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Russo A, Örzsik B, Yalin N, Simpson I, Nwaubani P, Pinna A, De Marco R, Sharp H, Kartar A, Singh N, Blockley N, Stone AJL, Turkheimer FE, Young AH, Cercignani M, Zelaya F, Asllani I, Colasanti A. Altered oxidative neurometabolic response to methylene blue in bipolar disorder revealed by quantitative neuroimaging. J Affect Disord 2024; 362:790-798. [PMID: 39019231 DOI: 10.1016/j.jad.2024.07.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 06/05/2024] [Accepted: 07/12/2024] [Indexed: 07/19/2024]
Abstract
BACKGROUND Cerebral mitochondrial and hemodynamic abnormalities have been implicated in Bipolar Disorder pathophysiology, likely contributing to neurometabolic vulnerability-leading to worsen clinical outcomes and mood instability. To investigate neurometabolic vulnerability in patients with BD, we combined multi-modal quantitative MRI assessment of cerebral oxygenation with acute administration of Methylene Blue, a neurometabolic/hemodynamic modulator acting on cerebral mitochondria. METHODS Fifteen euthymic patients with chronic BD-type 1, and fifteen age/gender-matched healthy controls underwent two separate MRI sessions in a single-blinded randomized cross-over design, each after intravenous infusion of either MB (0.5 mg/kg) or placebo. MRI-based measures of Cerebral Blood Flow and Oxygen Extraction Fraction were integrated to compute Cerebral Metabolic Rate of Oxygen in Frontal Lobe, Anterior Cingulate, and Hippocampus-implicated in BD neurometabolic pathophysiology. Inter-daily variation in mood rating was used to assess mood instability. RESULTS A decrease in global CBF and CMRO2 was observed after acutely administrating MB to all participants. Greater regional CMRO2 reductions were observed after MB, in patients compared to controls in FL (mean = -14.2 ± 19.5 % versus 2.3 ± 14.8 %), ACC (mean = -14.8 ± 23.7 % versus 2.4 ± 15.7 %). The effects on CMRO2 in those regions were primarily driven by patients with longer disease duration and higher mood instability. LIMITATIONS Sample size; medications potentially impacting on response to MB. CONCLUSIONS An altered neurometabolic response to MB, a mitochondrial/hemodynamic modulator, was observed in patients, supporting the hypothesis of vulnerability to neurometabolic stress in BD. Integrating quantitative imaging of cerebral oxygen metabolism with a mitochondrial-targeting pharmacological challenge could provide a novel biomarker of neurometabolic and cerebrovascular pathophysiology in BD.
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Affiliation(s)
- Alfonso Russo
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK; Sussex Partnership NHS Foundation Trust, Worthing, UK.
| | - Balázs Örzsik
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK; Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Nefize Yalin
- Section on the Neurobiology and Treatment of Mood Disorders, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, USA
| | - Ivor Simpson
- School of Engineering and Informatics, University of Sussex, Falmer, Brighton, UK
| | - Prince Nwaubani
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Antonello Pinna
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK
| | - Riccardo De Marco
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK
| | - Harriet Sharp
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK
| | - Amy Kartar
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK
| | - Nisha Singh
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK; Department of Paediatrics, University of Oxford, Oxford, UK
| | | | | | | | - Allan H Young
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Mara Cercignani
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Fernando Zelaya
- Institute of Psychiatry, Psychology and Neuroscience, King's College, London, UK
| | - Iris Asllani
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK; Biomedical Engineering, Rochester Institute of Technology, Rochester, USA
| | - Alessandro Colasanti
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer, Brighton, UK; Sussex Partnership NHS Foundation Trust, Worthing, UK
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Thomaidis GV, Papadimitriou K, Michos S, Chartampilas E, Tsamardinos I. A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning. IBRO Neurosci Rep 2023; 15:77-89. [PMID: 38025660 PMCID: PMC10668096 DOI: 10.1016/j.ibneur.2023.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/19/2023] [Accepted: 06/29/2023] [Indexed: 12/01/2023] Open
Abstract
Background Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully automated machine learning algorithms can achieve extremely high classification scores and disease-related predictive biosignature identification, in short time frames and scaled down to small datasets. Method A fully automated machine learning platform, based on the most suitable algorithm selection and relevant set of hyper-parameter values, was applied on a preprocessed transcriptomics dataset, in order to produce a model for biosignature selection and to classify subjects into groups of patients and controls. The parent GEO datasets were originally produced from the cerebellar and parietal lobe tissue of deceased bipolar patients and healthy controls, using Affymetrix Human Gene 1.0 ST Array. Results Patients and controls were classified into two separate groups, with no close-to-the-boundary cases, and this classification was based on the cerebellar transcriptomic biosignature of 25 features (genes), with Area Under Curve 0.929 and Average Precision 0.955. The biosignature includes both genes connected before to bipolar disorder, depression, psychosis or epilepsy, as well as genes not linked before with any psychiatric disease. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed participation of 4 identified features in 6 pathways which have also been associated with bipolar disorder. Conclusion Automated machine learning (AutoML) managed to identify accurately 25 genes that can jointly - in a multivariate-fashion - separate bipolar patients from healthy controls with high predictive power. The discovered features lead to new biological insights. Machine Learning (ML) analysis considers the features in combination (in contrast to standard differential expression analysis), removing both irrelevant as well as redundant markers, and thus, focusing to biological interpretation.
