Literature DB >> 33654399

Association Analysis Between Catechol-O-Methyltransferase Expression and Cognitive Function in Patients with Schizophrenia, Bipolar Disorder, or Major Depression.

Peiyan Ni1,2,3, Manli Liu1,2,3, Dequan Wang1,2,3, Yang Tian1,2,3, Liansheng Zhao1,2,3, Jinxue Wei1,2,3, Xueli Yu1,2,3, Xueyu Qi1,2,3, Xiaojing Li1,2,3, Hua Yu1,2,3, Rongjun Ni1,2,3, Xiaohong Ma1,2,3, Wei Deng1,2,3, Wanjun Guo1,2,3, Qiang Wang1,2,3, Tao Li1,2,3,4.   

Abstract

INTRODUCTION: Schizophrenia, bipolar disorder (BD), and major depressive disorder are three common mental disorders. Although their diagnosis and treatment differ, they partially overlap.
METHODS: To explore the similarities and characteristics of these three psychiatric diseases, an intelligence quotient (IQ) assessment was performed to evaluate cognitive deficits. Relative catechol-O-methyltransferase (COMT) expression in peripheral blood mononuclear cells was examined in all three groups compared with healthy controls (HCs).
RESULTS: The results indicated that patients with any of the three psychiatric diseases presented IQ deficits, and that the first-episode schizophrenia (FES) group had even lower cognitive function than the other two groups. The relative COMT expression decreased in the FES group and increased in the BD group compared with the HC group. The correlation analysis of COMT expression level and IQ scores showed a positive correlation between relative COMT expression and full-scale IQ in the HC group. However, this correlation disappeared in all three psychiatric diseases studied.
CONCLUSION: In conclusion, this cross-disease strategy provided important clues to explain lower IQ scores and dysregulated COMT expression among three common mental illnesses.
© 2021 Ni et al.

Entities:  

Keywords:  BD; COMT; FES; IQ; MDD; bipolar disorder; catechol-O-methyltransferase; first-episode major depressive disorder; first-episode schizophrenia; intelligence quotient

Year:  2021        PMID: 33654399      PMCID: PMC7910219          DOI: 10.2147/NDT.S286102

Source DB:  PubMed          Journal:  Neuropsychiatr Dis Treat        ISSN: 1176-6328            Impact factor:   2.570


