Schizophrenia Research 159 (2014) 114–117
Contents lists available at ScienceDirect
Schizophrenia Research journal homepage: www.elsevier.com/locate/schres
Effects of COMT genotype on cognitive ability and functional capacity in individuals with schizophrenia Elizabeth W. Twamley a,b,⁎, Jessica P.Y. Hua c, Cynthia Z. Burton d, Lea Vella d, Kelly Chinh c, Robert M. Bilder e,f, John R. Kelsoe g,h a
Department of Psychiatry, University of California, San Diego, United States Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, United States University of California, San Diego, United States d San Diego State University and University of California, San Diego Joint Doctoral Program in Clinical Psychology, United States e Department of Psychology, University of California, Los Angeles, United States f Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, United States g Department of Psychiatry, University of California, San Diego, United States h Psychiatry Service, VA San Diego Healthcare System, United States b c
a r t i c l e
i n f o
Article history: Received 10 February 2014 Received in revised form 19 July 2014 Accepted 20 July 2014 Available online 16 August 2014 Keywords: Cognition Functioning Psychosis Executive functioning Learning Memory Genetics
a b s t r a c t Cognitive and functional impairments are core features of schizophrenia. This study examined the catechol-O-methyltransferase (COMT) genotype and its relationship to cognition and functional capacity in 188 individuals with schizophrenia or schizoaffective disorder. We found that in a dose–response fashion, individuals with more Met alleles performed significantly better on tests of learning/memory and abstraction. The effects of COMT genotype on cognition were modest, explaining about 3% of the variance in learning/memory and abstraction. Larger studies will be needed to examine the relationships between COMT and other genes and cognitive performance and everyday functioning. Published by Elsevier B.V.
Neurocognitive impairment is widely recognized as a core feature of schizophrenia, reflected in its recent inclusion in the diagnostic criteria in the DSM-5. Cognitive impairments are associated with difficulties across the lifespan in school achievement, employment, social functioning, and independent living (Green et al., 2000; Twamley et al., 2002; Nuechterlein et al., 2011). Neuroimaging studies have found evidence that at least some of the cognitive deficits of schizophrenia are related to dopamine activity in the prefrontal cortex of the brain (McGowan et al., 2004; Kendler and Schaffner, 2011). Thus, it is possible that the abnormal dopamine activity in the brain may not only explain psychotic symptoms and antipsychotic response (Moncrieff, 2009; Kendler and Schaffner, 2011), but also apply to neurocognition. In the past decade, research on the catechol-O-methyltransferase (COMT) gene has
⁎ Corresponding author at: Department of Psychiatry, University of California, San Diego, 140 Arbor Drive (0851), San Diego, CA 92103, United States. Tel.: +1 619 543 6684. E-mail address: [email protected] (E.W. Twamley).
http://dx.doi.org/10.1016/j.schres.2014.07.041 0920-9964/Published by Elsevier B.V.
demonstrated that the single nucleotide polymorphism Val158Met is implicated in the cognitive deficits of schizophrenia (Goldberg et al., 2003; Bilder et al., 2004; Krabbendam et al., 2006). The COMT gene, located on chromosome 22, contains a mutation that creates a guanine to adenine transition, resulting in a substitution of a Met allele instead of a Val allele on codon 158, a mutation that affects the catabolism of dopamine in the prefrontal cortex (Egan et al., 2001). The Met allele is the low activity allele associated with decreased catabolism of dopamine, resulting in increased prefrontal dopamine; the Val allele is the high activity allele associated with increased catabolism of dopamine, resulting in decreased prefrontal dopamine. Previous research with schizophrenia patients has demonstrated that compared with Val homozygotes, Met carriers perform better on most neuropsychological tests, including tests of working memory (nback tasks; Egan et al., 2001), executive functioning (Wisconsin Card Sorting Test; Joober et al., 2002), and processing speed (Trail Making and Digit Symbol; Bilder et al., 2002; Goldberg et al., 2003). However, the Met allele has been associated with worse performance on tests
E.W. Twamley et al. / Schizophrenia Research 159 (2014) 114–117