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Affiliation(s)
- Georgios V. Thomaidis
- Greek National Health System, Psychiatric Department, Katerini General Hospital, Katerini, Greece
| | - Konstantinos Papadimitriou
- Greek National Health System, G. Papanikolaou General Hospital, Organizational Unit - Psychiatric Hospital of Thessaloniki, Thessaloniki, Greece
| | | | - Evangelos Chartampilas
- Laboratory of Radiology, AHEPA General Hospital, University of Thessaloniki, Thessaloniki, Greece
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Fincham GW, Kartar A, Uthaug MV, Anderson B, Hall L, Nagai Y, Critchley H, Colasanti A. High ventilation breathwork practices: An overview of their effects, mechanisms, and considerations for clinical applications. Neurosci Biobehav Rev 2023; 155:105453. [PMID: 37923236 DOI: 10.1016/j.neubiorev.2023.105453] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/19/2023] [Accepted: 10/30/2023] [Indexed: 11/07/2023]
Abstract
High Ventilation Breathwork (HVB) refers to practices employing specific volitional manipulation of breathing, with a long history of use to relieve various forms of psychological distress. This paper seeks to offer a consolidative insight into potential clinical application of HVB as a treatment of psychiatric disorders. We thus review the characteristic phenomenological and neurophysiological effects of these practices to inform their mechanism of therapeutic action, safety profiles and future clinical applications. Clinical observations and data from neurophysiological studies indicate that HVB is associated with extraordinary changes in subjective experience, as well as with profound effects on central and autonomic nervous systems functions through modulation of neurometabolic parameters and interoceptive sensory systems. This growing evidence base may guide how the phenomenological effects of HVB can be understood, and potentially harnessed in the context of such volitional perturbation of psychophysiological state. Reports of putative beneficial effects for trauma-related, affective, and somatic disorders invite further research to obtain detailed mechanistic knowledge, and rigorous clinical testing of these potential therapeutic uses.
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Affiliation(s)
- Guy W Fincham
- Brighton & Sussex Medical School, Department of Neuroscience, University of Sussex, UK; University of Sussex, School of Psychology, Brighton, UK.
| | - Amy Kartar
- Brighton & Sussex Medical School, Department of Neuroscience, University of Sussex, UK
| | - Malin V Uthaug
- The Centre for Psychedelic Research, Division of Psychiatry, Imperial College London, UK; Department of Neuropsychology & Psychopharmacology, Faculty of Psychology & Neuroscience, Maastricht University, The Netherlands
| | - Brittany Anderson
- University of Wisconsin School of Medicine & Public Health, Department of Psychiatry, University of Wisconsin-Madison, USA
| | - Lottie Hall
- Brighton & Sussex Medical School, Department of Neuroscience, University of Sussex, UK
| | - Yoko Nagai
- Brighton & Sussex Medical School, Department of Neuroscience, University of Sussex, UK
| | - Hugo Critchley
- Brighton & Sussex Medical School, Department of Neuroscience, University of Sussex, UK
| | - Alessandro Colasanti
- Brighton & Sussex Medical School, Department of Neuroscience, University of Sussex, UK; Sussex Partnership NHS Foundation Trust.
