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Inicio Neurología Genetic predisposition of BDNF (rs6265) gene is susceptible to Schizophrenia: A ...
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Vol. 39. Núm. 4.
Páginas 361-371 (mayo 2024)
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Vol. 39. Núm. 4.
Páginas 361-371 (mayo 2024)
Review article
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Genetic predisposition of BDNF (rs6265) gene is susceptible to Schizophrenia: A prospective study and updated meta-analysis
Asociación entre el gen BDNF (rs6265) y predisposición a la esquizofrenia: estudio prospectivo y metaanálisis actualizado
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M. Vajagathali, V. Ramakrishnan
Autor para correspondencia
rkgenes@gmail.com

Corresponding author.
Human Cytogenetics and Genomics Laboratory, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam 603103, Tamilnadu, India
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Table 1. The characteristics of included studies in the meta-analysis.
Table 2. Genotypic and allelic frequency of rs6265 polymorphism.
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Abstract
Introduction

Genetic polymorphism in the BDNF gene has been found to cause neuronal alterations and has been identified as a causal factor for many neuropsychiatric disorders. Therefore, various neurological case–control studies and meta-analyses have been conducted to find the possible link between BDNF and susceptibility to schizophrenia.

Method

This meta-analysis gathered data from 25 case–control studies including a total of 8384 patients with schizophrenia and 8821 controls in order to identify the relationship between the rs6265 single nucleotide polymorphism and the disease, evaluating the combined odds ratio and 95% confidence intervals under 5 different genetic models. Validation followed the “Leave one out” method, and we used the Egger test and Begg's funnel plot to identify publication bias.

Results

Research into the rs6265 (G/A) polymorphism revealed a non-significant association with schizophrenia in all 5 genetic models; in the subgroup analysis, no association was found between white and Asian populations, with a p value>.05.

Conclusions

Overall, the updated meta-analysis revealed that rs6265 exonic polymorphisms do not increase susceptibility to this disease. However, to better understand the pathogenesis of the disease, there is a need for further case–control studies into the BDNF polymorphism including larger sample sizes and different ethnic groups.

Keywords:
Schizophrenia
Genetic polymorphism
Meta-analysis
BDNF
Neuropsychiatric disorder
Resumen
Introducción

Se sabe que los polimorfismos del gen BDNF provocan alteraciones neuronales y parecen ser un factor causal en muchos trastornos neuropsiquiátricos. Es por ello que se han llevado a cabo varios metaanálisis y estudios de casos y controles con el objetivo de evaluar la posible relación entre BDNF y la esquizofrenia.

Método

Realizamos un metaanálisis de 25 estudios de casos y controles, que incluyó un total de 8.384 pacientes con esquizofrenia y 8.821 controles. Se analizó la relación entre el polimorfismo de nucleótido simple rs6265 y la esquizofrenia mediante odds ratios combinados y sus intervalos de confianza del 95% con 5 modelos genéticos diferentes. Utilizamos el método de validación cruzada dejando uno fuera («leave one out»), la prueba de Egger y el gráfico en embudo de Begg para identificar posibles sesgos de publicación.

Resultados

Los estudios sobre el polimorfismo rs6265 (G/A) muestran una asociación no significativa con la esquizofrenia en los 5 modelos genéticos. En el análisis por subgrupos, no se encontró relación con las poblaciones caucásica y asiática (p>0,05).

Conclusiones

La presencia de polimorfismos rs6265 no aumenta la predisposición a desarrollar esquizofrenia. Sin embargo, se deben realizar más estudios de casos y controles sobre polimorfismos de BDNF, con muestras más numerosas y con individuos de diferentes grupos étnicos, para comprender mejor los mecanismos patogénicos de la enfermedad.

Palabras clave:
Esquizofrenia
Polimorfismo genético
Metaanálisis
BDNF
Trastorno neuropsiquiátrico
Texto completo
Introduction

