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Woolway GE, Legge SE, Lynham AJ, Smart SE, Hubbard L, Daniel ER, Pardiñas AF, Escott-Price V, O'Donovan MC, Owen MJ, Jones IR, Walters JTR. Assessing the validity of a self-reported clinical diagnosis of schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:99. [PMID: 39477999 PMCID: PMC11526013 DOI: 10.1038/s41537-024-00526-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 10/15/2024] [Indexed: 11/02/2024]
Abstract
The increasing availability of biobanks is changing the way individuals are identified for genomic research. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia. The study included 1744 clinically-ascertained participants with schizophrenia or schizoaffective disorder depressed-type (SA-D) diagnosed by self-report and/or research interview and 1453 UK Biobank participants with self-reported and/or medical record diagnosis of schizophrenia or SA-D. Unaffected controls included a total of 501,837 participants. We assessed the positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. Polygenic risk scores (PRS) and phenotypes relating to demographics, education and employment were compared across diagnostic groups. The variance explained (r2) in schizophrenia PRS for each diagnostic group was compared to samples in the Psychiatric Genomics Consortium (PGC). In the clinically-ascertained participants, the PPV of self-reported schizophrenia for a research diagnosis of schizophrenia was 0.70, which increased to 0.81 after expanding the research diagnosis to schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia for a medical record diagnosis was 0.74. Compared to participants who self-reported, participants with a clinically-ascertained research diagnosis were younger and more likely to have a high school qualification. Participants with a medical record diagnosis in UK Biobank were less likely to be employed or have a high school qualification than those who self-reported. Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical records. Polygenic liability r2, for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts. Self-reported measures of schizophrenia are justified in genomic research to maximise sample size and reduce the burden of in-depth interviews on participants, although within sample validation of diagnoses is recommended.
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Affiliation(s)
- Grace E Woolway
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Legge
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
| | - Amy J Lynham
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Smart
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Leon Hubbard
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Ellie R Daniel
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Valentina Escott-Price
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Ian R Jones
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
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Woolway GE, Legge SE, Lynham A, Smart SE, Hubbard L, Daniel ER, Pardiñas AF, Escott-Price V, O'Donovan MC, Owen MJ, Jones IR, Walters JT. Assessing the validity of a self-reported clinical diagnosis of schizophrenia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.06.23299622. [PMID: 38106032 PMCID: PMC10723562 DOI: 10.1101/2023.12.06.23299622] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Background Diagnoses in psychiatric research can be derived from various sources. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia. Methods The study included 3,029 clinically ascertained participants with schizophrenia or psychotic disorders diagnosed by self-report and/or research interview and 1,453 UK Biobank participants with self-report and/or medical record diagnosis of schizophrenia or schizoaffective disorder depressed-type (SA-D). We assessed positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. We compared polygenic risk scores (PRS) and phenotypes across diagnostic groups, and compared the variance explained by schizophrenia PRS to samples in the Psychiatric Genomics Consortium (PGC). Results In the clinically ascertained sample, the PPV of self-reported schizophrenia to a research diagnosis of schizophrenia was 0.70, which increased to 0.81 when benchmarked against schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia to a medical record diagnosis was 0.74. Compared to self-report participants, those with a research diagnosis were younger and more likely to have a high school qualification (clinically ascertained sample) and those with a medical record diagnosis were less likely to be employed or have a high school qualification (UK Biobank). Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical record diagnosis. Polygenic liability r2, for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts. Conclusions Self-report measures of schizophrenia are justified in research to maximise sample size and representativeness, although within sample validation of diagnoses is recommended.