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Singh N, MacNicol E, DiPasquale O, Randall K, Lythgoe D, Mazibuko N, Simmons C, Selvaggi P, Stephenson S, Turkheimer FE, Cash D, Zelaya F, Colasanti A. The effects of acute Methylene Blue administration on cerebral blood flow and metabolism in humans and rats. J Cereb Blood Flow Metab 2023; 43:95-105. [PMID: 36803299 PMCID: PMC10638993 DOI: 10.1177/0271678x231157958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 11/09/2022] [Accepted: 12/26/2022] [Indexed: 02/23/2023]
Abstract
Methylene Blue (MB) is a brain-penetrating drug with putative neuroprotective, antioxidant and metabolic enhancing effects. In vitro studies suggest that MB enhances mitochondrial complexes activity. However, no study has directly assessed the metabolic effects of MB in the human brain. We used in vivo neuroimaging to measure the effect of MB on cerebral blood flow (CBF) and brain metabolism in humans and in rats. Two doses of MB (0.5 and 1 mg/kg in humans; 2 and 4 mg/kg in rats; iv) induced reductions in global cerebral blood flow (CBF) in humans (F(1.74, 12.17)5.82, p = 0.02) and rats (F(1,5)26.04, p = 0.0038). Human cerebral metabolic rate of oxygen (CMRO2) was also significantly reduced (F(1.26, 8.84)8.01, p = 0.016), as was the rat cerebral metabolic rate of glucose (CMRglu) (t = 2.6(16) p = 0.018). This was contrary to our hypothesis that MB will increase CBF and energy metrics. Nevertheless, our results were reproducible across species and dose dependent. One possible explanation is that the concentrations used, although clinically relevant, reflect MB's hormetic effects, i.e., higher concentrations produce inhibitory rather than augmentation effects on metabolism. Additionally, here we used healthy volunteers and healthy rats with normal cerebral metabolism where MB's ability to enhance cerebral metabolism might be limited.
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Affiliation(s)
- Nisha Singh
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Eilidh MacNicol
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ottavia DiPasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Karen Randall
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - David Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ndabezinhle Mazibuko
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Camilla Simmons
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Pierluigi Selvaggi
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Stephanie Stephenson
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Federico E Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Diana Cash
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Alessandro Colasanti
- Department of Clinical Neuroscience and Neuroimaging, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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Caddye E, Pineau J, Reyniers J, Ronen I, Colasanti A. Lactate: A Theranostic Biomarker for Metabolic Psychiatry? Antioxidants (Basel) 2023; 12:1656. [PMID: 37759960 PMCID: PMC10526106 DOI: 10.3390/antiox12091656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/01/2023] [Accepted: 08/16/2023] [Indexed: 09/29/2023] Open
Abstract
Alterations in neurometabolism and mitochondria are implicated in the pathophysiology of psychiatric conditions such as mood disorders and schizophrenia. Thus, developing objective biomarkers related to brain mitochondrial function is crucial for the development of interventions, such as central nervous system penetrating agents that target brain health. Lactate, a major circulatory fuel source that can be produced and utilized by the brain and body, is presented as a theranostic biomarker for neurometabolic dysfunction in psychiatric conditions. This concept is based on three key properties of lactate that make it an intriguing metabolic intermediate with implications for this field: Firstly, the lactate response to various stimuli, including physiological or psychological stress, represents a quantifiable and dynamic marker that reflects metabolic and mitochondrial health. Second, lactate concentration in the brain is tightly regulated according to the sleep-wake cycle, the dysregulation of which is implicated in both metabolic and mood disorders. Third, lactate universally integrates arousal behaviours, pH, cellular metabolism, redox states, oxidative stress, and inflammation, and can signal and encode this information via intra- and extracellular pathways in the brain. In this review, we expand on the above properties of lactate and discuss the methodological developments and rationale for the use of functional magnetic resonance spectroscopy for in vivo monitoring of brain lactate. We conclude that accurate and dynamic assessment of brain lactate responses might contribute to the development of novel and personalized therapies that improve mitochondrial health in psychiatric disorders and other conditions associated with neurometabolic dysfunction.