Schizophrenia (SCZ) affects 1% of the world's total population, and it is one of the essential neurologic disorders.1 The etiopathogenesis of this disease is quite complex and involves the interaction between several genetic and environmental factors.2,3 Genetic associations and neuropathological studies indicate that the modifications in synapse density cause these variations in the organization of the macroscale connectome in this psychiatric disease.4–7 Younger adults with this psychiatric condition are prone to age-related diseases, such as diabetes and cardiovascular disease. The age of onset of this disease from early childhood (6 years) to the youngest adults (20 years old), and earlier studies have shown that the mean age of 19 years has an ultra-high risk of this disease.8 Young SCZ adults are susceptible to aging-related conditions like diabetes mellitus (DM) and cardiovascular diseases (CVD).9–12 The average life expectancy of the individual with this disease condition is between 15 and 20 years lesser than that of the healthy individual,13,14 and the patients have 2–12 times the overall age-related mortality rate than the general population.15–17 GWAS on the genetic association of SCZ has recently been published, and it has been reported that the genes DRD2, GRM3, GRIN2A, SRR, GRIA1, BDNF, NRG1, COMT, and AKT1 are associated with the pathogenesis of this disease.18 Among these genes, BDNF is the most acceptable studied gene to find the relationship and pathogenesis of this disease,19 and this gene expansion is a brain-derived neurotrophic factor that belongs to the group of neurotrophins on chromosome 11 (11p14.1).20 It is responsible for various brain development processes such as neuronal development, neurite growth, and neuron survival.21 Many single nucleotide polymorphisms (SNPs) have been studied to identify the link to schizophrenia.22–24 A main functional genetic variation was discovered at the molecular level of this gene at codon 66, which leads to the substitution of valine (Val) and methionine (Met). The alteration in neurons and BDNF secretion affects the hippocampal brain function due to this polymorphism.25 rs6265 is also known as Val66Met or G196A. It has been extensively studied in relationship with schizophrenia among Asian, Caucasian, and Mixed populations.26–28 Many research projects can show results of type I (false positive) and therefore cannot recognize type II (false negative), which makes it challenging to make medical decisions when the data published contain conflicts or tiny sample sizes, which are shown by meta-analysis.29 We have investigated the relationship between the rs6265 polymorphism and susceptibility to SCZ based on the PRISMA guidelines.30

Subjects, materials, and methodsData sources

Online databases (Google Scholar, Medline, PubMed, PsycINFO, and Embase) were reviewed checked from January 2005 to May 2021 for all case–control studies assessing any genetic variants and schizophrenia in humans. Abstract, letters, and other than English language articles were omitted in this study. The Medical terms and keywords used for the search were schizophrenia or SCZ or BDNF or rs6265 gene polymorphism or Psychosis susceptibility syndrome or mutation or genes or genotype.

Study selection

The research articles were examined on the source of our selection criteria for further procedures. The study includes a case–control design for assessing risk links between BDNF polymorphism and SCZ, articles including sample size, allelic and genotypic frequencies were freely accessible, schizophrenic patients diagnosed on the DSM-IV criteria. Therefore, the research performed by cell lines, animal models, state of the art, case report, insufficient genotypic information were excluded.

Data extraction

Two authors (VM and RV) individually obtained the data and variations fixed by a group conversation. The obtained information: author name, year of publication, country of study, population background, source of DNA, sample size (cases/controls), Hardy Weinberg Equilibrium (HWE), NOS score, and genotyping approaches were mined from certain studies (Table 1). Based on the HWE with p-value (<0.05) and NOS, the value of those studies was evaluated. The selection of the study, comparability between the parameters of the study, and study exposure are the three critical features of NOS with a rating of six or more were examined for this study.

Table 1.

The characteristics of included studies in the meta-analysis.

Author name  Year  Study region  Ethnicity  Source of DNA  Diagnostic criteria  No. of cases/controlsNOS  Genotyping method 
Anttila et al.  2005  Finland  Caucasian  Blood  DSM-IV  94  98  RT-PCR 
Chen et al.  2006  China  Asian  Blood  DSM-IV  560  576  PCR 
Chen et al.  2014  Taiwan  Asian  Blood  DSM-IV  151  126  PCR 
Ho et al.  2006  USA  Caucasian  Blood  DSM-III-R or DSM-IV  293  144  PCR 
Kawashima et al.  2009  Japan  Asian  NA  DSM-IV  1111  1100  NA 
Kim  2018  Korea  Asian  Blood  DSM-IV  157  241  PCR 
Kumar et al.  2020  India  Asian  Blood  DSM IV and ICD10  50  50  ARMS-PCR 
Li et al.  2013  China  Asian  Blood  DSM-IV  373  318  RFLP 
Lu et al.  2012  China  Asian  Blood  DSM-IV  112  394  NA 
Morozova et al.  2021  Russia  Caucasian  Blood  ICD-10  767  655  RT-PCR 
Naoe et al.  2007  Japan  Asian  Blood  DSM-IV  211  205  PCR 
Pae et al.  2012  Korea  Asian  Blood  DSM-IV  221  170  PCR 
Pereira et al.  2005  UK  Caucasian  Blood  DSM-IV  321  350  PCR 
Qian et al.  2007  China  Asian  Blood  DSM-IV  604  650  NA 
Ryabokowski et al.  2008  Poland  Caucasian  NA  NA  129  92  NA 
Sotiropoulou et al.  2013  Greece  Caucasian  Blood  GHQ-28  275  297  PCR 
Takahashi et al.  2008  Japan  Asian  Blood  ICD-10  33  29  PCR 
Tochigi et al.  2006  Japan  Asian  Blood  DSM-IV  401  569  NA 
Watanabe et al.  2006  Japan  Asian  Blood  DSM-IV  349  423  NA 
Wysiecka et al.  2013  Poland  Caucasian  NA  ICD-10  194  96  NA 
Yi et al.  2011  China  Asian  Blood  DSM-IV  353  394  NA 
Zakharyan et al.  2014  Armenia  Asian  Blood  ICD-10, DSM-IV  103  105  NA 
Zhang et al.  2012  USA  Caucasian  Blood  DSM-IV  441  649  NA 
Zhang et al.  2018  China  Asian  Blood  DSM-IV-TR Axis I  694  725  TaqMan assays 
Zhou et al.  2010  China  Asian  Blood  DSM-IV  387  365  PCR 

NA; not available, PCR; polymerase chain reaction, RT; real-time; NOS; Newcastle Ottawa Scale; RFLP; Restriction Fragment Length Polymorphism, DSM-IV; Diagnostic and Statistical Manual of Mental Disorders-IV, ICD-10; International Classification of Diseases 10th Revision, GHQ-28; General Health Questionnaire-28.

