Cognitive dysfunction is common in schizophrenia (Meier et al., Reference Meier, Caspi, Reichenberg, Keefe, Fisher, Harrington and Moffitt2014; Reichenberg & Harvey, Reference Reichenberg and Harvey2007) with the variation in social, functional and occupational outcomes being significantly attributable to cognitive heterogeneity (Green, Reference Green2006; Green, Kern, Braff, & Mintz, Reference Green, Kern, Braff and Mintz2000). Cognitive subtypes have been identified based on differences between premorbid and post-illness onset measures of intellectual function. Most studies describe three cognitive trajectories: below average premorbid and post-onset cognition indicating long-standing impairment (compromised); at least average premorbid cognition but cognitive scores after illness onset that suggest deterioration (deteriorated); and at least average premorbid and post-onset cognition indicating preserved cognition (preserved) (Ammari et al., Reference Ammari, Heinrichs, Pinnock, Miles, Muharib and McDermid Vaz2014; Badcock, Dragović, Waters, & Jablensky, Reference Badcock, Dragović, Waters and Jablensky2005; Czepielewski, Wang, Gama, & Barch, Reference Czepielewski, Wang, Gama and Barch2017; Dickinson et al., Reference Dickinson, Zaidman, Giangrande, Eisenberg, Gregory and Berman2020; Kremen, Seidman, Faraone, & Tsuang, Reference Kremen, Seidman, Faraone and Tsuang2008; Leeson et al., Reference Leeson, Sharma, Harrison, Ron, Barnes and Joyce2011; Mercado, Johannesen, & Bell, Reference Mercado, Johannesen and Bell2011; Weickert et al., Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000; Wells et al., Reference Wells, Swaminathan, Sundram, Weinberg, Bruggemann, Jacomb and Weickert2015; Woodward & Heckers, Reference Woodward and Heckers2015). We previously showed that these cognitive subtypes are present at psychosis onset in two first-episode schizophrenia-spectrum cohorts suggesting that when cognitive deterioration is present, it occurs early in the illness (Joyce, Hutton, Mutsatsa, & Barnes, Reference Joyce, Hutton, Mutsatsa and Barnes2005; Leeson et al., Reference Leeson, Sharma, Harrison, Ron, Barnes and Joyce2011).
There are several outstanding questions regarding the validity of these cognitive subtypes. One is whether they reflect different neurobiological trajectories (Weickert et al., Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000). Woodward and Heckers (Reference Woodward and Heckers2015) observed smaller MRI intra-cranial volumes (ICV) in a compromised subtype compared with healthy volunteers. As ICV is a proxy for premorbid brain volume, it was hypothesised that this is a neurodevelopmental subtype of schizophrenia with ‘cerebral hypoplasia’. They distinguished this from a deteriorated cognitive subgroup which showed normal ICV but smaller total brain volume (TBV) which is indicative of neurodegeneration. Supporting these findings, a different study found that neurodevelopmental and neurodegenerative MRI profiles mapped onto their conjugate cognitive subtypes (Czepielewski et al., Reference Czepielewski, Wang, Gama and Barch2017). However, Van Rheenen et al. (Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018) did not find evidence for a neurodevelopmental subtype with reduced ICV. Instead, they found reduced TBVs indicative of brain shrinkage across all subtypes which was regionally more pronounced in the compromised group. This was suggestive of a continuum of progressive brain neurodegeneration across all subgroups in association with the degree of cognitive impairment. Another neurobiological mechanism which may differentiate cognitive subgroups concerns the effect of innate inflammatory responses. Several studies have shown that elevated C-reactive protein (CRP), a marker of systemic low-grade inflammation, is associated with cognitive impairment in adults with schizophrenia (Bulzacka et al., Reference Bulzacka, Boyer, Schürhoff, Godin, Berna, Brunel and Fond2016; Dickerson, Stallings, Origoni, Boronow, & Yolken, Reference Dickerson, Stallings, Origoni, Boronow and Yolken2007; Johnsen et al., Reference Johnsen, Fathian, Kroken, Steen, Jørgensen, Gjestad and Løberg2016; Misiak et al., Reference Misiak, Stańczykiewicz, Kotowicz, Rybakowski, Samochowiec and Frydecka2018). Other inflammatory markers, IL-6, IL-1 receptor antagonist (IL1RA), and tumour necrosis factor-alpha (TNF-a) have also been implicated but less consistently so (Frydecka et