Abstract
Objective
Zinc finger protein 804A (ZNF804A) protein participates in embryonic neural repair and development. The single nucleotide polymorphism rs1344706 in ZNF804A gene is closely related to functional abnormalities of the human brain. However, these results are inconsistent. This association was verified by meta-analysis in this study.
Methods
Fifteen studies on functional magnetic resonance imaging involving 1710 healthy individuals were included in the systematic review and meta-analysis used by Anisotropic Effect-Size Signed Differential Mapping software.
Results
Functional connectivity of the right dorsolateral prefrontal cortex (rDLPFC)–left hippocampus in the rs1344706 risk allele carrier was significantly increased (z = 2.066, p < 0.001), while those in the rDLPFC–left middle frontal gyrus (z = −1.420, p < 0.001) and rDLPFC–right middle frontal gyrus (z = −1.298, p < 0.001) were significantly decreased. Neural activity of the left anterior cingulate gyrus in the rs1344706 risk allele carrier was significantly decreased (z = −2.525, p < 0.001). Sensitivity analysis was almost stable, and no publication bias was found.
Conclusion
The changes in brain function have a clear correlation with ZNF804A gene in healthy individuals, which indicate the contribution of genetic variants on brain dysfunction.
Registration Number
This meta-analysis is registered in PROSPERO (No. CRD42016051331).
Keywords: functional magnetic resonance imaging, zinc finger protein 804A, meta-analysis
Introduction
Genome-wide association (GWA) studies have revealed that zinc finger protein 804 (ZNF804A) gene is associated with the susceptibility of mental disorders, such as schizophrenia, bipolar disorder, and depression.1–3 ZNF804A encodes a transcription factor; it is highly expressed in the brain and involved in the development and functionality of the human brain.4 Carriers with risk allele in ZNF804A have higher risk for developing mental illnesses than non-carriers.3 A single-nucleotide polymorphism (SNP) named rs1344706 in ZNF804A was first identified by a previous GWA study in worldwide population.5 From the studies that detected the functional effect of ZNF804A gene polymorphisms, the most reproducible result is that the risk allele A in rs1344706 is associated with the neurophenotype of mental disorders, patients’ performance, and their treatment prognosis.6,7 Our previous meta-analysis in Chinese population detected the relationship between rs1344706 genotype distribution and susceptibility and drug efficacy for schizophrenia and concluded that risk allele A carriers in this SNP had higher risk for schizophrenia but not for treatment efficacy.8 Furthermore, another meta-analysis that included studies in worldwide population demonstrated a very strong association between the risk allele A in rs1344706 and risk for schizophrenia.9
The human brain is the foundation of mental activity. Brain injury and developmental abnormalities can directly lead to the occurrence of mental disorders.10 Neuroimaging studies suggest that patients with mental disorders, such as schizophrenia, have certain abnormalities on brain function.11,12 “Imaging genetics” aims to detect the associations between risk genes and the changes in brain function and/or structure of individuals with mental disorders, and to clarify the contributions of these risk genes to abnormalities in the development of the human brain. Numerous studies showed that the ZNF804A gene might be associated with brain function and structure in healthy individuals and patients with mental disorders.13,14 Lencz et al verified the effects of rs1344706 in schizophrenia risk allele gene ZNF804A on neuroanatomy and neurocognitive phenotype.15 Research on functional connectivity by Esslinger et al found that the risk allele in rs1344706 carrier had a significantly increased functional coupling in the right amygdala.16 However, another study revealed that risk allele in rs1344706 had a negative effect on functional connectivity between the right dorsolateral prefrontal cortex (rDLPFC) and the left hippocampus.17 For neural activity studies in healthy individuals, risk allele carriers exhibited a significant risk allele dose effect on neural activity in the medial prefrontal cortex and left temporoparietal cortex under a theory-of-mind task.18 In a neural activity research based on the amplitude of low-frequency fluctuation, the risk allele A exhibited a negative effect on the left calcarine gyrus.19
Several studies have explored the effects of risk allele in rs1344706 of ZNF804A gene on human brain functional connectivity and neural activity in healthy individuals. However, the affected brain regions and effect sizes are inconsistent due to the differences in clinical baselines and research methods. Previous brain imaging studies also have a relatively small sample size and low statistical test power. In addition, systematic conclusions to comprehensively determine the effects of risk allele A on brain function are lacking. Therefore, this study aimed to explore these effects by signed differential mapping meta-analysis and systematic review in healthy individuals, which could further determine the important role of the SNP rs1344706 in ZNF804A gene in the development of schizophrenia.
