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Gray matter endophenotypes

Abstract | ABSTRACT | Figures in this Article | SUBJECTS | GENETIC LIABILITY SCALE | MRI DATA ACQUISITION AND PREPROCESSING | UNIVARIATE ANALYSIS OF MRI ENDOPHENOTYPES | MULTILEVEL MODELING OF MRI ENDOPHENOTYPES | Figure 2. | DISORDER SPECIFICITY OF GRAY AND WHITE MATTER ENDOPHENOTYPES |


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  2. DISORDER SPECIFICITY OF GRAY AND WHITE MATTER ENDOPHENOTYPES
  3. Family matters
  4. MULTILEVEL MODELING OF MRI ENDOPHENOTYPES
  5. UNIVARIATE ANALYSIS OF MRI ENDOPHENOTYPES

Genetic risk for schizophrenia was associated with distributed graymatter volume deficits in the orbital, prefrontal, and premotor parts of thefrontal cortex, caudate nucleus, and bilateral thalamus as well as the leftinsula and lateral temporal cortex (Figure 1Aand Table 2). The PC analysis showedthat these gray matter deficits were highly correlated across regions, implyinggenetically determined effects on the volume of a cortical-subcortical network.All regions of gray matter volume deficit loaded positively for the firstPC (Table 2), which explained 73.5%of the total variance in the group of patients with schizophrenia and theirrelatives. Scores for the first PC were strongly associated with genetic riskin patients with schizophrenia and their relatives without psychosis (Table 3). There was no significant interactionbetween subject group (patient vs relative) and genetic liability score, indicatingthat this pattern of gray matter deficit was not determined solely by abnormalitiesin the patients (Table 3 and Figure 1B). The relationship between increasedgenetic risk and greater gray matter volume deficits in this cortical-subcorticalsystem remained significant when the analysis was confined to the 20 familiesin which the patient’s family history consisted specifically of schizophrenia(β = −1.49; P =.02;95% confidence interval, −2.63 to −0.31).


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SUBJECTS| Figure 1.

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