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As an initial starting point, one should briefly define Schizophrenia and outline its key characteristics. It is well established that Schizophrenia is a highly devastating psychiatric syndrome which affects 1% of the world's population (Schultz & Andreason, 1999). It is well established that Schizophrenia is a severe, chronic and debilitating mental illness which typically develops in early adulthood or in adolescence (Breier et al, 1999). In addition, it has also been suggested that symptoms typically appear by the second and third decades of life of the affected individual (Meltzer et al, 1997). It is thought Schizophrenia is strongly 'familial' in the sense that it is hereditary, and risk of onset is increased about ten-fold in first degree relatives of schizophrenic individuals (Riley & Kendler, 2006). In this way, it has been postulated that potential genes conferring vulnerability to this illness have been identified (Kedzior & Martin-Iverson, 2007). Nonetheless, evidence also points to the fact that vulnerabilities may also exist in conjunction with environmental factors (Schultz & Andreason, 1999).

It should be evident that the term Schizophrenia (split mind) was introduced in 1911 by Paul Eugen Bleuler, a Swiss psychiatrist who characterized this condition by the splitting ('schizo') of cognition from of affect or emotional tone (Breier et al, 1999). Furthermore, it has also been postulated that Schizophrenia is normally characterized by heterogeneous clinical symptoms such as social withdrawal, disorganized behaviour, hallucinations, affective flattening and delusions (Wittchen et al, 2011). Similarly, among the sum of Schizophrenia symptoms one can identify somatic comorbidity (van Os & Kapur, 2009). This disorder is thought to resemble many other disorders given that complex, multi-factorial, and the effect of multiple genes is relatively small (Tsuang et al, 2001).

It is interesting to notice that although there have been considerable advances in psychosocial and pharmacological treatments, unravelling its etiology, as well as understanding its neurobiology still remains a major challenge (Ross et al, 2006). There is much heterogeneity among clinical population diagnosed with schizophrenia, specifically when it comes to understating of factors associated with onset, outcome and certain combinations of symptoms. Nonetheless, among heterogeneous groups one can still identify a number of symptoms which typically include peculiar thoughts and feelings, depression, inadvertent mood changes, sleeping problems and aggressiveness (Drake et al, 2007). In addition, it is thought that such symptoms can persist for months or even years (Tandom et al, 2009). Despite the wealth of research and scholarship on this disorder it should be evident that there is still an element of uncertainty surrounding the etiology of schizophrenia. Nonetheless, the general consensus within the empirical literature is that both environmental and genetic factors may play a pivotal role in the schizophrenia spectrum disorders (Rutter & Silberg, 2002).

Genetic Studies in Schizophrenia

It is thought that in terms of genetic architecture, Schizophrenia is composed by a several sources of genetic variation (Kim et al, 2011). This factor alone indicates that there is much complexity surrounding genetic effects of Schizophrenia. However, current research seems to indicate that the underlying genetic epistemology of schizophrenia can be organized into a coherent model (Gejman et al, 2011). It is interesting to notice that prominent genetic epidemiological research indicates that family history can constitute a significantly high risk (Sullivan et al, 2003). This pattern of findings is in line with twin studies which have suggested high heritability estimates. In this respect, it was found that heritability could range between 0.25-0.95, and results from meta-analysis show an aggregate of 0.81 (95%CI [Sullivan et al., 2003]). From this vantage point, one could argue that high heritability values equate to higher association between genetic traits and Schizophrenia. Nonetheless, it should be evident that results from genetic studies should not be taken as conclusive given that such results have also demonstrated low replicability. In this respect, it should be evident that among some of the most researched gene candidates such as DTNBP1 (dysbindin), NRG1 (neuregulin), RGS4 (G-protein signalling 4) provide only minor and subtle clues as to what is their involvement in the etiology of schizophrenia, as well as any issues relating to genetic risk factors (Allen et al, 2008).