measuring cognitive flexibility and switching (Nolan et al., 2004), leading Bilder and colleagues to propose the tonic–phasic dopamine hypothesis. This theory posits that the Met allele is associated with better performance on tests requiring adequate tonic levels of dopamine (those tests requiring cognitive stability), whereas the Val allele is associated with better performance on tests requiring phasic dopamine release (Bilder et al., 2004). Our goal was to evaluate the association between COMT genotype and cognitive performance on a comprehensive battery of executive functioning tests, in the context of broader neuropsychological functioning. We hypothesized that “dosage” of Met alleles (0, 1, or 2) would be associated with better neuropsychological performance in most domains, but there would be a Met-associated disadvantage on tests of cognitive flexibility and switching. 1. Method 1.1. Participants and procedure One hundred eighty-eight outpatients with schizophrenia (n = 94) or schizoaffective disorder (n = 94) participated in the study. Potential participants were excluded if they had comorbidities that affected cognition (i.e., developmental disability, neurological illness, brain injury with loss of consciousness N30 min, or substance abuse within one month). Diagnoses were confirmed using the Mini-International Neuropsychiatric Interview (MINI; Sheehan et al., 1998). Demographic and clinical characteristics of the sample are provided in Table 1. On average, participants were 47 years old and completed 12 years of education. Most were male, Caucasian, and taking atypical antipsychotic medication. Participants were chronically ill, with a mean duration of illness of 24 years and mean daily chlorpromazine equivalent (CPZE) dose of 402 mg. The genotype groups were categorized based on the number of Met alleles (0, 1, or 2, i.e., Val/Val, Val/Met, or Met/Met), and the groups did not differ on any of the demographic variables except sex (women were underrepresented in the Met/Met group). The groups did not differ on any of the clinical variables except depressive symptom severity (Met homozygotes had less severe depressive symptoms). All participants provided informed consent, and this study was approved by the Institutional Review Board. Assessments (including interview measures and cognitive tests) and a blood draw were completed in a single day. Whole blood was obtained by venipuncture and buffy coat isolated by Ficoll gradient. DNA was extracted from leukocytes using the QIAamp kit (Qiagen, San Diego). Blood was assayed for COMT genotype using a 5′ exonuclease assay (ABI Taqman) design to detect rs4680
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and run on an ABI 7900. rs4680 is a G → A substitution resulting in the missense Val158Met mutation that has been associated with differences in COMT activity. The number of individuals with Val/Val (n = 69), Val/Met (n = 80), and Met/Met (n = 39) genotypes fell within the Hardy–Weinberg equilibrium (Hardy, 1908) when considering the entire sample (n = 188), Caucasians only (n = 112), or Blacks/AfricanAmericans (n = 58) only.
1.2. Measures Severity of psychiatric symptoms was assessed with the Positive and Negative Syndrome Scale (PANSS; Kay et al., 1987) and the Hamilton Depression Rating Scale (HAM-D; Hamilton, 1967). Everyday functional skills were evaluated with the UCSD Performance-Based Skills Assessment, (UPSA; Patterson et al., 2001), which assesses capacity to perform tasks necessary for independent living, related to finances, communication, recreation planning, transportation, and household chores. Neurocognitive assessments included the American National Adult Reading Test (ANART; Grober and Sliwinski, 1991), an oral reading test measuring crystallized verbal knowledge and therefore used as an estimate of premorbid IQ; the Brief Visuospatial Memory Test—Revised (BVMT-R; Benedict, 1997) and Hopkins Verbal Learning Test—Revised (HVLT-R; Brandt and Benedict, 2001) as tests of visual and verbal learning and memory; the Continuous Performance Test—Identical Pairs (CPT-IP; Cornblatt et al., 1988) d prime as a measure of sustained attention; the Wechsler Adult Intelligence Scale—Third Edition (WAIS-III; Wechsler, 1997) Digit Symbol and Symbol Search subtests, measuring processing speed; the WAIS-III Digit Span and Letter–Number Sequencing subtests, measuring attention and working memory; and the Delis–Kaplan Executive Function System (D–KEFS; Delis et al., 2001), a nine-subtest battery assessing multiple aspects of executive functioning that load on two factors, cognitive flexibility and abstraction (Savla et al., 2012). To reduce the number of neuropsychological variables, we performed a principal component analysis with varimax rotation and Kaiser normalization using all neuropsychological normed scores. Only factors with an eigenvalue ≥1.0 were accepted, and only cognitive tests with a loading of ≥0.4 were retained. The analysis was repeated after excluding the only test that did not load on a factor (CPT-IP), and the results of the second principal components analysis are presented in Table 2. Six cognitive factors were identified, which we named trail making, learning/memory, verbal fluency, speeded switching, reasoning, and planning. We also report on Savla and colleagues' (2012) original D– KEFS factors, cognitive flexibility (comprised of color–word inhibition, color–word inhibition/switching, design fluency switching, trails
Table 1 Sample characteristics.