Introduction

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are three types of common mental diseases, which severely affect psychological, biological, and social functioning. Although their diagnosis and treatment are different, there is some overlap in symptoms and treatment.1–3 Although symptoms are complex and heterogeneous, cognitive impairment is prevalent in SCZ, BD, and MDD.4 Cognitive deficit is regarded as a core symptom of SCZ and BD.5,6 Cognitive impairment is also one of the most common symptoms of MDD,7 and approximately 90% of patients with MDD complained about cognitive issues.8 The intelligence quotient (IQ) score refers to the intelligence level, which can rate the subjects’ cognitive ability, is an important indicator of cognitive assessment.9 Numerous studies have shown that the aforementioned mental diseases can lead to an impaired IQ.10–12 Although higher childhood IQ may predict increased risk of adult mania,13 IQ impairments in childhood and adolescence are often observed in individuals who later develop SCZ, BD, and MDD.14 Mental disorders are multifactorial diseases influenced by both genetic and environmental factors.15–17 All three common mental disorders have a high heritability,18–20 which means that genes play a crucial role in the pathophysiology of these psychiatric diseases. Furthermore, disease-related susceptible genes/loci provide some clues for diagnosis and treatment.21–23 The catechol-O-methyltransferase (COMT) gene has been widely investigated because of its high correlation with the risk of common psychiatric diseases, especially SCZ.24–26 COMT is located on chromosome 22q11.22627 and its single nucleotide polymorphisms (SNPs) are regarded as promising candidates for understanding the genetic basis of many common psychiatric disorders, especially rs4680, which can affect COMT activity.28 COMT transfers a methyl group from S-adenosylmethionine to catecholamines to degrade dopamine, epinephrine, and norepinephrine.28 Therefore, abnormal COMT expression or activity may cause dopaminergic dysfunction, which may, in turn, lead to common mental disease symptoms such as impaired cognition.29–31 A large number of studies focused on the relationship between the COMT gene and cognitive function in SCZ, BD, and MDD,32–35 while others have indicated that the relative risk of SCZ is 20 to 25 times higher in patients with 22q11.2 deletion syndrome (one COMT copy is deleted) than in the general population.36 Patients with a 22q11.2 deletion syndrome SCZ form also showed a lower IQ.37 In studies on BD, however, there are contradictory findings on the correlation between COMT and cognitive function.38 This inconsistency may be due to the fact that some studies did consider factors that may influence the cognitive performance of BD patients, such as disease stage or medical treatment at the time of assessment.39,40 Antypa et al proposed a tentative pathway whereby the COMT gene may influence cognitive vulnerability to depression.41 In healthy research participants, the COMT genotype could help predict a small proportion of the variance in baseline cognition and neurophysiology,42 but the association is modest and inconsistent.43 Therefore, it is very important to explore the correlation between COMT expression and IQ defects with cross-disease strategies among different mental illnesses. Studies have suggested that both relative COMT expression and IQ assessment could dynamically change according to the state of the episode and pharmacologic treatment.30,39,40,44–46 To exclude the possible influence of pharmacologic treatment, the patients with SCZ and MDD included in this study were all drug-naïve first-episode subjects, and patients with BD did not take any medication 3 months before enrollment. In this cross-disease study, the combination of relative COMT expression and IQ assessment was considered to be a powerful approach to identify the potential path between the expression of risk genes and phenotype. We hypothesized that COMT expression was different in patients with mental disorders, and that the correlation between COMT expression and IQ scores may not be consistent.

Methods

Demographic Characteristics and General Cognitive Function Assessment

This study recruited 150 patients with FES (in acute or post-acute phase), 182 patients with BD (in depressive and manic as well as mixed phase), and 183 first-episode patients with MDD (in acute or post-acute phase) from the Mental Health Center of West China Hospital of Sichuan University. All patients were interviewed using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) Patient edition (SCID-P). Both patients with FES and MDD were drug-naïve, and patients with BD were not medicated in the 3 months prior to enrollment. All subjects were followed up for at least 6 months to further confirm the initial diagnosis. We also recruited 261 healthy controls (HCs) by poster advertisements within the local community in Chengdu, Sichuan Province, China. The HCs were interviewed using the SCID-NP. All subjects were recruited over the period from 2012–2016. IQ was tested using the short version of the Chinese Revised Wechsler Adult Intelligence Scale (WAIS-RC) according to the WAIS-RC manual.47 The IQ assessment included seven subtests: information, digital span, digital symbol, picture completion, block design, similarities, and arithmetic. Verbal IQ, performance IQ, and full-scale IQ were calculated referring to the weighted formulas previously described.47,48 This study was conducted in accordance with the Declaration of Helsinki. Approval for this study was granted by the Ethics Committee of the West China Hospital of Sichuan University. All participants signed an informed consent form, and patient’s demographic characteristics are shown in Table 1.
Table 1

Demographic Data and IQ Scores of All Subjects Among Different Groups of Patients and Controls