al., Reference Frydecka, Misiak, Pawlak-Adamska, Karabon, Tomkiewicz, Sedlaczek and Beszłej2015; Misiak et al., Reference Misiak, Stańczykiewicz, Kotowicz, Rybakowski, Samochowiec and Frydecka2018). Elevated childhood IL-6 levels have been shown to increase the risk of psychotic symptoms in young adults (Khandaker, Pearson, Zammit, Lewis, & Jones, Reference Khandaker, Pearson, Zammit, Lewis and Jones2014) and CRP levels to be associated with subclinical psychotic symptoms in adolescents (Khandaker et al., Reference Khandaker, Stochl, Zammit, Lewis, Dantzer and Jones2021). Furthermore, a higher erythrocyte sedimentation rate (ESR), another inflammatory marker, was associated with lower premorbid IQ and higher risk for schizophrenia in army recruits (Kappelmann et al., Reference Kappelmann, Khandaker, Dal, Stochl, Kosidou, Jones and Karlsson2019). These findings provide tentative evidence for the hypothesis of Miller and Goldsmith (Reference Miller and Goldsmith2019) that genetic and environmental factors encountered during development lead to peripheral and central inflammation which influences premorbid cognitive function and risk of schizophrenia.
A second question regarding the cognitive subtypes is whether patients with the ‘preserved’ subtype have intact cognitive function (Carruthers, Van Rheenen, Gurvich, Sumner, & Rossell, Reference Carruthers, Van Rheenen, Gurvich, Sumner and Rossell2019). This is important because it challenges the commonly held notion that cognitive impairment is a core attribute of schizophrenia. For example, one study comparing high IQ patients and closely matched controls found no statistical difference between the two groups on a range of neuropsychological measures suggesting that cognitive function may not always be affected by the neuropathological process thought to underlie schizophrenia (MacCabe et al., Reference MacCabe, Brébion, Reichenberg, Ganguly, McKenna, Murray and David2012). However another study of schizophrenia patients and healthy controls matched for IQ, found that subtest index scores differed so that patients had worse processing speed task performance, but better verbal comprehension and perceptual organisation, a pattern present even in a high IQ subgroup (Wilk et al., Reference Wilk, Gold, McMahon, Humber, Iannone and Buchanan2005). This question is also relevant for the interpretation of MRI studies in the context of cognitive subtypes. For example, both Woodward and Heckers (Reference Woodward and Heckers2015) and Van Rheenen et al. (Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018) found that their preserved cognitive subgroups showed a degree of brain shrinkage which suggested to them that this group might not be neuropsychologically intact.
We aimed to address these questions by applying a data-driven approach to classify the three IQ trajectory-based subtypes externally validated in previous studies (Dickinson et al., Reference Dickinson, Zaidman, Giangrande, Eisenberg, Gregory and Berman2020); Weickert et al., Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000), to cognitive data from a new cohort of patients who had recently developed a schizophrenia-spectrum disorder. In each of the three subtypes, we measured TBV, grey matter volumes and cortical thickness and the inflammatory markers previously associated with cognition in schizophrenia: CRP, Il-6, IL1RA and TNF alpha. We also included a healthy control group to examine further the notion of intact cognition pertaining to the preserved subtype. We hypothesised that a compromised group would have smaller ICV than preserved and deteriorated groups. In comparison with a preserved group, the deteriorated group was expected to show smaller TBV after adjusting for ICV. Examining differential inflammatory marker profiles between groups was exploratory.
To address the research questions, we performed a secondary analysis of the BeneMin clinical trial data (Deakin et al., Reference Deakin, Suckling, Barnes, Byrne, Chaudhry and Dazzan2018). BeneMin was designed to test whether the anti-inflammatory drug minocycline improves psychotic symptoms and cognition in patients with early-phase schizophrenia spectrum disorder, recruited within 5 years of onset. CRP, proinflammatory cytokines and MRI brain volume were measured as potential biomarkers of effect. We restricted the analysis to baseline data before allocation of patients to the investigational drug or placebo.