Materials and Methods
Registration
This systematic review and meta-analysis was registered in PROSPERO (CRD42016051331).
Study Design
Voxel-based and general meta-analysis methods based on clinical data of statistical maps, peak coordinates, and statistical effect size, which were collected from previous association studies of brain function changes and ZNF804A gene rs1344706 polymorphism, were used to design the study.
Search Strategy
This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020 statement.20 PubMed, Medline, ScienceDirect, and Scopus were used to search for literature from January 2006 until April 2021. The following search terms were combined and used: “functional MRI/fMRI/functional magnetic resonance imaging/brain function” and “ZNF804A/rs1344706.” Publications from conferences, monographs, theses, or reference lists in identified studies were also regarded as potential sources to be included in the systematic review.
Selection Criteria
The studies that met the following criteria were included in the meta-analysis: 1) original cross-sectional research that detected the association between ZNF804A gene and brain function; 2) individuals scanned by functional magnetic resonance imaging (fMRI) in the whole brain; 3) comparison of brain function among different genotypes in rs1344706 polymorphism; 4) English publication in peer-reviewed journals and monographs. Studies were excluded if they met the following criteria: 1) data were unavailable or generated from region of interest approaches; 2) repetitive publications; 3) conference papers; 4) fMRI method was not used for detection. Two researchers (LY and FX) independently performed the study search and selection. Furthermore, the citations in the included studies were searched to identify potential eligible studies.
Data Extraction and Literature Quality Assessment
Two independent reviewers (LY and SW) extracted the data. In the first screening, all eligible titles and abstracts of studies were carefully reviewed using Endnote software (EndNote X8, Thomson Corporation). The full texts of the remaining papers were evaluated for inclusion in the meta-analysis. Disagreements were resolved through discussion. The two reviewers independently extracted the specific information in the included articles and recorded these in detail in pre-set standard electronic form. The extracted contents were not limited to the following: 1) general information of the studies (publication year and last name of the first author); 2) characteristics of the investigated sample (sample cohort, gender, mean age, size); 3) scanning parameter, including but not limited to the full width at half maximum; 4) distribution of genotypes and alleles of rs1344706; 5) effect size and its peak coordinates of voxel-based data in brain function of statistically significant differences. If the incomplete data could not be addressed by obtaining the rest of the data from the original authors, then the study was excluded. All data were checked for internal consistency. The quality of the included studies was assessed following the checklist that focused on the clinical and demographic aspects of individual study samples and imaging-specific methodology.21
AES-SDM Analysis
Anisotropic effect-size version of seed-based d mapping (AES-SDM) is a meta-analytic method for voxel-based imaging studies. It reports the peak coordinates of gray and/or white matter differences in the whole brain. The user instructions have been described in a previous study.22 Several meta-analyses on neuropsychiatric disorders were conducted by AES-SDM, including our two previous works.21,23 Four researchers (FX, YH, YL, and ZC) performed the meta-analysis. The main threshold was set at uncorrected p<0.001 (empirically equivalent to corrected p<0.05) with cluster extent≥20 voxels and z score>1.21 Q statistic value with a threshold of p<0.05 was considered to be significantly heterogeneous.24 A leave-one-out jackknife method was used in the sensitivity analysis. Funnel plots were then obtained through Egger’s test to evaluate the possibility of publication bias.25
Results
General Characteristics of the Included Studies
A flowchart of the search process is presented in Figure 1. PRISMA checklist of this meta-analysis is presented in the supplement material. Fifteen studies16–19,26–36 on brain functional connectivity and activity involving 1710 healthy individuals were included in the systematic review and meta-analysis. The general characteristics and research quality assessment of the included studies are shown in Table 1. The main results of risk allele affected regions in healthy individuals in each study are summarized in Table 2. The different brain regions and different effects of rs1344706 risk allele A on functional connectivity and neural activity were exhibited.
Figure 1.
Flowchart of the selection process.
Table 1.
