- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06945627
Profiling Vulnerability and Resilience for Mental Illness Following Viral Infections (VIRAL-MI)
Profiling Vulnerability and Resilience for Mental Illness Following Viral Infections: Translating Epidemiology to Deep-phenotyping
This observational study aims to identify the underlying neurobiological and environmental mechanisms that influence vulnerability or resilience to mental illness in the context of infection and their contribution to severe infective outcomes in people with pre-existing mental illness. The main questions it aims to answer are:
- How do viral infections influence the development of mental illness?
- What neurobiological and environmental factors contribute to influence the development of mental illness following infection?
- How do these factors relate to the severity of infectious illness in people with pre-existing mental disorders?
Researchers will move from large population databases to well-defined, deeply characterised samples to explore the association between infection and subsequent mental health outcomes, and the biological mechanisms behind these changes.
Participants's data has already been collected.
Study Overview
Status
Intervention / Treatment
Study Type
Enrollment (Actual)
Contacts and Locations
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria for the MOOD-MI cohort:
A depressive episode according to Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria in the course of MDD or BD with:
- HDRS score > 17
- Age 18-65 years;
- Signed informed consent, able to understand, speak and write the national language
Inclusion Criteria for the COVID-MI cohort:
- Having a positive nasopharyngeal swab for COVID-19 in the last 36 months;
- Age between 18-25 years;
- Signed informed consent, able to understand, speak and write the national language
Exclusion Criteria for the MOOD-MI cohort:
- History of schizophrenia, schizoaffective disorder, psychosis not otherwise specified; anorexia or bulimia nervosa;
- Taking following medications: antipsychotics, anticonvulsants, mood stabilizers; stimulants
- Active infection requiring antibiotics therapy;
- Immunosuppressed patient or other chronic diseases
- Signs of active infection requiring treatment
- Use of anti-inflammatory medication on a regular basis for a chronic inflammatory/autoimmune Disorder. Forbidden treatment: corticosteroids, Non Steroidal Anti-inflammatory Drugs, immunosuppressant IV-Ig based treatment
- Ongoing fever, infection treated by antibiotics or uncontrolled diabetes type I or II;
- Existing cancer or history of cancer in the last 5 years (except skin epidermoid cancer or in-situ cervix cancer);
- Known HIV infection or clinically manifest Acquired Immune Deficiency Syndrome (AIDS), Parkinson's or Alzheimer's disease, or any other serious condition likely to interfere e with the conduct of the trial;
- Abuse of drugs or alcohol in the past 6 months
Exclusion Criteria for the COVID-MI cohort:
- Comorbidity for psychotic disorders, verified by SCID-CV;
- Current and clinically significant substance use disorder;
- Current comorbidity with neurological conditions or severe head trauma, general brain disorder preceding the emergence of PASC, including microhaemorrhages and/or ischaemia occurring during the acute phase of COVID;
- Neuropsychological diagnosis of intellectual disability;
- Presence of contraindications to blood sampling and/or MRI;
- Pregnancy status at the time of recruitment.
Other exclusion criteria related to the MRI procedure include:
- Aneurysm clip
- Implanted neural stimulator
- Implanted cardiac pacemaker or auto-defibrillator
- Cochlear implant
- Ocular foreign body (e.g., metal shavings)
- Any implanted device (pumps, infusion devices, etc)
- Shrapnel injuries.
