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Mürner-Lavanchy I, Koenig J, Reichl C, Josi J, Cavelti M, Kaess M. The quest for a biological phenotype of adolescent non-suicidal self-injury: a machine-learning approach. Transl Psychiatry 2024; 14:56. [PMID: 38267430 PMCID: PMC10810046 DOI: 10.1038/s41398-024-02776-4] [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: 08/01/2023] [Revised: 01/05/2024] [Accepted: 01/12/2024] [Indexed: 01/26/2024] Open
Abstract
Non-suicidal self-injury (NSSI) is a transdiagnostic psychiatric symptom with high prevalence and relevance in child and adolescent psychiatry. Therefore, it is of great interest to identify a biological phenotype associated with NSSI. The aim of the present study was to cross-sectionally investigate patterns of biological markers underlying NSSI and associated psychopathology in a sample of female patients and healthy controls. Comprehensive clinical data, saliva and blood samples, heart rate variability and pain sensitivity, were collected in n = 149 patients with NSSI and n = 40 healthy participants. Using machine-based learning, we tested the extent to which oxytocin, dehydroepiandrosterone (DHEA), beta-endorphin, free triiodothyronine (fT3), leukocytes, heart rate variability and pain sensitivity were able to classify participants regarding their clinical outcomes in NSSI, depression and borderline personality disorder symptomatology. We evaluated the predictive performance of several models (linear and logistic regression, elastic net regression, random forests, gradient boosted trees) using repeated cross-validation. With NSSI as an outcome variable, both logistic regression and machine learning models showed moderate predictive performance (Area under the Receiver Operating Characteristic Curve between 0.67 and 0.69). Predictors with the highest predictive power were low oxytocin (OR = 0.55; p = 0.002), low pain sensitivity (OR = 1.15; p = 0.021), and high leukocytes (OR = 1.67; p = 0.015). For the psychopathological outcome variables, i.e., depression and borderline personality disorder symptomatology, models including the biological variables performed not better than the null model. A combination of hormonal and inflammatory markers, as well as pain sensitivity, were able to discriminate between participants with and without NSSI disorder. Based on this dataset, however, complex machine learning models were not able to detect non-linear patterns of associations between the biological markers. These findings need replication and future research will reveal the extent to which the respective biomarkers are useful for longitudinal prediction of clinical outcomes or treatment response.
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Affiliation(s)
- Ines Mürner-Lavanchy
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Julian Koenig
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Corinna Reichl
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Johannes Josi
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Marialuisa Cavelti
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
- Department of Child and Adolescent Psychiatry, Centre for Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany.
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Fares-Otero NE, O J, Spies G, Womersley JS, Gonzalez C, Ayas G, Mossie TB, Carranza-Neira J, Estrada-Lorenzo JM, Vieta E, Schalinski I, Schnyder U, Seedat S. Child maltreatment and resilience in adulthood: a protocol for a systematic review and meta-analysis. Eur J Psychotraumatol 2023; 14:2282826. [PMID: 38010898 PMCID: PMC10993816 DOI: 10.1080/20008066.2023.2282826] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 11/05/2023] [Indexed: 11/29/2023] Open
Abstract
Background: Although child maltreatment (CM) has been linked to health problems and poor psychosocial functioning, not all individuals exposed to CM develop or experience negative consequences later in life. This suggests that some individuals show resilience after being exposed to CM. However, conclusions have been limited by inconsistent findings across different CM subtypes and resilience domains.Objective: To develop a protocol for conducting a systematic review and meta-analysis to quantify associations between CM (overall and its subtypes) and resilience (global and its multiple domains) in adulthood, and to examine moderators and mediators of these associations.Method: PubMed, PsycINFO, Embase, Scopus, and Web of Science will be searched to identify relevant studies on the association between CM (exposure) and resilience (outcome) in adults (≥ 18 years). Data will be screened and extracted by at least two independent reviewers. The methodological quality of the included studies will be independently assessed with a modified version of the Newcastle-Ottawa Scale (NOS). If deemed viable, a meta-analysis will be conducted using a random effects model. Heterogeneity of evidence will be estimated with the I2 statistic, and publication bias will be assessed. The effects of potential moderators (e.g. timing and severity of CM, age, sex, family cohesion, socio-economic status, country/region) will be analysed using meta-regression and subgroup analyses, and meta-analytical structural equation modelling will be employed to synthesise indirect mediation effects. Candidate moderators and mediators (e.g. genetic factors, brain functioning, attachment style, personality traits, physical activity, and social support) will be also examined qualitatively.Conclusions: This protocol will facilitate a systematic review and meta-analysis that has the potential to enhance our knowledge about the association between CM exposure in early life and resilience in adulthood. Understanding associations and underlying mechanisms between CM and resilience is potentially important in informing prevention and interventions to sustain health and improve outcomes among adults with a history of CM.PROSPERO registration: CRD42023394120.
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Affiliation(s)
- Natalia E. Fares-Otero
- Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Hospital Clínic, Institute of Neurosciences (UBNeuro), Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Spain
- Fundació Clínic per a la Recerca Biomèdica (FCRB), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Network Centre for Biomedical Research in Mental Health (CIBERSAM), Health Institute Carlos III (ISCIII), Barcelona, Spain
| | - Jiaqing O
- Health and Social Sciences Cluster, Singapore Institute of Technology, Singapore
| | - Georgina Spies
- South African PTSD Research Programme of Excellence, Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Genomics of Brain Disorders Research Unit, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Jacqueline S. Womersley
- South African PTSD Research Programme of Excellence, Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Genomics of Brain Disorders Research Unit, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Carolina Gonzalez
- School of Psychology and Wellbeing, University of Southern Queensland, Ipswich, Australia
| | - Görkem Ayas
- Graduate School of Health Sciences, Koç Üniversitesi, Istanbul, Turkey
| | - Tilahun Belete Mossie
- Department of Psychiatry, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia
| | - Julia Carranza-Neira
- Faculty of Health Sciences, School of Medicine, Universidad Peruana de Ciencias Aplicadas (UPC), Lima, Peru
| | | | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Hospital Clínic, Institute of Neurosciences (UBNeuro), Department of Medicine, Faculty of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Spain
- Fundació Clínic per a la Recerca Biomèdica (FCRB), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Network Centre for Biomedical Research in Mental Health (CIBERSAM), Health Institute Carlos III (ISCIII), Barcelona, Spain
| | - Inga Schalinski
- Universität der Bundeswehr München, Department of Human Sciences, Munich, Germany
| | | | - Soraya Seedat
- South African PTSD Research Programme of Excellence, Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- South African Medical Research Council Genomics of Brain Disorders Research Unit, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
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