Interaction between catechol-O-methyltransferase Val/Met polymorphism and cognitive reserve for negative symptoms in schizophrenia

Abstract

BACKGROUND

Cognitive reserve (CR) and the catechol-O-methyltransferase (COMT) Val/Met polymorphism are reportedly linked to negative symptoms in schizophrenia. However, the regulatory effect of the COMT genotype on the relationship between CR and negative symptoms is still unexamined.

AIM

To investigate whether the relationship between CR and negative symptoms could be regulated by the COMT Val/Met polymorphism.

METHODS

In a cross-sectional study, 54 clinically stable patients with schizophrenia underwent assessments for the COMT genotype, CR, and negative symptoms. CR was estimated using scores in the information and similarities subtests of a short form of the Chinese version of the Wechsler Adult Intelligence Scale.

RESULTS

COMT Met-carriers exhibited fewer negative symptoms than Val homozygotes. In the total sample, significant negative correlations were found between negative symptoms and information, similarities. Associations between information, similarities and negative symptoms were observed in Val homozygotes only, with information and similarities showing interaction effects with the COMT genotype in relation to negative symptoms (information, β = -0.282, 95%CI: -0.552 to -0.011, P = 0.042; similarities, β = -0.250, 95%CI: -0.495 to -0.004, P = 0.046).

CONCLUSION

This study provides initial evidence that the association between negative symptoms and CR is under the regulation of the COMT genotype in schizophrenia.

Key Words: Catechol-O-methyltransferase Val/Met polymorphism, Cognitive reserve, Crystallized intelligence, Negative symptoms, Schizophrenia

Core Tip: Cognitive reserve (CR) and the catechol-O-methyltransferase (COMT) Val/Met polymorphism are reportedly linked to negative symptoms, which are a core clinical manifestation of schizophrenia. However, the regulatory effect of the COMT genotype on the relationship between CR and negative symptoms is unclear. In this study, COMT Met-carriers exhibited fewer negative symptoms than Val homozygotes. Information and similarities showed interaction effects with the COMT genotype in terms of negative symptoms. This preliminary study shows that the association between negative symptoms and CR may be under the regulation of the COMT genotype in schizophrenia.

INTRODUCTION

Negative symptoms are a core clinical manifestation of schizophrenia, encompassing blunted affect, alogia, apathy, anhedonia, and avolition[1]. Negative symptoms and cognitive deficits are the most critical determinants in the functional outcome and overall quality of life in schizophrenia[2,3]. Furthermore, negative symptoms have been documented as mediators in the influence of cognitive impairments on functional outcomes[4]. Currently, both pharmacological and non-pharmacological interventions show limited efficacy in treating negative symptoms[5-7]. It is essential to identify the influential factors of negative symptoms to develop individualized and comprehensive intervention strategies for patients with schizophrenia.

Cognitive reserve (CR) is frequently reported as a predictor of negative symptoms in cross-sectional and longitudinal studies[8-11]. CR refers to the ability to buffer the effects of illness through pre-existing and compensatory cognitive processes[12]. It is typically assessed using socio-behavioral measures, including intelligence quotient (IQ), educational level, occupational attainment, and leisure activity participation[13,14]. Apart from affecting negative symptoms, CR can also mitigate the adverse effects of exaggerated structural brain deterioration and disease relapse on neurocognitive function while concurrently enhancing psychosocial functioning[15-20]. The relationship between CR and negative symptoms may be even more pronounced in more severe pathological states[21,22].

Standardized and unified assessment tools are lacking in terms of assessing CR. Although educational level is the most commonly used indicator[12], it is a static measure that reflects learning and cognitive activities during a specific period in early life. By contrast, crystallized intelligence refers to the breadth and depth of knowledge and information that a person acquires over their lifetime[23]. Thus, measures of crystallized intelligence are dynamic and can capture the effects of continuous learning, thereby making them more suitable as alternative indicators of CR[24,25].