For epidemiological cohorts (MoBa, TOP, CHS) age between 18 and 65 ya, diagnosis of a severe mental illness (Schizophrenia, Major Depression, Bipolar disorder, anxiety disorders),
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Trans-D
|
This research doesn't involve any kind of intervention on the study participants
|
|
Cov-N-Psy
|
This research doesn't involve any kind of intervention on the study participants
|
|
CHS1
|
This research doesn't involve any kind of intervention on the study participants
|
|
CHS2
|
This research doesn't involve any kind of intervention on the study participants
|
|
MOOD-MI
|
This research doesn't involve any kind of intervention on the study participants
|
|
COVID-MI
|
This research doesn't involve any kind of intervention on the study participants
|
|
MoBa
|
This research doesn't involve any kind of intervention on the study participants
|
|
TOP
|
This research doesn't involve any kind of intervention on the study participants
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
number of hospital admission for mental illness after infection diagnosis
Time Frame: 3 years
|
number of onset or relapse of mental illness following infection
|
3 years
|
|
number of infections (Pathogen Burden Summary - PBS) in patients with mental illness
Time Frame: 3 years
|
number of samples positive for antibodies for viruses associated with Mental illness in the literature (IgG, expressed as AU/mL)
|
3 years
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Neurobiological risk and resilience factors for mental illnesses and severe outcomes
Time Frame: 3 years
|
differentially expressed gene between patients with high vs low Pathogen Burden Summary (PBS) with or without mental illness
|
3 years
|
|
Predictive risk models based on an individual biological and environmental signatures
Time Frame: 3 years
|
stratification of patients in risk and resilence clusters using unsupervised machine learning algorithms based on
|
3 years
|
|
Environmental risk and resilience factors for mental illness and severe outcomes
Time Frame: 3 years
|
socio-economic socio-demographic variables inflammatory markers levels, timing and type of infection,
|
3 years
|
|
genes or proteins that might be modified using drugs
Time Frame: 3 years
|
target genes involved in severe and post-infectious MI.
|
3 years
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Sara Poletti, PhD, Irccs Ospedale San Raffaele
Publications and helpful links
General Publications
- Mazza MG, De Lorenzo R, Conte C, Poletti S, Vai B, Bollettini I, Melloni EMT, Furlan R, Ciceri F, Rovere-Querini P; COVID-19 BioB Outpatient Clinic Study group; Benedetti F. Anxiety and depression in COVID-19 survivors: Role of inflammatory and clinical predictors. Brain Behav Immun. 2020 Oct;89:594-600. doi: 10.1016/j.bbi.2020.07.037. Epub 2020 Jul 30.
- Goldsmith DR, Rapaport MH, Miller BJ. A meta-analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Mol Psychiatry. 2016 Dec;21(12):1696-1709. doi: 10.1038/mp.2016.3. Epub 2016 Feb 23.
- Lalousis PA, Schmaal L, Wood SJ, Reniers RLEP, Barnes NM, Chisholm K, Griffiths SL, Stainton A, Wen J, Hwang G, Davatzikos C, Wenzel J, Kambeitz-Ilankovic L, Andreou C, Bonivento C, Dannlowski U, Ferro A, Lichtenstein T, Riecher-Rossler A, Romer G, Rosen M, Bertolino A, Borgwardt S, Brambilla P, Kambeitz J, Lencer R, Pantelis C, Ruhrmann S, Salokangas RKR, Schultze-Lutter F, Schmidt A, Meisenzahl E, Koutsouleris N, Dwyer D, Upthegrove R; PRONIA Consortium. Neurobiologically Based Stratification of Recent-Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes. Biol Psychiatry. 2022 Oct 1;92(7):552-562. doi: 10.1016/j.biopsych.2022.03.021. Epub 2022 Apr 12.
- Zhang Y, Wang J, Ye Y, Zou Y, Chen W, Wang Z, Zou Z. Peripheral cytokine levels across psychiatric disorders: A systematic review and network meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry. 2023 Jul 13;125:110740. doi: 10.1016/j.pnpbp.2023.110740. Epub 2023 Mar 8.
