Common genetic variants and the association with cognitive phenotypes

To the best of our knowledge, at the time of publication our study was the largest to investigate how both polygenic scores for schizophrenia and cognition were associated with

a broad set of well-defined cognitive phenotypes in participants with psychotic disorders and healthy controls. Our cognitive phenotypes included the cognitive domains of verbal learning, verbal memory, processing speed, working memory, attentional control, and category fluency, as well as an estimate of premorbid intelligence (NART) and a cognitive composite score. We did not find the hypothesized negative association between the polygenic score for schizophrenia and any of the eight cognitive phenotypes in either population. Inspecting the plotted data there was no observable systematic trend in the data suggestive of this hypothesized association. These findings add to the pool of studies aimed at disentangling the genetic architecture of cognitive symptoms in schizophrenia and related psychotic disorders.

Modelling of genetic data has estimated that a large portion (one third) of schizophrenia risk variants is mediated through genes expressed in cognition-relevant pathways (Toulopoulou et al., 2019). Also, GWAS meta-analyses have consistently reported negative genetic correlations between schizophrenia and general cognitive ability (Davies et al., 2018; Lam et al., 2017; Sniekers et al., 2017; Trampush et al., 2017). Consequently, a primary hypothesis when investigating cognitive phenotypes using the schizophrenia polygenic score is to expect negative associations. Furthermore, our cognitive phenotypes were formed to align closely with those specified in the MCCB (Nuechterlein et al., 2008), which had previously been found to associate with the schizophrenia polygenic score in study with 127 patients with schizophrenia and 136 healthy controls (Nakahara et al., 2018). As our study included similar cognitive phenotypes, a larger clinical sample, and a larger sample of healthy controls, we concluded that our findings were a failed attempt at replication of these results. Our findings go against the proposed hypothesis that well-defined cognitive domains, such as those in the MCCB, would yield stronger associations to genetic risk variants for schizophrenia (Schaupp et al., 2018). Correcting for other clinical variables did not affect the results. All tests were also performed in a narrow schizophrenia spectrum sample only, without any change in the results.

The polygenic score for cognition was included in the study to investigate to what degree genetic variation related to cognition in the general population was associated with cognition

in our two study populations: patients with psychotic disorders and healthy controls. We observed a systematic trend towards more nominally significant associations in healthy controls, and a Bonferroni-corrected significant association for working memory in healthy controls only. Correcting for clinical variables associated with working memory performance did not change the results in participants with a psychotic disorder. Because our clinical and control population varied in size, we performed a statistical test accounting for variance and sample size, confirming a significant difference in the level of association between participants with psychosis and healthy controls. A significant (negative) association between cognitive performance and polygenic score for schizophrenia in healthy controls, but not in individuals with a psychotic disorder has previously been reported (Shafee et al., 2018). Although the difference in our study was evident using the polygenic score for cognition and not schizophrenia, we also conclude that the differing associations probably are due to environmental factors related to having a psychotic illness.

There are several possible explanations for the finding of no associations between normal schizophrenia risk variants and cognitive phenotypes. A study of general cognitive ability and polygenic factors in 3034 participants with schizophrenia also reported no association with the polygenic score for schizophrenia, but strong associations with polygenic scores for IQ and educational attainment (Richards et al., 2019). The authors of this study concluded that a portion of genetic variation in schizophrenia is explained by genetic factors commonly explaining variation in the general population (Richards et al., 2019). This interpretation suggests that, although schizophrenia is associated with lower level of cognitive performance, the variation of cognitive performance is explained by genetic factors shared with the general population, albeit the variation occurs around a lower mean.

A different but related explanation for the weak genetic signal in our study, and in related studies of cognitive phenotypes, concerns statistical power both for the current schizophrenia GWAS and the necessary sample size to enable detection of associations with phenotypes.

The GWAS used to calculate the polygenic score for schizophrenia in our study account for a mere 7% of the liability to schizophrenia, where only a portion of these variants are expected

to be relevant for cognitive impairments (Schizophrenia Working Group of the Psychiatric Genomics, 2014). Furthermore, schizophrenia is itself a very heterogeneous disorder, also when it comes to cognitive variation (Carruthers et al., 2019; Tan et al., 2021; Vaskinn et al., 2020). An interesting study by Bansal and colleagues revealed some genes with pleiotropic effects on both schizophrenia and educational attainment (a proxy for cognitive ability) (Bansal et al., 2018). The authors found that genetic variants associated for both high and low educational attainment were associated to schizophrenia risk in an independent sample.

Furthermore, they investigated how shared and non-shared genetic variation with bipolar disorder influenced the association, and found that a subtype of participants with schizophrenia who have ‘unique schizophrenia polygenic risk’ (i.e. do not have variants known to be shared with bipolar disorder) account for a clear negative association with both educational attainment and a measure of childhood IQ. The authors conclude that within the heterogeneous group of individuals with schizophrenia there is a genetically based subtype resembling bipolar disorder which is associated with higher intelligence (Bansal et al., 2018).

This finding, along with similar studies uncovering the overlapping relationship between bipolar disorder, schizophrenia, and cognitive ability (Smeland et al., 2019), suggests that the use of polygenic scores to study cognitive phenotypes may be less straight forward than has previously been assumed. The role of common genetic variants for schizophrenia in explaining cognitive variation in individuals with psychotic disorders may have been overestimated in previous research, but more importantly, studies detailing the specific genetic architecture are needed for more nuanced hypotheses to be formulated in future research. The study of pleiotropic effects of common genetic variants associated with schizophrenia show promise in addressing issues of the observed heterogeneity, particularly addressing the phenotypic and genotypic overlap between bipolar disorder and schizophrenia (Bansal et al., 2018;

Smeland et al., 2019).

The positive finding from Study I was the association between working memory and the PGSCOG in healthy controls only. This association withstood Bonferroni-correction and a statistical test showed that the association was stronger with statistical significance (at p=.05) in the healthy controls as compared to the sample of participants with a psychotic disorder.

We hypothesized stronger associations with cognitive phenotypes in healthy controls due to

morbid factors possibly overshadowing the association with genetic underpinnings in participants with a psychotic disorder. Similar findings have also been reported by others, albeit with a general cognitive ability measure and PGSSCZ (Shafee et al., 2018).

Endophenotypes are heritable, quantitative traits that are associated with the disorder, and lie closer to its pathophysiological underpinnings (Gottesman & Gould, 2003). Working memory has been proposed as a candidate endophenotype for schizophrenia (Horan et al., 2008; Park & Gooding, 2014), as well as for other disorders such as ADHD (Nigg et al., 2018).

Moreover, in a proposed model for cognitive impairments in psychotic disorders, working memory has been given a central role (Barch & Sheffield, 2014). This model builds on findings where deficits in working memory, episodic memory and cognitive control are all linked to neural circuitry in the dorsolateral prefrontal cortex. It proposes a that proactive cognitive control is impaired due to these deficits and results in reduced cognitive performance in widespread domains (Barch & Sheffield, 2014). Because of its putative role as an important illness mechanism, we suggest that our finding should encourage the use of working memory in future studies.