level in schizophrenia compared to healthy controls and latter was reported to be predominantly expressed fetally, suggesting a role in developmental process. In this study, GAD67 and GAD25 mRNA levels were measured by quantitative PCR (qPCR) in peripheral blood of subjects with first-episode psychosis (FEP) and from healthy controls. We observed low GAD25 and GAD67 gene expression levels in human peripheral blood. There was no difference in GAD25 and GAD67 gene expression level, and GAD25/GAD67 ratio between patients with FEP and healthy controls. PANSS negative symptoms were associated with levels of GAD25 mRNA transcripts in patients with FEP. While the current study provides information on GAD25 and GAD67 mRNA transcript levels in whole blood of FEP patients, further correlation and validation work between brain regions, cerebrospinal fluid and peripheral blood expression profiling are required to provide a better understanding of GAD25 and GAD67.
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Affiliation(s)
- Jie Yin Yee
- Research Division, Institute of Mental Health, Singapore, Singapore
- * E-mail:
| | - Milawaty Nurjono
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Stephanie Ruth Teo
- Neuroscience & Behavioural Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Tih-Shih Lee
- Neuroscience & Behavioural Disorders, Duke-NUS Medical School, Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore, Singapore
- Department of General Psychiatry 1, Institute of Mental Health, Singapore, Singapore
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15
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Poremski D, Sagayadevan VD, Wang P, Lum A, Subramaniam M, Ann CS. The Impact of Stakeholder Preferences on Service User Adherence to Treatments for Schizophrenia and Metabolic Comorbidities. PLoS One 2016; 11:e0166171. [PMID: 27851771 PMCID: PMC5112999 DOI: 10.1371/journal.pone.0166171] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Accepted: 10/24/2016] [Indexed: 11/18/2022] Open
Abstract
Objective To determine how stakeholder opinions of treatments influence service user decisions to adhere to courses of actions necessary to treat metabolic conditions. Methods Qualitative open-ended interviews were conducted with 20 service providers, 25 service users, and 9 caregivers. Grounded theory was used to generate an understanding that linked preferences of care with adherence to follow-up treatments. Results Participants spoke about several considerations when discussing adherence: Resource limitations were the predominant consideration. Social considerations such as stigma and support surfaced in caregiver and service-user interviews. The influence of symptoms, especially their absence could reduce adherence, and organizational considerations related to the opinions they had about the qualifications of professionals. Discussion A rational patient model partially organizes our findings, but emotional components related to stigma and the opinion of service providers do not fit well into such a model. If service providers do not consider components of the decision making process which fall outside of the rational patient model, they may incorrectly be leveraging suboptimal values to bring about adherence to treatment plans. Being sensitive to the values of service users and their caregivers may allow service providers to better act on points that may bring about change in non-compliant service users with schizophrenia and metabolic comorbidities.
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Affiliation(s)
- Daniel Poremski
- Research Division, Institute of Mental Health, Singapore, Singapore
- * E-mail:
| | | | - Peizhi Wang
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Alvin Lum
- Research Division, Institute of Mental Health, Singapore, Singapore
| | | | - Chong Siow Ann
- Research Division, Institute of Mental Health, Singapore, Singapore
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