The family caregivers of people with mental illness may internalize the public stereotypes into the affiliate stigma (i.e., the self-stigma of family members). This study aimed to compare the affiliate stigma across schizophrenia, bipolar disorder, and major depressive disorder, and to investigate potential factors associated with affiliate stigma. Each caregiver of family members with schizophrenia (n = 215), bipolar disorder (n = 85), and major depressive disorder (n = 159) completed the Affiliate Stigma Scale, Rosenberg Self-Esteem Scale, Caregiver Burden Inventory, Taiwanese Depression Questionnaire, and Beck Anxiety Inventory. After controlling for potential confounders, the hierarchical regression models showed that caregivers of a family member with schizophrenia had a higher level of affiliate stigma than those of bipolar disorder (β = -0.109; p < 0.05) and major depressive disorder (β = -0.230; p < 0.001). Self-esteem, developmental burden, and emotional burden were significant factors for affiliate stigma. The affiliate stigma of caregivers is associated with their self-esteem, caregiver burden, and by the diagnosis.

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Several studies have been suggested that immunity plays a part in neurodevelopment and schizophrenia pathogenesis. Early age of onset in schizophrenia is associated with genetic factors which affect neurodevelopment. This study aims to identify immune abnormalities associated with neurodevelopmental impairments in early-onset schizophrenia (EOS) and adult-onset schizophrenia (AOS) patients. We determined the plasma levels of six cytokines (IL-1β, IL-4, IL-6, IL-10, IL-12 and TNF-α) in schizophrenia patients and healthy controls. Measurements included neurological soft signs (NSS) to distinguish and subgroup those with neurodevelopmental impairments. The study included 210 schizophrenia patients, which were divided into 84 EOS and 126 AOS patients, as well as 122 healthy controls. We observed significant differences in levels of IL-4, IL-6 and IL-10 between EOS and AOS patients. The results demonstrated the area under ROC curve (AUC) of the IL-4 in EOS and healthy controls was 0.81. Moreover, these results indicated that AUC of the IL-4 and the combination of IL-4, IL-6 and IL-12 in EOS with NSS and healthy controls were 0.91 and 0.95. These cytokines are altered in EOS and schizophrenia patients with neurodevelopmental impairments and demonstrated good classification abilities. These findings manifested that both pro-and anti-inflammatory cytokines are contributed to the clinical and pathophysiological features of schizophrenia. Future works are expected to explore potential genetic effectors and predictors as well as therapeutic directions in personalized medicine for early-onset schizophrenia.

Many family characteristics were reported to increase the risk of bipolar disorder (BPD). The development of BPD may be mediated through different pathways, involving diverse risk factor profiles. We evaluated the associations of family characteristics to build influential causal-pie models to estimate their contributions on the risk of developing BPD at the population level. We recruited 329 clinically diagnosed BPD patients and 202 healthy controls to collect information in parental psychopathology, parent-child relationship, and conflict within family. Other than logistic regression models, we applied causal-pie models to identify pathways involved with different family factors for BPD. The risk of BPD was significantly increased with parental depression, neurosis, anxiety, paternal substance use problems, and poor relationship with parents. Having a depressed mother further predicted early onset of BPD. Additionally, a greater risk for BPD was observed with higher numbers of paternal/maternal psychopathologies. Three significant risk profiles were identified for BPD, including paternal substance use problems (73.0%), maternal depression (17.6%), and through poor relationship with parents and conflict within the family (6.3%). Our findings demonstrate that different aspects of family characteristics elicit negative impacts on bipolar illness, which can be utilized to target specific factors to design and employ efficient intervention programs.