It follows that, with the advent and development of genome-wide association studies (GWAS) it became possible to investigate single nucleotide polymorphisms (SNPs) which made it possible to identify rare and variant genomes which show a consistent association with Schizophrenic spectrum disorders (Purcell et al, 2009). In this way, studies on common variants (or SNPs) have shown that this factor is observed in at least 1% of the general population and are thought to impact upon the risk of development of schizophrenia, specifically on polygenic basis (Purcell et al, 2009). In this respect, a meta-analysis revealed that there are several consistently replicated loci and polymorphisms associated with the Schizophrenia risk (Ripke et al, 2013). In addition, it is also interesting to notice that in all studies included in the meta-analysis, Schizophrenia was associated with MHC (histocompatibility complex) on chromosome 6 (Ripke et al, 2011). However, these findings were target of much criticism due to lack of specificity and sampling bias issues. Nonetheless, from such findings one could infer that the role of MHC proteins in immune response pathways may be strongly associated with synaptic plasticity and neuronal development. Some neurodevelopmental studies have shown that these two processes have been strongly implicated in the etiology of schizophrenia (Shatz, 2009).

Gene-Environment Interactions in Schizophrenia

It could be argued that the gene-environment interactions paradigm is rooted in much of the work produced by Sir Francis Galton through his work entitled English Men of Science: Their Nature and Nurture (Galton, 1874). It should also be noted that the presupposition that genes interact with the environment also underpins the biopsychosocial model as proposed by Engel (1977). Similarly, the work of Zubin and Spring (1977) has postulated that there is an inextricable relationship between genes and the environment. In this way, through the work of the aforementioned authors it has become evident that mental health sciences can in fact bootstrap with neuroscience and neurobiology as means of investigating the etiology of Schizophrenia.

Validity and Reliability of Schizophrenia Diagnostic

When it comes to the very definition of Schizophrenia, there is a lack of consistency and persistent disagreement as to what how it should be defined (Carpenter, Strauss & Muleh, 1973). Disagreement over its definition has brought to light some important validity and reliability issues. This is particularly the case due to the fact that most Schizophrenia diagnosis lacked cross-national reference points, and seemed to be carried out non -bona fide experts (Carpenter, Strauss & Muleh, 1973). It is also interesting to notice that the definition of schizophrenia evolved through six editions of the Diagnostic and Statistical Manual of Mental Disorders, and emphasis in different symptoms over the period of 1952 to 2000. It is thought that the DSM-IV construct of Schizophrenia has been found to be clinically robust, and with a fair validity and high reliability. In this way, the DSM-IV stipulates 5 items as diagnostic criteria for Schizophrenia. These include (1) Delusions, (2) Hallucinations, (3) Disorganized speech, (4) Grossly disorganized or catatonic behaviour (5) Negative symptoms, i.e. affective flattering, alogia, or avolition (Coyle, 2006). It is also interesting to notice that throughout the literature there are considerable variations concerning the definition of Schizophrenia, as well as a broad variety of assumptions about what it should constitute (Gottesman & Shields, 1976). Previous validity and reliability criticisms of the diagnosis stem from the fact that such diagnosis lacked of standardised input information from patients, as well as competent experts who could assess diagnostic information collected from patients (Sawa & Snyder, 2003).

Adoption Studies and Schizophrenia

Early findings from adoption studies strongly suggested that offspring of schizophrenic parents can have an elevated risk for schizophrenic spectrum disorders (Erlenmeyer-Kimling et al, 1997). It was also found that when considering all psychiatric disorders, one can identify a higher frequency for offspring with high risk for Schizophrenia compared to offspring at low risk (Tienari et al, 2000; Schubert & McNeil, 2003). However, one of the weaknesses of the aforementioned study is the fact that rearing parents of selected twin pairs were in fact also the biological parents of the participants in the studies. For this reason, it was virtually impossible to differentiate between genetic and environmental risks involved in the study. Research investigating genotype-environment interaction has also identified a number of variables which could play a key role in development Schizophrenia. In this respect, Whalberg et al (2004) argued that communication patterns from both biological and adoptive parents can influence growing children, and may in fact determine the severity with which this disorder express itself.

