Risk Factors for Schizophrenia

McGuffin, Peter; Gottesman,

doi:10.1056/nejm199907293410513

Cited by 42 publications

(8 citation statements)

References 4 publications

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“…Studies predict the genetic risk to be up to 80%, 1,2 but despite strenuous research efforts the genes and polymorphisms found to be associated with schizophrenia account for very little of the genetic risk. Environmental risk such as urbancity, 3 migrant status, 4 childhood maltreatment, 5 prenatal infections, 6 cannabis use 7 and maternal vitamin D deficiency 8 also contribute to schizophrenia susceptibility.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients

et al. 2014

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Recent studies suggest that genetic and environmental factors do not account for all the schizophrenia risk, and epigenetics also has a role in disease susceptibility. DNA methylation is a heritable epigenetic modification that can regulate gene expression. Genome-wide DNA methylation analysis was performed on post-mortem human brain tissue from 24 patients with schizophrenia and 24 unaffected controls. DNA methylation was assessed at over 485 000 CpG sites using the Illumina Infinium HumanMethylation450 Bead Chip. After adjusting for age and post-mortem interval, 4641 probes corresponding to 2929 unique genes were found to be differentially methylated. Of those genes, 1291 were located in a CpG island and 817 were in a promoter region. These include NOS1, AKT1, DTNBP1, DNMT1, PPP3CC and SOX10, which have previously been associated with schizophrenia. More than 100 of these genes overlap with a previous DNA methylation study of peripheral blood from schizophrenia patients in which 27 000 CpG sites were analysed. Unsupervised clustering analysis of the top 3000 most variable probes revealed two distinct groups with significantly more people with schizophrenia in cluster one compared with controls (P=1.74 × 10−4). The first cluster composed of 88% of patients with schizophrenia and only 12% controls, whereas the second cluster composed of 27% of patients with schizophrenia and 73% controls. These results strongly suggest that differential DNA methylation is important in schizophrenia etiology and add support for the use of DNA methylation profiles as a future prognostic indicator of schizophrenia.

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Section: Introductionmentioning

confidence: 99%

Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients

et al. 2014

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“…While neurogenesis and massive dendritic connectivity characterize the early postnatal period, the adolescent period is characterized by NMDA-dependent synaptic pruning and the final maturation of the GABA-glutamate circuitry in the prefrontal cortex (Bale et al, 2010). Schizophrenia is believed to be 70–80% heritable, but the risk for monozygotic twins is only 50%, suggesting that environmental factors may be as important as genetic risk factors (McGuffin and Gottesman, 1999). In the following review, we suggest that the role of environment on the development and course of schizophrenia are mediated by epigenetic factors including DNA promoter methylation/hydroxymethylation, histone expression and post-translational modifications, and the interaction between these factors and other environmentally responsive molecules such as microRNAs (miRNAs) and other non-coding RNAs.…”

Section: Introductionmentioning

confidence: 99%

Epigenetic mechanisms in schizophrenia

Shorter

Miller

2015

Progress in Biophysics and Molecular Biology

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Epigenetic modifications, including DNA methylation, histone modifications, and non-coding RNAs, have been implicated in a number of complex diseases. Schizophrenia and other major psychiatric and neurodevelopmental disorders are associated with abnormalities in multiple epigenetic mechanisms, resulting in altered gene expression during development and adulthood. Polymorphisms and copy number variants in schizophrenia risk genes contribute to the high heritability of the disease, but environmental factors that lead to epigenetic modifications may either reduce or exacerbate the expression of molecular and behavioral phenotypes associated with schizophrenia and related disorders. In the present paper, we will review the current understanding of molecular dysregulation in schizophrenia, including disruption of the dopamine, NMDA, and GABA signaling pathways, and discuss the role of epigenetic factors underlying disease pathology.

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“…Indeed, it has been suggested that genetic factors contribute to 80% of the risk of developing schizophrenia [3]. In addition, it is supported that the similar genetic backgrounds between patients with schizophrenia and their healthy siblings result in an approximately nine-fold higher risk for those siblings to develop schizophrenia than that of the general population [4-6].…”

Section: Introductionmentioning

confidence: 99%

Functional connectivity-based signatures of schizophrenia revealed by multiclass pattern analysis of resting-state fMRI from schizophrenic patients and their healthy siblings

Shen

Zhang

et al. 2013

BioMed Eng OnLine

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BackgroundRecently, a growing number of neuroimaging studies have begun to investigate the brains of schizophrenic patients and their healthy siblings to identify heritable biomarkers of this complex disorder. The objective of this study was to use multiclass pattern analysis to investigate the inheritable characters of schizophrenia at the individual level, by comparing whole-brain resting-state functional connectivity of patients with schizophrenia to their healthy siblings.MethodsTwenty-four schizophrenic patients, twenty-five healthy siblings and twenty-two matched healthy controls underwent the resting-state functional Magnetic Resonance Imaging (rs-fMRI) scanning. A linear support vector machine along with principal component analysis was used to solve the multi-classification problem. By reconstructing the functional connectivities with high discriminative power, three types of functional connectivity-based signatures were identified: (i) state connectivity patterns, which characterize the nature of disruption in the brain network of patients with schizophrenia; (ii) trait connectivity patterns, reflecting shared connectivities of dysfunction in patients with schizophrenia and their healthy siblings, thereby providing a possible neuroendophenotype and revealing the genetic vulnerability to develop schizophrenia; and (iii) compensatory connectivity patterns, which underlie special brain connectivities by which healthy siblings might compensate for an increased genetic risk for developing schizophrenia.ResultsOur multiclass pattern analysis achieved 62.0% accuracy via leave-one-out cross-validation (p < 0.001). The identified state patterns related to the default mode network, the executive control network and the cerebellum. For the trait patterns, functional connectivities between the cerebellum and the prefrontal lobe, the middle temporal gyrus, the thalamus and the middle temporal poles were identified. Connectivities among the right precuneus, the left middle temporal gyrus, the left angular and the left rectus, as well as connectivities between the cingulate cortex and the left rectus showed higher discriminative power in the compensatory patterns.ConclusionsBased on our experimental results, we saw some indication of differences in functional connectivity patterns in the healthy siblings of schizophrenic patients compared to other healthy individuals who have no relations with the patients. Our preliminary investigation suggested that the use of resting-state functional connectivities as classification features to discriminate among schizophrenic patients, their healthy siblings and healthy controls is meaningful.

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Risk Factors for Schizophrenia

Cited by 42 publications

References 4 publications

Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients

Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients

Epigenetic mechanisms in schizophrenia

Functional connectivity-based signatures of schizophrenia revealed by multiclass pattern analysis of resting-state fMRI from schizophrenic patients and their healthy siblings

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