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Affiliation(s)
- Grace E Woolway
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Legge
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Amy Lynham
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie E Smart
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Leon Hubbard
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Ellie R Daniel
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Valentina Escott-Price
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Ian R Jones
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - James Tr Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
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Jiang C, Jiang W, Chen G, Xu W, Sun T, You L, Chen S, Yin Y, Liu X, Hou Z, Qing Z, Xie C, Zhang Z, Turner JA, Yuan Y. Childhood trauma and social support affect symptom profiles through cortical thickness abnormalities in major depressive disorder: A structural equation modeling analysis. Asian J Psychiatr 2023; 88:103744. [PMID: 37619416 DOI: 10.1016/j.ajp.2023.103744] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/10/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023]
Abstract
BACKGROUND Childhood trauma, low social support, and alexithymia are recognized as risk factors for major depressive disorder (MDD). However, the mechanisms of risk factors, symptoms, and corresponding structural brain abnormalities in MDD are not fully understood. Structural equation modeling (SEM) has advantages in studying multivariate interrelationships. We aim to illustrate their relationships using SEM. METHODS 313 MDD patients (213 female; mean age 42.49 years) underwent magnetic resonance imaging and completed assessments. We integrated childhood trauma, alexithymia, social support, anhedonia, depression, anxiety, suicidal ideation and cortical thickness into a multivariate SEM. RESULTS We first established the risk factors-clinical phenotype SEM with an adequate fit. Cortical thickness results show a negative correlation of childhood trauma with the left middle temporal gyrus (MTG) (p = 0.012), and social support was negatively correlated with the left posterior cingulate cortex (PCC) (p < 0.001). The final good fit SEM (χ2 = 32.92, df = 21, χ2/df = 1.57, CFI = 0.962, GFI = 0.978, RMSEA = 0.043) suggested two pathways, with left PCC thickness mediating the relationship between social support and suicidal ideation, and left MTG thickness mediating between childhood trauma and anhedonia/anxiety. CONCLUSION Our findings provide evidence for the impact of risk factor variables on the brain structure and clinical phenotype of MDD patients. Insufficient social support and childhood trauma might lead to corresponding cortical abnormalities in PCC and MTG, affecting the patient's mood and suicidal ideation. Future interventions should aim at these nodes.
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Affiliation(s)
- Chenguang Jiang
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Wenhao Jiang
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Gang Chen
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University; Department of Medical Psychology, Huai'an No.3 People's Hospital, Huaian, China
| | - Wei Xu
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University; Department of Clinical Psychology, Northern Jiangsu People's Hospital, Yangzhou, China
| | - Taipeng Sun
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University; Department of Medical Psychology, Huai'an No.3 People's Hospital, Huaian, China
| | - Linlin You
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Suzhen Chen
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yingying Yin
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Xiaoyun Liu
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhenghua Hou
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhao Qing
- Shing-Tung Yau Center; School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhijun Zhang
- Department of Neurology, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, OH, United States.
| | - Yonggui Yuan
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.
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Nikolac Perkovic M, Gredicak M, Sagud M, Nedic Erjavec G, Uzun S, Pivac N. The association of brain-derived neurotrophic factor with the diagnosis and treatment response in depression. Expert Rev Mol Diagn 2023; 23:283-296. [PMID: 37038358 DOI: 10.1080/14737159.2023.2200937] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
INTRODUCTION Recent evidence from the studies evaluating the association between brain derived neurotrophic factor (BDNF) concentration/levels, BDNF Val66Met (rs6265) polymorphism and major depressive disorders, referred as depression, and the association between BDNF levels and/or BDNF Val66Met with the treatment response in depression, is presented. AREAS COVERED This mini review focuses on the changes in the peripheral BDNF levels in blood (serum, plasma, platelets) in patients with depression before or after treatment with antidepressant drugs or different therapeutic strategies. In addition, this review describes the recent data on the possible association between different antidepressants/therapeutic strategies and the particular BDNF Val66Met genotypes, evaluating the risk alleles associated with the response in patients with depression. EXPERT OPINION BDNF has an important role in the pathophysiology and treatment response in depression. Most data reveal that peripheral BDNF levels are lower before than after antidepressant treatment and might be used as potential biomarkers of therapeutic response. Novel therapeutic strategies should target restoring/increasing BDNF levels.
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Affiliation(s)
- Matea Nikolac Perkovic
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia
| | - Martin Gredicak
- General Hospital Zabok and Hospital for the Croatian Veterans, Zabok, Croatia
| | - Marina Sagud
- Department for Psychiatry and Psychological Medicine, University Hospital Centre Zagreb, Zagreb, Croatia
- School of Medicine,University of Zagreb, Zagreb, Croatia
| | - Gordana Nedic Erjavec
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia
| | - Suzana Uzun
- School of Medicine,University of Zagreb, Zagreb, Croatia
- Department for Biological Psychiatry and Psychogeriatry, Clinics for Psychiatry Vrapce, Zagreb, Croatia
| | - Nela Pivac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia
- Croatian Zagorje Polytechnic Krapina,Krapina, Croatia
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