HCFESBDMDDF/χ2P valueFES vs HCBD vs HCMDD vs HCFES vs BDFES vs MDDMDD vs BD
Gender (n)2611501821836.8990.075
Male (%)97 (37.2)72 (48.0)75 (41.2)64 (35.0)
Female (%)164 (62.8)78 (52.0)107 (58.8)119 (65.0)
Age (years)25.6±7.523.4±7.125.2±7.828.3±9.630.077<0.001***<0.001***0.2120.020*0.028*<0.001***0.001***
Education years15.1±3.112.2±2.813.7±2.813.8±3.188.082<0.001***<0.001***<0.001***<0.001***<0.001***<0.001***0.526
BMI21.0±2.920.6±3.121.9±3.321.4±3.314.4030.002**0.2400.005**0.207<0.001***0.028***0.160
Verbal IQ114.0±15.299.7±14.2109.4±13.1107.1±14.691.171<0.001***<0.001***<0.001***<0.001***<0.001***<0.001***0.217
Performance IQ111.4±13.893.0±16.8103.0±15.0104.7±13.8118.992<0.001***<0.001***<0.001***<0.001***<0.001***<0.001***0.375
Full-scale IQ114.1±14.596.6±14.2107.2±13.3106.7±13.849.477<0.001***<0.001***<0.001***<0.001***<0.001***<0.001***>0.999

Notes: Data were presented as mean±SD (standard Deviation); the difference of gender was analyzed by the χ2 test among four groups. The data distribution of age, education years, and BMI deviated from normality; the Kruskal–Wallis ANOVA test was used to compare their differences among groups followed by post hoc Bonferroni correction for multiple comparisons; *indicate P<0.05; **indicate P<0.01; ***indicate P<0.001.

Abbreviations: HC, healthy controls; FES, first-episode schizophrenia; BD, bipolar disorder; MDD, first-episode major depressive disorder; BMI, body mass index; IQ, intelligence quotient.

Demographic Data and IQ Scores of All Subjects Among Different Groups of Patients and Controls Notes: Data were presented as mean±SD (standard Deviation); the difference of gender was analyzed by the χ2 test among four groups. The data distribution of age, education years, and BMI deviated from normality; the Kruskal–Wallis ANOVA test was used to compare their differences among groups followed by post hoc Bonferroni correction for multiple comparisons; *indicate P<0.05; **indicate P<0.01; ***indicate P<0.001. Abbreviations: HC, healthy controls; FES, first-episode schizophrenia; BD, bipolar disorder; MDD, first-episode major depressive disorder; BMI, body mass index; IQ, intelligence quotient.

Total RNA Extraction and Relative COMT Expression

Patients not treated with any medication after cognitive function assessment were scheduled for peripheral blood mononuclear cell (PBMC) collection at 8:00–9:00AM. For the patients and healthy controls, whose demographic characteristics are shown in Table 2, and could attend the PBMC collection, peripheral blood samples (3 mL) were collected. For total RNA extraction, whole blood samples were immediately preserved in Tempus Blood RNA Tubes (Applied Biosystems, Foster, USA). To avoid blood coagulation, the tubes were vigorously mixed for ≥10 seconds. All tubes were preserved at −80°C until use. According to the manufacturer’s instruction, total RNA was extracted from the sample with MagMAX for Stabilized Blood Tubes RNA Isolation Kit (Thermo Fisher Scientific, Waltham, USA). cDNA was generated using the iScript cDNA Synthesis Kit (Bio-Rad, Hercules, USA) with 1 μg total RNA. Quantitative polymerase chain reaction (qPCR) was performed with the SsoFast EvaGreenTM Supermix Real-time PCR kit (Bio-Rad, Hercules, USA). Relative mRNA expression was measured using the CFX96TM Real-Time System (Bio-Rad, Hercules, USA). The PCR cycling parameters were: 95°C for 1 min for denaturing, followed by 40 cycles of a two-step PCR (melting for 10 s at 95°C, annealing for 20 s at 60°C). Relative COMT mRNA expression was analyzed using the 2−ΔΔCt method and normalized by GAPDH expression. The corresponding primer sequences are listed as follows:
Table 2

Demographic Data and IQ Scores of Subjects with COMT Expression Analysis in HC, FES, BD, and MDD Groups

