The impact of parent socio-economic status on executive functioning and cortical morphology in individuals with schizophrenia and healthy controls

Yeo, Ronald A.; Martínez, Diana; Pommy, Jessica; Ehrlich, Stefan; Schulz, S. Charles; Ho, Beng-Choon; Bustillo, Juan; Calhoun, Vince D.

doi:10.1017/s0033291713001608

Cited by 17 publications

(16 citation statements)

References 42 publications

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“…The genetic factors did not interact with the repeated EF measures factor; thus, all genetic effects reflect impact on overall EF functioning. The significant effects of pSES and group × pSES were as identified in a similar analysis reported in (Yeo et al, 2013b). There was no main effect of GRS on EF (F(1,117) = 3.04, p = 0.08, partial eta squared = 0.02), though there was a main effect for deletion burden (F(1,117) = 9.06, p = 0.003, partial eta squared = 0.07).…”

Section: Resultssupporting

confidence: 77%

“…But, what are these pathways? Is it the reduced buffering capacity typically linked with deletion burden, an effect consistent with evidence for greater sensitivity among patients to environmental perturbations such as obstetric complications (McNeil et al, 2000) and low parent SES (Yeo et al, 2013b) ? Is it abnormal neural development and synaptic functioning, as suggested by the ontology of the GRS constituents (Walton et al, 2013)?…”

Section: Discussionmentioning

confidence: 91%

“…This analysis was performed on the full sample (N = 237) described in (Yeo et al, 2013b), some of whom did not have genetic data, allowing for the emergence of a maximally stable factor structure. Given the pattern of results obtained, a follow-up analysis examined “overall EF”, which was determined by simply averaging the three components emerging from the original PCA; this overall measure correlated with a simple unweighted aggregrate of all EF variables at r = .99.…”

Section: Methodsmentioning

confidence: 99%

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Genetic influences on cognitive endophenotypes in schizophrenia

Yeo¹,

Gangestad²,

Walton³

et al. 2014

Schizophrenia Research

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Background Cognitive deficits are prominent in schizophrenia and represent promising endophenotypes for genetic research. Methods The current study investigated the importance of two conceptually distinct genetic aggregates, one based on copy number variations (uncommon deletion burden), and one based on single nucleotide polymorphisms identified in recent risk studies (genetic risk score). The impact of these genetic factors, and their interaction, was examined on cognitive endophenotypes defined by principal component analysis (PCA) in a multi-center sample of 50 patients with schizophrenia and 86 controls. PCA was used to identify three different types of executive function (EF: planning, fluency, and inhibition), and in separate analyses, a measure general cognitive ability (GCA). Results Cognitive deficits were prominent among individuals with schizophrenia, but no group differences were evident for either genetic factor. Among patients the deletion burden measures predicted cognitive deficits across the three EF components and GCA. Further, an interaction was noted between the two genetic factors for both EF and GCA and the observed patterns of interaction suggested antagonistic epistasis. In general, the set of genetic interactions examined predicted a substantial portion of variance in these cognitive endophenotypes. Limitations Though adequately powered, our sample size is small for a genetic study. Conclusions These results draw attention to genetic interactions and the possibility that genetic influences on cognition differ in patients and controls.

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Section: Resultssupporting

confidence: 77%

Section: Discussionmentioning

confidence: 91%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Genetic influences on cognitive endophenotypes in schizophrenia

Yeo¹,

Gangestad²,

Walton³

et al. 2014

Schizophrenia Research

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“…The patients and the control group of subjects were matched based on age, gender, and race. They were also matched on the basis of their parental socio‐economic status (SES), which has been indicated as a more unbiased potential confounder associated with premorbid intelligence in previous works [Calvin et al, ; Saykin et al, ; Yeo et al, ]. However, both the WTAR and WASI IQ scores of patients were significantly lower than those of controls.…”

Section: Discussionmentioning

confidence: 99%

Connectivity‐based whole brain dual parcellation by group ICA reveals tract structures and decreased connectivity in schizophrenia