Dopamine activity in the prefrontal cortex plays a vital role in regulating negative symptoms in schizophrenia[26]. The catechol-O-methyltransferase (COMT) enzyme deactivates dopamine[27]. The COMT Val/Met polymorphism is a key genetic factor affecting the activity variation of the eponymous enzyme. Val homozygotes have approximately 40% higher enzyme activity in the prefrontal cortex than Met/Met carriers, potentially leading to lower levels of prefrontal dopamine signaling[28]. Therefore, the COMT genotype may be a remarkable factor influencing negative symptoms[29-31], as evidenced by studies that reported increased levels of negative symptoms in Val homozygotes[29].

To date, no study has been conducted on the interaction effects of the COMT genotype with CR in terms of negative symptoms. We hypothesized that the association between CR and negative symptoms would be regulated by the COMT genotype. Specifically, the correlation between CR and negative symptoms could be stronger in Val homozygotes with relatively more severe pathological features. A cross-sectional study was conducted among stable patients with schizophrenia to test this hypothesis. In this study, CR was primarily estimated by crystallized intelligence.

MATERIALS AND METHODS

Subjects

All data were derived from the baseline dataset of a randomized, controlled, double-blind clinical trial. The trial was conducted from September 2021 to May 2023 at Beijing Anding Hospital in China. The trial was approved by the Ethics Committee of Beijing Anding Hospital (No. 2020-70), and it was registered in the Chinese Clinical Trial Registry (ChiCTR2000038961). The participants in the trial were clinically stable outpatients or community-dwelling individuals with schizophrenia, aged between 18 and 50 years, with an IQ score above 70, and a minimum of 8 years of education. The primary exclusion criteria included a history of severe physical illness such as craniocerebral trauma or infection, brain tumor, cerebrovascular disease, and epilepsy according to patient self-description; as well as a history of alcohol or substance use disorders during the past 6 months. Sixty participants were enrolled at baseline, of which 54 completed testing for single-nucleotide polymorphisms for the cross-sectional analysis of this study.

Assessment tools

The diagnoses of schizophrenia and alcohol or substance use disorders were based on the DSM-5 criteria utilizing the Mini International Neuropsychiatric Interview (version 7.0.2). Clinical symptoms were assessed using the Positive and Negative Syndrome Scale, which includes a positive subscale for positive symptoms, a negative subscale for negative symptoms, and the general psychopathology subscale for general symptoms[32]. IQ was evaluated using a short form of the Chinese version of the Wechsler Adult Intelligence Scale (WAIS-RC), consisting of four subtests[33]. The information and similarities subtests primarily reflect crystallized intelligence, whereas the picture completion and block design subtests are designed to measure fluid intelligence which is the capacity to think logically and solve problems in novel situations. Together, these four subtests represent a rough measure of general ability[33,34].

Genotyping

Whole blood was utilized for DNA extraction. The rs4680 locus sequence was probed for the COMT Val/Met polymorphism. Genotypes were identified by polymerase chain reaction amplification, incorporation of terminator nucleotides and subsequent agarose gel electrophoresis. Among the 54 samples analyzed, 27 were Val/Val carriers, 22 were Val/Met carriers, and five were Met/Met carriers. The Val/Met and Met/Met carriers were combined as Met-carriers for subsequent analysis.

Statistical analysis

Chi square test was utilized to examine whether the distribution of the COMT genotype deviated from the Hardy-Weinberg equilibrium. Chi square tests, Fisher’s exact tests, and t-tests were applied to compare differences in demographics, negative symptoms, other clinical symptoms, and IQ between the two genotype groups (COMT Met-carriers and Val homozygotes). Where applicable, multiple linear regression analysis was conducted to control for potential confounding variables. Pearson’s correlation analyses and t-tests were used to identify potential indicators associated with negative symptoms in the total sample, including scores from the four WAIS-RC subtests and the total score, educational level, age, chlorpromazine equivalents, duration of illness, gender, employment and marriage.