HCFESBDMDDF/χ2P valueFES vs HCBD vs HCMDD vs HCFES vs BDFES vs MDDMDD vs BD
Gender, (n)533247253.7240.293
Male (%)27 (50.9)18 (56.2)24 (51.1)8 (32.0)
Female (%)26 (49.1)14 (43.8)23 (48.9)17 (68.0)
Age (years)24.2±6.722.8±6.426.7±7.930.1±10.911.4860.009**0.2910.1150.020*0.016*0.003**0.317
Education years15.4±2.811.8±3.413.7±3.514.1±2.721.772<0.001***<0.001***0.014*0.1690.017*0.008**0.522
BMI20.7±3.521.0±3.122.6±3.121.8±3.111.4320.010*0.5420.001**0.0700.032*0.2700.408
Verbal IQ115.9±12.4101.1±15.1112.1±11.6110.0±12.721.339<0.001***<0.001***0.1190.0750.002**0.024*0.627
Performance IQ112.4±12.791.8±17.7100.8±16.4102.7±14.032.359<0.001***<0.001***<0.001***0.010*0.040*0.025*0.607
Full-scale IQ115.8±11.896.5±15.5107.9±13.5107.4±12.514.027<0.001***<0.001***0.022*0.0620.002**0.015*>0.999

Notes: Data were presented as mean±SD (standard Deviation); the difference of gender was analyzed by the χ2 test among four groups; the data distribution of age, education years, and BMI deviated from normality; the Kruskal–Wallis ANOVA test was used to compare their differences among groups followed by post hoc Bonferroni correction for multiple comparisons; *indicate P<0.05; **indicate P<0.01; ***indicate P<0.001.

Abbreviations: HC, healthy controls; FES, first-episode schizophrenia; BD, bipolar disorder; MDD, first-episode major depressive disorder; BMI, body mass index; IQ, intelligence quotient.

Demographic Data and IQ Scores of Subjects with COMT Expression Analysis in HC, FES, BD, and MDD Groups Notes: Data were presented as mean±SD (standard Deviation); the difference of gender was analyzed by the χ2 test among four groups; the data distribution of age, education years, and BMI deviated from normality; the Kruskal–Wallis ANOVA test was used to compare their differences among groups followed by post hoc Bonferroni correction for multiple comparisons; *indicate P<0.05; **indicate P<0.01; ***indicate P<0.001. Abbreviations: HC, healthy controls; FES, first-episode schizophrenia; BD, bipolar disorder; MDD, first-episode major depressive disorder; BMI, body mass index; IQ, intelligence quotient. COMT, Sense Primer: 5′–CGACTGTGCCGCCATCA Anti-sense Primer: 5′–GCAGCAGGCCACATTCCTC GAPDH, Sense Primer: 5′–GTCTCCTCTGACTTCAACAGCG Anti-sense Primer: 5′–ACCACCCTGTTGCTGTAGCCAA.

Statistical Analyses

All statistical analyses were performed using SPSS version 24 (IBM, Armonk, USA). The chi-square (χ2) test was conducted to compare the frequency difference in qualitative characteristics (ie, gender) among the four groups. The Shapiro–Wilk test was employed for the normal distribution test, and equal variance was tested by Levene’s test. Statistical analysis was performed using Welch’s ANOVA test followed by the post hoc Tamhane’s T2 test when normal distribution was assumed, but equal variance was not. When the data distribution deviated from normality, the Kruskal–Wallis ANOVA test was used to compare differences among groups followed by post hoc Bonferroni correction for multiple comparisons. The statistical methods for each statistical result are detailed in and . Correlation between IQ and relative COMT expression in each group was examined by a partial correlation analysis with age, education years, and BMI as covariates.

Results

Demographic Characteristics

The demographic data of all subjects are shown in Table 1. A total of 776 subjects participated in this study, including 261 HC (97M/164F), 150 FES (72M/78F), 182 BD (75M/107F), and 183 MDD (64M/119F). There was no significant difference in gender among groups (χ2=6.899, p=0.075). However, age (χ2=30.077, p<0.001), education years (χ2=88.082, p<0.001), and BMI (χ2=14.403, p=0.002) were significantly different among groups. Patients with FES had the lowest average age at onset and education years, which was significantly lower than that of the HC group (age: p<0.001; education years: p<0.001) and patients with BD (age: p<0.001; education years: p<0.001) or MDD (age: p=0.028; education years: p<0.001). With respect to BMI, patients with BD had a significantly higher BMI than HC (p=0.005) and FES (p<0.001).