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Affiliation(s)
- Edward Caddye
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Falmer BN1 9RR, UK
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer BN1 9RR, UK
| | - Julien Pineau
- Independent Researcher, Florianópolis 88062-300, Brazil
| | - Joshua Reyniers
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer BN1 9RR, UK
- School of Life Sciences, University of Sussex, Falmer BN1 9RR, UK
| | - Itamar Ronen
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Falmer BN1 9RR, UK
| | - Alessandro Colasanti
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Falmer BN1 9RR, UK
- Department of Clinical Neuroscience, Brighton and Sussex Medical School, University of Sussex, Falmer BN1 9RR, UK
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Druga R, Salaj M, Al-Redouan A. Parvalbumin - Positive Neurons in the Neocortex: A Review. Physiol Res 2023; 72:S173-S191. [PMID: 37565421 PMCID: PMC10660579 DOI: 10.33549/physiolres.935005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 02/02/2023] [Indexed: 12/01/2023] Open
Abstract
The calcium binding protein parvalbumin (PV) in the mammalian neocortex is expressed in a subpopulation of cortical GABAergic inhibitory interneurons. PV - producing interneurons represent the largest subpopulation of neocortical inhibitory cells, exhibit mutual chemical and electrical synaptic contacts and are well known to generate gamma oscillation. This review summarizes basic data of the distribution, afferent and efferent connections and physiological properties of parvalbumin expressing neurons in the neocortex. Basic data about participation of PV-positive neurons in cortical microcircuits are presented. Autaptic connections, metabolism and perineuronal nets (PNN) of PV positive neurons are also discussed.
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Affiliation(s)
- R Druga
- Department of Anatomy, 2nd Medical Faculty, Charles University Prague, Czech Republic.
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Dang X, Song M, Lv L, Yang Y, Luo XJ. Proteome-wide Mendelian randomization reveals the causal effects of immune-related plasma proteins on psychiatric disorders. Hum Genet 2023; 142:809-818. [PMID: 37085628 DOI: 10.1007/s00439-023-02562-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 04/17/2023] [Indexed: 04/23/2023]
Abstract
Immune dysregulation has been consistently reported in psychiatric disorders, however, the causes and mechanisms underlying immune dysregulation in psychiatric disorders remain largely unclear. Here we conduct a Mendelian randomization study by integrating plasma proteome and GWASs of schizophrenia, bipolar disorder and depression. The primate-specific immune-related protein BTN3A3 showed the most significant associations with all three psychiatric disorders. In addition, other immune-related proteins, including AIF1, FOXO3, IRF3, CFHR4, IGLON5, FKBP2, and PI3, also showed significant associations with psychiatric disorders. Our study showed that a proportion of psychiatric risk variants may contribute to disease risk by regulating immune-related plasma proteins, providing direct evidence that connect the genetic risk of psychiatric disorders to immune system.
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Affiliation(s)
- Xinglun Dang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650204, Yunnan, China
| | - Meng Song
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China
- Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, Xinxiang, 453002, Henan, China
| | - Luxian Lv
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China.
- Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, Xinxiang, 453002, Henan, China.
| | - Yongfeng Yang
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453002, Henan, China.
- Henan Key Lab of Biological Psychiatry of Xinxiang Medical University, Xinxiang, 453002, Henan, China.
- Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang, 453002, Henan, China.
| | - Xiong-Jian Luo
- Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, 210096, Jiangsu, China.