Schizophrenia spectrum disorder: Patients were recruited from 11 UK mental health trusts as part of a double-blind randomised-controlled trial (BeneMIn) assessing the potential benefit of minocycline on negative symptoms in early-phase psychosis (Deakin et al., Reference Deakin, Suckling, Barnes, Byrne, Chaudhry and Dazzan2018). Ethical approval was obtained from the North West Research Ethics Committee (ref.11/NW/0218). All participants met the criteria for schizophrenia spectrum disorder using the Mini-International Neuropsychiatric Interview (MINI) and were aged 16-35 years at the onset of psychosis, currently receiving care from UK NHS Early Intervention Services (EIS) and within the first 5 years of their first presentation to mental health services. All had at least mild persisting psychotic symptoms, defined by a score >2 on the delusions, hallucinations, suspiciousness or conceptual disorganisation items on the Positive and Negative Syndrome Scale (PANSS) (Kay, Fiszbein, & Opler, Reference Kay, Fiszbein and Opler1987). Exclusion criteria were alcohol or substance abuse seriously affecting function; inability to communicate fluently in English; estimated WTAR premorbid IQ of <70; and current suicide or violence risk. Participants were required to be taking stable antipsychotic treatment from a mental health care team (Lisiecka et al., Reference Lisiecka, Suckling, Barnes, Chaudhry, Dazzan, Husain and Deakin2015). Psychotic symptoms were assessed with the PANSS (Kay et al., Reference Kay, Fiszbein and Opler1987). Depression was assessed with The Calgary Depression Scale for Schizophrenia (CDSS) (Addington, Addington, & Schissel, Reference Addington, Addington and Schissel1990) and social function with the self-report Social Function Scale (SFS) (Birchwood, Smith, Cochrane, Wetton, & Copestake, Reference Birchwood, Smith, Cochrane, Wetton and Copestake1990) and observer-rated Global Assessment of Functioning (GAF) scale. Lifetime cannabis use was assessed using a self-report measure and current BMI was calculated as both can effect inflammatory measures (Mastinu et al., Reference Mastinu, Premoli, Ferrari-Toninelli, Tambaro, Maccarinelli, Memo and Bonini2018; Visser, Bouter, McQuillan, Wener, & Harris, Reference Visser, Bouter, McQuillan, Wener and Harris1999).
Out of 207 participants in the BeneMin trial, 166 were included in this study based on the completion of cognitive tests. All measures and the MRI scans were performed before allocation to placebo or minocycline conditions (Deakin et al., Reference Deakin, Suckling, Barnes, Byrne, Chaudhry and Dazzan2018).
To examine the question of intact cognition in the preserved subtype, we used equivalent age-matched neuropsychological data from 82 healthy volunteers who took part in the West London First-Episode Psychosis Study and were recruited by advertising in local job centres, schools and hospitals. Exclusion criteria were a personal history of psychiatric illness or a history of such illness in any first-degree relatives, previous head injury, a neurological or endocrine disorder known to affect brain function, and drug or alcohol abuse (Leeson, Barnes, Hutton, Ron, and Joyce, Reference Leeson, Barnes, Hutton, Ron and Joyce2009)
Of those with complete cognitive data, 141 completed MRI scans, nine of these were excluded due to motion artefacts and two due to data acquisition errors, leaving data for 130 scans. Inflammatory markers were available for 138 participants with complete cognitive assessments after exclusions. Five did not complete a blood-draw and those with hsCRP > 10 were excluded (n = 10), as this is thought to reflect the presence of an acute infection rather than systemic inflammation (Osimo, Baxter, Lewis, Jones, & Khandaker, Reference Osimo, Baxter, Lewis, Jones and Khandaker2019). The remaining exclusions were due to outliers (n = 13).
Premorbid IQ was estimated using the Wechsler Test of Adult Reading (WTAR) which is co-normed against the WAIS-III. Current IQ was estimated with a short form of the WAIS-III (Blyler, Gold, Iannone, & Buchanan, Reference Blyler, Gold, Iannone and Buchanan2000), developed for use in schizophrenia. This uses 4 subtests: Digit Symbol, Information, Block Design and Arithmetic for the calculation of pro-rated full-scale IQ. The Rey Auditory Verbal Learning Test (AVLT) (Lezak, Howieson, Loring, Hannay, & Fischer, Reference Lezak, Howieson, Loring, Hannay and Fischer2004) was used to assess verbal learning and memory in which participants were read a list of 15 nouns and asked to recall as many as possible immediately afterwards on each of five trials.