Lower IQ Scores of Patients with Psychiatric Disease

As shown in Table 1, there were significant differences in verbal IQ score (χ2=91.171, p<0.001), performance IQ score (χ2=118.992, p<0.001), and full-scale IQ score (F(3, 772) =49.477, p<0.001) among the four groups. Compared with the HC group, all psychiatric groups showed lower verbal IQ, performance IQ, and full-scale IQ. Among psychiatric groups, all IQ scores of the FES group were significantly lower than those of the BD group (verbal IQ score: p<0.001, performance IQ score: p<0.001, and full-scale IQ score: p<0.001) and MDD group (verbal IQ score: p<0.001, performance IQ score: p<0.001, and full-scale IQ score: p<0.001). However, no difference in any IQ scores was found between the BD and MDD groups.

Dysregulated COMT Expression in Patients with Psychiatric Disease

Consistent with the overall demographic data, the subjects with analyzed COMT expression well represented the demographic distribution of all subjects (Table 2). Meanwhile, the IQ score distribution in the subgroup with analyzed COMT expression was also very similar to the overall results of all subjects (Table 2). There were significant differences in relative COMT expression among all groups (F(3, 153) = 40.120, p<0.001). Compared with the HC group, there was a significantly lower COMT expression in the FES group (p<0.001) while COMT expression was upregulated in the BD group (p=0.001), and no difference was observed in the MDD group (p=0.248) (Figure 1A). The partial correlation analysis results of IQ scores and relative COMT expression in all groups are listed in Table 3. As shown in Figure 1B, the full-scale IQ score was positively correlated with relative COMT expression in the HC group (r=0.301, p=0.040).
Figure 1

Full-scale IQ score positively correlated with relative COMT expression in the HC group. (A) Relative COMT expression among different groups of patients and controls. (B) Correlation analysis of COMT expression and full-scale IQ score in the HC group. Gene expression data normalized by GAPDH expression. Data are presented as mean±SEM. Asterisks indicate P<0.001.

Table 3

The Correlation of Verbal IQ, Performance IQ, Full Scale IQ with Relative COMT Expression in All Groups

IQHCFESBDMDD
rprprprp
Verbal IQ0.2850.052−0.1290.5390.0310.843−0.1640.466
Performance IQ0.1990.1790.0780.711−0.0800.605−0.0660.769
Full scale IQ0.3010.040*−0.0350.867−0.0270.861−0.1240.582

Notes: Data were analyzed by Partial correlation analysis after adjusting for age, education years and BMI; *indicate P<0.05.

Abbreviations: HC, healthy controls; FES, first-episode schizophrenia; BD, bipolar disorder; MDD, first-episode major depressive disorder; IQ, intelligence quotient.

The Correlation of Verbal IQ, Performance IQ, Full Scale IQ with Relative COMT Expression in All Groups Notes: Data were analyzed by Partial correlation analysis after adjusting for age, education years and BMI; *indicate P<0.05. Abbreviations: HC, healthy controls; FES, first-episode schizophrenia; BD, bipolar disorder; MDD, first-episode major depressive disorder; IQ, intelligence quotient. Full-scale IQ score positively correlated with relative COMT expression in the HC group. (A) Relative COMT expression among different groups of patients and controls. (B) Correlation analysis of COMT expression and full-scale IQ score in the HC group. Gene expression data normalized by GAPDH expression. Data are presented as mean±SEM. Asterisks indicate P<0.001.