- Tylee DS, Sun J, Hess JL, Tahir MA, Sharma E, Malik R, Worrall BB, Levine AJ, Martinson JJ, Nejentsev S, Speed D, Fischer A, Mick E, Walker BR, Crawford A, Grant SFA, Polychronakos C, Bradfield JP, Sleiman PMA, Hakonarson H, Ellinghaus E, Elder JT, Tsoi LC, Trembath RC, Barker JN, Franke A, Dehghan A; 23 and Me Research Team; Inflammation Working Group of the CHARGE Consortium; METASTROKE Consortium of the International Stroke Genetics Consortium; Netherlands Twin Registry; neuroCHARGE Working Group; Obsessive Compulsive and Tourette Syndrome Working Group of the Psychiatric Genomics Consortium; Faraone SV, Glatt SJ. Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data. Am J Med Genet B Neuropsychiatr Genet. 2018 Oct;177(7):641-657. doi: 10.1002/ajmg.b.32652. Epub 2018 Oct 16.
- Shorter JR, Meijsen J, Nudel R, Krebs M, Gadin J, Mikkelsen DH, Nogueira Avelar E Silva R, Benros ME, Thompson WK, Ingason A, Werge T. Infection Polygenic Factors Account for a Small Proportion of the Relationship Between Infections and Mental Disorders. Biol Psychiatry. 2022 Aug 15;92(4):283-290. doi: 10.1016/j.biopsych.2022.01.007. Epub 2022 Jan 24.
- Debost JPG, Thorsteinsson E, Trabjerg B, Benros ME, Albinana C, Vilhjalmsson BJ, Borglum A, Mors O, Werge T, Mortensen PB, Agerbo E, Petersen LV. Genetic and psychosocial influence on the association between early childhood infections and later psychiatric disorders. Acta Psychiatr Scand. 2022 Nov;146(5):406-419. doi: 10.1111/acps.13491. Epub 2022 Sep 8.
- Benros ME, Waltoft BL, Nordentoft M, Ostergaard SD, Eaton WW, Krogh J, Mortensen PB. Autoimmune diseases and severe infections as risk factors for mood disorders: a nationwide study. JAMA Psychiatry. 2013 Aug;70(8):812-20. doi: 10.1001/jamapsychiatry.2013.1111.
- Vai B, Parenti L, Bollettini I, Cara C, Verga C, Melloni E, Mazza E, Poletti S, Colombo C, Benedetti F. Predicting differential diagnosis between bipolar and unipolar depression with multiple kernel learning on multimodal structural neuroimaging. Eur Neuropsychopharmacol. 2020 May;34:28-38. doi: 10.1016/j.euroneuro.2020.03.008. Epub 2020 Mar 29.
- Benros ME, Nielsen PR, Nordentoft M, Eaton WW, Dalton SO, Mortensen PB. Autoimmune diseases and severe infections as risk factors for schizophrenia: a 30-year population-based register study. Am J Psychiatry. 2011 Dec;168(12):1303-10. doi: 10.1176/appi.ajp.2011.11030516.
- McGrath JJ, Pemberton MR, Welham JL, Murray RM. Schizophrenia and the influenza epidemics of 1954, 1957 and 1959: a southern hemisphere study. Schizophr Res. 1994 Dec;14(1):1-8. doi: 10.1016/0920-9964(94)90002-7.
- Mazza MG, Palladini M, Villa G, Agnoletto E, Harrington Y, Vai B, Benedetti F. Prevalence of depression in SARS-CoV-2 infected patients: An umbrella review of meta-analyses. Gen Hosp Psychiatry. 2023 Jan-Feb;80:17-25. doi: 10.1016/j.genhosppsych.2022.12.002. Epub 2022 Dec 7.
- Vai B, Mazza MG, Delli Colli C, Foiselle M, Allen B, Benedetti F, Borsini A, Casanova Dias M, Tamouza R, Leboyer M, Benros ME, Branchi I, Fusar-Poli P, De Picker LJ. Mental disorders and risk of COVID-19-related mortality, hospitalisation, and intensive care unit admission: a systematic review and meta-analysis. Lancet Psychiatry. 2021 Sep;8(9):797-812. doi: 10.1016/S2215-0366(21)00232-7. Epub 2021 Jul 17.