Statistical analysis

BDNF genes were selected to identify the significant association with SCZ. The author has selected the SNP rs6265 based on the number of studies available in the electronic database. The risk association was considered by odds ratios (ORs) with a 95% confidence interval (CIs) with p-value (<0.05) under allelic (G vs. A) (G-major, A-minor allele), homozygote (GG vs. AA), heterozygote (GA vs. AA), dominant (GG+GA vs. AA) and recessive (GG vs. GA+AA) genetic models. Q-statistic tests and I2 values were considered to identify the heterogeneity of the selected SNP.31 Based on the I2 value, random-effects (DerSimonian and Laird's) and fixed-effects (Mantel-Haenszel) were implemented.32 The Begg's funnel plot and Egger's linear test were done to avoid publication bias.33 The leave one out method was used to confirm the adaptability of this meta-analysis for the sensitivity test: the Rev-Man 5.4 software generated all the statistical meta-analyses, forest plots, and funnel plots.

ResultsLiterature extraction

835 potentially relevant studies were identified through different databases related to genetic polymorphism in schizophrenia. 650 studies based on abstracts or full study articles were skipped due to irrelevant genetic information. There are 108 possibly eligible articles selected that are related to the objective of this research. The study flow diagram shows that only 2526–28,34–55 articles were considered based on the eligibility criteria (Fig. 1). All selected studies were evaluated using HWE and NOS. The information obtained from the selected studies is mentioned in Table 2.

Figure 1.

Study flow diagram.

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Table 2.

Genotypic and allelic frequency of rs6265 polymorphism.

Author name & year  CaseAllelic frequencyControlAllelic frequencyHWE/Chi 
  GG  GA  AA  GG  GA  AA   
Anttila et al., 2005  65  26  156  32  73  20  166  30  0.03/4.43 
Chen et al., 2006  157  259  144  573  547  158  291  127  607  545  0.75/0.10 
Chen et al., 2014  35  79  37  149  153  38  57  31  133  119  0.29/1.08 
Ho et al., 2006  182  100  11  464  122  95  43  233  55  0.68/0.16 
Kawashima 2009  394  516  201  1304  918  365  529  206  1259  941  0.56/0.34 
Kim 2018  45  88  24  178  136  75  123  43  273  209  0.54/0.37 
Kumar et al., 2020  29  18  76  24  35  12  82  18  0.19/1.75 
Li et al., 2013  104  187  82  395  351  75  170  73  320  316  0.22/1.52 
Lu et al., 2012  27  56  29  110  114  111  193  90  415  373  0.73/0.12 
Morozova et al., 2021  566  188  13  1320  214  459  177  19  1095  215  0.69/0.15 
Naoe et al., 2007  71  107  33  249  173  77  104  24  258  152  0.21/1.56 
Pae et 2012  77  106  38  260  182  58  81  31  197  143  0.77/0.10 
Pereira 2005  229  83  541  101  208  131  11  547  153  0.07/3.21 
Qian et al., 2007  152  312  140  616  592  174  309  167  657  643  0.21/1.57 
Ryabokowski 2008  84  34  11  202  56  56  33  145  39  0.48/0.50 
Sotiropoulou et al., 2013  79  134  62  292  258  84  129  84  297  297  0.02/5.12 
Takahashi et al., 2008  12  15  39  27  13  11  37  21  0.34/0.99 
Tochigi et al., 2006  151  185  65  487  315  201  273  95  675  463  0.88/0.02 
Watanabe et al., 2006  122  163  64  407  291  142  207  74  491  355  0.92/0.01 
Wysiecka et al., 2013  136  51  323  65  72  22  166  26  0.83/0.04 
Yi et al., 2011  93  186  74  372  334  111  193  90  415  373  0.73/0.12 
Zakharyan et al., 2014  46  51  143  63  68  35  171  39  0.30/1.10 
Zhang et al., 2012  104  236  101  444  438  175  347  127  697  601  0.05/3.67 
Zhang et al., 2018  173  352  169  698  690  217  345  163  779  671  0.24/1.34 
Zhou et al., 2010  94  208  85  396  378  91  197  77  379  351  0.12/2.40 

HWE; Hardy Weinberg Equilibrium.