Pearson’s correlation analyses were used to assess the correlation of negative symptoms with information, similarities in COMT Met-carriers and Val homozygotes. Following Fisher’s r to z transformation, Z-tests were employed to compare the correlation coefficients between the two genotype groups[35]. Additionally, multiple linear regression analyses were conducted to investigate the interaction effects of information, similarities and the genotype, and other influential factors in relation to negative symptoms. The variables were standardized to reduce collinearity in the multiple linear regression. All the above analyses were conducted in SPSS 20.0 (SPSS Inc., Chicago, IL, United States), and the results were visualized with the ggplot2 package in R version 4.2.3. Statistical significance was established at P < 0.05.

RESULTS

Demographics, clinical symptoms, and IQ of the genotype groups

The distribution of the COMT genotype showed no deviation from the Hardy-Weinberg equilibrium (χ² = 0.013, P = 0.993). Met-carriers showed significantly lower scores in negative symptoms than Val homozygotes (t₅₂ = -2.138, P = 0.037) (Table 1) (Figure 1A). The inclusion of employment as a covariate did not significantly alter the results.

Figure 1 Catechol-O-methyltransferase genotypes, negative symptoms, information and similarities. A: Comparison of negative symptoms across catechol-O-methyltransferase genotypes; B: Association between information and negative symptoms in the entire sample; C: Association between similarities and negative symptoms in the entire sample; D: Correlation of information with negative symptoms in Met-carriers; E: Correlation of similarities with negative symptoms in Met-carriers; F: Association between information and negative symptoms in Val homozygotes; G: Association between similarities and negative symptoms in Val homozygotes. ^aP < 0.05.

Table 1 Demographics, clinical symptoms and intelligence quotient in catechol-O-methyltransferase Met-carriers and Val homozygotes.

	Met-carriers, n = 27			Val homozygotes, n = 27			Statistic	u value	P value
	Mean	SD		Mean		SD
Age	34.59	7.66		33.15		7.23	t = 0.713	52	0.479
Educational level	14.37	3.52		14.98		3.90	t = -0.604	52	0.548
Female/male	16/11			14/13			χ² = 0.300	1	0.584
Han nationality/non	24/3			25/2			NA	NA	1.000
Employment/non	8/19			15/12			χ² = 3.711	1	0.054
Marriage/non	12/15			10/17			χ² = 0.307	1	0.580
Current smoker/non	3/24			3/24			NA	NA	1.000
Clozapine user/non	5/22			4/23			NA	NA	1.000
Chlorpromazine equivalents	474.96		258.23	426.50	323.60		t = 0.608	52	0.546
Duration of illness	11.73		8.56	11.24	7.51		t = 0.223	52	0.825
PANSS positive	9.48		3.89	8.56	2.90		t = 0.992	52	0.326
PANSS negative	11.15		3.31	13.59	4.93		t = -2.138	52	0.037
PANSS general	21.48		5.15	20.59	3.86		t = 0.718	52	0.476
PANSS total	42.11		10.02	42.74	7.89		t = -0.257	52	0.799
WAIS-RC information	20.67		4.66	18.41	4.80		t = 1.756	52	0.085
WAIS-RC similarities	18.67		2.27	18.33	2.76		t = 0.485	52	0.630
WAIS-RC picture completion	11.41		3.12	10.15	2.80		t = 1.563	52	0.124
WAIS-RC block design	36.19		7.19	36.44	8.44		t = -0.122	52	0.904
WAIS-RC total	106.61		9.75	103.00	10.54		t = 1.306	52	0.197

COMT: Catechol-O-methyltransferase; PANSS: Positive and negative syndrome scale; WAIS-RC: Chinese version of the Wechsler adult intelligence scale.

Correlations between negative symptoms and IQ, demographics, clinical characteristics in the total sample

In the total sample, significant negative correlations were observed between negative symptoms and information (r = -0.405, P = 0.002), similarities (r = -0.475, P < 0.001) (Figure 1B and C). In addition, negative symptoms also correlated with picture completion, block design, WAIS-RC total scores and educational level (all P < 0.05) (Table 2). However, t-test did not reveal any significant effects of gender, employment, and marital status on negative symptoms (Table 3).

Table 2 Correlations between negative symptoms and intelligence quotient, demographics, clinical characteristics in total participants (n = 54).

