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Duo Y, Song S, Zhang Y, Qiao X, Xu J, Zhang J, Peng Z, Chen Y, Nie X, Sun Q, Yang X, Wang A, Sun W, Fu Y, Dong Y, Lu Z, Yuan T, Zhao W. Predictability of HOMA-IR for Gestational Diabetes Mellitus in Early Pregnancy Based on Different First Trimester BMI Values. J Pers Med 2022; 13:jpm13010060. [PMID: 36675721 PMCID: PMC9866419 DOI: 10.3390/jpm13010060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/24/2022] [Accepted: 12/27/2022] [Indexed: 12/29/2022] Open
Abstract
Objective: To investigate the ability of homeostasis model assessment of insulin resistance (HOMA-IR) in early pregnancy for predicting gestational diabetes mellitus (GDM) in Chinese women with different first-trimester body mass index (FT-BMI) values. Methods: Baseline characteristics and laboratory tests were collected at the first prenatal visit (6−12 weeks of gestation). GDM was diagnosed by a 75 g oral glucose tolerance test (OGTT) at 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression were applied to identify the association between HOMA-IR and GDM. The cutoff points for predicting GDM were estimated using receiver operating characteristic (ROC) curve analysis. Results: Of the total of 1343 women, 300 (22.34%) were diagnosed with GDM in the 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression verified HOMA-IR as a significant risk factor for GDM in the normal weight subgroup (FT-BMI < 24 kg/m2) (adjusted OR 2.941 [95% CI 2.153, 4.016], P < 0.001), overweight subgroup (24.0 kg/m2 ≤ FT-BMI < 28.0 kg/m2) (adjusted OR 3.188 [95% CI 2.011, 5.055], P < 0.001), and obese subgroup (FT-BMI ≥ 28.0 kg/m2) (adjusted OR 9.415 [95% CI 1.712, 51.770], p = 0.01). The cutoff values of HOMA-IR were 1.52 (area under the curve (AUC) 0.733, 95% CI 0.701−0.765, p < 0.001) for all participants, 1.43 (AUC 0.691, 95% CI 0.651−0.730, p < 0.001) for normal weight women, 2.27 (AUC 0.760, 95% CI 0.703−0.818, p < 0.001) for overweight women, and 2.31 (AUC 0.801, 95% CI 0.696−0.907, p < 0.001) for obese women. Conclusions: Increased HOMA-IR in early pregnancy is a risk factor for GDM, and HOMA-IR can be affected by body weight. The cutoff value of HOMA-IR to predict GDM should be distinguished by different FT-BMI values.
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Affiliation(s)
- Yanbei Duo
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Shuoning Song
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Yuemei Zhang
- Department of Obstetrics, Haidian District Maternal and Child Health Care Hospital, Beijing 100080, China
| | - Xiaolin Qiao
- Department of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Jiyu Xu
- Core Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
| | - Jing Zhang
- Department of Laboratory, Haidian District Maternal and Child Health Care Hospital, Beijing 100080, China
| | - Zhenyao Peng
- Department of Dean’s Office, Haidian District Maternal and Child Health Care Hospital, Beijing 100080, China
| | - Yan Chen
- Department of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Xiaorui Nie
- Department of Obstetrics, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Qiujin Sun
- Department of Clinical Laboratory, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Xianchun Yang
- Department of Clinical Laboratory, Beijing Chaoyang District Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Ailing Wang
- National Center for Women and Children’s Health, China CDC, Beijing 100013, China
| | - Wei Sun
- Core Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
| | - Yong Fu
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Yingyue Dong
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Zechun Lu
- National Center for Women and Children’s Health, China CDC, Beijing 100013, China
| | - Tao Yuan
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Weigang Zhao
- Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
- Correspondence:
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Mukherjee S, Skrede S, Milbank E, Andriantsitohaina R, López M, Fernø J. Understanding the Effects of Antipsychotics on Appetite Control. Front Nutr 2022; 8:815456. [PMID: 35047549 PMCID: PMC8762106 DOI: 10.3389/fnut.2021.815456] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/10/2021] [Indexed: 12/16/2022] Open
Abstract
Antipsychotic drugs (APDs) represent a cornerstone in the treatment of schizophrenia and other psychoses. The effectiveness of the first generation (typical) APDs are hampered by so-called extrapyramidal side effects, and they have gradually been replaced by second (atypical) and third-generation APDs, with less extrapyramidal side effects and, in some cases, improved efficacy. However, the use of many of the current APDs has been limited due to their propensity to stimulate appetite, weight gain, and increased risk for developing type 2 diabetes and cardiovascular disease in this patient group. The mechanisms behind the appetite-stimulating effects of the various APDs are not fully elucidated, partly because their diverse receptor binding profiles may affect different downstream pathways. It is critical to identify the molecular mechanisms underlying drug-induced hyperphagia, both because this may lead to the development of new APDs, with lower appetite-stimulating effects but also because such insight may provide new knowledge about appetite regulation in general. Hence, in this review, we discuss the receptor binding profile of various APDs in relation to the potential mechanisms by which they affect appetite.