BDNF gene polymorphism with SCZMeta-analysis of rs6265

The heterogeneity was carried out in this SNP and found the no significance in homozygous, heterozygous and recessive (I2=0%) and moderate I2 in allelic model (I2=33%) and dominant model (I2=39%) was adopted fixed effect model. The p-value (>0.05) exposed irrelevant relationship with SCZ risk in allelic, homozygote, heterozygote, dominant and recessive model shows (OR=1.01, 95% CI=0.96–1.05, z=0.34, p=0.73: OR=1.03, 95% CI=0.94–1.14, Z=0.70, p=0.48; OR=1.00, 95% CI=0.92–1.09, z=0, p=1.00; OR=1.01, 95% CI=0.95–1.08, z=0.29, p=0.77; OR=1.01, 95% CI=0.93–1.10, z=0.26, p=0.80). The Meta-analysis data was generated as a forest plot shown in Figs. 2–6. In the investigated models, the Egger's test and Begg's funnel plot (Supplementary file 1) were performed to identify the publication bias.

Figure 2.

Forest plots representing the overall risk for SNP (rs6265) polymorphism in the allelic model.

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Figure 3.

Forest plots representing the overall risk for SNP (rs6265) polymorphism in homozygote model.

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Figure 4.

Forest plots representing the overall risk for SNP (rs6265) polymorphism in heterozygote model.

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Figure 5.

Forest plots representing the overall risk for SNP (rs6265) polymorphism in the dominant model.

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Figure 6.

Forest plots representing the overall risk for SNP (rs6265) polymorphism in recessive model.

(0.55MB).
Subgroup investigation of rs6265 polymorphism with SCZ

To analyze the association between the ethnicity and rs6265 polymorphism in SCZ, the authors have done the subgroup analysis by separating the selected studies as Caucasian, Asian and mixed. From a total of 25 studies, it was found that 17 are Asian and 8 have Caucasian ethnic origins. The subgroup analysis of the Asian population revealed no heterogeneity in all the investigated genotypic models {allelic (I2=10%); homozygous, heterozygous, recessive (I2=0%); dominant (I2=25%)}. Hence, the fixed effect was implemented for all the genetic models which showed no relationship in the SCZ with allelic, homozygote, heterozygote, dominant and recessive model shows (OR=1.02, 95% CI=0.97–1.08, z=0.89, p=0.37; OR=1.04, 95% CI=0.94–1.15, z=0.73, p=0.47; OR=1.00, 95% CI=0.91–1.09, z=0.10, p=0.92; OR=1.01, 95% CI=0.99–1.04, z=1.05, p=0.30; OR=1.02, 95% CI=0.93–1.11, z=0.36, p=0.72).

Likewise, the subgroup analysis of SNP in rs6265 in Caucasian population revealed no heterogeneity in homozygous (I2=25%) and recessive (I2=29%), moderate heterogeneity in heterozygous (I2=30%), substantial heterogeneity in allelic (I2=55%), and dominant (I2=55%). Depend on the I2 value, the random and fixed effect was applied which revealed insignificant association in the SCZ with allelic, homozygote, heterozygote, dominant and recessive model shows (OR=0.96, 95% CI=0.82–1.13, z=0.55, p=0.58, OR=1.01, 95% CI=0.80–1.27, z=0.09, p=0.93; OR=1.02, 95% CI=0.83–1.27, z=0.22, p=0.83; OR=0.96, 95% CI=0.78–1.17, z=0.41, p=0.68; OR=0.98, 95% CI=0.80–1.20, z=0.18, p=0.86). The meta-data subgroup analyses were represented as forest plots and Begg's funnel plots (Supplementary file 2).

Sensitivity analysis

The sensitivity test was implemented using the leave-one-out procedure to analyze the influence on pooled ORs of each research. There were no changes in pooled ORs that consistently confirmed our results. In addition, Begg's funnel plot and Egger's test were used to identifying the study's publication bias and conclude that there is no publication bias for the investigated polymorphism in any of the genetic models.

Discussion

Schizophrenia is a complex inheritance disease that weakens neurons in the brain, and the symptoms of this neuropsychiatric disorder are delusions, hallucinations, disorganized thoughts, and lack of motivation.56 The successful investigation of many genes in the last few decades has provided valuable insights into the molecular epidemiology of this disease.57 Numerous studies on genetic polymorphism found the>100 schizophrenia-linked loci and revealed that it is a multiple genetic disorder (polygenic) defined by distinct genetic variations but with a small effect size.58,59 Studies of the association of candidate genes have revealed specific genes that could be assumed to contribute to this psychiatric condition in both functional and positional, such as neuregulin 1 (NRG1),60 brain-derived neurotrophic factor (BDNF),61 catechol-O-methyltransferase (COMT)62 and protein kinase 1 (AKT1).63 The most extensively studied SNP is rs6265 in the BDNF gene, which shows the possible association with this disease.19 Therefore, a BDNF meta-analysis of the rs6265 polymorphism was achieved, which can help assess the polymorphism's effect in a larger sample. In addition, through the genotyping testing, it might be helpful to diagnose this disease in the earlier stage. This meta-analysis did the subgroup investigation of Asian and Caucasian ethnic backgrounds that contradict the findings of existing case–control researches.