General Characteristics, Imaging Scan Features and Quality Assessment Results Included in the Study
| Author | Year of Publication | Sample Size(n) | Age (Years) | Sex(Male, n) | Ancestry | Genotype Distribution | fMRI Information | Indicators | Quality | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AA | AC | CC | HWE | Tesla | FWHM (mm) | Task | ||||||||
| Esslinger16 | 2009 | 115 | 33.8 | 49 | Caucasian | 43 | 51 | 21 | Yes | 3.0 | 9 | N-back | FC | High |
| Esslinger26 | 2011 | 111 | 33.8 | 49 | Caucasian | 40 | 50 | 21 | Yes | 3.0 | 9 | N-back, Face match | FC | High |
| Rasetti17 | 2011 | 96 | 35 | 44 | NS | 37 | 45 | 14 | NS | 3.0 | 8 | 2-back | FC | High |
| Walter18 | 2011 | 109 | 32.3 | 47 | Caucasian | 42 | 49 | 18 | Yes | 3.0 | 9 | Theory of mind | FC, Activity | High |
| Linden28 | 2013 | 43 | 32.3 | 24 | Caucasian | 11 | 21 | 11 | NS | 1.5 | NS | Face paradigm | Activity | Medium |
| Paulus30 | 2013 | 94 | 23.1 | 66 | Caucasian | 27 | 46 | 21 | NS | 3.0 | NS | N-back | FC, Activity | Medium |
| Thurin27 | 2013 | 208 | 31.4 | 103 | Caucasian | 89 | 93 | 26 | Yes | 3.0 | 8 | Eriksen Flanker | FC, Activity | High |
| Mohnke29 | 2014 | 188 | 34.1 | 94 | Caucasian | 63 | 87 | 38 | Yes | 3.0 | 9 | Theory of mind | Activity | High |
| Cousijn31 | 2015 | 50 | 24 | 23 | Caucasian | 25 | 0 | 25 | Yes | 3.0 | 6 | Resting state | FC | High |
| Zhang32 | 2016 | 87 | 27.6 | 68 | Chinese | 23 | 43 | 21 | Yes | 3.0 | 8 | N-back, Resting state | FC | High |
| Chen33 | 2018 | 128 | 27 | 99 | Chinese | 32 | 62 | 34 | Yes | 3.0 | 4 | Resting state | FC | High |
| Tecelão34 | 2018 | 80 | 39.1 | 34 | Caucasian | NS | NS | NS | Yes | 1.5 | 5 | Verbal Fluency | FC, Activity | High |
| Zhang35 | 2018 | 99 | 25.8 | 49 | Chinese | 25 | 45 | 24 | Yes | 3.0 | NS | Resting state | FC | High |
| Cui19 | 2019 | 218 | 29.0 | 85 | Chinese | 49 | 120 | 49 | Yes | 3.0 | 6 | Resting state | Activity | High |
| Zhao36 | 2020 | 84 | 21.2 | 19 | Chinese | 23 | 40 | 21 | Yes | 3.0 | 8 | Resting state | FC | High |
Abbreviations: HWE, Hardy-Weinberg’ equilibrium; HC, healthy control; NS, not reported; FWHM, full width half height; FC, functional connectivity.
Table 2.
The Main Results of Risk Allele Effected Regions in Healthy Individuals in the Included Studies
| Study | Significant Region in Functional Connectivity | Significant Region in Neural Activity |
|---|---|---|
| Esslinger 200916 | Right amygdala, rDLPFC-HF | - |
| Esslinger 201126 | rDLPFC-left middle frontal gyrus, rDLPFC-right middle frontal gyrus, rDLPFC-right superior frontal gyrus, et al. | - |
| Rasetti 201117 | rDLPFC-HF, rDLPFC-inferior parietal lobule | - |
| Walter 201118 | lTPJ-inferior frontal gyrus, lTPJ-cuneus, rDLPFC-middle frontal gyrus, rDLPFC-precentral gyrus, et al. | DLPFC, DMPFC, VLPFC, TPJ, IPL, PCC |
| Linden 201328 | - | Right inferior frontal gyrus |
| Paulus 201330 | rDLPFC-left HF, rDLPFC-right HF | No significant region was found |
| Thurin 201327 | rDLPFC-anterior cingulate cortex | rDLPFC, anterior cingulate cortex |
| Mohnke 201429 | lTPJ-inferior frontal gyrus | TPJ, DMPFC, PCC |
| Cousijn 201531 | Hippocampal-prefrontal cortex | - |
| Zhang 201632 | rDLPFC-left HF | - |
| Chen 201833 | No significant region was found | - |
| Tecelão 201834 | - | Left inferior frontal gyrus |
| Zhang 201835 | Left HF-rDLPFC | - |
| Cui 201919 | - | Left calcarine gyrus |
| Zhao 202036 | rDLPFC-left HF | - |
Abbreviations: DLPFC, dorsolateral prefrontal cortex; DMPFC, dorsomedial prefrontal cortex; VLPFC, ventrolateral prefrontal cortex; IPL, inferior parietal lobe; PCC, posterior cingulate cortex; TPJ, temporo-parietal junction; HF, hippocampus formation.