		Information	Similarities	Picture completion	Block design	WAIS-RC total	Education	Age	CE	Duration of illness
PANSS negative	r value	-0.405	-0.475	-0.332	-0.385	-0.527	-0.384	0.019	-0.243	-0.119
	P value	0.002	< 0.001	0.014	0.004	< 0.001	0.004	0.894	0.076	0.391

PANSS: Positive and negative syndrome scale; WAIS-RC: Chinese version of the Wechsler adult intelligence scale; CE: Chlorpromazine equivalents.

Table 3 The effects of gender, employment and marriage on negative symptoms.

	Gender/employment/marriage	n	Mean	SD	t value	u value	P value
PANSS negative	Male	24	13.63	4.79	1.949	52	0.057
	Female	30	11.37	3.73
	Employed	23	11.91	3.85	-0.663	52	0.510
	Non	31	12.71	4.71
	Married	32	12.09	4.71	-0.561	52	0.577
	Non	22	12.77	3.80

PANSS: Positive and negative syndrome scale.

Correlations of negative symptoms with IQ and educational level in the genotype groups

Negative symptoms were associated with information (r = -0.544, P = 0.003) and similarities (r = -0.620, P = 0.001) in Val homozygotes only (Figure 1D-G). Moreover, the correlation coefficients of information and similarities with negative symptoms showed significant differences between the two genotype groups (information, Z = 1.768, P = 0.038; similarities, Z = 1.726, P = 0.042).

Given the marginally significant effects of chlorpromazine equivalents (P = 0.076) and gender (P = 0.057) on negative symptoms in the univariate analyses, these variables were subsequently included in the multiple linear regression analyses. In these analyses, negative symptoms were treated as the dependent variable, with COMT genotype, information or similarities, the product of COMT genotype and information or similarities, gender, and chlorpromazine equivalents serving as independent variables. Multiple linear regression analyses further revealed the interaction effects of information, similarities with the genotype in terms of negative symptoms (information, β = -0.282, 95%CI: -0.552 to -0.011, P = 0.042; similarities, β = -0.250, 95%CI: -0.495 to -0.004, P = 0.046; Table 4). However, the effects of gender and chlorpromazine equivalents on negative symptoms were not found to be significant.

Table 4 Correlations of negative symptoms with information, similarities in catechol-O-methyltransferase met-carriers and Val homozygotes.

			Information	Similarities
PANSS negative	Met-carriers (n = 27)	r value	-0.099	-0.223
		P value	0.624	0.263
	Val/Val (n = 27)	r value	-0.544	-0.62
		P value	0.003	0.001
	Correlation coefficient comparison	Z value	1.768	1.726
		P value	0.038	0.042
	Interaction test1	β value	-0.282	-0.250
		95%CI	-0.552 to -0.011	-0.495 to -0.004
		P value	0.042	0.046

¹In the multiple linear regression, negative symptoms were treated as the dependent variable, with catechol-O-methyltransferase (COMT) genotype, information or similarities, the product of COMT genotype and information or similarities, gender, and chlorpromazine equivalents serving as independent variables.

PANSS: Positive and negative syndrome scale.

DISCUSSION

This study is the first to examine the regulatory role of the COMT Val/Met polymorphism in the relationship between negative symptoms and CR in schizophrenia. The results showed that COMT Met-carriers exhibited milder negative symptoms than Val homozygotes. In the total sample, negative symptoms were associated with CR reflected by information and similarities. Furthermore, the correlation of negative symptoms with CR was regulated by the COMT genotype.

COMT Met-carriers showed fewer negative symptoms than Val homozygotes. This observation aligns with the findings of Wang et al[29], who reported milder negative symptoms in Met-carriers among older patients with schizophrenia. Bosia et al[36] documented that the COMT genotype influenced the improvement of negative symptoms in patients with schizophrenia after taking clozapine. These findings support the statement that prefrontal dopamine levels mediated by the COMT genotype contribute to inter-individual variability of negative symptoms[1].