The meta-analysis of BDNF rs6265 genetic alteration showed an inconsistent relationship with all the genetic models with a p-value>0.05. The subgroup analysis also revealed no association between the selected SNP (rs6265) with schizophrenia in Caucasian and Asian populations. Three studies34,47,52 investigated the rs6265 polymorphism had insignificant sample sizes, representing probable population classification. The cross-validation was done by the leave one out method, Egger's test, and generating Begg's funnel plot to identify the publication bias. In agreement with our results, earlier meta-analyses have also recommended that BDNF rs6265 polymorphism is not associated with SCZ.19,38,63

In contrast,64 study showed a significant association with the heterozygous model (Met/Met carriers) with schizophrenia, and23 revealed a significant association between Met/Met carriers with Asian, Caucasian, and mixed SCZ populations. However, this study consists of 8384 patients with schizophrenia and 8821 controls (no sign of any psychiatric disorder) for the current meta-analysis. Compared to earlier meta-studies, the sample size is small, but the authors have included the most recently published case–control studies and compared for the same (Kumar et al., 2020, Morozova et al., 2021). The main limitation of this meta-study is that we did not identify the possible relationship between the rs6265 polymorphism and the heterogeneity of subclinical schizophrenic conditions.

Conclusion

In this meta-analysis, the SNP rs6265 in BDNF exposed the irrelevant association with this disease, and the gene is not susceptible to schizophrenia. The collected literature studies might indicate that the role of BDNF in several neuropsychiatric disorders, but it is not a functional gene in this disease. More research has been done in the same parameters in the past few decades, but only a few studies have shown the associated results. Therefore, BDNF could be a perfect target for this psychiatric condition to diagnose the disease pathogenesis. However, as expected, the results were not obtained in the previous case–control studies due to the lack of research design, inadequate sample size, and ethnic selection. So, in the future, to understand the pathogenesis of this disease through this gene, the researcher should choose a proper ethnic background with larger sample size.

Author's contributions

VM extracted the literature from the database, assessed the allelic and genotypic frequency, done the statistical analysis, and generated the plots.

RV design, revise and corrected the manuscript.

Availability of data and material

Not applicable.

Code availability

Not applicable.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

All authors approved the manuscript for publication.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflict of interest

The authors declare no conflict of interest to report.

Acknowledgment

The authors thank the Chettinad Academy of Research Education (CARE) for the constant support and encouragement.