Age, years Education, years Duration of illness, years Gender, % male Race, % Caucasian Diagnosis, % schizophrenia (vs. schizoaffective) History of substance use disorder, % Antipsychotic medication type, % atypical only Antipsychotic medication dose (mg CPZE) HAM-D total PANSS positive total PANSS negative total ANART (estimated IQ)
Total sample (n = 188)
Val/Val (n = 69)
Val/Met (n = 80)
Met/Met (n = 39)
Test statistic (df)
p-Value
47.3 (8.9) 12.5 (2.4) 24.1 (11.7) 64% 60% 50% 79% 79% 402.0 (398.9) 11.3 (6.8) 15.8 (5.8) 14.5 (5.0) 105.2 (9.8)
46.8 (8.0) 12.2 (2.0) 24.5 (13.1) 57% 45% 51% 74% 81% 380.8 (342.8) 11.0 (6.7) 15.6 (6.3) 14.4 (5.1) 103.0 (9.9)
47.4 (9.3) 12.8 (2.6) 23.9 (10.9) 61% 64% 48% 79% 78% 438.0 (465.2) 12.6 (7.1) 16.1 (5.4) 14.6 (4.9) 106.3 (9.8)
47.8 (9.7) 12.4 (2.4) 23.7 (10.9) 82% 77% 54% 90% 77% 369.0 (358.7) 9.3 (5.9) 15.6 (6.0) 14.4 (5.1) 106.7 (9.2)
F = 0.2 (2,185) F = 1.4 (2,185) F = 0.9 (2,181) Χ2 = 7.4 (2) Χ2 = 14.9 (8) Χ2 = 0.4 (2) Χ2 = 6.7 (4) Χ2 = 7.4 (2) F = 0.4 (2,118) F = 3.2 (2,181) F = 0.1 (2,181) F = 0.0 (2,182) F = 2.8 (2,185)
.835 .242 .417 .024 .060 .800 .156 .024 .705 .045 .865 .973 .063
Note. Data not presented as percentages are means (standard deviations). Degrees of freedom varied due to missing data. ANART = American National Adult Reading Test. CPZE = Chlorpromazine equivalent (not available for certain medications, including injectable medications). HAM-D = Hamilton Depression Rating Scale. PANSS = Positive and Negative Syndrome Scale.
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E.W. Twamley et al. / Schizophrenia Research 159 (2014) 114–117
Table 2 Factor analysis rotated component matrix of cognitive factors.
D–KEFS trail making 5: motor speed SS D–KEFS trail making 1: visual scanning SS D–KEFS trail making 2: number sequencing SS D–KEFS trail making 3: letter sequencing SS HVLT-R delayed recall T-score BVMT-R total recall T-score HVLT-R total recall T-score BVMT-R delayed recall T-score D–KEFS verbal fluency: letter fluency SS D–KEFS verbal fluency: category fluency SS D–KEFS color–word: inhibition/switching SS D–KEFS color–word: inhibition SS D–KEFS verbal fluency: category switching accuracy SS D–KEFS design fluency: switching SS WAIS-III digit symbol SS D–KEFS trail making 4: number–letter switching SS WAIS-III symbol search SS D–KEFS proverb test: total achievement SS D–KEFS word context: total consecutively correct SS D–KEFS sorting: confirmed correct SS WAIS-III digit span SS WAIS-III letter–number sequencing SS D–KEFS tower: total achievement SS D–KEFS twenty questions: weighted achievement SS
Trail making
Learning/memory
Verbal fluency
Speeded switching
Reasoning
Planning
.809 .741 .699 .642 .035 .138 .044 .207 .146 .299 .161 .218 .071 .175 .318 .273 .359 .137 .066 .170 .176 .135 .128 −.086
.036 .070 .175 .111 .818 .753 .731 .717 .212 .044 .098 .119 .036 .182 .266 .205 .309 .106 .290 .260 .431 .391 .124 −.022
.105 .195 .000 .122 .278 −.119 .312 −.166 .724 .688 .007 .094 .361 −.027 .189 .176 .204 .071 .007 .021 .184 .271 .053 .301
.062 .188 .357 .474 .110 .229 .146 .174 .096 .331 .770 .714 .623 .594 .569 .528 .510 .143 .249 .188 .130 .377 .062 .134
.208 .012 .110 .125 .226 .093 .322 .136 .257 −.044 .260 .302 −.010 .127 .175 .108 .088 .778 .667 .550 .534 .414 .092 .407
.073 −.040 .160 .184 −.078 .397 −.072 .411 .083 .096 −.158 .020 .112 .378 .157 .376 .291 .010 .268 .381 .057 .241 .746 .551
Did not load N.4 on any factor: Continuous Performance Test — Identical Pairs. Note. BVMT-R = Brief Visuospatial Memory Test, Revised. D–KEFS = Delis–Kaplan Executive Function System. HVLT-R = Hopkins Verbal Learning Test, Revised. SS = scaled score. WAIS-III = Wechsler Adult Intelligence Scale, 3rd Edition. Loadings in bold font identify the factor on which items best loaded.