Discussion

There is certain overlap in symptoms and treatment among the three common mental diseases examined here: SCZ, BD, and MDD. It is therefore of great significance for the objective diagnosis and precise treatment of these mental diseases to explore their similarities and characteristics. In this study, we identified consistent IQ impairment and different COMT expression in PBMCs among patients with FES, BD, and MDD, suggesting that a cross-disease strategy could provide important clues for the phenotypic and mechanistic characterization of mental diseases. As an effective indicator of state assessment, IQ scores were used to evaluate the cognitive function of patients with different psychiatric diseases.9–12 In this study, we found that the IQ scores of all three groups of patients with psychiatric diseases were significantly decreased, especially in the FES group, consistent with the severe cognitive impairment of FES patients observed in clinical practice.49,50 Worse cognitive impairment and earlier age at onset51–53 are possible explanations for the younger age and fewer education years of FES patients in this study. Interestingly, the relative COMT expression in FES and BD groups presented an opposite trend compared with the HC group, that is, COMT expression significantly decreased in the FES group and increased in the BP group. According to previous studies, COMT is a risk gene for SCZ, BD, and MDD, and its risk effects are not consistent in different mental illnesses.54,55 The inconsistent relative COMT expression in PBMCs among patients with SCZ and BD in this study might be due to genetic risk,56 the disease course,57,58 or the sample size, which may also be another important factor.30,58 COMT is known to play an important role in the biological process of dopamine degradation through methyl transfer.28 The relationship between dopamine levels and cognitive function presents an inverted U-shaped pattern,59 thus implying the existence of an optimal dopamine level, and those with lower and higher predicted dopamine levels perform worse,60 which has fundamental implications for the effects of dopaminergic treatment on cognition,61 and also suggests that the expression level of COMT has meaningful implications for cognitive impairment and its potential biological mechanisms. To explore this significance, a correlation analysis of COMT expression level and IQ score was performed. The results showed that there was a positive correlation between relative COMT expression and full-scale IQ only in the HC group. This correlation disappeared in all groups with psychiatric diseases. As mentioned above, the U-shaped pattern between dopamine concentration and cognitive function59 might mean that abnormal COMT expression may lead to its negative correlation with lower IQ in the three groups with psychiatric diseases. Some limitations of the current study should be mentioned. The present observations await replication with a larger sample size in future studies, and more cognitive domains such as executive functions and working memory should be considered. Although PBMCs are more accessible, considering the tissue/cell specificity of COMT expression, research based on postmortem samples and/or specific neurons differentiated from induced pluripotent stem cells (iPSCs) will provide a more deliberate opportunity to explore the biological mechanism. Even though all patients in the FES and MDD groups were drug-naïve first-episode, the patients with BD may have taken some medications that affect COMT expression or cognitive responses during previous episodes of mania or depression, such as dopamine agonists.62 Considering that such treatment can change the relative COMT expression,30 it is difficult to rule out whether the abnormal COMT expression observed in the BD group corresponded to disease-innate abnormalities or was a side-effect of drug treatment. As a cross-sectional study, this study did not examine the effects of drug treatments on relative COMT expression. Therefore, subsequent longitudinal studies might provide evidence to support relative COMT expression as a biological marker for psychiatric diseases.
  61 in total

1.  DNA hypomethylation of MB-COMT promoter in the DNA derived from saliva in schizophrenia and bipolar disorder.

Authors:  Shabnam Nohesara; Mohammad Ghadirivasfi; Sahar Mostafavi; Mohammad-Reza Eskandari; HamidReza Ahmadkhaniha; Sam Thiagalingam; Hamid Mostafavi Abdolmaleky
Journal:  J Psychiatr Res       Date:  2011-08-05       Impact factor: 4.791

2.  Human catechol-O-methyltransferase pharmacogenetics: description of a functional polymorphism and its potential application to neuropsychiatric disorders.

Authors:  H M Lachman; D F Papolos; T Saito; Y M Yu; C L Szumlanski; R M Weinshilboum
Journal:  Pharmacogenetics       Date:  1996-06

Review 3.  Genes, cognition and brain through a COMT lens.