References
[1]
N.C. Andreasen.
Schizophrenia: the fundamental questions.
Brain Res Rev, 31 (2000), pp. 106-112
[2]
L. Hosak.
New findings in the genetics of schizophrenia.
World J Psychiatry, 3 (2013), pp. 57
[3]
K.Q. Do.
Schizophrenia: genes, environment, and neurodevelopment.
Revue Medicale Suisse, 9 (2013), pp. 1672-1674
[4]
A. Berdenis van Berlekom, C.H. Muflihah, G.J. Snijders, H.D. MacGillavry, J. Middeldorp, E.M. Hol, R.S. Kahn, L.D. De Witte.
Synapse pathology in schizophrenia: a meta-analysis of postsynaptic elements in postmortem brain studies.
Schizophr Bull, 46 (2020), pp. 374-386
[5]
D. Schijven, D. Kofink, V. Tragante, M. Verkerke, S.L. Pulit, R.S. Kahn, J.J. Luykx.
Comprehensive pathway analyses of schizophrenia risk loci point to dysfunctional postsynaptic signaling.
Schizophr Res, 199 (2018), pp. 195-202
[6]
J. Soler, L. Fañanás, M. Parellada, M.O. Krebs, G.A. Rouleau, M. Fatjó-Vilas.
Genetic variability in scaffolding proteins and risk for schizophrenia and autism spectrum disorders: a systematic review.
J Psychiatry Neurosci, 43 (2018), pp. 223
[7]
A.A. Coley, W.J. Gao.
PSD95: a synaptic protein implicated in schizophrenia or autism?.
Prog Neuropsychopharmacol Biol Psychiatry, 82 (2018), pp. 187-194
[8]
N. Gogtay, N.S. Vyas, R. Testa, S.J. Wood, C. Pantelis.
Age of onset of schizophrenia: perspectives from structural neuroimaging studies.
Schizophr Bull, 37 (2011), pp. 504-513
[9]
C.H. Hennekens, A.R. Hennekens, D. Hollar, D.E. Casey.
Schizophrenia and increased risks of cardiovascular disease.
Am Heart J, 150 (2005), pp. 1115-1121
[10]
P.W. Wilson, R.B. D’Agostino, D. Levy, A.M. Belanger, H. Silbershatz, W.B. Kannel.
Prediction of coronary heart disease using risk factor categories.
Circulation, 97 (1998), pp. 1837-1847
[11]
A.J. Mitchell, D. Malone.
Physical health and schizophrenia.
Curr Opin Psychiatry, 19 (2006), pp. 432-437
[12]
R.B. D’Agostino, S. Grundy, L.M. Sullivan, P. Wilson, CHD Risk Prediction Group.
Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.
JAMA, 286 (2001), pp. 180-187
[13]
B. Kirkpatrick, E. Messias, P.D. Harvey, E. Fernandez-Egea, C.R. Bowie.
Is schizophrenia a syndrome of accelerated aging?.
Schizophr Bull, 34 (2008), pp. 1024-1032
[14]
S. Saha, D. Chant, J. McGrath.
A systematic review of mortality in schizophrenia: is the differential mortality gap worsening over time?.
Arch Gen Psychiatry, 64 (2007), pp. 1123-1131
[15]
M.T. Tsuang, R.F. Woolson.
Excess mortality in schizophrenia and affective disorders: do suicides and accidental deaths solely account for this excess?.
Arch Gen Psychiatry, 35 (1978), pp. 1181-1185
[16]
S. Brown.
Excess mortality of schizophrenia: a meta-analysis.
Br J Psychiatry, 171 (1997), pp. 502-508
[17]
D.E. Casey, T.E. Hansen, J. Meyer, H. Nasrallah.
Excessive mortality and morbidity associated with schizophrenia.
Med Illness Schizophr, 17 (2009), pp. 36
[18]
Y. Wu, H. Cao, A. Baranova, H. Huang, S. Li, L. Cai, S. Rao, M. Dai, M. Xie, Y. Dou, Q. Hao.
Multi-trait analysis for genome-wide association study of five psychiatric disorders.
Transl Psychiatry, 10 (2020),
[19]
X. Zhao, Y. Huang, K. Chen, D. Li, C. Han, Q. Kan.
The brain-derived neurotrophic factor Val66Met polymorphism is not associated with schizophrenia: an updated meta-analysis of 11,480 schizophrenia cases and 13,490 controls.
Psychiatry Res, 225 (2015), pp. 217-220
[20]
I.M. Hanson, A. Seawright, V. van Heyningen.
The human BDNF gene maps between FSHB and HVBS1 at the boundary of 11p13-p14.
Genomics, 13 (1992), pp. 1331-1333
[21]
S.D. Kuipers, C.R. Bramham.
Brain-derived neurotrophic factor mechanisms and function in adult synaptic plasticity: new insights and implications for therapy.
Curr Opin Drug Discov Dev, 9 (2006), pp. 580
[22]
C.C. Zai, M. Manchia, V. De Luca, A.K. Tiwari, A. Squassina, G.C. Zai, J.L. Kennedy.
Association study of BDNF and DRD3 genes in schizophrenia diagnosis using matched case–control and family based study designs.
Prog Neuropsychopharmacol Biol Psychiatry, 34 (2010), pp. 1412-1418
[23]
M. Kheirollahi, E. Kazemi, S. Ashouri.
Brain-derived neurotrophic factor gene Val66Met polymorphism and risk of schizophrenia: a meta-analysis of case–control studies.
Cell Mol Neurobiol, 36 (2016), pp. 1-10
[24]
R. Saravani, H.R. Galavi, M.L. Sargazi.
Catechol-O-methyltransferase (COMT) gene (Val158Met) and brain-derived neurotrophic factor (BDNF)(Val66Met) genes polymorphism in schizophrenia: a case–control study.