3 T MRI scans were performed at each of the study sites. The MRI sequences were coordinated across imaging centres by author JS based on the previous NeuroPsygGrid multi-centre validation and reliability study (Suckling et al., Reference Suckling, Barnes, Job, Brennan, Lymer, Dazzan and Lawrie2012) comprising three-dimensional T1-weighted magnetisation-prepared rapid gradient-echo (MPRAGE/SPGR) as described in Deakin et al. (Reference Deakin, Suckling, Barnes, Byrne, Chaudhry and Dazzan2018). Whole-brain segmentation and cortical reconstruction were carried out by author AG using FreeSurfer v5.3.0 (Massachusetts General Hospital, Harvard Medical School; http://surfer.nmr.mgh.harvard.edu). The fully automated procedure used has been described by Fischl et al. (Reference Fischl, Salat, Busa, Albert, Dieterich, Haselgrove and Dale2002). All volumes and thickness measures were visually inspected after the segmentation pipeline and no manual edits were necessary. In contrast to the ‘cortex’ measure, ‘total grey volume’ also includes subcortical and cerebellum volumes. Participant sex and age, and MRI acquisition centre were included as covariates in between-group analyses.
Measures of inflammation
Blood samples were collected in a 9 ml ethylenediamine tetraacetic acid tube and spun in a centrifuge, within four hours of collection, for 15 min at 20 degrees Celsius and 2000 g. Measurements were of high-sensitivity C-reactive protein (hs-CRP), Interleukin 1-receptor antagonist (IL-1RA), Interleukin 6 (IL-6), and Tumour Necrosis Factor-alpha (TNF-α). Details of the assays can be located in the online Supplementary materials.
The three cognitive subgroups were classified with data-driven cluster analysis according to the method of Weickert et al. (Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000). As the WTAR is a reading test it can be inaccurate for estimating IQ in dyslexia or when English is not the first language, we excluded participants with a WTAR IQ of more than 10 IQ points below WAIS IQ for both the patient group (n = 5) and healthy controls (n = 35). Estimated premorbid IQ (WTAR score) and current WAIS IQ score were entered into a non-hierarchical iterative k-means cluster analysis with the number of clusters set to ‘3’, to create three clusters with the greatest separation after allowing for iterations.
We used linear discriminant function analysis (DFA) on the three-cluster solution to ascertain the relative accuracy of the IQ variables in predicting cluster membership. Homogeneity of variance was confirmed using Box's M test (p = 0.124). To assess the reliability of the classification model, a ‘leave-one-out’ classification was performed.
The resulting clusters were analysed using one-way analysis of variance (ANOVA) or analysis of covariance (ANCOVA) for normally distributed continuous cognitive measures. χ2 was used for demographic and categorical data. Logarithm transformations were used on non-normally distributed continuous data. Z score transformations of patient scaled scores were calculated in relation to the mean and standard deviation of healthy control scaled scores on each of the IQ subtests.
Due to differences between the healthy volunteer and patient groups, sex was entered as a covariate in all cognitive analyses comparing patients with healthy controls. For the imaging analysis, sex, age and scan site were controlled for when comparing groups. BMI and lifetime cannabis use were controlled for as potential confounders in the analysis of inflammation markers (Mastinu et al., Reference Mastinu, Premoli, Ferrari-Toninelli, Tambaro, Maccarinelli, Memo and Bonini2018; Visser et al., Reference Visser, Bouter, McQuillan, Wener and Harris1999).
Raw p values are reported for ANOVAs. To control for multiple testing, main effects were adjusted for false discovery rate (FDR) using the Benjamini–Hochberg method (Benjamini & Hochberg, Reference Benjamini and Hochberg1995). Cognitive, clinical, functioning, imaging and inflammation variables were tested separately. For main effects significant after this adjustment (p = <0.05), post-hoc between-group comparisons were made using Bonferonni corrections (Bland & Altman, Reference Bland and Altman1995). Cohen's effect sizes (ES) were calculated (Cohen, Reference Cohen1998).