Authors:  D Dickinson; B Elvevåg
Journal:  Neuroscience       Date:  2009-05-13       Impact factor: 3.590

4.  Childhood IQ and adult mental disorders: a test of the cognitive reserve hypothesis.

Authors:  Karestan C Koenen; Terrie E Moffitt; Andrea L Roberts; Laurie T Martin; Laura Kubzansky; HonaLee Harrington; Richie Poulton; Avshalom Caspi
Journal:  Am J Psychiatry       Date:  2008-12-01       Impact factor: 18.112

5.  Association of the COMT val158met variant with antidepressant treatment response in major depression.

Authors:  Bernhard T Baune; Christa Hohoff; Klaus Berger; Anna Neumann; Sünke Mortensen; Tilmann Roehrs; Jürgen Deckert; Volker Arolt; Katharina Domschke
Journal:  Neuropsychopharmacology       Date:  2007-05-23       Impact factor: 7.853

6.  Allele-specific expression in a family quartet with autism reveals mono-to-biallelic switch and novel transcriptional processes of autism susceptibility genes.

Authors:  Chun-Yen Lin; Kai-Wei Chang; Chia-Yi Lin; Jia-Ying Wu; Hilary Coon; Pei-Hsin Huang; Hong-Nerng Ho; Schahram Akbarian; Susan Shur-Fen Gau; Hsien-Sung Huang
Journal:  Sci Rep       Date:  2018-03-09       Impact factor: 4.379

7.  Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.

