Schizophrenia, "Just the Facts" What we know in 2008. 2. Epidemiology and etiology

University of Florida, 3706 Glin Circle, Tallahassee, FL 32309, United States.
Schizophrenia Research (Impact Factor: 3.92). 08/2008; 102(1-3):1-18. DOI: 10.1016/j.schres.2008.04.011
Source: PubMed


Although we have studied schizophrenia as a major disease entity over the past century, its causes and pathogenesis remain obscure. In this article, we critically review genetic and other epidemiological findings and discuss the insights they provide into the causes of schizophrenia. The annual incidence of schizophrenia averages 15 per 100,000, the point prevalence averages approximately 4.5 per population of 1000, and the risk of developing the illness over one's lifetime averages 0.7%. Schizophrenia runs in families and there are significant variations in the incidence of schizophrenia, with urbanicity, male gender, and a history of migration being associated with a higher risk for developing the illness. Genetic factors and gene-environment interactions together contribute over 80% of the liability for developing schizophrenia and a number of chromosomal regions and genes have been "linked" to the risk for developing the disease. Despite intensive research and spectacular advances in molecular biology, however, no single gene variation has been consistently associated with a greater likelihood of developing the illness and the precise nature of the genetic contribution remains obscure at this time. Environmental factors linked to a higher likelihood of developing schizophrenia include cannabis use, prenatal infection or malnutrition, perinatal complications, and a history of winter birth; the exact relevance or nature of these contributions is, however, unclear. How various genetic and environmental factors interact to cause schizophrenia and via which precise neurobiological mechanisms they mediate this effect is not understood. Etiological heterogeneity, complex patterns of gene-gene and gene-environment interaction, and inadequately elucidated schizophrenia pathophysiology are among the explanations invoked to explain our inadequate understanding of the etio-pathogenesis of schizophrenia. The ability to question some of our basic assumptions about the etiology and nature of schizophrenia and greater rigor in its study appear critical to improving our understanding about its causation.

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Available from: Matcheri Keshavan, Aug 07, 2014
    • "Schizophrenia (SZ) is a severe psychiatric brain disorder that affects about 1% of the population (Harrison, 1999; Insel, 2010; Ripke et al., 2013; Tandon et al., 2008). Symptoms of SZ suggest brain disturbances which affect many systems, and include hallucinations, delusions, disorganized thinking, loss of motivation, cognitive impairment and blunted emotional expression. "
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    ABSTRACT: A disturbance in the integration of information during mental processing has been implicated in schizophrenia, possibly due to faulty communication within and between brain regions. Graph theoretic measures allow quantification of functional brain networks. Functional networks are derived from correlations between time courses of brain regions. Group differences between SZ and control groups have been reported for functional network properties, but the potential of such measures to classify individual cases has been little explored. We tested whether the network measure of betweenness centrality could classify persons with schizophrenia and normal controls. Functional networks were constructed for 19 schizophrenic patients and 29 non-psychiatric controls based on resting state functional MRI scans. The betweenness centrality of each node, or fraction of shortest-paths that pass through it, was calculated in order to characterize the centrality of the different regions. The nodes with high betweenness centrality agreed well with hub nodes reported in previous studies of structural and functional networks. Using a linear support vector machine algorithm, the schizophrenia group was differentiated from non-psychiatric controls using the ten nodes with the highest betweenness centrality. The classification accuracy was around 80%, and stable against connectivity thresholding. Better performance was achieved when using the ranks as feature space as opposed to the actual values of betweenness centrality. Overall, our findings suggest that changes in functional hubs are associated with schizophrenia, reflecting a variation of the underlying functional network and neuronal communications. In addition, a specific network property, betweenness centrality, can classify persons with SZ with a high level of accuracy. Copyright © 2015. Published by Elsevier B.V.
    Schizophrenia Research 08/2015; 168(1). DOI:10.1016/j.schres.2015.08.011 · 3.92 Impact Factor
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    • "Genetic and gene–environment interactions account for over 80% susceptibility in the development of schizophrenia (Tandon et al., 2008). De-novo mutations contribute toward the constant replenishment of the pathogenic alleles involved in the disease development (Hatzimanolis et al., 2013). "
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    ABSTRACT: Neurodevelopmental and neuroimmunological genes critically regulate antipsychotic treatment outcome. We report genetic associations of antipsychotic response in 742 schizophrenia patients from Indian populations of Indo-European and Dravidian ancestry, segregated by disease severity. Meta-analysis comparing the two populations identified CCL2 [rs4795893: OR (95% CI) = 1.79 (1.27–2.52), P = 7.62 × 10−4; rs4586: OR (95% CI) = 1.74 (1.24–2.43), P = 1.13 × 10−3] and GRIA4 [rs2513265: OR (95% CI) = 0.53 (0.36–0.78), P = 1.44 × 10−3] in low severity group; and, ADCY2 [rs1544938: OR (95% CI) = 0.36 (0.19–0.65), P = 7.68 × 10−4] and NRG1 [rs13250975, OR (95% CI) = 0.42 (0.23–0.79), P = 6.81 × 10−3; rs17716295, OR (95% CI) = 1.78 (1.15–2.75), P = 8.71 × 10−3] in high severity group, with incomplete response toward antipsychotics. To our knowledge, this is the first study to identify genetic polymorphisms associated with the efficacy of antipsychotic treatment of schizophrenia patients from two major India populations.
    08/2015; DOI:10.1002/mgg3.169
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    • "Genetic and gene–environment interactions account for over 80% susceptibility in the development of schizophrenia (Tandon et al., 2008). De-novo mutations contribute toward the constant replenishment of the pathogenic alleles involved in the disease development (Hatzimanolis et al., 2013). "
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    ABSTRACT: Schizophrenia is a severe psychiatric disorder with lifetime prevalence of ~ 1% worldwide. A genotyping study was conducted using a custom panel of Illumina 1536 SNPs in 840 schizophrenia cases and 876 controls (351 patients and 385 controls from North India; and 436 patients, 401 controls and 143 familial samples with 53 probands containing 37 complete and 16 incomplete trios from South India). Meta-analysis of this population of Indo-European and Dravidian ancestry identified three strongly associated variants with schizophrenia: STT3A (rs548181, p = 1.47 × 10− 5), NRG1 (rs17603876, p = 8.66 × 10− 5) and GRM7 (rs3864075, p = 4.06 × 10− 3). Finally, a meta-analysis was conducted comparing our data with data from the Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ) that supported rs548181 (p = 1.39 × 10− 7). In addition, combined analysis of sporadic case–control association and a transmission disequilibrium test in familial samples from South Indian population identified three associations: rs1062613 (p = 3.12 × 10− 3), a functional promoter variant of HTR3A; rs6710782 (p = 3.50 × 10− 3), an intronic variant of ERBB4; and rs891903 (p = 1.05 × 10− 2), an intronic variant of EBF1. The results support the risk variants observed in the earlier published work and suggest a potential role of neurodevelopmental genes in the schizophrenia pathogenesis.
    Schizophrenia Research 01/2015; 162(1-3). DOI:10.1016/j.schres.2014.12.031 · 3.92 Impact Factor
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