One should also note that among the early reports on adoption studies relating to Schizophrenia the one presented by Heston (1966) reported the case of offspring from severely schizophrenic mothers when removed from them within a week of birth still grew up to have schizophrenia. This is thought to have happened at the same rate as those children reared by their schizophrenic mothers. Further evidence in support of Heston's thesis was provided by Wender, Rosenthal and Kety (1968). They conducted a series of studies using Danish adopted twin pairs, and put beyond any doubt any uncertainties about the usefulness of twin and adoption studies. It is also interesting to notice that the Danish adoption studies conducted by Wender, Rosenthal and Kety also helped to establish twin studies as a robust and useful strategy for studying schizophrenia. In addition, it also acted as further incentive for neurochemists and pharmacologists to take schizophrenia disorder seriously. Furthermore, their studies also determined that the vast array of alleged environmental factors were neither sufficient nor necessary for the occurrence of schizophrenia. It is also interesting to notice that such studies acted as a catalyst for the re-awakened interest in studies relating to Schizophrenia spectrum disorders. More importantly, adoption strategies assume that genotypes are constant and by varying the postnatal rearing environment allow for confirmation or refutation of hypothesis concerning the environment. In general, from the aforementioned studies one could infer that there is a genotype-environment interaction which seems to predict mental disorders of adoptees. Furthermore, this interaction appears to be a more significant predictor of adoptee mental illness than genetic high risk (Whalberg et al, 2004).

Twin Studies and Schizophrenia

In contrast to adoption studies, classical comparison of Monozygotic (MZ) and Dizygotic (DZ) twin studies assume that within-family environmental factors are controlled by gene dosage. In this way gene dosage permits the refutation or confirmation of genetic hypothesis. Over the past two decades, twin studies have played a pivotal role in establishing a genetic contribution to the etiology of Schizophrenia (Gottesman, 1991). More specifically, a number of studies (see Klaning, 1996; Cannon et al., 1998; Cardno et al, 1999) have been particularly vital for understanding the genetic contribution to the etiology of schizophrenia, given that they yielded a concordance rate of 41-65% in monozygotic (MZ) twins and 0-28% in dizygotic (DZ) twins. These studies have also found in both MZ and DZ pairs heritability estimates of 80-85%. Similarly, meta-analytic results from 12 twin studies of schizophrenia revealed that this disorder is marked by very complex traits that may result from environmental and genetic etiological influences (Sullivan, Kendler & Neale, 2003).

However, there are some issues using twin sampling methods for studying mental illnesses. For instance, it has been argued that twins usually born prematurely, and this factor makes them a deviant sample. Another objection with twin studies is the fact that Monozygotic Twins (MZ) have unique psychological characteristics, and this factor may sometimes contribute to increased concordance rates (Rosenthal, 1962). Despite being subjected to some criticism and considerable academic scrutiny, twin studies of schizophrenia have withstood the test of time and are currently placed within a much broader context whereby such studies only provide converging evidence to genetic studies rather than bearing the burden of advancing the research in genetics per se.

Probabilistic Epigenesis: An Alternative Model for Schizophrenia?

As discussed in the paper, a wide range of models for Schizophrenia are grounded on a biopsychosocial perspective which seem to assume that neuropsychological and genetic factors play core hierarchical roles by conferring certain vulnerabilities to development of Schizophrenia. In contrast to the biopsychosocial model, the probabilistic epigenesis approach postulates that phenotypic traits such as behaviour and symptoms associated with Schizophrenia can be explained through the reciprocity between different levels of reciprocity of influences between developmental levels (neuro-genetic activity, behaviour, social, physical, and cultural influences) and gene-environment interaction (Gottlieb, 2007). Should one adopt this model to understand Schizophrenia one could argue that it is precisely this interaction that acts as primary catalyst in the realization of all phenotypes associated with the disorder. In addition, one it has been postulated that there might also be an element of adaptive self-organization whereby randomness may act as an important source of biological organisation in addition to deterministic genetic factors (Atlan, 1979).