Authors:  Naomi R Wray; Stephan Ripke; Manuel Mattheisen; Maciej Trzaskowski; Enda M Byrne; Abdel Abdellaoui; Mark J Adams; Esben Agerbo; Tracy M Air; Till M F Andlauer; Silviu-Alin Bacanu; Marie Bækvad-Hansen; Aartjan F T Beekman; Tim B Bigdeli; Elisabeth B Binder; Douglas R H Blackwood; Julien Bryois; Henriette N Buttenschøn; Jonas Bybjerg-Grauholm; Na Cai; Enrique Castelao; Jane Hvarregaard Christensen; Toni-Kim Clarke; Jonathan I R Coleman; Lucía Colodro-Conde; Baptiste Couvy-Duchesne; Nick Craddock; Gregory E Crawford; Cheynna A Crowley; Hassan S Dashti; Gail Davies; Ian J Deary; Franziska Degenhardt; Eske M Derks; Nese Direk; Conor V Dolan; Erin C Dunn; Thalia C Eley; Nicholas Eriksson; Valentina Escott-Price; Farnush Hassan Farhadi Kiadeh; Hilary K Finucane; Andreas J Forstner; Josef Frank; Héléna A Gaspar; Michael Gill; Paola Giusti-Rodríguez; Fernando S Goes; Scott D Gordon; Jakob Grove; Lynsey S Hall; Eilis Hannon; Christine Søholm Hansen; Thomas F Hansen; Stefan Herms; Ian B Hickie; Per Hoffmann; Georg Homuth; Carsten Horn; Jouke-Jan Hottenga; David M Hougaard; Ming Hu; Craig L Hyde; Marcus Ising; Rick Jansen; Fulai Jin; Eric Jorgenson; James A Knowles; Isaac S Kohane; Julia Kraft; Warren W Kretzschmar; Jesper Krogh; Zoltán Kutalik; Jacqueline M Lane; Yihan Li; Yun Li; Penelope A Lind; Xiaoxiao Liu; Leina Lu; Donald J MacIntyre; Dean F MacKinnon; Robert M Maier; Wolfgang Maier; Jonathan Marchini; Hamdi Mbarek; Patrick McGrath; Peter McGuffin; Sarah E Medland; Divya Mehta; Christel M Middeldorp; Evelin Mihailov; Yuri Milaneschi; Lili Milani; Jonathan Mill; Francis M Mondimore; Grant W Montgomery; Sara Mostafavi; Niamh Mullins; Matthias Nauck; Bernard Ng; Michel G Nivard; Dale R Nyholt; Paul F O'Reilly; Hogni Oskarsson; Michael J Owen; Jodie N Painter; Carsten Bøcker Pedersen; Marianne Giørtz Pedersen; Roseann E Peterson; Erik Pettersson; Wouter J Peyrot; Giorgio Pistis; Danielle Posthuma; Shaun M Purcell; Jorge A Quiroz; Per Qvist; John P Rice; Brien P Riley; Margarita Rivera; Saira Saeed Mirza; Richa Saxena; Robert Schoevers; Eva C Schulte; Ling Shen; Jianxin Shi; Stanley I Shyn; Engilbert Sigurdsson; Grant B C Sinnamon; Johannes H Smit; Daniel J Smith; Hreinn Stefansson; Stacy Steinberg; Craig A Stockmeier; Fabian Streit; Jana Strohmaier; Katherine E Tansey; Henning Teismann; Alexander Teumer; Wesley Thompson; Pippa A Thomson; Thorgeir E Thorgeirsson; Chao Tian; Matthew Traylor; Jens Treutlein; Vassily Trubetskoy; André G Uitterlinden; Daniel Umbricht; Sandra Van der Auwera; Albert M van Hemert; Alexander Viktorin; Peter M Visscher; Yunpeng Wang; Bradley T Webb; Shantel Marie Weinsheimer; Jürgen Wellmann; Gonneke Willemsen; Stephanie H Witt; Yang Wu; Hualin S Xi; Jian Yang; Futao Zhang; Volker Arolt; Bernhard T Baune; Klaus Berger; Dorret I Boomsma; Sven Cichon; Udo Dannlowski; E C J de Geus; J Raymond DePaulo; Enrico Domenici; Katharina Domschke; Tõnu Esko; Hans J Grabe; Steven P Hamilton; Caroline Hayward; Andrew C Heath; David A Hinds; Kenneth S Kendler; Stefan Kloiber; Glyn Lewis; Qingqin S Li; Susanne Lucae; Pamela F A Madden; Patrik K Magnusson; Nicholas G Martin; Andrew M McIntosh; Andres Metspalu; Ole Mors; Preben Bo Mortensen; Bertram Müller-Myhsok; Merete Nordentoft; Markus M Nöthen; Michael C O'Donovan; Sara A Paciga; Nancy L Pedersen; Brenda W J H Penninx; Roy H Perlis; David J Porteous; James B Potash; Martin Preisig; Marcella Rietschel; Catherine Schaefer; Thomas G Schulze; Jordan W Smoller; Kari Stefansson; Henning Tiemeier; Rudolf Uher; Henry Völzke; Myrna M Weissman; Thomas Werge; Ashley R Winslow; Cathryn M Lewis; Douglas F Levinson; Gerome Breen; Anders D Børglum; Patrick F Sullivan
Journal:  Nat Genet       Date:  2018-04-26       Impact factor: 38.330

8.  A longitudinal study of premorbid IQ Score and risk of developing schizophrenia, bipolar disorder, severe depression, and other nonaffective psychoses.

Authors:  Stanley Zammit; Peter Allebeck; Anthony S David; Christina Dalman; Tomas Hemmingsson; Ingvar Lundberg; Glyn Lewis
Journal:  Arch Gen Psychiatry       Date:  2004-04

9.  The quantification of COMT mRNA in post mortem cerebellum tissue: diagnosis, genotype, methylation and expression.

Authors:  Emma L Dempster; Jonathan Mill; Ian W Craig; David A Collier
Journal:  BMC Med Genet       Date:  2006-02-16       Impact factor: 2.103

10.  COMT, 5-HTR2A, and SLC6A4 mRNA Expressions in First-Episode Antipsychotic-Naïve Schizophrenia and Association With Treatment Outcomes.

Authors:  Zongchang Li; Ying He; Hongying Han; Yao Zhou; Xiaoqian Ma; Dong Wang; Jun Zhou; Honghong Ren; Liu Yuan; Jinsong Tang; Xiaofen Zong; Maolin Hu; Xiaogang Chen
Journal:  Front Psychiatry       Date:  2018-11-13       Impact factor: 4.157

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