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Affiliation(s)
- Sayani Mukherjee
- Hormone Laboratory, Haukeland University Hospital, Bergen, Norway
| | - Silje Skrede
- Department of Clinical Science, University of Bergen, Bergen, Norway.,Section of Clinical Pharmacology, Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
| | - Edward Milbank
- NeurObesity Group, Department of Physiology, Center for Research in Molecular Medicine and Chronic Diseases, University of Santiago de Compostela-Instituto de Investigación Sanitaria, Santiago de Compostela, Spain.,CIBER Fisiopatología de la Obesidad y Nutrición, Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición, Madrid, Spain.,SOPAM, U1063, INSERM, University of Angers, SFR ICAT, Bat IRIS-IBS, Angers, France
| | | | - Miguel López
- NeurObesity Group, Department of Physiology, Center for Research in Molecular Medicine and Chronic Diseases, University of Santiago de Compostela-Instituto de Investigación Sanitaria, Santiago de Compostela, Spain.,CIBER Fisiopatología de la Obesidad y Nutrición, Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición, Madrid, Spain
| | - Johan Fernø
- Hormone Laboratory, Haukeland University Hospital, Bergen, Norway
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Liu Z, Zhang Y, Wang J, Xia L, Yang Y, Sun L, Zhang D, Li W, Yao X, Yang R, Liu Y, Liu H. Association of higher plasma leptin levels with HOMA-IR index, high sensitivity C-reactive protein and glycolipid metabolism in patients with chronic schizophrenia: A multi-center cross-sectional study. Front Psychiatry 2022; 13:992988. [PMID: 36090349 PMCID: PMC9453303 DOI: 10.3389/fpsyt.2022.992988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 08/09/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Previous research has revealed that plasma leptin levels were closely related to glycolipid metabolism in schizophrenic patients. Insulin resistance (IR) and high sensitivity C-reactive protein (hs-CRP) were involved in glucolipid metabolism disorders. This study explored the correlation between plasma higher leptin levels, homeostasis model assessment of insulin resistance (HOMA-IR) index, hs-CRP and glycolipid metabolism in patients with chronic schizophrenia (CS). METHODS 322 subjects were enrolled, and the psychopathological symptoms of each patient were assessed by a 30-item Positive and Negative Syndrome Scale (PANSS-30). Patients' plasma leptin levels were measured by enzyme-linked immunosorbent assay (ELISA). Fasting blood glucose (FBG) levels were determined by oxidase method. Insulin levels were tested by electrochemiluminescence, and hs-CRP levels were tested by immunoturbidimetry. IBM SPSS 22.0 was used for data analysis. RESULTS Compared to the lower leptin group, patients in the higher leptin group had significantly higher body mass index (BMI), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-C), insulin, HOMA-IR and hs-CRP levels; and lower negative factor scores, cognitive factor scores, and PANSS total scores (P < 0.05). Plasma leptin levels in CS patients were positively correlated with BMI, TC, TG, LDL-C, insulin, HOMA-IR and hs-CRP levels, and were negatively correlated with gender (male = 1, Female = 2), positive factor scores, negative factor scores, cognitive factor scores and PANSS total scores. Multiple linear regression analysis revealed that gender, BMI, positive factor scores, PANSS total scores, FBG, LDL-C, insulin, HOMA-IR and hs-CRP levels were independent influencing factors of leptin levels in CS patients (P < 0.05). CONCLUSION Gender, BMI, positive factor scores, PANSS total scores, FBG, LDL-C, insulin, HOMA-IR and hs-CRP levels were independent influencing factors of plasma leptin levels in CS patients. Plasma leptin, HOMA-IR and hs-CRP levels should be measured regularly in CS patients to prevent or treat the disorders of glucose and lipid metabolism comorbidity with schizophrenia patients in clinical diagnosis and treatment.
