Abstract:Background
Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence.
Method
IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP… Show more
“…To our knowledge such studies have not yet been conducted. But proof of concept can be seen in two recent studies showing that genetic risks discovered in GWAS of schizophrenia are related to cognitive ability and cognitive decline (McIntosh et al 2013; Lencz et al 2014), although this finding remains contentious (van Scheltinga et al 2013). …”
Section: Genetic Risk Scores In Social Science Research: 3 Suggestionsmentioning
The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public-use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry.
“…To our knowledge such studies have not yet been conducted. But proof of concept can be seen in two recent studies showing that genetic risks discovered in GWAS of schizophrenia are related to cognitive ability and cognitive decline (McIntosh et al 2013; Lencz et al 2014), although this finding remains contentious (van Scheltinga et al 2013). …”
Section: Genetic Risk Scores In Social Science Research: 3 Suggestionsmentioning
The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public-use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry.
“…It has also been used to differentiate genetically, for example, schizophrenia and autism (Vorstman et al, 2013) or schizophrenia and intelligence (van Scheltinga et al, 2013). The schizophrenia PRS has been correlated with quantitative measures of psychosis in terms of symptoms scales (Derks et al, 2012) and neuroimaging measures (Walton et al, 2013).…”
This is the accepted version of the paper.This version of the publication may differ from the final published version. After the first GWAS studies in schizophrenia it soon became apparent there were no common variants that had a large influence on risk, but rather that there were thousands of variants of very small effect that together acted to increase or reduce Ferreira et al., 2008;Sklar et al., 2008;Schulze et al., 2009;Scott et al., 2009;Smith et al., 2009;Athanasiu et al., 2010;Tesli et al., 2011), the SYNE1 (Sklar et al., 2011Green et al., 2013) and the ODZ4 gene (Sklar et al., 2011).
Permanent repository linkThe question that arises is how to utilize the predictive power of GWAS
“…A further study by the same group [6] found no link between total deletion burden and intelligence as measured by the Wechsler Adult Intelligence Scale (WAIS). However, this may be due to the inclusion of all deletions regardless of Page 4 of 38 A c c e p t e d M a n u s c r i p t 4 frequency and could explain the discrepancy between their findings and the findings of Yeo et al [4].…”
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