ArticleNeuropsychiatric disease and treatment2019
Serum BICC1 levels are significantly different in various mood disorders.
Article in Neuropsychiatric disease and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Exploring the BICC1 Interactome in HEK293T Cells: Insights Into RNA-Mediated Protein Networks and Biomolecular Condensates.FASEB bioAdvances · 2026Article
- Stratification by a polygenic risk score of common variation aids in Alzheimer's disease rare variant discovery.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Observational
- Diagnostic value and role of serum miR-15a-5p in patients with schizophrenia.Annals of general psychiatry · 2024Article
- Predicting the diagnosis of various mental disorders in a mixed cohort using blood-based multi-protein model: a machine learning approach.European archives of psychiatry and clinical neuroscience · 2023Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeMood disorders are recurrent chronic disorders with fluctuating mood states and energy, and misdiagnosis is common when based solely on clinical interviews because of overlapping symptoms. Because misdiagnosis may lead to inappropriate treatment and poor prognosis, finding an easily implemented objective tool for the discrimination of different mood disorders is very necessary and urgent. However, there has been no accepted objective tool until now. Recently, PATIENTS AND
methodsSerum BICC1 levels in drug-free patients with MDD (n=30), BM (n=30), and BD (n=13), and well-matched healthy controls (HC, n=30) were measured with ELISA kits. Pearson correlation analyses were used to analyze the correlations between serum BICC1 levels and clinical information. Receiver operating characteristic (ROC) curve analysis was used to analyze the differential discriminative potential of BICC1 for different mood disorders.
resultsOne-way ANOVA indicated that serum BICC1 levels were significantly increased in all patient groups compared with the HC group and significantly different between each pair of patient groups. Correlation analyses found no relationship between serum BICC1 levels and any clinical variables in any study group. ROC curve analysis showed that serum BICC1 could discriminate among all three mood disorders from each other accurately with fair-to-excellent discriminatory capacity (area under the ROC curve from 0.787 to 1.0).
conclusionThe findings of this preliminary study indicated significant differences in serum BICC1 levels in patients with different mood disorders. This study provides preliminary evidence that serum BICC1 may be regarded as a promising, objective, easy-to-use tool for diagnosing different mood disorders.
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