number–letter switching, and verbal fluency switching) and abstraction (comprised of word context, proverbs, sorting, twenty questions, and tower).
factor and the D–KEFS abstraction factor. No other correlations reached statistical significance, although all were in the positive direction, suggesting that a higher number of Met alleles was associated with better functioning across all cognitive domains.
1.3. Analyses 3. Discussion All continuous variables were examined for normality. The relationships between genotype and cognitive and functional capacity scores were analyzed with partial correlations controlling for sex. Statistical analyses were 2-tailed with a significance level at alpha ≤ .05. 2. Results Results are shown in Table 3. Partial correlations controlling for sex and depressive symptom severity revealed a statistically significant relationship between the number of Met alleles and the learning/memory Table 3 Partial correlations between Met allele dose and cognitive and functional performance, controlling for sex and depressive symptom severity (n = 173).
Trail making Learning/memory Verbal fluency Speeded switching Reasoning Planning D–KEFS abstraction D–KEFS cognitive flexibility UPSA recreation planning UPSA financial UPSA communication UPSA transportation UPSA household chores UPSA total score
Partial correlation with Met allele dose
p
.022 .160 .069 .102 .107 .030 .157 .067 .055 .036 .088 .108 .122 .108
.777 .034⁎ .361 .181 .159 .692 .038⁎ .377 .470 .639 .248 .155 .107 .155
Note. D–KEFS = Delis–Kaplan Executive Function System. UPSA = UCSD PerformanceBased Skills Assessment. ⁎ p b .05.
Supporting our hypothesis, individuals with a greater number of Met alleles, in a dose–response fashion, performed significantly better on tests of learning/memory and abstraction. However, the tonic–phasic hypothesis was not supported, as the Met allele was not associated with a disadvantage on tests of cognitive flexibility and switching. Instead, Met allele dose was non significantly related to better performance in cognitive flexibility and the remainder of the cognitive and functional capacity domains. Our sample was larger (n = 188) than the Nolan et al. (2004) sample (n = 26), and we assessed switching with multiple tests, but still found no Val advantage in switching. It may be that the Met advantages for generalized cognitive functioning outweigh any Metassociated disadvantages. Importantly, the differential effects of COMT genotype did not appear to be attributable to a generalized cognitive deficit, as the mean premorbid IQ estimate was average in all three genotype groups, and the groups did not differ on premorbid IQ. COMT genotype explained about 3% of the variance in learning/memory and abstraction performance, consistent with prior research finding that the effects of Met allele dose on cognition in schizophrenia are subtle (Egan et al., 2001; Malhotra et al., 2002). Our study has limitations. The effects of the COMT polymorphism on cognition and functional capacity are small, and these abilities are clearly multiply-determined. We elected to retain a six-factor principal component analysis solution to evaluate a larger number of factors than scree plot examination may have suggested retaining (Genderson et al., 2007). Our sample size was small for a genetic study, given that genotypes typically explain a small proportion of variance in cognitive functioning. Additionally, we did not have sufficient sample size to examine racial subgroups. Not all research studies are able to find significant effects of COMT genotype on cognitive abilities (Blanchard et al., 2011),
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particularly in the context of small samples, and larger samples examining other candidate genotypes will be needed to better understand the genetic basis of cognition and functioning in schizophrenia. The effects of sex and racial/ethnic differences and the COMT polymorphism on cognition merits further study because research has shown that sex hormones can interact in the expression of the COMT gene, and that there may be an interaction between COMT genotype and race/ethnicity (Bilder et al., 2004; Rybakowski et al., 2006; Harrison and Tunbridge, 2008). Role of the funding source Funding for this study was provided by the Brain and Behavior Research Foundation, National Alliance for Research on Schizophrenia and Depression Award to Dr. Twamley. Contributors Authors Twamley, Kelsoe, and Bilder designed the study and wrote the protocol. Author Hua managed the literature searches. Authors Twamley, Hua, Burton, Vella, and Chinh conducted the statistical analyses. Authors Twamley and Hua wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript. Conflict of interest None. Acknowledgments The authors gratefully acknowledge funding from the Brain and Behavior Research Foundation (NARSAD Award to EWT) and the contributions of the participants who took part in this research.
