Linking prolonged childhood and adolescent loneliness to schizophrenia spectrum disorders: results from EU-GEI study

Prolonged childhood and adolescent loneliness (CAL) is linked to various adverse mental health outcomes, yet its impact on schizophrenia spectrum disorders (SSD) has been understudied. While loneliness is associated with psychosis and worsens symptoms in SSD, few studies have explored the long-term effects of early loneliness on SSD risk. Understanding how CAL interacts with genetic liability to schizophrenia is essential for identification of high-risk individuals.

This study evaluated whether prolonged CAL is associated with increased SSD risk and examined the interaction between CAL and genetic liability for schizophrenia. Gender differences in these associations were also explored.

Data from the European Gene-Environment Interactions in Schizophrenia (EU-GEI) study were analysed, including 1261 individuals with SSD, 1282 unaffected siblings and 1525 healthy controls. CAL was retrospectively assessed for periods before age 12 years and age 12-16 years. Genetic risk was measured using polygenic risk scores for schizophrenia. Logistic regression models and the Relative Excess Risk due to Interaction (RERI) method were used to examine gene-environment interactions, with stratification by gender.

Prolonged CAL was associated with higher odds of SSD (odds ratio [95% CI] = 5.20 [3.85-7.01] for loneliness before age 12; odds ratio [95% CI] = 7.26 [5.63-9.38] for loneliness during adolescence). The interaction between CAL and genetic risk was strongest during adolescence (RERI [95% CI] = 23.46 [10.75-53.53]). Females showed a greater effect (odds ratio [95 %CI] = 10.04 [6.80-14.94]) than males (odds ratio [95% CI] = 5.50 [3.95-7.66]). Incorporating CAL and genetic interaction increased predictive values to 17% for SSD risk - rising to 22.5% in females - compared with 2.6 and 2.8%, respectively, for genetic risk alone.

Prolonged CAL significantly increases SSD risk, particularly in females. The inclusion of CAL alongside genetic risk substantially enhances predictive accuracy. Early identification of CAL could inform preventive strategies, especially in genetically vulnerable populations.