Iran J Psychiatry, 12 (2017), pp. 265
[25]
M.F. Egan, M. Kojima, J.H. Callicott, T.E. Goldberg, B.S. Kolachana, A. Bertolino, D.R. Weinberger.
The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function.
[26]
P.K. Kumar, P. Mitra, R. Ghosh, S. Sharma, N. Nebhinani, P. Sharma.
Association of circulating BDNF levels with BDNF rs6265 polymorphism in schizophrenia.
Behav Brain Res, 15 (2020), pp. 112832
[27]
M. Neves-Pereira, J.K. Cheung, A. Pasdar, F. Zhang, G. Breen, P. Yates, D.M. St Clair.
BDNF gene is a risk factor for schizophrenia in a Scottish population.
Mol Psychiatry, 10 (2005), pp. 208-212
[28]
A. Morozova, Y. Zorkina, K. Pavlov, O. Pavlova, O. Abramova, V. Ushakova, V. Chekhonin.
Associations of genetic polymorphisms and neuroimmune markers with some parameters of frontal lobe dysfunction in schizophrenia.
Front Psychiatry, (2021), pp. 12
[29]
Y.H. Lee.
An overview of meta-analysis for clinicians.
Korean J Intern Med, 33 (2018), pp. 277
[30]
S.S. Ahmed, R.A. Husain, S. Kumar, V. Ramakrishnan.
Association between NOS1 gene polymorphisms and Schizophrenia in Asian and Caucasian populations: a meta-analysis.
Neuromol Med, 19 (2017), pp. 452-461
[31]
J.P. Higgins, S.G. Thompson, J.J. Deeks, D.G. Altman.
Measuring inconsistency in meta-analyses.
[32]
R. DerSimonian, N. Laird.
Meta-analysis in clinical trials.
Control Clin Trials, 7 (1986), pp. 177-188
[33]
M. Egger, G.D. Smith, M. Schneider, C. Minder.
Bias in meta-analysis detected by a simple, graphical test.
BMJ, 315 (1997), pp. 629-634
[34]
S. Anttila, A. Illi, O. Kampman, K.M. Mattila, T. Lehtimäki, E. Leinonen.
Lack of association between two polymorphisms of brain-derived neurotrophic factor and response to typical neuroleptics.
J Neural Transm, 112 (2005), pp. 885-890
[35]
Q.Y. Chen, Q. Chen, G.Y. Feng, C.L. Wan, K. Lindpaintner, L.J. Wang, L. He.
Association between the brain-derived neurotrophic factor (BDNF) gene and schizophrenia in the Chinese population.
Neurosci Lett, 397 (2006), pp. 285-290
[36]
S.L. Chen, S.Y. Lee, Y.H. Chang, T.Y. Wang, S.H. Chen, C.H. Chu, R.B. Lu.
The BDNF Val66Met polymorphism and plasma brain-derived neurotrophic factor levels in Han Chinese heroin-dependent patients.
Sci Rep, 5 (2015), pp. 1-6
[37]
B.C. Ho, P. Milev, D.S. O’Leary, A. Librant, N.C. Andreasen, T.H. Wassink.
Cognitive and magnetic resonance imaging brain morphometric correlates of brain-derived neurotrophic factor Val66Met gene polymorphism in patients with schizophrenia and healthy volunteers.
Arch Gen Psychiatry, 63 (2006), pp. 731-740
[38]
K. Kawashima, M. Ikeda, T. Kishi, T. Kitajima, Y. Yamanouchi, Y. Kinoshita, N. Iwata.
BDNF is not associated with schizophrenia: data from a Japanese population study and meta-analysis.
Schizophr Res, 112 (2009), pp. 72-79
[39]
E.J. Kim, Y.K. Kim.
196G/A of the brain-derived neurotrophic factor gene polymorphisms predicts suicidal behavior in schizophrenia patients.
Psychiatry Investig, 15 (2018), pp. 733
[40]
W. Li, N. Zhou, Q. Yu, X. Li, Y. Yu, S. Sun, X.Y. Zhang.
Association of BDNF gene polymorphisms with schizophrenia and clinical symptoms in a Chinese population.
Am J Med Genet B: Neuropsychiatr Genet, 162 (2013), pp. 538-545
[41]
W. Lu, C. Zhang, Z. Yi, Z. Li, Z. Wu, Y. Fang.
Association between BDNF Val66Met polymorphism and cognitive performance in antipsychotic-naive patients with schizophrenia.
J Mol Neurosci, 47 (2012), pp. 505-510
[42]
Y. Naoe, T. Shinkai, H. Hori, Y. Fukunaga, K. Utsunomiya, S. Sakata, C. Matsumoto, K. Shimizu, R. Hwang, O. Ohmori, J. Nakamura.
No association between the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and schizophrenia in Asian populations: evidence from a case–control study and meta-analysis.
Neurosci Lett, 415 (2007), pp. 108-112
[43]
C.U. Pae, A. Chiesa, S. Porcelli, C. Han, A.A. Patkar, S.J. Lee, D. De Ronchi.
Influence of BDNF variants on diagnosis and response to treatment in patients with major depression, bipolar disorder, and schizophrenia.
Neuropsychobiology, 65 (2012), pp. 1-11
[44]
L. Qian, J. Zhao, Y. Shi, X. Zhao, G. Feng, F. Xu, L. He.
Brain-derived neurotrophic factor and risk of schizophrenia: an association study and meta-analysis.
Biochem Biophys Res Commun, 353 (2007), pp. 738-743
[45]
J.K. Rybakowski.
BDNF gene: functional Val66Met polymorphism in mood disorders and schizophrenia.
(2008),
[46]
M. Sotiropoulou, C. Mantas, P. Bozidis, M. Marselos, V. Mavreas, T. Hyphantis, K. Antoniou.