Effect of ZNF804A Gene rs1344706 Risk Allele on Brain Functional Connectivity
The seed regions reported in 12 studies16–18,26,27,30–36 regarding functional connectivity are summarized in Figure 2. Due to the high frequencies of rDLPFC-based seed (reported by eight studies16–18,26,27,30,32,36), the subsequent AES-SDM analysis of brain functional connectivity mainly focused on the rDLPFC seed. In the healthy population, the functional connectivity of the rDLPFC–left hippocampus in the rs1344706 risk allele carrier was significantly increased (z=2.066, p<0.001), while those in the rDLPFC–left middle frontal gyrus (z=−1.420, p<0.001) and rDLPFC–right middle frontal gyrus (z=−1.298, p<0.001) were significantly reduced (Table 3 and Figure 3). Result of connectivity coupling between rDLPFC and left middle frontal gyrus had a significant heterogeneity (p<0.05). The area of interest with peak coordinate only reported in one study was not included in AES-SDM meta-analysis. Generally, the risk allele of rs1344706 showed mainly negative effects on functional connectivity (Table 4).
Figure 2.
Frequency distribution of brain regions involved in brain functional connectivity.
Abbreviations: rDLPFC, right dorsolateral prefrontal cortex; TPJ, temporoparietal junction; PCC, posterior cingulate cortex.
Table 3.
Effect of Rs1344706 Risk Allele on Brain Functional Connectivity Based on rDLPFC Seed Region
| Connected Region | Peak Coordinate | Cluster Size in Voxels | ||||
|---|---|---|---|---|---|---|
| MNI (x, y, z) | SDM-z | p | ||||
| Positive effects of rs1344706 risk alleles | ||||||
| Left hippocampus | −32 | −24 | −12 | 2.066 | <0.001 | 888 |
| Negative effects of rs1344706 risk alleles | ||||||
| Left middle frontal gyrus | −46 | 32 | 34 | −1.420 | <0.001 | 226 |
| Right middle frontal gyrus | 30 | 50 | 32 | −1.298 | <0.001 | 150 |
Abbreviation: rDLPFC, right dorsolateral prefrontal cortex.
Figure 3.
Effect of rs1344706 risk allele on brain functional connectivity on the basis of rDLPFC seed region.
Table 4.
Summary of Functional Connectivity and Neural Activity Studies Not Included in AES-SDM Analysis
| Study | Indicator Characteristic | A>C | C>A | C=A | Reasons of No Including |
|---|---|---|---|---|---|
| Functional connectivity | |||||
| Cousijn 201531 | Hippocampal theta seed | √ | No rDLPFC seed | ||
| Tecelão 201834 | Left inferior frontal gyrus | √ | No rDLPFC seed | ||
| Zhang 201835 | Left hippocampal seed | √ | No rDLPFC seed | ||
| Chen 201833 | Degree centrality method | √ | No rDLPFC seed | ||
| Neural activity | |||||
| Paulus 201330 | Working memory related | √ | No significant result | ||
| Tecelão 201834 | Verbal fluency related | √ | No peak coordinate in healthy individuals | ||
Notes: A>C means risk allele had positive effect on functional connectivity or neural activity; C>A means risk allele had negative effect on functional connectivity or neural activity; C=A means risk allele had no significant effect on functional connectivity or neural activity.
Abbreviation: rDLPFC, right dorsolateral prefrontal cortex.
Effect of ZNF804A Gene rs1344706 Risk Allele on Neural Activity
Seven studies18,19,27–30,34 reported significant results in neural activity. However, only five studies18,19,27–29 had peak coordinates. AES-SDM analyzed the effect of ZNF804A gene rs1344706 risk allele on neural activity. After data integration and image reconstruction, the neural activity of the left anterior cingulate gyrus was significantly decreased in the rs1344706 risk allele carrier of the healthy population (MNI: x=0, y=34, z=22; z=−2.525, p<0.001; voxels=2463), and no other brain area showed significantly increased neural activity (Figure 4). Result of this brain region had no heterogeneity (p>0.05). The remaining two studies30,34 had a negative result of neural activity or did not report the peak coordinates in healthy individuals (Table 4).