Demographics (Table 1)
There was no significant difference in age between the patient and healthy control groups [t (242) = 3.72, p = 0.06]. There were more males in the patient group [χ2 (1) = 18.19, p = <0.001] and the control group had more years of education [t (242) = −3.99, p = <0.001]. The patient sample had moderate symptoms and difficulty in social functioning, as indicated by mean PANSS total [67.62 (14.48)] and GAF [55.81 (10.65)] scores (see online Supplementary Table S1). There were no differences between cognitive subtype groups in symptom scores and social function (see online Supplementary Table S2).
HC, Healthy Controls; PIQ, Preserved IQ; DIQ, Deteriorated IQ; CIQ, Compromised IQ.
a following Bonferroni correction.
Cognition (Table 2)
K-means cluster analysis with groups set to ‘3’ showed good cluster stability with few iterations. DFA (χ2 (4) = 102.85, p < 0.001, canonical correlation = 0.921): showed high correct classification rates (96.4%). with the overall classification accuracy remaining high in the leave-one-out analysis (94.5%) (See online Supplementary Table S3). 35% of patients were classified as putatively preserved (PIQ), 38% as deteriorated (DIQ) and 27% as compromised (CIQ). The estimated premorbid IQ of the healthy controls (HC), PIQ and DIQ groups was in the average range whereas that of the CIQ group was in the low average range. Figure 1 shows that the estimated premorbid IQ of the PIQ group was higher than the HC group and that PIQ and HC estimated current IQ was equivalent, with a small but significant fall in IQ in the PIQ group [t (56) = 2.99, p = 0.004]; the DIQ group had a significant fall in mean IQ into the low average range [t (60) = 12.49, p < 0.001]; and the CIQ group also showed significant deterioration into the below-average range [t (42) = 6.95. p < 0.001].
a Sex was entered as a covariate for comparisons with healthy controls. *indicates medium effect size, ** indicates large effect size. HC, healthy controls; PIQ, preserved IQ group; DIQ, deteriorated IQ group; CIQ, compromised IQ group; FSIQ, full-scale IQ; AVLT, Auditory Verbal Learning Test. Bold font denotes significance following FDR correction. Scaled scores reported.
In general, the PIQ group performed better than the DIQ group on all domains who in turn performed better or equivalent to the CIQ group. When compared with HCs, the PIQ group performed significantly better on block design, information and arithmetic tests subtests but significantly worse on the digit symbol test [ES 0.7]. Verbal learning was also significantly worse [ES 0.7] in PIQ than HCs (Table 2).
Figure 2 shows the standardised z-scores of the patient groups for each IQ subtest in relation to HC performance; 95% CIs for HCs – Digit Symbol: [8.74–9.74]; Arithmetic: [11.88–13.09]; Block Design: [9.73–10.84]; Information: [10.85–11.93]. In general, the PIQ group performed better than the DIQ group on all domains who in turn performed better or equivalent to the CIQ group. When compared with HCs, the PIQ group performed significantly better on block design, information and arithmetic tests subtests but significantly worse on the digit symbol test [ES 0.7]. Verbal learning was also significantly worse [ES 0.7] in PIQ than HCs (Table 2).
Neuroimaging (Table 3)
Intracranial volume (ICV) was significantly larger in the PIQ group than the CIQ group. Absolute total brain volume (aTBV) was significantly smaller in the CIQ group than both the DIQ and PIQ groups. When controlling for ICV, differences were not found between groups on measures of TBV, cortical volume, or grey matter volume. There was no difference between groups on a measure of mean cortical thickness.
PIQ, Preserved IQ; DIQ, Deteriorated IQ; CIQ, Compromised IQ.
*indicates medium effect size, ** indicates large effect size.
1 After Bonferonni correction.
2 Controlling for age, sex and site.
3 Controlling for ICV, age, sex and site.
Inflammatory markers (Tables 3 and 4)
Between-group comparisons were performed on log10 transformed measures, adjusting for age, sex, BMI and cannabis use. There was a significant difference in hsCRP levels. Post-hoc tests showed that the PIQ group had significantly lower hsCRP levels than the CIQ patients, which remained after correction for multiple comparisons. There were no between-group differences on any of the other inflammation measures.