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Contents lists available at ScienceDirect
Schizophrenia Research journal homepage: www.elsevier.com/locate/schres
Effects of COMT genotype on cognitive ability and functional capacity in individuals with schizophrenia Elizabeth W. Twamley a,b,⁎, Jessica P.Y. Hua c, Cynthia Z. Burton d, Lea Vella d, Kelly Chinh c, Robert M. Bilder e,f, John R. Kelsoe g,h a
Department of Psychiatry, University of California, San Diego, United States Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, United States University of California, San Diego, United States d San Diego State University and University of California, San Diego Joint Doctoral Program in Clinical Psychology, United States e Department of Psychology, University of California, Los Angeles, United States f Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, United States g Department of Psychiatry, University of California, San Diego, United States h Psychiatry Service, VA San Diego Healthcare System, United States b c
a r t i c l e
i n f o
Article history: Received 10 February 2014 Received in revised form 19 July 2014 Accepted 20 July 2014 Available online 16 August 2014 Keywords: Cognition Functioning Psychosis Executive functioning Learning Memory Genetics
a b s t r a c t Cognitive and functional impairments are core features of schizophrenia. This study examined the catechol-O-methyltransferase (COMT) genotype and its relationship to cognition and functional capacity in 188 individuals with schizophrenia or schizoaffective disorder. We found that in a dose–response fashion, individuals with more Met alleles performed significantly better on tests of learning/memory and abstraction. The effects of COMT genotype on cognition were modest, explaining about 3% of the variance in learning/memory and abstraction. Larger studies will be needed to examine the relationships between COMT and other genes and cognitive performance and everyday functioning. Published by Elsevier B.V.
Neurocognitive impairment is widely recognized as a core feature of schizophrenia, reflected in its recent inclusion in the diagnostic criteria in the DSM-5. Cognitive impairments are associated with difficulties across the lifespan in school achievement, employment, social functioning, and independent living (Green et al., 2000; Twamley et al., 2002; Nuechterlein et al., 2011). Neuroimaging studies have found evidence that at least some of the cognitive deficits of schizophrenia are related to dopamine activity in the prefrontal cortex of the brain (McGowan et al., 2004; Kendler and Schaffner, 2011). Thus, it is possible that the abnormal dopamine activity in the brain may not only explain psychotic symptoms and antipsychotic response (Moncrieff, 2009; Kendler and Schaffner, 2011), but also apply to neurocognition. In the past decade, research on the catechol-O-methyltransferase (COMT) gene has
⁎ Corresponding author at: Department of Psychiatry, University of California, San Diego, 140 Arbor Drive (0851), San Diego, CA 92103, United States. Tel.: +1 619 543 6684. E-mail address: [email protected] (E.W. Twamley).
http://dx.doi.org/10.1016/j.schres.2014.07.041 0920-9964/Published by Elsevier B.V.
demonstrated that the single nucleotide polymorphism Val158Met is implicated in the cognitive deficits of schizophrenia (Goldberg et al., 2003; Bilder et al., 2004; Krabbendam et al., 2006). The COMT gene, located on chromosome 22, contains a mutation that creates a guanine to adenine transition, resulting in a substitution of a Met allele instead of a Val allele on codon 158, a mutation that affects the catabolism of dopamine in the prefrontal cortex (Egan et al., 2001). The Met allele is the low activity allele associated with decreased catabolism of dopamine, resulting in increased prefrontal dopamine; the Val allele is the high activity allele associated with increased catabolism of dopamine, resulting in decreased prefrontal dopamine. Previous research with schizophrenia patients has demonstrated that compared with Val homozygotes, Met carriers perform better on most neuropsychological tests, including tests of working memory (nback tasks; Egan et al., 2001), executive functioning (Wisconsin Card Sorting Test; Joober et al., 2002), and processing speed (Trail Making and Digit Symbol; Bilder et al., 2002; Goldberg et al., 2003). However, the Met allele has been associated with worse performance on tests
E.W. Twamley et al. / Schizophrenia Research 159 (2014) 114–117