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Affiliation(s)
- Zhiwei Liu
- Department of Psychiatry, The Third People's Hospital of Fuyang, Fuyang, China
| | - Yulong Zhang
- Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Chaohu, China.,Anhui Psychiatric Center, Anhui Medical University, Chaohu, China
| | - Juan Wang
- Department of Psychiatry, Chengdu Fourth People's Hospital, Chengdu, China
| | - Lei Xia
- Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Chaohu, China.,Anhui Psychiatric Center, Anhui Medical University, Chaohu, China
| | - Yating Yang
- Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Chaohu, China.,Anhui Psychiatric Center, Anhui Medical University, Chaohu, China
| | - Liang Sun
- Department of Psychiatry, The Third People's Hospital of Fuyang, Fuyang, China
| | - Dapeng Zhang
- Department of Psychiatry, The Third People's Hospital of Fuyang, Fuyang, China
| | - Wenzheng Li
- Department of Psychiatry, Hefei Fourth People's Hospital, Hefei, China
| | - Xianhu Yao
- Department of Psychiatry, Maanshan Fourth People's Hospital, Maanshan, China
| | - Rongchun Yang
- Department of Psychiatry, The Third People's Hospital of Fuyang, Fuyang, China
| | - Yun Liu
- Department of Psychiatry, The Third People's Hospital of Fuyang, Fuyang, China
| | - Huanzhong Liu
- Department of Psychiatry, Chaohu Hospital of Anhui Medical University, Chaohu, China.,Anhui Psychiatric Center, Anhui Medical University, Chaohu, China
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Improving Clinical, Cognitive, and Psychosocial Dysfunctions in Patients with Schizophrenia: A Neurofeedback Randomized Control Trial. Neural Plast 2021; 2021:4488664. [PMID: 34434228 PMCID: PMC8380506 DOI: 10.1155/2021/4488664] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 07/30/2021] [Accepted: 08/04/2021] [Indexed: 12/17/2022] Open
Abstract
Objectives The aim of this study was to use neurofeedback (NF) training as the add-on therapy in patients with schizophrenia to improve their clinical, cognitive, and psychosocial condition. The study, thanks to the monitoring of various conditions, quantitative electroencephalogram (QEEG) and brain-derived neurotrophic factor (BDNF), was supposed to give an insight into mechanisms underlying NF training results. Methods Forty-four male patients with schizophrenia, currently in a stable, incomplete remission, were recruited into two, 3-month rehabilitation programs, with standard rehabilitation as a control group (R) or with add-on NF training (NF). Pre- and posttherapy primary outcomes were compared: clinical (Positive and Negative Syndrome Scale (PANSS)), cognitive (Color Trails Test (CTT), d2 test), psychosocial functioning (General Self-Efficacy Scale (GSES), Beck Cognitive Insight Scale (BCIS), and Acceptance of Illness Scale (AIS)), quantitative electroencephalogram (QEEG), auditory event-related potentials (ERPs), and serum level of BDNF. Results. Both groups R and NF improved significantly in clinical ratings (Positive and Negative Syndrome Scale (PANSS)). In-between analyses unveiled some advantages of add-on NF therapy over standard rehabilitation. GSES scores improved significantly, giving the NF group of patients greater ability to cope with stressful or difficult social demands. Also, the serum-level BDNF increased significantly more in the NF group. Post hoc analyses indicated the possibility of creating a separate PANSS subsyndrome, specifically related to cognitive, psychosocial, and BDNF effects of NF therapy. Conclusions Neurofeedback can be effectively used as the add-on therapy in schizophrenia rehabilitation programs. The method requires further research regarding its clinical specificity and understanding mechanisms of action.
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