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Casquero-Veiga M, Lamanna-Rama N, Romero-Miguel D, Rojas-Marquez H, Alcaide J, Beltran M, Nacher J, Desco M, Soto-Montenegro ML. The Poly I:C maternal immune stimulation model shows unique patterns of brain metabolism, morphometry, and plasticity in female rats. Front Behav Neurosci 2023; 16:1022622. [PMID: 36733452 PMCID: PMC9888250 DOI: 10.3389/fnbeh.2022.1022622] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 12/05/2022] [Indexed: 01/07/2023] Open
Abstract
Introduction: Prenatal infections are associated with an increased risk of the onset of schizophrenia. Rodent models of maternal immune stimulation (MIS) have been extensively used in preclinical studies. However, many of these studies only include males, omitting pathophysiological features unique to females. The aim of this study is to characterize the MIS model in female rats using positron emission tomography (PET), structural magnetic resonance imaging (MR), and neuroplasticiy studies. Methods: In gestational day 15, Poly I:C (or Saline) was injected into pregnant Wistar rats to induce the MIS model. Imaging studies: [18F]-fluoro-2-deoxy-D-glucose-PET scans of female-offspring were acquired at post-natal day (PND) 35 and PND100. Furthermore, T2-MR brain images were acquired in adulthood. Differences in FDG uptake and morphometry between groups were assessed with SPM12 and Regions of Interest (ROI) analyses. Ex vivo study: The density of parvalbumin expressing interneurons (PV), perineuronal nets (PNN), and parvalbumin expressing interneurons surrounded by perineuronal nets (PV-PNN) were evaluated in the prelimbic cortex and basolateral amygdala using confocal microscopy. ROIs and neuroplasticity data were analyzed by 2-sample T-test and 2-way-ANOVA analyses, respectively. Results: A significant increase in brain metabolism was found in all animals at adulthood compared to adolescence. MIS hardly modified brain glucose metabolism in females, highlighting a significant hypometabolism in the thalamus at adulthood. In addition, MIS induced gray matter (GM) enlargements in the pituitary, hippocampus, substantia nigra, and cingulate cortex, and GM shrinkages in some thalamic nuclei, cerebelar areas, and brainstem. Moreover, MIS induced white matter shrinkages in the cerebellum, brainstem and corpus callosum, along with cerebrospinal fluid enlargements in the lateral and 4th ventricles. Finally, MIS reduced the density of PV, PNN, and PV-PNN in the basolateral amygdala. Conclusion: Our work showed in vivo the differential pattern of functional and morphometric affectation in the MIS model in females, as well as the deficits caused at the synaptic level according to sex. The differences obtained highlight the relevance of including both sexes in psychiatric research in order to consider their pathophysiological particularities and successfully extend the benefits obtained to the entire patient population.
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Affiliation(s)
- Marta Casquero-Veiga
- Laboratorio de Imagen Médica, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,Cardiovascular Imaging and Population Studies, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
| | - Nicolás Lamanna-Rama
- Laboratorio de Imagen Médica, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,Departamento de Bioingeniería e Ingeniería Aeroespacial, Escuela Técnica Superior de Ingeniería, Universidad Carlos III de Madrid, Madrid, Spain
| | - Diego Romero-Miguel
- Laboratorio de Imagen Médica, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,Departamento de Bioingeniería e Ingeniería Aeroespacial, Escuela Técnica Superior de Ingeniería, Universidad Carlos III de Madrid, Madrid, Spain
| | - Henar Rojas-Marquez
- Laboratorio de Imagen Médica, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (UPV/EHU), Leioa, Spain,Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
| | - Julia Alcaide
- Neurobiology Unit, Cell Biology Departament, BIOTECMED Institute, Universitat de València, Burjassot, Spain,CIBER de Salud Mental (CIBERSAM), Madrid, Spain,Fundación Investigación Hospital Clínico de Valencia, INCLIVA, Valencia, Spain
| | - Marc Beltran
- Neurobiology Unit, Cell Biology Departament, BIOTECMED Institute, Universitat de València, Burjassot, Spain
| | - Juan Nacher
- Neurobiology Unit, Cell Biology Departament, BIOTECMED Institute, Universitat de València, Burjassot, Spain,CIBER de Salud Mental (CIBERSAM), Madrid, Spain,Fundación Investigación Hospital Clínico de Valencia, INCLIVA, Valencia, Spain
| | - Manuel Desco
- Laboratorio de Imagen Médica, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,CIBER de Salud Mental (CIBERSAM), Madrid, Spain,Advanced Imaging Unit, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain,Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Campus de Getafe, Madrid, Spain,*Correspondence: Manuel Desco Maria Luisa Soto-Montenegro
| | - Maria Luisa Soto-Montenegro
- Laboratorio de Imagen Médica, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain,CIBER de Salud Mental (CIBERSAM), Madrid, Spain,High Performance Research Group in Physiopathology and Pharmacology of the Digestive System (NeuGut), University Rey Juan Carlos (URJC), Alcorcón, Spain,*Correspondence: Manuel Desco Maria Luisa Soto-Montenegro