PIQ, Preserved IQ: DIQ, Deteriorated IQ: CIQ, Compromised IQ.
*indicates medium effect size
1 Controlling for age, sex, BMI and cannabis smoking status. Mean raw hsCRP scores [s.d.]: PIQ group = 1.94 [2.18]; DIQ group = 2.84 [2.70]; CIQ group = 3.18 [2.36].
In this study, we replicated our previous findings of three cognitive subtypes in early-phase schizophrenia-spectrum disorder using a data-driven approach in a new cohort of patients (Joyce et al., Reference Joyce, Hutton, Mutsatsa and Barnes2005). These corresponded to preserved (PIQ, normal estimated premorbid and current IQ), deteriorated (DIQ: normal estimated premorbid and low current IQ) and compromised (CIQ: low premorbid and current IQ) subgroups (Weickert et al., Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000). We examined the relationship between cognitive subtype and MRI-derived ICV, brain volume and cortical thickness to assess whether these subtypes reflect differences in neurobiological trajectories (Weickert et al., Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000). The compromised subgroup had a significantly smaller aTBV than both the preserved and deteriorated subgroups, indicative of a smaller brain. The compromised group also had a smaller ICV compared with the preserved group. When ICV was entered as a covariate in the analysis, the difference in aTBV in the compromised group was no longer evident. As ICV is a proxy for premorbid brain volume, this suggests that smaller brain size in the compromised group was neurodevelopmental. Intracranial and brain volume increase in parallel during childhood. From early adolescence, ICV is static but brain volume begins to decrease as a reflection of normal brain maturation. Abnormally reduced brain volume is thought to reflect neurodegenerative processes whereas reduced ICV indicates an early neurodevelopmental deficit (Woodward & Heckers, Reference Woodward and Heckers2015). Therefore our finding of smaller brain size in the compromised group may reflect premorbid intellectual function linked to early brain development. This finding supports that of previous studies comparing cognitive subgroups with healthy controls showing reduced ICV only in the compromised subgroups (Czepielewski et al., Reference Czepielewski, Wang, Gama and Barch2017; Woodward & Heckers, Reference Woodward and Heckers2015). These studies also found evidence for neurodegeneration in patients with a deteriorated cognitive trajectory. Compared to controls, TBV was reduced but ICV was normal suggesting that brain shrinkage had occurred after maximal brain growth. We were unable to find evidence of this in relation to cognitive decline in the deteriorated subgroup, which would have been evident with a smaller brain volume adjusted for ICV compared with the preserved subgroup (Woodward & Heckers, Reference Woodward and Heckers2015). Possible explanations are that neurodegeneration is present in all subtypes but we did not have a healthy control group to ascertain this (Van Rheenen et al., Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018; Woodward & Heckers, Reference Woodward and Heckers2015); that our patients were earlier in the illness course and progressive atrophy was not yet evident (Van Rheenen et al., Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018); or that we did not have the statistical power to detect differences between the PIQ and DIQ subgroups. Van Rheenen et al. (Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018), in a large study which included healthy controls, did not find the reduced total ICV in a compromised subgroup and instead found reduced brain volume, corrected for ICV, in all subgroups. The compromised subgroup had more pronounced reductions in global and specific volumetric measures and also uniquely smaller volumes in certain frontal and temporal cortical areas. Thus, this study demonstrated a continuum of brain neurodegeneration in association with cognitive function and evidence of specific, earlier brain changes indicative of an additional neurodevelopmental process in those with evidence of premorbid compromised intellectual function.