measuring cognitive flexibility and switching (Nolan et al., 2004), leading Bilder and colleagues to propose the tonic–phasic dopamine hypothesis. This theory posits that the Met allele is associated with better performance on tests requiring adequate tonic levels of dopamine (those tests requiring cognitive stability), whereas the Val allele is associated with better performance on tests requiring phasic dopamine release (Bilder et al., 2004). Our goal was to evaluate the association between COMT genotype and cognitive performance on a comprehensive battery of executive functioning tests, in the context of broader neuropsychological functioning. We hypothesized that “dosage” of Met alleles (0, 1, or 2) would be associated with better neuropsychological performance in most domains, but there would be a Met-associated disadvantage on tests of cognitive flexibility and switching. 1. Method 1.1. Participants and procedure One hundred eighty-eight outpatients with schizophrenia (n = 94) or schizoaffective disorder (n = 94) participated in the study. Potential participants were excluded if they had comorbidities that affected cognition (i.e., developmental disability, neurological illness, brain injury with loss of consciousness N30 min, or substance abuse within one month). Diagnoses were confirmed using the Mini-International Neuropsychiatric Interview (MINI; Sheehan et al., 1998). Demographic and clinical characteristics of the sample are provided in Table 1. On average, participants were 47 years old and completed 12 years of education. Most were male, Caucasian, and taking atypical antipsychotic medication. Participants were chronically ill, with a mean duration of illness of 24 years and mean daily chlorpromazine equivalent (CPZE) dose of 402 mg. The genotype groups were categorized based on the number of Met alleles (0, 1, or 2, i.e., Val/Val, Val/Met, or Met/Met), and the groups did not differ on any of the demographic variables except sex (women were underrepresented in the Met/Met group). The groups did not differ on any of the clinical variables except depressive symptom severity (Met homozygotes had less severe depressive symptoms). All participants provided informed consent, and this study was approved by the Institutional Review Board. Assessments (including interview measures and cognitive tests) and a blood draw were completed in a single day. Whole blood was obtained by venipuncture and buffy coat isolated by Ficoll gradient. DNA was extracted from leukocytes using the QIAamp kit (Qiagen, San Diego). Blood was assayed for COMT genotype using a 5′ exonuclease assay (ABI Taqman) design to detect rs4680
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and run on an ABI 7900. rs4680 is a G → A substitution resulting in the missense Val158Met mutation that has been associated with differences in COMT activity. The number of individuals with Val/Val (n = 69), Val/Met (n = 80), and Met/Met (n = 39) genotypes fell within the Hardy–Weinberg equilibrium (Hardy, 1908) when considering the entire sample (n = 188), Caucasians only (n = 112), or Blacks/AfricanAmericans (n = 58) only.
1.2. Measures Severity of psychiatric symptoms was assessed with the Positive and Negative Syndrome Scale (PANSS; Kay et al., 1987) and the Hamilton Depression Rating Scale (HAM-D; Hamilton, 1967). Everyday functional skills were evaluated with the UCSD Performance-Based Skills Assessment, (UPSA; Patterson et al., 2001), which assesses capacity to perform tasks necessary for independent living, related to finances, communication, recreation planning, transportation, and household chores. Neurocognitive assessments included the American National Adult Reading Test (ANART; Grober and Sliwinski, 1991), an oral reading test measuring crystallized verbal knowledge and therefore used as an estimate of premorbid IQ; the Brief Visuospatial Memory Test—Revised (BVMT-R; Benedict, 1997) and Hopkins Verbal Learning Test—Revised (HVLT-R; Brandt and Benedict, 2001) as tests of visual and verbal learning and memory; the Continuous Performance Test—Identical Pairs (CPT-IP; Cornblatt et al., 1988) d prime as a measure of sustained attention; the Wechsler Adult Intelligence Scale—Third Edition (WAIS-III; Wechsler, 1997) Digit Symbol and Symbol Search subtests, measuring processing speed; the WAIS-III Digit Span and Letter–Number Sequencing subtests, measuring attention and working memory; and the Delis–Kaplan Executive Function System (D–KEFS; Delis et al., 2001), a nine-subtest battery assessing multiple aspects of executive functioning that load on two factors, cognitive flexibility and abstraction (Savla et al., 2012). To reduce the number of neuropsychological variables, we performed a principal component analysis with varimax rotation and Kaiser normalization using all neuropsychological normed scores. Only factors with an eigenvalue ≥1.0 were accepted, and only cognitive tests with a loading of ≥0.4 were retained. The analysis was repeated after excluding the only test that did not load on a factor (CPT-IP), and the results of the second principal components analysis are presented in Table 2. Six cognitive factors were identified, which we named trail making, learning/memory, verbal fluency, speeded switching, reasoning, and planning. We also report on Savla and colleagues' (2012) original D– KEFS factors, cognitive flexibility (comprised of color–word inhibition, color–word inhibition/switching, design fluency switching, trails
Table 1 Sample characteristics.