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Zhong H, Huan X, Jiao K, He S, Wen Z, Zhao R, Goh LY, Su M, Song J, Yan C, Xi J, Zheng X, Zhou Z, Luo S, Zhao C. Causal relationships between mood instability and autoimmune diseases: A mendelian randomization analysis. Autoimmun Rev 2023; 22:103214. [PMID: 36272539 DOI: 10.1016/j.autrev.2022.103214] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/12/2022] [Accepted: 10/12/2022] [Indexed: 12/27/2022]
Abstract
OBJECTIVES The interrelationship between mental health and autoimmunity gains more and more attention in recent years. However, the causality between personality traits and autoimmune diseases remained largely unknown. METHODS We first conducted two-sample mendelian randomization (MR) analysis on the relationships between mood instability, which is a common personality trait in the general population, and 10 autoimmune diseases. The results were further validated in secondary analyses of sensitivity where different MR methods, ethnicities, genders, and ascertainment methods were compared. RESULTS In the primary analyses, three autoimmune diseases showed genetical predisposition to mood instability: asthma (OR [95%CI] = 3.45 [2.48, 4.78], P = 1.33E- 13), hypothyroidism (OR [95%CI] = 1.02 [1.00, 1.03], P = 1.71E-02), and systemic lupus erythematosus (OR [95%CI] = 5.25 [1.21, 22.76], P = 2.67E-02). The results were consistent in subsequent secondary analyses. Three diseases remained significantly correlated with mood instability by different MR methods with asthma remaining significant in Finnish and mixed populations, and in females from the UK biobank, while hypothyroidism remained significant in both genders from the UK biobank. CONCLUSION Mood instability is a modifiable risk factor for three autoimmune diseases including asthma, hypothyroidism and systemic lupus erythematosus.
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Affiliation(s)
- Huahua Zhong
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Xiao Huan
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Kexin Jiao
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Shen He
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhu Wen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Rui Zhao
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Li-Ying Goh
- Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Manqiqige Su
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Jie Song
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Chong Yan
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Jianying Xi
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China
| | - Xueying Zheng
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, Shanghai 200032, China
| | - Zhirui Zhou
- Radiation Oncology Center, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - Sushan Luo
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China.
| | - Chongbo Zhao
- Department of Neurology and Huashan Rare Disease Center, Huashan Hospital, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai 200040, China.
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Grodstein F, Yu L, de Jager PL, Levey A, Seyfried NT, Bennett DA. Exploring Cortical Proteins Underlying the Relation of Neuroticism to Cognitive Resilience. AGING BRAIN 2022; 2:100031. [PMID: 36874358 PMCID: PMC9979250 DOI: 10.1016/j.nbas.2022.100031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Some individuals maintain cognitive health despite neuropathology. Targets impacting "cognitive resilience" may provide interventions for preventing dementia without decreasing neuropathology. Neuroticism represents the tendency to experience negative emotions, and is related to worse cognitive resilience. Exploring proteins associated with cognitive resilience risk factors, such as neuroticism, could yield new protein targets. We used 355 postmortem prefrontal cortex from two cohorts to measure 8356 proteins. We identified (i) proteins associated with both neuroticism and cognitive resilience, and (ii) proteins statistically mediating relations of neuroticism to cognitive resilience. We found two proteins, 40S ribosomal proteinS3 (RPS3) and branched chain keto acid dehydrogenase E1, subunit beta (BCKDHB), ranked in the top 1% of smallest p-values in parallel linear regression models of neuroticism to protein levels, and protein levels to cognitive decline resilience. In mediation models, RPS3 and BCKDHB accounted for 25% (p=0.005) of the relation of neuroticism to cognitive resilience. Our sample size is modest, thus results may be due to chance (p-values did not meet Bonferroni significance) and will require further confirmation; however, investigating biologic mediators of associations of risk factors to cognitive resilience may help discover targets to promote cognitive resilience and reduce dementia.
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Affiliation(s)
- Francine Grodstein
- Rush Alzheimer's Disease Center, Chicago, IL, 60612, USA.,Department of Internal Medicine, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Chicago, IL, 60612, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Philip L de Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, NY, NY, 10032, USA
| | - Allan Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Nicholas T Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Chicago, IL, 60612, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
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