Taken together, these findings support the validity of defining compromised cognitive subgroups using low estimated premorbid and current cognitive function as indicative of abnormal brain development (Van Rheenen et al., Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018). Whether defining a specific deteriorated cognitive subgroup is in itself biologically meaningful requires further study, as both Woodward and Heckers (Reference Woodward and Heckers2015) and Van Rheenen et al. (Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018) found evidence of MRI brain shrinkage in their preserved cognitive subgroups when compared to healthy controls. This suggests that there is a continuum of neurodegeneration across all cognitive subgroups. To support the notion that the extent of MRI identified neurodegeneration is associated with the degree of impaired cognition, they suggested that ‘preserved’ subgroups are not neuropsychologically intact. In our study, although there was no significant difference between the estimated current IQ of the PIQ group and healthy controls, the PIQ group showed a small but significant decline from their own estimated premorbid IQ. The PIQ group also showed an aberrant IQ subtest profile compared to healthy controls, with worse performance on processing speed (digit symbol subtest) and better performance on information, block design and arithmetic subtests. This group was also worse than controls on the auditory verbal learning and memory task. This accords with the findings of Wilk et al. (Reference Wilk, Gold, McMahon, Humber, Iannone and Buchanan2005) who compared WAIS index scores in schizophrenia patients and healthy controls, closely matched for IQ, and found patients were worse on processing speed but better on verbal comprehension and perceptual organisation. Other studies have also found that those with seemingly intact cognition can be separated from healthy controls by poorer performance on tests of processing speed (González-Blanch et al., Reference González-Blanch, Pérez-Iglesias, Rodríguez-Sánchez, Pardo-García, Martínez-García, Vázquez-Barquero and Crespo-Facorro2011; Heinrichs et al., Reference Heinrichs, Pinnock, Muharib, Hartman, Goldberg and McDermid Vaz2015) and verbal memory (Hill, Beers, Kmiec, Keshavan, & Sweeney, Reference Hill, Beers, Kmiec, Keshavan and Sweeney2004). These findings add weight to the evidence that impaired processing speed and verbal memory are evident in patients even when matched with healthy controls for IQ, suggesting that cognitive impairment is a fundamental feature of schizophrenia (Gray, McMahon, & Gold, Reference Gray, McMahon and Gold2013; Wilk et al., Reference Wilk, Gold, McMahon, Humber, Iannone and Buchanan2005). They also support the proposal of Carruthers et al. (Reference Carruthers, Van Rheenen, Gurvich, Sumner and Rossell2019) that ‘preserved’ subgroups be relabelled as ‘relatively intact’ when classified according to the cognitive trajectory methodology in future studies.
When we examined markers of inflammation in the cognitive subtypes we found that all subgroups had moderate (>1.0–<3.0 mg/l) to high (>3.0 mg/l) CRP levels (Metcalf et al., Reference Metcalf, Jones, Nordstrom, Timonen, Mäki, Miettunen and Khandaker2017) with a linear relationship, so that the PIQ group had the lowest level and the CIQ group the highest. The CIQ group had a significantly higher mean CRP level than the PIQ group even after controlling for confounders. These findings support an association between higher low-grade inflammation and worse cognitive performance rather than inflammation being specific to a particular cognitive subgroup. In support of this, several studies have found a relationship between current cognitive function (including IQ) and CRP in schizophrenia (Bulzacka et al., Reference Bulzacka, Boyer, Schürhoff, Godin, Berna, Brunel and Fond2016; Dickerson et al., Reference Dickerson, Stallings, Origoni, Boronow and Yolken2007; Johnsen et al., Reference Johnsen, Fathian, Kroken, Steen, Jørgensen, Gjestad and Løberg2016; Misiak et al., Reference Misiak, Stańczykiewicz, Kotowicz, Rybakowski, Samochowiec and Frydecka2018). Kappelman et al., (2019), in a large epidemiological study, found a linear association between lower premorbid IQ and higher ESR at the time of recruitment to the Swedish army. They also showed that lower premorbid IQ was a robust risk factor for a subsequent diagnosis of schizophrenia and that premorbid IQ partly mediated the ESR-psychosis relationship. They concluded that low-grade inflammation is a factor influencing cognitive development and schizophrenia risk. In a meta-analysis of population-based longitudinal studies, Osimo et al. (Reference Osimo, Baxter, Lewis, Jones and Khandaker2019) found an association between high CRP at baseline (>3.0 mg/l) and the subsequent development of schizophrenia thus supporting low-grade inflammation being a risk factor for this disorder. Although we found the highest CRP in the group with the lowest estimated premorbid IQ, this was cross-sectional and it therefore cannot be concluded that high CRP was present before psychosis onset and related to compromised IQ. Future longitudinal developmental studies are required to investigate this possibility
Significant group differences in inflammatory markers were limited to CRP only. CRP serum concentration is known to be elevated in response to inflammation, though evidence suggests that CRP is not only a marker, but also important in the mediation of inflammatory processes and expression of cytokines (Sproston & Ashworth, Reference Sproston and Ashworth2018). The mechanisms underlying this induction and exact relationships with the expression of individual cytokines remain unclear. One possible explanation for group differences in CRP, is that its transcription is induced by a combination of essential and supplementary inflammatory responses resulting from the overall acute phase response (Weinhold, Bader, Poli, & Rüther, Reference Weinhold, Bader, Poli and Rüther1997; Zhang, Sun, Samols, & Kushner, Reference Zhang, Sun, Samols and Kushner1996). Longitudinal studies are needed to investigate whether this inflammation is chronic, and the mechanisms leading to its induction.