- Vai B, Mazza MG, Marisa CD, Beezhold J, Karkkainen H, Saunders J, Samochowiec J, Benedetti F, Leboyer M, Fusar-Poli P, De Picker L. Joint European policy on the COVID-19 risks for people with mental disorders: An umbrella review and evidence- and consensus-based recommendations for mental and public health. Eur Psychiatry. 2022 Aug 16;65(1):e47. doi: 10.1192/j.eurpsy.2022.2307.
- De Picker LJ, Victoriano GM, Richards R, Gorvett AJ, Lyons S, Buckland GR, Tofani T, Norman JL, Chatelet DS, Nicoll JAR, Boche D. Immune environment of the brain in schizophrenia and during the psychotic episode: A human post-mortem study. Brain Behav Immun. 2021 Oct;97:319-327. doi: 10.1016/j.bbi.2021.07.017. Epub 2021 Jul 30.
- Tzur Bitan D, Krieger I, Kridin K, Komantscher D, Scheinman Y, Weinstein O, Cohen AD, Cicurel AA, Feingold D. COVID-19 Prevalence and Mortality Among Schizophrenia Patients: A Large-Scale Retrospective Cohort Study. Schizophr Bull. 2021 Aug 21;47(5):1211-1217. doi: 10.1093/schbul/sbab012.
- Mazza MG, Palladini M, De Lorenzo R, Bravi B, Poletti S, Furlan R, Ciceri F; COVID-19 BioB Outpatient Clinic Study group; Rovere-Querini P, Benedetti F. One-year mental health outcomes in a cohort of COVID-19 survivors. J Psychiatr Res. 2021 Nov 22;145:118-124. doi: 10.1016/j.jpsychires.2021.11.031. Online ahead of print.
- Poletti S, Vai B, Mazza MG, Zanardi R, Lorenzi C, Calesella F, Cazzetta S, Branchi I, Colombo C, Furlan R, Benedetti F. A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach. Prog Neuropsychopharmacol Biol Psychiatry. 2021 Mar 8;105:110136. doi: 10.1016/j.pnpbp.2020.110136. Epub 2020 Oct 9.
- Poletti S, de Wit H, Mazza E, Wijkhuijs AJM, Locatelli C, Aggio V, Colombo C, Benedetti F, Drexhage HA. Th17 cells correlate positively to the structural and functional integrity of the brain in bipolar depression and healthy controls. Brain Behav Immun. 2017 Mar;61:317-325. doi: 10.1016/j.bbi.2016.12.020. Epub 2016 Dec 23.
- Poletti S, Leone G, Hoogenboezem TA, Ghiglino D, Vai B, de Wit H, Wijkhuijs AJM, Locatelli C, Colombo C, Drexhage HA, Benedetti F. Markers of neuroinflammation influence measures of cortical thickness in bipolar depression. Psychiatry Res Neuroimaging. 2019 Mar 30;285:64-66. doi: 10.1016/j.pscychresns.2019.01.009. Epub 2019 Jan 29.
- Benedetti F, Palladini M, Paolini M, Melloni E, Vai B, De Lorenzo R, Furlan R, Rovere-Querini P, Falini A, Mazza MG. Brain correlates of depression, post-traumatic distress, and inflammatory biomarkers in COVID-19 survivors: A multimodal magnetic resonance imaging study. Brain Behav Immun Health. 2021 Dec;18:100387. doi: 10.1016/j.bbih.2021.100387. Epub 2021 Nov 2.
- Tzur Bitan D, Kridin K, Cohen AD, Weinstein O. COVID-19 hospitalisation, mortality, vaccination, and postvaccination trends among people with schizophrenia in Israel: a longitudinal cohort study. Lancet Psychiatry. 2021 Oct;8(10):901-908. doi: 10.1016/S2215-0366(21)00256-X. Epub 2021 Aug 6.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- ERP-2023-23684210
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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