BACKGROUND: A number of studies have provided evidence for genetic modulation of brain structure in unaffected family members (FM) of schizophrenia patients using conventional volumetric analysis. High-dimensional pattern classification methods have been reported to have the capacity to determine subtle and spatially complex structural patterns that distinguish schizophrenia patients from healthy control subjects using standard magnetic resonance imaging. This study investigates whether such endophenotypic patterns are found in FM via similar image analysis approaches. METHODS: A high-dimensional pattern classifier was constructed from a group of 69 patients and 79 control subjects, via an analysis that identified a subtle and spatially complex pattern of reduced brain volumes. The constructed classifier was applied to examine brain structure of 30 FM. RESULTS: The classifier indicated that FM had highly overlapping structural profiles with those of patients. Moreover, an orbitofrontal region of relatively increased white matter was found to contribute significantly to the classification, indicating that white matter alterations, along with reductions of gray matter volumes, might be present in patients and unaffected FM. CONCLUSIONS: These findings provide evidence that high-dimensional pattern classification can identify complex and subtle structural endophenotypes that are shared by probands and their unaffected FM.
BACKGROUND: A number of studies have provided evidence for genetic modulation of brain structure in unaffected family members (FM) of schizophreniapatients using conventional volumetric analysis. High-dimensional pattern classification methods have been reported to have the capacity to determine subtle and spatially complex structural patterns that distinguish schizophreniapatients from healthy control subjects using standard magnetic resonance imaging. This study investigates whether such endophenotypic patterns are found in FM via similar image analysis approaches. METHODS: A high-dimensional pattern classifier was constructed from a group of 69 patients and 79 control subjects, via an analysis that identified a subtle and spatially complex pattern of reduced brain volumes. The constructed classifier was applied to examine brain structure of 30 FM. RESULTS: The classifier indicated that FM had highly overlapping structural profiles with those of patients. Moreover, an orbitofrontal region of relatively increased white matter was found to contribute significantly to the classification, indicating that white matter alterations, along with reductions of gray matter volumes, might be present in patients and unaffected FM. CONCLUSIONS: These findings provide evidence that high-dimensional pattern classification can identify complex and subtle structural endophenotypes that are shared by probands and their unaffected FM.
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