Figure 4.
Effect of rs1344706 risk allele on neural activity.
Sensitivity Analysis and Publication Bias
Leave-one-out jackknife analyses showed that most functional connectivity and neural activity results were not significantly changed. When removed the study of Esslinger,16 Rasetti,17 or Thurin,27 respectively, the results were slightly changed (Table 5). Further sensitivity analysis excluded the studies of Esslinger26 and Zhao36 due to the potential partially duplicated sample. However, the results were not significantly changed (Table 6).
Table 5.
Leave One Out Jackknife Sensitivity Analysis Results
| Study of Leave Out | Functional Connectivity | Neural Activity | ||
|---|---|---|---|---|
| rDLPFC-Left Hippocampus | rDLPFC-Left Middle Frontal Gyrus | rDLPFC- Right Middle Frontal Gyrus | Left Anterior Cingulate Gyrus | |
| Functional connectivity | ||||
| Esslinger 200916 | No significant changed | Peak coordinate changed | No significant changed | - |
| Esslinger 201126 | No significant changed | No significant changed | No significant changed | - |
| Rasetti 201117 | No significant changed | Reported no region | Reported no region | - |
| Walter 201118 | No significant changed | No significant changed | No significant changed | - |
| Paulus 201330 | No significant changed | No significant changed | No significant changed | - |
| Thurin 201327 | No significant changed | No significant changed | No significant changed | - |
| Zhang 201632 | No significant changed | No significant changed | No significant changed | - |
| Zhao 202036 | No significant changed | No significant changed | No significant changed | - |
| Neural activity | ||||
| Walter 201118 | - | - | - | No significant changed |
| Linden 201328 | - | - | - | No significant changed |
| Thurin 201327 | - | - | - | Peak coordinate changed |
| Mohnke 201429 | - | - | - | No significant changed |
| Cui 201919 | - | - | - | No significant changed |
Abbreviation: rDLPFC, right dorsolateral prefrontal cortex.
Table 6.
Sensitivity Analysis of Function Connections Based on rDLPFC Seed Region When Removed Two Studies
| Connected Region | Peak Coordinate | Cluster Size in Voxels | ||||
|---|---|---|---|---|---|---|
| MNI (x, y, z) | SDM-z | p | ||||
| Positive effects of rs1344706 risk alleles | ||||||
| Left hippocampus | −28 | −20 | −14 | 1.763 | <0.001 | 578 |
| Negative effects of rs1344706 risk alleles | ||||||
| Left middle frontal gyrus | −46 | 32 | 36 | −1.494 | <0.001 | 210 |
| Right middle frontal gyrus | 28 | 50 | 30 | −1.342 | <0.001 | 167 |
Abbreviation: rDLPFC, right dorsolateral prefrontal cortex.
In addition, according to Egger’s test, no publication bias was found in functional connectivity and neural activity analyses (t=1.410, p=0.208; t=0.05, p=0.963; Figure 5).
Figure 5.
Publication bias of funnel plots.
Note: (A) Functional connectivity; (B) Neural activity.
Discussion
In this study, AES-SDM was used in the meta-analysis of studies regarding the effects of risk allele in rs1344706 polymorphisms of ZNF804A gene on brain function. The AES-SDM analysis found that in healthy populations, the functional connectivity of the rDLPFC–left hippocampus in the rs1344706 risk allele carrier was significantly increased, but those of the rDLPFC–right middle frontal gyrus and rDLPFC–left middle frontal gyrus were significantly decreased. Analysis of local activity revealed that the neural activity in this risk allele carrier was significantly decreased in the left anterior cingulate gyrus.
The outcomes of the present meta-analysis are generally consistent with previous observational studies, although some differences were observed. The connectivity couplings such as rDLPFC–inferior parietal lobule, rDLPFC–anterior cingulate cortex, and rDLPFC–precentral gyrus was reported by other studies.18,26,27 However, they were not significant in our meta-analysis. Furthermore, we found that risk allele A was associated with neural activity only in the left anterior cingulate gyrus but not in rDLPFC, dorsomedial prefrontal cortex, left calcarine gyrus, and posterior cingulate cortex, which were reported in other studies.18,19,29 These differences may be due to a higher statistical powerful in our meta-analysis. Thus, relatively less regions were found to be associated with risk allele A. However, the total effect of this risk allele on brain function was never changed in our meta-analysis in healthy individuals.