Negative symptoms were negatively related to CR and IQ. Similarly, Bucci et al[37] and Chang et al[9] reported that patients with poor CR exhibited more severe primary negative symptoms and worse working memory in cross-sectional studies. Furthermore, prospective studies found CR to be predictive of improvements in the negative symptoms or persistent negative symptoms within 1-10 years after first-episode psychosis[8,11,38]. CR-related factors may mitigate the effect of the disease pathology on the clinical phenotype through fostering new connections between neurons or different brain regions, activating compensatory neural networks, or enhancing the efficiency of existing neural network connections[39,40]. Nevertheless, the detailed mechanisms are yet to be elucidated, and relevant research remains limited in schizophrenia.

Our study did not observe significant effects of demographic or clinical characteristics on negative symptoms. However, previous research has identified several factors associated with negative symptoms, such as gender[41], psychiatric comorbidities, medication side effects, and prenatal events[42]. This discrepancy arises because our study did not collect data on some of these factors, and its ability to detect factors weakly correlated with negative symptoms was constrained due to the small sample size. Additionally, antipsychotics may impair the ability to attribute incentive salience and drive by blocking dopamine receptors, thus leading to secondary negative symptoms or exacerbating primary negative symptoms[43]. However, our study did not find an association between antipsychotic dose and negative symptoms, consistent with the results of a clinical trial involving 520 patients with schizophrenia[43]. These findings suggest that the negative impact of antipsychotics on negative symptoms may be mild.

The relationship of negative symptoms with CR was regulated by the COMT genotype. This study is a novel report in the context of schizophrenia. Similarly, research demonstrated that CR interacted with the apolipoprotein ε4 (APOE-ε4) genotype, a genetic risk factor for dementia, in relation to cognitive function in healthy elders[44]. CR may have a stronger protective effect against the risk of dementia in APOE-ε4 carriers[45]. These findings may suggest that in increased pathological states, there is greater room for clinical phenotype improvement, thereby leading to more pronounced protective effects of CR.

Considering that the protective effect of CR is evident only in the early stages of dementia[46,47], further investigation is warranted to determine whether a similar threshold phenomenon exists in the interaction effects of certain factors with CR in terms of the clinical phenotype of schizophrenia. Nonetheless, the current findings hold implications for the individualized and comprehensive intervention of negative symptoms in clinically stable patients with schizophrenia, suggesting that the intervention for negative symptoms in COMT Val homozygotes may require the application of more CR strategies. Additionally, our findings indicate that the effect of COMT on negative symptoms may be influenced by complex factors. This complexity might result in negative outcomes in clinical trials of COMT inhibitors for negative symptoms[48], despite the effect of COMT genotype on dopamine activity suggesting the potential efficacy of COMT inhibitors[49].

One of the strengths of this study is that it is the first report on the regulatory effect of the COMT genotype on the relationship between CR and negative symptoms. Additionally, all participants were clinically stable patients, thereby reducing potential confounding effects of fluctuating medications and clinical symptoms on the findings. Despite this, this study has some limitations that need to be acknowledged. Firstly, as a cross-sectional survey, it could not establish the dynamic and causal relationships among CR, COMT genotype and negative symptoms, necessitating further cohort studies and intervention trials. Secondly, the relatively small sample size limited the generalizability of the findings, thus requiring validation through larger-scale studies. Thirdly, due to the limited sample size, we combined the Val/Met and Met/Met carriers into a single group identified as Met-carriers. Although this grouping strategy is a common analysis approach[50-52], it may overlook valuable information that warrants further investigation in studies with larger sample sizes. Fourthly, this study did not comprehensively collect potential factors influencing negative symptoms and faced limitations in detecting weakly associated factors due to the small sample size. Lastly, due to relatively mild negative symptoms of the participants, it remains unknown whether the interaction effects of CR and the COMT genotype are influenced by negative symptom severity.

CONCLUSION

In summary, our study showed that the correlation between negative symptoms and CR was regulated by the COMT Val/Met polymorphism. The findings enhance the understanding of the mechanisms underlying individual differences in negative symptoms and provide insightful evidence for the individualized and comprehensive intervention of negative symptoms in schizophrenia.

ACKNOWLEDGEMENTS

The authors would like to thank all participants in this study.