BDNF serum concentrations in first psychotic episode drug-naive schizophrenic patients: associations with personality and BDNF Val66Met polymorphism.
Life Sci, 92 (2013), pp. 305-310
[47]
T. Takahashi, M. Suzuki, M. Tsunoda, Y. Kawamura, N. Takahashi, N. Maeno, N. Ozaki.
The association of genotypic combination of the DRD3 and BDNF polymorphisms on the adhesion interthalamica and medial temporal lobe structures.
Prog Neuropsychopharmacol Biol Psychiatry, 32 (2008), pp. 1236-1242
[48]
M. Tochigi, T. Otowa, M. Suga, M. Rogers, T. Minato, H. Yamasue, T. Sasaki.
No evidence for an association between the BDNF Val66Met polymorphism and schizophrenia or personality traits.
Schizophr Res, 87 (2006), pp. 45-47
[49]
Y. Watanabe, T. Muratake, N. Kaneko, A. Nunokawa, T. Someya.
No association between the brain-derived neurotrophic factor gene and schizophrenia in a Japanese population.
Schizophr Res, 84 (2006), pp. 29-35
[50]
J. Pełka-Wysiecka, M. Wroński, A. Jasiewicz, A. Grzywacz, P. Tybura, J. Kucharska-Mazur, P. Bieńkowski, J. Samochowiec.
BDNF rs 6265 polymorphism and COMT rs 4680 polymorphism in deficit schizophrenia in Polish sample.
Pharmacol Rep, 65 (2013 Sep 1), pp. 1185-1193
[51]
Z. Yi, C. Zhang, Z. Wu, W. Hong, Z. Li, Y. Fang, S. Yu.
Lack of effect of brain derived neurotrophic factor (BDNF) Val66Met polymorphism on early-onset schizophrenia in Chinese Han population.
Brain Res, 1417 (2011), pp. 146-150
[52]
R. Zakharyan, A. Boyajyan.
Brain-derived neurotrophic factor blood levels are decreased in schizophrenia patients and associate with rs6265 genotypes.
Clin Biochem, 47 (2014), pp. 1052-1055
[53]
X.Y. Zhang, D.C. Chen, M.H. Xiu, C.N. Haile, X. Luo, K. Xu, H.P. Zhang, L. Zuo, Z. Zhang, X. Zhang, T.A. Kosten.
Cognitive and serum BDNF correlates of BDNF Val66Met gene polymorphism in patients with schizophrenia and normal controls.
Hum Genet, 131 (2012), pp. 1187-1195
[54]
Y. Zhang, X. Fang, W. Fan, W. Tang, J. Cai, L. Song, C. Zhang.
Interaction between BDNF and TNF-α genes in schizophrenia.
Psychoneuroendocrinology, 89 (2018), pp. 1-6
[55]
D.H. Zhou, Q.Z. Yan, X.M. Yan, C.B. Li, H. Fang, Y.L. Zheng, C.X. Zhang, H.J. Yao, M.H. Xiu, T.R. Kosten, X.Y. Zhang.
The study of BDNF Val66Met polymorphism in Chinese schizophrenic patients.
Prog Neuro-Psychopharmacol Biol Psychiatry, 34 (2010), pp. 930-933
[56]
F. Guan, T. Ni, W. Zhu, L.K. Williams, L.B. Cui, M. Li, H. Gui.
Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction.
Mol Psychiatry, (2021), pp. 1-14
[57]
C. Zhuo, W. Hou, G. Li, F. Mao, S. Li, X. Lin, L. Cheng.
The genomics of schizophrenia: shortcomings and solutions.
Prog Neuropsychopharmacol Biol Psychiatry, 93 (2019), pp. 71-76
[58]
Q. Wang, R. Chen, F. Cheng, Q. Wei, Y. Ji, H. Yang, B. Li.
A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data.
Nat Neurosci, 22 (2019), pp. 691-699
[59]
M. Ikeda, A. Takahashi, Y. Kamatani, Y. Momozawa, T. Saito, K. Kondo, et al.
Genome-wide association study detected novel susceptibility genes for schizophrenia and shared trans-populations/diseases genetic effect.
Schizophr Bull, 45 (2019), pp. 824-834
[60]
H. Stefansson, H. Petursson, E. Sigurdsson, V. Steinthorsdottir, S. Bjornsdottir, T. Sigmundsson, S. Ghosh, J. Brynjolfsson, S. Gunnarsdottir, O. Ivarsson, T.T. Chou.
Neuregulin 1 and susceptibility to schizophrenia.
Am J Hum Genet, 71 (2002), pp. 877-892
[61]
S.J. Glatt, S.V. Faraone, M.T. Tsuang.
Association between a functional catechol O-methyltransferase gene polymorphism and schizophrenia: meta-analysis of case–control and family-based studies.
Am J Psychiatry, 160 (2003), pp. 469-476
[62]
E.S. Emamian, D. Hall, M.J. Birnbaum, M. Karayiorgou, J.A. Gogos.
Convergent evidence for impaired AKT1-GSK3β signaling in schizophrenia.
Nat Genet, 36 (2004), pp. 131-137
[63]
M.Q. Xu, D. St Clair, J. Ott, G.Y. Feng, L. He.
Brain-derived neurotrophic factor gene C-270T and Val66Met functional polymorphisms and risk of schizophrenia: a moderate-scale population-based study and meta-analysis.
Schizophr Res, 91 (2007), pp. 6-13
[64]
M. Gratacòs, J.R. González, J.M. Mercader, R. de Cid, M. Urretavizcaya, X. Estivill.
Brain-derived neurotrophic factor Val66Met and psychiatric disorders: meta-analysis of case–control studies confirm association to substance-related disorders, eating disorders, and schizophrenia.
Biol Psychiatry, 61 (2007), pp. 911-922
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