The functional connectivity of the rDLPFC–left hippocampus in the rs1344706 risk allele carrier was significantly increased, which showed the positive and obviously strong effect of this gene in our meta-analysis. However, in patients with chronic schizophrenia, the hippocampal–prefrontal functional connectivity seemed to be reduced in the resting state, suggesting the negative effect of rs1344706 risk allele.37 On the one hand, it may be due to differences in the observation indicators and clinical baselines of the included samples. On the other hand, it may be due to the difference in the races of subjects because the frequency of rs1344706 allele distribution varies widely among different populations, and this difference may directly affect the results of association studies.
Imaging genetic studies generally evaluate the risks of specific genes on functional development of the cerebrum. However, how the protein or nucleic acid produced by gene coding affects the execution of brain function is not clear. ZN804A is a schizophrenia susceptibility gene that is strongly supported by GWA analysis. In our meta-analysis and previous studies, rs1344706 risk allele influenced the different regions of the brain. In complementary gene expression analyses, the rs1344706 risk allele was found to be associated with increased ZNF804A exonic transcription levels in the hippocampus, medulla oblongata, occipital cortex, and other regions.34,38 Hence, the effects of the risk allele on brain function may result from the different expression of ZNF804A gene in different brain regions. The dosage of ZNF804A may determine some functions of the human brain. Animal experiments, biological information analysis, and functional MRI scanning suggested that the polymorphic site of rs1344706 affects human brain functional connectivity and is related to the development of white matter circuits.39 For the ZNF804A gene, studies have shown that the gene only affects the early development of the brain, but has no effect on the mature adult brain.40 However, from the perspective of autopsy, the ZNF804A gene showed differential expression between healthy individuals and patients with schizophrenia.41–43 These pieces of evidence indirectly or directly reveal that ZNF804A expression is associated with brain development and different phenotypes. Nevertheless, direct experimental data on the ZNF804A gene rs1344706 risk allele are still lacking to determine how brain development affects different individuals to exhibit different brain function characteristics.
ZNF804A is closely related to the cognitive function of the brain.44 An investigation in healthy subjects showed that cortical connectivity and activation were related to rs1344706 during performance on a theory of mind task (which measures the participant’s ability to infer mental state).16 The regional activation of the temporoparietal cortex and rDLPFC, which are implicated in the function in theory of mind, was found to be affected by the dosage of risk allele.18 Our meta-analysis conducted in healthy individuals revealed the association between ZNF804A rs1344706 allele gene expression and rDLPFC seeded functional connectivity, highlighting the key role of ZNF804A in cognitive function. One important characteristic of patients with schizophrenia is impaired cognitive function. Thus, the function of this risk gene in healthy individuals could also reflect the potential effect of rs1344706 on the abnormal cognitive function of patients with schizophrenia.
No publication bias was found in this meta-analysis, but a significant heterogeneity existed when synthesizing functional connectivity indicators. The heterogeneity most likely come from the different analytical indicators and scanning models among the including studies. In general, this study clarified the effect of ZNF804A gene rs1344706 risk allele on function through meta-analysis and provided a more in-depth reference for the study of genetic related pathogenesis of mental disorders such as schizophrenia.
Conclusion
The ZNF804A gene rs1344706 polymorphism has a strong correlation with brain functional connectivity and neural activity in healthy individuals. The risk allele A may be associated with abnormal or changed brain function in individuals and play a key role in the execution of brain function. This meta-analysis provides important information for the further study of genetic related mechanisms of schizophrenia and other mental disorders. The relationship between the rs1344706 risk allele of ZNF804A and brain dysfunction also provides an important reference for the prevention and treatment of mental disorders.
Acknowledgments
This study was supported by grants from the Natural Science Foundation of Chengdu Medical College (grant no. CYZ18-08), Research Foundation of Sichuan Applied Psychology Research Center (grant no. CSXL-192A13), and Student Innovation and Entrepreneurship Training Program for Universities in Sichuan (grant no. S201913705056).
Author Contributions
All authors contributed to data analysis, drafting, and revision of the article. All authors have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.
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