Age, years Education, years Duration of illness, years Gender, % male Race, % Caucasian Diagnosis, % schizophrenia (vs. schizoaffective) History of substance use disorder, % Antipsychotic medication type, % atypical only Antipsychotic medication dose (mg CPZE) HAM-D total PANSS positive total PANSS negative total ANART (estimated IQ)
Total sample (n = 188)
Val/Val (n = 69)
Val/Met (n = 80)
Met/Met (n = 39)
Test statistic (df)
p-Value
47.3 (8.9) 12.5 (2.4) 24.1 (11.7) 64% 60% 50% 79% 79% 402.0 (398.9) 11.3 (6.8) 15.8 (5.8) 14.5 (5.0) 105.2 (9.8)
46.8 (8.0) 12.2 (2.0) 24.5 (13.1) 57% 45% 51% 74% 81% 380.8 (342.8) 11.0 (6.7) 15.6 (6.3) 14.4 (5.1) 103.0 (9.9)
47.4 (9.3) 12.8 (2.6) 23.9 (10.9) 61% 64% 48% 79% 78% 438.0 (465.2) 12.6 (7.1) 16.1 (5.4) 14.6 (4.9) 106.3 (9.8)
47.8 (9.7) 12.4 (2.4) 23.7 (10.9) 82% 77% 54% 90% 77% 369.0 (358.7) 9.3 (5.9) 15.6 (6.0) 14.4 (5.1) 106.7 (9.2)
F = 0.2 (2,185) F = 1.4 (2,185) F = 0.9 (2,181) Χ2 = 7.4 (2) Χ2 = 14.9 (8) Χ2 = 0.4 (2) Χ2 = 6.7 (4) Χ2 = 7.4 (2) F = 0.4 (2,118) F = 3.2 (2,181) F = 0.1 (2,181) F = 0.0 (2,182) F = 2.8 (2,185)
.835 .242 .417 .024 .060 .800 .156 .024 .705 .045 .865 .973 .063
Note. Data not presented as percentages are means (standard deviations). Degrees of freedom varied due to missing data. ANART = American National Adult Reading Test. CPZE = Chlorpromazine equivalent (not available for certain medications, including injectable medications). HAM-D = Hamilton Depression Rating Scale. PANSS = Positive and Negative Syndrome Scale.
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Table 2 Factor analysis rotated component matrix of cognitive factors.
D–KEFS trail making 5: motor speed SS D–KEFS trail making 1: visual scanning SS D–KEFS trail making 2: number sequencing SS D–KEFS trail making 3: letter sequencing SS HVLT-R delayed recall T-score BVMT-R total recall T-score HVLT-R total recall T-score BVMT-R delayed recall T-score D–KEFS verbal fluency: letter fluency SS D–KEFS verbal fluency: category fluency SS D–KEFS color–word: inhibition/switching SS D–KEFS color–word: inhibition SS D–KEFS verbal fluency: category switching accuracy SS D–KEFS design fluency: switching SS WAIS-III digit symbol SS D–KEFS trail making 4: number–letter switching SS WAIS-III symbol search SS D–KEFS proverb test: total achievement SS D–KEFS word context: total consecutively correct SS D–KEFS sorting: confirmed correct SS WAIS-III digit span SS WAIS-III letter–number sequencing SS D–KEFS tower: total achievement SS D–KEFS twenty questions: weighted achievement SS
Trail making
Learning/memory
Verbal fluency
Speeded switching
Reasoning
Planning
.809 .741 .699 .642 .035 .138 .044 .207 .146 .299 .161 .218 .071 .175 .318 .273 .359 .137 .066 .170 .176 .135 .128 −.086
.036 .070 .175 .111 .818 .753 .731 .717 .212 .044 .098 .119 .036 .182 .266 .205 .309 .106 .290 .260 .431 .391 .124 −.022
.105 .195 .000 .122 .278 −.119 .312 −.166 .724 .688 .007 .094 .361 −.027 .189 .176 .204 .071 .007 .021 .184 .271 .053 .301
.062 .188 .357 .474 .110 .229 .146 .174 .096 .331 .770 .714 .623 .594 .569 .528 .510 .143 .249 .188 .130 .377 .062 .134
.208 .012 .110 .125 .226 .093 .322 .136 .257 −.044 .260 .302 −.010 .127 .175 .108 .088 .778 .667 .550 .534 .414 .092 .407
.073 −.040 .160 .184 −.078 .397 −.072 .411 .083 .096 −.158 .020 .112 .378 .157 .376 .291 .010 .268 .381 .057 .241 .746 .551
Did not load N.4 on any factor: Continuous Performance Test — Identical Pairs. Note. BVMT-R = Brief Visuospatial Memory Test, Revised. D–KEFS = Delis–Kaplan Executive Function System. HVLT-R = Hopkins Verbal Learning Test, Revised. SS = scaled score. WAIS-III = Wechsler Adult Intelligence Scale, 3rd Edition. Loadings in bold font identify the factor on which items best loaded.
number–letter switching, and verbal fluency switching) and abstraction (comprised of word context, proverbs, sorting, twenty questions, and tower).
factor and the D–KEFS abstraction factor. No other correlations reached statistical significance, although all were in the positive direction, suggesting that a higher number of Met alleles was associated with better functioning across all cognitive domains.