In this way, one can only begin to contemplate the complexity surrounding the aetiology of Schizophrenia, given that the aforementioned approaches advocate a multifaceted, dynamic and fluid approach to understanding this disorder. Moreover, both self-organisation and probabilistic approaches favour a point of view which could account for the complexity surrounding Schizophrenia, as well as understanding the both diversity and different factors which contribute for the development of this disorder. In this respect, some have postulated that probabilistic epigenetic theoretical models are the best for taking into account complexity and diversity of determinant factors (Sullivan, Kendler & Neale, 2003). Furthermore, it also asserts that all the different participatory levels (neuro-genetic activity, behaviour, social, physical, and cultural influences) interact with each other through both unidirectional and bidirectional forms. Given that interactions between all of the aforementioned levels of analysis is by no means perfect, it is thought that the introduction of a probabilistic element provides useful insight into understanding systems development and evolution at a structural and functional level (Gottlieb, 2007). In this way, this model permits the examination of Schizophrenia by implicating the different known determinants at each level of analysis. In addition, the probabilistic model also allows for further understanding of how interactions between levels of analysis can lead to very specific effects due to their bidirectional nature (Gottlieb, 2007). Thus, whether extrinsically derived or intrinsically stimulated, activity generated by the different levels of analysis may play a significant role in the developmental process of Schizophrenia. Therefore, one could argue that in order to gain further and more useful insights into the understanding the nature of Schizophrenia, one must take into account a multidisciplinary approach which integrates a variety of viewpoints into a probabilistic model. Such models may in fact represent a more accurate representation of diversity and complexity surrounding the aetiology of Schizophrenia.


A considerable amount of research and scholarship has devoted their efforts to provide some useful insights into understanding correlations between genotype and phenotype in Schizophrenia (Bakker et al, 2006; Bakker et al, 2007; Burdick et al, 2007; Esslinger et al, 2009; Stefansson, et al, 2009). It should also be evident that there is still an element of uncertainty surrounding the etiology of schizophrenia. In this respect, it could be argued that one of the biggest challenges for psychiatrists, clinicians and researchers in general is to fully understanding the ways in which genetic and environmental effects may actually converge on molecular disease pathways, as means of giving rise to divergent symptoms associated with Schizophrenia.

Nonetheless, it would appear the genetic-environment interactions have proved to be very influential on etiological studies connected with schizophrenia research. But perhaps, taking behavioural genetics one step further would be to examine the contributions offered by probabilistic epigenesis model. This model could provide useful insights into understanding the etiology of Schizophrenia given that it takes into account the multifaceted, diverse and complex factors implicated in this disorder.

Recommendations for Future

So far research results and current theoretical models should not be taken as final given that much scholarship is still needed until we fully understand the intricacies surrounding gene-environment interactions implicated in the etiology of schizophrenia. In this way, future studies should carefully select candidate variables through experimental manipulation in order to test the validity of probabilistic epigenesis model. Furthermore, development of mathematical modelling through neural networks could also prove to be useful for understanding Schizophrenia. Future research should also focus on the possibility of adopting an ever more multidisciplinary approach to studying the nature of this disorder. The investigation of Schizophrenia through neural networks and probabilistic models will certainly imply some fundamental changes for clinical practice. In this way, it is hoped that the present paper will act as catalyst and stimulate further debate, theory and practice within this area.


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Author:Tikovsky, Emil
Publication:Journal of Social and Psychological Sciences
Article Type:Report
Date:Jan 1, 2017

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