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Efthymiou D, Zekakos DX, Papatriantafyllou E, Ziagkas E, Petrelis AN, Vassilopoulou E. Gait Alterations in the Prediction of Metabolic Syndrome in Patients With Schizophrenia: A Pilot Study With PODOSmart ® Insoles. Front Psychiatry 2022; 13:756600. [PMID: 35153872 PMCID: PMC8829465 DOI: 10.3389/fpsyt.2022.756600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 01/04/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Second-generation antipsychotics (APs) are associated with metabolic syndrome (MetS), characterized by abnormal pro-inflammatory cytokine production and oxidative stress due to the reduced antioxidant systems, and neurological effects, including mobility impairment. This pilot study investigated relationships between inflammatory-metabolic biomarkers, MetS and gait alterations in patients with psychosis treated with APs. METHODS Patients with psychosis treated with APs, 20 with MetS (MPS group) and 20 without MetS (PS group) were studied, usinganthropometric data, blood measurements and gait analysis performed with the PODOSmart ® gait analysis device. RESULTS AND DISCUSSION The MPS group had significantly higher mean body mass index (BMI) and arterial blood pressure (BP) than the PS group. PODOSmart ® gait analysis recorded significant differences between groups in pronation-supination at Heel Off (HO), gaitline HO and gaitline Toe Off (TO). Multifactorial elastic net regression models demonstrated significant association with MetS of inflammatory markers, specific AP2 treatment, gender, age; BMI; BP and smoking (accuracy λ = 0.08), and in relation to gait parameters (accuracy λ = 0.750), the three pronation- supination variables, i.e., at HO, flat foot in (AP2 related) and TO, and propulsion speed. The gait parameters were at the edges of the model, thus indicating a more significant role of these parameters compared to the other clinical variables. Early diagnosis of MetS in patients with schizophrenia via identification of gait alterations can be a screening measure for serious cardiovascular complications related to psychosis and APs, to enable timely dietary intervention that can control the pro-inflammatory state and reduce oxidative stress.
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Affiliation(s)
- Dimitris Efthymiou
- Division of Neurosciences, Department of Psychiatry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | | | - Efthimis Ziagkas
- Laboratory of Motor Behaviour, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Emilia Vassilopoulou
- Department of Nutritional Sciences and Dietetics, International Hellenic University, Thessaloniki, Greece
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Sneller MH, de Boer N, Everaars S, Schuurmans M, Guloksuz S, Cahn W, Luykx JJ. Clinical, Biochemical and Genetic Variables Associated With Metabolic Syndrome in Patients With Schizophrenia Spectrum Disorders Using Second-Generation Antipsychotics: A Systematic Review. Front Psychiatry 2021; 12:625935. [PMID: 33868046 PMCID: PMC8044798 DOI: 10.3389/fpsyt.2021.625935] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/24/2021] [Indexed: 12/30/2022] Open
Abstract
Background: Individuals with severe mental illness experience increased morbidity and mortality compared to the general population. Adverse effects of antipsychotics, including weight gain, may contribute to the development of metabolic syndrome (MetS), which is associated with increased risks of all-cause and cardiovascular disease mortality. We aim to provide a comprehensive overview of clinical, biochemical and genetic factors associated with MetS among patients with schizophrenia spectrum disorders using second-generation antipsychotics (SGA). Methods: A literature search was performed in Pubmed and Embase to identify all cohort studies, cross-sectional studies and clinical trials investigating associations with MetS in patients with schizophrenia spectrum disorders using SGAs. We extracted and enumerated clinical, biochemical and genetic factors reported to be associated with MetS. We defined factors associated with MetS as factors being reported as associated with MetS in two or more studies. Results: 58 studies were included in this review (n = 12,123). In total, 62 factors were found to be associated with increased risk of MetS. Thirty one out of 58 studies investigated factors that were reported as associated with MetS in two or more studies. With regard to clinical factors, we found gender, higher age, concomitant use of mood stabilizers, higher baseline and current BMI, earlier SGA exposure, higher dose, longer duration of treatment, psychosis and tobacco smoking to be significantly associated with MetS. Furthermore, the biochemical factors hypo-adiponectinemia, elevated levels of C-reactive protein (CRP) and higher white blood cell (WBC) count were identified as factors associated with MetS. Among pharmacogenetic factors, the rs1414334 C-allele of the HTR2C-gene was associated with MetS in patients using SGA. Conclusion: In this systematic review investigating clinical, biochemical and genetic factors associated with MetS in patients using SGAs we found that higher age, higher baseline BMI, higher current BMI and male as well as female gender were positively associated with MetS across all antipsychotics. This study may set the stage for the application of clinical, biochemical and genetic factors to predict the risk of developing MetS in patients using SGAs. Future research is needed to determine which patients using SGAs are at risk to develop MetS in clinical practice.
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Affiliation(s)
- Marius H Sneller
- Faculty of Biomedical Sciences, Utrecht University, Utrecht, Netherlands
| | - Nini de Boer
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Sophie Everaars
- Faculty of Medicine, Utrecht University, Utrecht, Netherlands
| | - Max Schuurmans
- Faculty of Medicine, Utrecht University, Utrecht, Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, Netherlands.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Altrecht Mental Health, Utrecht, Netherlands
| | - Jurjen J Luykx
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.,GGNet Mental Health, Apeldoorn, Netherlands
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