1.3. Analyses 3. Discussion All continuous variables were examined for normality. The relationships between genotype and cognitive and functional capacity scores were analyzed with partial correlations controlling for sex. Statistical analyses were 2-tailed with a significance level at alpha ≤ .05. 2. Results Results are shown in Table 3. Partial correlations controlling for sex and depressive symptom severity revealed a statistically significant relationship between the number of Met alleles and the learning/memory Table 3 Partial correlations between Met allele dose and cognitive and functional performance, controlling for sex and depressive symptom severity (n = 173).
Trail making Learning/memory Verbal fluency Speeded switching Reasoning Planning D–KEFS abstraction D–KEFS cognitive flexibility UPSA recreation planning UPSA financial UPSA communication UPSA transportation UPSA household chores UPSA total score
Partial correlation with Met allele dose
p
.022 .160 .069 .102 .107 .030 .157 .067 .055 .036 .088 .108 .122 .108
.777 .034⁎ .361 .181 .159 .692 .038⁎ .377 .470 .639 .248 .155 .107 .155
Note. D–KEFS = Delis–Kaplan Executive Function System. UPSA = UCSD PerformanceBased Skills Assessment. ⁎ p b .05.
Supporting our hypothesis, individuals with a greater number of Met alleles, in a dose–response fashion, performed significantly better on tests of learning/memory and abstraction. However, the tonic–phasic hypothesis was not supported, as the Met allele was not associated with a disadvantage on tests of cognitive flexibility and switching. Instead, Met allele dose was non significantly related to better performance in cognitive flexibility and the remainder of the cognitive and functional capacity domains. Our sample was larger (n = 188) than the Nolan et al. (2004) sample (n = 26), and we assessed switching with multiple tests, but still found no Val advantage in switching. It may be that the Met advantages for generalized cognitive functioning outweigh any Metassociated disadvantages. Importantly, the differential effects of COMT genotype did not appear to be attributable to a generalized cognitive deficit, as the mean premorbid IQ estimate was average in all three genotype groups, and the groups did not differ on premorbid IQ. COMT genotype explained about 3% of the variance in learning/memory and abstraction performance, consistent with prior research finding that the effects of Met allele dose on cognition in schizophrenia are subtle (Egan et al., 2001; Malhotra et al., 2002). Our study has limitations. The effects of the COMT polymorphism on cognition and functional capacity are small, and these abilities are clearly multiply-determined. We elected to retain a six-factor principal component analysis solution to evaluate a larger number of factors than scree plot examination may have suggested retaining (Genderson et al., 2007). Our sample size was small for a genetic study, given that genotypes typically explain a small proportion of variance in cognitive functioning. Additionally, we did not have sufficient sample size to examine racial subgroups. Not all research studies are able to find significant effects of COMT genotype on cognitive abilities (Blanchard et al., 2011),
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particularly in the context of small samples, and larger samples examining other candidate genotypes will be needed to better understand the genetic basis of cognition and functioning in schizophrenia. The effects of sex and racial/ethnic differences and the COMT polymorphism on cognition merits further study because research has shown that sex hormones can interact in the expression of the COMT gene, and that there may be an interaction between COMT genotype and race/ethnicity (Bilder et al., 2004; Rybakowski et al., 2006; Harrison and Tunbridge, 2008). Role of the funding source Funding for this study was provided by the Brain and Behavior Research Foundation, National Alliance for Research on Schizophrenia and Depression Award to Dr. Twamley. Contributors Authors Twamley, Kelsoe, and Bilder designed the study and wrote the protocol. Author Hua managed the literature searches. Authors Twamley, Hua, Burton, Vella, and Chinh conducted the statistical analyses. Authors Twamley and Hua wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript. Conflict of interest None. Acknowledgments The authors gratefully acknowledge funding from the Brain and Behavior Research Foundation (NARSAD Award to EWT) and the contributions of the participants who took part in this research.
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