Calhoun

Jung

et al. 2015

Human Brain Mapping

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Mapping brain connectivity based on neuroimaging data is a promising new tool for understanding brain structure and function. In this methods paper, we demonstrate that group independent component analysis (GICA) can be used to perform a dual parcellation of the brain based on its connectivity matrix (cmICA). This dual parcellation consists of a set of spatially independent source maps, and a corresponding set of paired dual maps that define the connectivity of each source map to the brain. These dual maps are called the connectivity profiles of the source maps. Traditional analysis of connectivity matrices has been used previously for brain parcellation, but the present method provides additional information on the connectivity of these segmented regions. In this paper the whole brain structural connectivity matrices were calculated on a 5mm3 voxel scale from diffusion imaging data based on the probabilistic tractography method. The effect of the choice of the number of components (30 and 100) and their stability were examined. This method generated a set of spatially independent components that are consistent with the canonical brain tracts provided by previous anatomic descriptions, with the high order model yielding finer segmentations. The corpus-callosum example shows how this method leads to a robust parcellation of a brain structure based on its connectivity properties. We applied cmICA to study structural connectivity differences between a group of schizophrenia subjects and healthy controls. The connectivity profiles at both model orders showed similar regions with reduced connectivity in schizophrenia patients. These regions included forceps major, right inferior fronto-occipital fasciculus, uncinate fasciculus, thalamic radiation and corticospinal tract. This paper provides a novel unsupervised data-driven framework that summarizes the information in a large global connectivity matrix and tests for brain connectivity differences. It has the potential for capturing important brain changes related to disease in connectivity-based disorders.

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“…voxel-by-voxel comparison of fractional anisotropy versus tractbased spatial statistics [TBSS]), or whether or not differences in total brain size were accounted for (Giedd et al, 2012). An additional confound may be differences in family and genetic background, given that associations with global and regional brain structure have been reported for early developmental family environment (Buss et al, 2007;Rao et al, 2010;Yeo et al, 2013) and genetic makeup Thompson et al, 2001;Toga and Thompson 2005).…”

Section: Palabras Clavementioning

confidence: 99%

Sex differences in gray and white matter structure in age-matched unrelated males and females and opposite-sex siblings.

Braber

Ent

Stoffers

et al. 2013

Int. j. psychol. res.

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Apart from the general finding of larger global brain volumes in men, neuroimaging studies that compared brain structure between men and women have yielded some inconsistencies with regard to regional differences. One confound when comparing men and women may be differences in their genetic and or family background. A design that addresses such confounds compares brain structures between brothers and sisters, who share their genetic and family background.In the present study, we aimed to contribute to the existing literature on structural brain sex differences by comparing regional gray and white matter volume, using voxel based morphometry (VBM); and white matter microstructure, using tract-based spatial statistics (TBSS), between 40 unrelated males and females, and contrasting the results with those obtained in a group of 47 opposite-sex siblings, including 42 dizygotic opposite-sex (DOS) twin pairs.”Our results showed that men had larger global brain volumes as well as higher mean fractional anisotropy across the brain and showed regionally enlarged gray matter volume and higher fractional anisotropy in, or surrounding, subcortical structures (hypothalamus, thalamus, putamen and globus pallidus and rostral midbrain). Increased gray matter volume in women was restricted to areas of the cortex, including inferior temporal, insular, cingulate, precentral and frontal/prefrontal regions.These sex differences were generally consistent between the unrelated male-female pairs and the opposite-sex sibling pairs. Therefore, we conclude that these sex differences are not the result of confounding differences in genetic or family background and that the etiology of these sex differences merits further investigation.

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The impact of parent socio-economic status on executive functioning and cortical morphology in individuals with schizophrenia and healthy controls

Cited by 17 publications

References 42 publications

Genetic influences on cognitive endophenotypes in schizophrenia

Genetic influences on cognitive endophenotypes in schizophrenia

Connectivity‐based whole brain dual parcellation by group ICA reveals tract structures and decreased connectivity in schizophrenia

Sex differences in gray and white matter structure in age-matched unrelated males and females and opposite-sex siblings.

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