We did not find significant differences between groups on measures of clinical symptoms or global and specific social functioning. Lack of differences in clinical symptoms is perhaps unsurprising, given that severity symptoms and cognition have largely been found to be independent (Heaton et al., Reference Heaton, Gladsjo, Palmer, Kuck, Marcotte and Jeste2001), though some studies in long-standing schizophrenia have shown evidence of more severe negative symptoms in compromised groups (Czepielewski et al., Reference Czepielewski, Wang, Gama and Barch2017; Van Rheenen et al., Reference Van Rheenen, Cropley, Zalesky, Bousman, Wells, Bruggemann and Pantelis2018). More surprising is the lack of differences in functional outcomes, given that cognition has been shown to be the best predictor of outcome following the onset of psychosis. Kendler Ohlsson, Mezuk, Sundquist, & Sundquist (Reference Kendler, Ohlsson, Mezuk, Sundquist and Sundquist2016) found that deviation from IQ level of biological relatives, rather than IQ score itself, confers the greatest risk for schizophrenia and it may be this differential which impacts differences in functional outcomes. Another possible explanation is that functional differences are not adequately captured by the measures used in this study.
This study has several limitations. The main one is that, because this was a secondary analysis, we were constrained by data collected in the original study (Deakin et al., Reference Deakin, Suckling, Barnes, Byrne, Chaudhry and Dazzan2018). All our patients were taking antipsychotic medication, but we did not have sufficient detail to assess medication effects. Furthermore, whilst we endeavoured to control for potential confounds of inflammatory status, we did not have data to adjust for smoking quantity or other health-related variables which could influence inflammation. We also did not have a healthy control group recruited at the same time and were unable to infer whether brain volumes or inflammation differed relative to controls. Furthermore, whilst the WTAR has been shown to be a reliable hold measure and is cross-validated with the WAIS-III, It would undeniably be preferable to have the same measure of IQ pre- and post-illness onset in a prospective cohort study. Finally, despite a relatively good overall sample size, stratifying participants into subgroups resulted in reduced statistical power. Caution in the interpretation of the results is therefore necessary, particularly with regard to the brain and inflammation markers.
Taken together our findings add validity to the presence of a neurodevelopmental subtype of schizophrenia (Weickert et al., Reference Weickert, Goldberg, Gold, Bigelow, Egan and Weinberger2000; Woodward & Heckers, Reference Woodward and Heckers2015), characterised in this study by smaller premorbid TBVs and higher measures of low-grade inflammation. However, we were unable to confirm that those with a deterioration in IQ from premorbid estimates had MRI evidence of brain shrinkage. Our finding of high CRP in the compromised group may indicate that low-grade inflammation contributes to abnormal brain development and premorbid cognitive function. Finally, we found that even when patients are thought to have preserved cognitive function, based on premorbid and current estimates of IQ, impaired verbal memory and processing speed are evident. This supports the notion that cognitive impairment is a fundamental feature of schizophrenia and which needs to be taken into account when investigating cognitive subtypes (Carruthers et al., Reference Carruthers, Van Rheenen, Gurvich, Sumner and Rossell2019).
The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721004815
The study was supported by the UK MRC EME programme (reference number 10/90/04) and The Wellcome Trust (reference number 064607). Author EMJ was supported by the UCL/UCLH NIHR Biomedical Research centre.
Conflict of interest
Author TREB has been a member of an advisory board for Gedeon Richter,.outside the current work. Author CMP has received funding from Johnson & Johnson, Boehringer Ingelheim and the Wellcome Trust, outside the current work. Author PD has received speaker fees from Janssen and Lundbeck. Other authors have no conflicts of interest to declare.