By Benjamin K. Brent, Isabelle M. Rosso, Heidi W. Thermenos, Daphne J. Holt, Stephen V. Faraone, Nikos Makris, Ming T. Tsuang, and Larry J. Seidman | Schizophrenia Research | November 24, 2015

Abstract:

Background

Structural alterations of the lateral temporal cortex (LTC) in association with memory impairments have been reported in schizophrenia. This study investigated whether alterations of LTC structure were linked with impaired facial and/or verbal memory in young first-degree relatives of people with schizophrenia and, thus, may be indicators of vulnerability to the illness.

Methods

Subjects included 27 non-psychotic, first-degree relatives of schizophrenia patients, and 48 healthy controls, between the ages of 13 and 28. Participants underwent high-resolution magnetic resonance imaging (MRI) at 1.5 Tesla. The LTC was parcellated into superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, and temporal pole. Total cerebral and LTC volumes were measured using semi-automated morphometry. The Wechsler Memory Scale — Third Edition and the Children’s Memory Scale — Third Edition assessed facial and verbal memory. General linear models tested for associations among LTC subregion volumes, familial risk and memory.

Results

Compared with controls, relatives had significantly smaller bilateral middle temporal gyri. Moreover, right middle temporal gyral volume showed a significant positive association with delayed facial memory in relatives.

Conclusion

These results support the hypothesis that smaller middle temporal gyri are related to the genetic liability to schizophrenia and may be linked with reduced facial memory in persons at genetic risk for the illness. The findings add to the growing evidence that children at risk for schizophrenia on the basis of positive family history have cortical and subcortical structural brain abnormalities well before psychotic illness occurs.

Read the full article here.

By Joseph Gonzalez-Heydrich, Michelle Bosquet Enlow, Eugene D’Angelo, Larry J. Seidman, Sarah Gumlak, April Kim, Kristen A. Woodberry, Ashley Rober, Sahil Tembulkar, Kelsey Graber, Kyle O’Donnell, Hesham M. Hamoda, Kara Kimball, Alexander Rotenberg, Lindsay M. Oberman, Alvaro Pascual-Leone, Matcheri S. Keshavan, and Frank H. Duffy | Schizophrenia Research | November 6, 2015

Abstract:

Background

The N100 is a negative deflection in the surface EEG approximately 100 ms after an auditory signal. It has been shown to be reduced in individuals with schizophrenia and those at clinical high risk (CHR). N100 blunting may index neural network dysfunction underlying psychotic symptoms. This phenomenon has received little attention in pediatric populations.

Method

This cross-sectional study compared the N100 response measured via the average EEG response at the left medial frontal position FC1 to 150 sinusoidal tones in participants ages 5 to 17 years with a CHR syndrome (n = 29), a psychotic disorder (n = 22), or healthy controls (n = 17).

Results

Linear regression analyses that considered potential covariates (age, gender, handedness, family mental health history, medication usage) revealed decreasing N100 amplitude with increasing severity of psychotic symptomatology from healthy to CHR to psychotic level.

Conclusions

Longitudinal assessment of the N100 in CHR children who do and do not develop psychosis will inform whether it predicts transition to psychosis and if its response to treatment predicts symptom change.

Read the entire study here.

By Diana O. Perkins, Clark D. Jeffries, Barbara A. Cornblatt, Scott W. Woods, Jean Addington, Carrie E. Bearden, Kristin S. Cadenhead, Tyrone D. Cannon, Robert Heinssen, Daniel H. Mathalon, Larry J. Seidman, Ming T. Tsuang, Elaine F. Walker, and Thomas H. McGlashan | Schizophrenia Research | October 2, 2015

Abstract:

Background

Improving predictive accuracy is of paramount importance for early detection and prevention of psychosis. We sought a symptom severity classifier that would improve psychosis risk prediction.

Methods

Subjects were from two cohorts of the North American Prodrome Longitudinal Study. All subjects met Criteria of Psychosis-Risk States. In Cohort-1 (n = 296) we developed a classifier that included those items of the Scale of Psychosis-Risk Symptoms that best distinguished subjects who converted to psychosis from nonconverters, with performance initially validated by randomization tests in Cohort-1. Cohort-2 (n = 592) served as an independent test set.

Results

We derived 2-Item and 4-Item subscales. Both included unusual thought content and suspiciousness; the latter added reduced ideational richness and difficulties with focus/concentration. The Concordance Index (C-Index), a measure of discrimination, was similar for each subscale across cohorts (4-Item subscale Cohort-2: 0.71, 95% CI = [0.64, 0.77], Cohort-1: 0.74, 95% CI = [0.69, 0.80]; 2-Item subscale Cohort-2: 0.68, 95% CI = [0.3, 0.76], Cohort-1: 0.72, 95% CI = [0.66–0.79]). The 4-Item performed better than the 2-Item subscale in 742/1000 random selections of 80% subsets of Cohort-2 subjects (p-value = 1.3E−55). Subscale calibration between cohorts was proportional (higher scores/lower survival), but absolute conversion risk predicted from Cohort-1 was higher than that observed in Cohort-2, reflecting the cohorts’ differences in 2-year conversion rates (Cohort-2: 0.16, 95% CI = [0.13, 0.19]; Cohort-1: 0.30, 95% CI = [0.24, 0.36]).

Conclusion

Severity of unusual thought content, suspiciousness, reduced ideational richness, and difficulty with focus/concentration informed psychosis risk prediction. Scales based on these symptoms may have utility in research and, assuming further validation, eventual clinical applications.

Read the full article here.

Larry Seidman et al | Schizophrenia Research | February 11, 2015

Abstract:

Background:
Although many endophenotypes for schizophrenia have been studied individually, few studies have examined the extent to which common neurocognitive and neurophysiological measures reflect shared versus unique endophenotypic factors. It may be possible to distill individual endophenotypes into composite measures that reflect dissociable, genetically informative elements.

Methods:
The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) is a multisite family study that collected neurocognitive and neurophysiological data between 2003 and 2008. For these analyses, participants included schizophrenia probands (n = 83), their nonpsychotic siblings (n = 151), and community comparison subjects (n = 209) with complete data on a battery of 12 neurocognitive tests (assessing domains of working memory, declarative memory, vigilance, spatial ability, abstract reasoning, facial emotion processing, and motor speed) and 3 neurophysiological tasks reflecting inhibitory processing (P50 gating, prepulse inhibition and antisaccade tasks). Factor analyses were conducted on the measures for each subject group and across the entire sample. Heritability analyses of factors were performed using SOLAR.

Results:
Analyses yielded 5 distinct factors: 1) Episodic Memory, 2) Working Memory, 3) Perceptual Vigilance, 4) Visual Abstraction, and 5) Inhibitory Processing. Neurophysiological measures had low associations with these factors. The factor structure of endophenotypes was largely comparable across probands, siblings and controls. Significant heritability estimates for the factors ranged from 22% (Episodic Memory) to 39% (Visual Abstraction).

Conclusions:
Neurocognitive measures reflect a meaningful amount of shared variance whereas the neurophysiological measures reflect largely unique contributions as endophenotypes for schizophrenia. Composite endophenotype measures may inform our neurobiological and genetic understanding of schizophrenia.

Read the full paper here.