Genetic liability, prenatal health, stress and family environment: risk factors in the Harvard Adolescent Family High Risk for schizophrenia study.

Objectives: The familial ("genetic") high-risk (FHR) paradigm enables assessment of individuals at risk for schizophrenia based on a positive family history of schizophrenia in first-degree, biological relatives. This strategy presumes genetic transmission of abnormal traits given high heritability of the illness. It is plausible, however, that adverse environmental factors are also transmitted in these families. Few studies have evaluated both biological and environmental factors within a FHR study of adolescents.

Methods: We conceptualize four precursors to psychosis pathogenesis: two biological (genetic predisposition, prenatal health issues (PHIs)) and two environmental (family environment, stressful life events (SLEs)). Participants assessed between 1998 and 2007 (ages 13-25) included 40 (20F/20M) adolescents at FHR for schizophrenia (FHRs) and 55 (31F/24M) community controls. 'Genetic load' indexed number of affected family members relative to pedigree size.

Results: PHI was significantly greater among FHRs, and family cohesion and expressiveness were less (and family conflict was higher) among FHRs; however, groups did not significantly differ in SLE indices. Among FHRs, genetic liability was significantly associated with PHI and family expressiveness.

Conclusions: Prenatal and family environmental disruptions are elevated in families with a first-degree relative with schizophrenia. Findings support our proposed 'polygenic neurodevelopmental diathesis-stress model' whereby psychosis susceptibility (and resilience) involves the independent and synergistic confluence of (temporally-sensitive) biological and environmental factors across development. Recognition of biological and social environmental influences across critical developmental periods points to key issues relevant for enhanced identification of psychosis susceptibility, facilitation of more precise models of illness risk, and development of novel prevention strategies.