Background: Subtle neurological impairments and inconsequential minor anomalies of the face and limbs are manifestations of neurodevelopmental and ontogenic abnormalities that are consistently found at higher rates in individuals with schizophrenia compared to healthy controls. Limited research has been conducted on these traits among biological relatives of patients with schizophrenia. This study hypothesized that the mean NSS score and the mean MPA score would be greater in patients than controls and that first-degree relatives would have intermediate scores. Furthermore, it was hypothesized that NSS scores and MPA scores would not be correlated. This study also explored correlations between patients' NSS and MPA scores and their relatives' respective scores and sought to replicate the finding that NSS are associated with negative and disorganized symptoms of schizophrenia, whereas MPAs are not.
Methods: Patients with schizophrenia and related psychotic disorders (n=73), first-degree relatives (n=44), and non-psychiatric controls (n=54) were assessed. Measures included the Neurological Evaluation Scale, a structured examination for MPAs, and the Positive and Negative Syndrome Scale in patients. Analyses accounted for clustering within families.
Results: Both NSS and MPAs were greater in patients than controls, and first-degree relatives had intermediate scores. Furthermore, NSS and MPA scores were independent in all three groups. Correlations were found between patients' and their relatives' scores on one NES subscale (sensory integration) and total MPA score and several MPA regions (eyes, ears, and hands). This study replicated previous findings that in patients with schizophrenia, NSS are associated with negative, disorganized, and other domains of symptoms. Associations between MPAs and symptoms were sparse and inconsistent.
Conclusion: These findings suggest that NSS and MPAs represent two quite distinct markers of risk for schizophrenia that may stem from genetic factors, as well as from environmental/developmental influences. Future research on multivariable risk prediction models may benefit from the use of somewhat independent risk markers or endophenotypes.