What this is
- This research identifies as a potential risk gene for schizophrenia through integrative analyses of East Asian populations.
- Using Transcriptome-Wide Association Studies () and Summary-data-based Mendelian Randomization (), the study highlights the gene's down-regulation in schizophrenia cases.
- It emphasizes the importance of using diverse population data to uncover genetic insights that may be missed in predominantly European studies.
Essence
- is identified as a schizophrenia risk gene, showing significant down-regulation in cases compared to controls in both blood and brain tissues. Integrative analyses using East Asian population data reveal its potential role in neurodevelopment.
Key takeaways
- mRNA expression is significantly lower in schizophrenia cases vs. controls, with P = 8.63 × 10-4 in blood and P = 1.87 × 10-5 in brain tissues. This consistent down-regulation across different samples suggests a strong association with schizophrenia.
- Knockdown of in mouse neural stem cells significantly affects their proliferation and differentiation, indicating its role in neurodevelopment. This suggests that may contribute to schizophrenia risk by influencing brain development.
- Integrative analyses identified as a schizophrenia risk gene, contrasting with previous studies that primarily focused on European populations. This highlights the need for diverse genetic research to uncover population-specific insights.
Caveats
- The sample size for the schizophrenia GWAS in this study is relatively small compared to European studies, which may limit the identification of additional risk genes.
- Using eQTL data from non-brain tissues may overlook critical information, as schizophrenia is primarily linked to brain function and development.
- Further functional studies are necessary to elucidate the exact mechanisms by which influences schizophrenia risk and neurodevelopment.
Definitions
- TMEM180: A gene encoding a transmembrane protein, implicated in schizophrenia risk through its role in neurodevelopment.
- TWAS: Transcriptome-Wide Association Study, a method that integrates gene expression data with genetic association studies to identify risk genes.
- SMR: Summary-data-based Mendelian Randomization, a statistical method used to infer causal relationships between gene expression and disease risk.
AI simplified
Introduction
Schizophrenia is a severe mental disorder imposing great economic and societal burden.1 High heritability indicates a dominant role of genetic risk factors in schizophrenia,2 and over 200 risk loci have been reported by genome-wide association studies (GWASs).3–12 Despite that GWASs have made unprecedented achievements in the past decade, deciphering the genetic underpinnings and pathophysiology of schizophrenia is still challenging owing to the genetic heterogeneity of the disease between continental populations13–15 and the unclear functionality of most GWAS loci.
Recent endeavors to overcome these challenges have achieved prominent success. For example, GWASs performed in populations of East Asian (EAS),8,9,11 Indian,16 African and Latino ancestries17 have identified novel risk loci for schizophrenia. In addition, integrative studies using European data have identified potential target genes of multiple schizophrenia risk variants.18–27 Although these studies have provided novel biological insights, almost all of these integrative analyses utilized genome-wide associations and eQTL data of populations of European ancestry, potentially missing pivotal genetic and biological insights in other populations. To overcome the deficiency of integrative analyses in non-European populations and to illuminate the potential roles of the identified risk genes in schizophrenia, in this study, we firstly conducted large-scale integrative analyses (ie, TWAS and Summary-Data-Based Mendelian Randomization [SMR]) using reported genome-wide associations and eQTL data of population of East Asian ancestry (EAS). We then explored if risk genes identified by integrative analyses were dysregulated in schizophrenia cases compared with controls. We also investigated the role of the identified risk gene (ie, Tmem180) in neurodevelopment by using neural stem cell model. Finally, we investigated the genes and pathways potentially regulated by Tmem180 using transcriptome sequencing. Our study suggests that TMEM180 is a schizophrenia risk gene whose expression alternation may have a role in schizophrenia (through affecting neurodevelopment and schizophrenia-associated biological pathways).
Materials and Methods
Genome-Wide Associations of EAS
Genome-wide SNP associations in EAS were retrieved from a recent schizophrenia GWAS.11 Briefly, Lam et al conducted the largest schizophrenia GWAS (22 778 cases and 35 362 controls) in EAS and identified 21 genome-wide significant associations at 19 loci.11 Detailed information about the EAS GWAS can be found in the original paper.11
eQTL Data of EAS
Recent studies have revealed differences in genetic architecture of gene expression in different populations,28,29 indicating the importance of conducting integrative analyses using genetic associations and eQTL data from the same population (ie, if GWAS associations were from EAS, it is better to use eQTL data from EAS). We used eQTL data from lymphoblastoid cell lines of EAS populations (162 donors) in this study.30 Detailed information about eQTL data of EAS are provided in the supplementary methods.
Transcriptome-Wide Association Study
To identify genes whose cis-regulated expression changes are associated with risk of schizophrenia, we performed a Transcriptome-Wide Association Study (TWAS) by integrating GWAS associations and eQTL data. The TWAS analysis was performed using the FUSION software31 (http://gusevlab.org/projects/fusion/↗). Detailed information about TWAS are provided in the supplementary methods.
SMR Analysis
We used SMR integrative analysis approach developed by Zhu et al. to identify schizophrenia risk genes through integrating eQTL data and GWAS signals.32 Details about the SMR analyses can be found in the original paper32 and are provided in the supplementary methods.
Functional Annotation of rs2902544
We explored the functionality of rs2902544 using functional annotation tools RegulomeDB33 and Alibaba234. Detailed information about functional annotation are provided in the supplementary methods.
Expression Analysis ofin Peripheral Blood of Schizophrenia Cases and Controls (EAS Sample) TMEM180
TWAS identifies disease-associated genes under the assumption that genetic variations confer risk of disease by modulating gene expression.31 To further explore if the schizophrenia risk gene TMEM180 identified by TWAS and SMR integrative analyses in EAS was dysregulated in schizophrenia cases, we examined gene expression level of TMEM180 in peripheral blood of schizophrenia cases and controls by using the expression data from the study of Sun et al.35 More detail information about schizophrenia diagnosis, blood collection, RNA extraction, quality control, and statistical analysis were provided in supplementary material and can be found in the original publication.35
Expression Analysis ofin Brain Tissues of Schizophrenia Cases and Controls (European Sample) TMEM180
We further examined TMEM180 mRNA expression level in brains of schizophrenia cases and controls. As there is no publicly available Asian brain expression data for analysis, we used European brain expression data from the PsychENCODE21 for TMEM180 expression analysis. We extracted the expression values (fragments per kilobase of transcript per million mapped reads (FPKM)) and P value of TMEM180 from PsychENCODE website. Detailed information about the study subjects are provided in supplementary material and can be found in the related publication.21
Isolation and Culture of Mouse Neural Stem Cells (mNSCs)
We isolated mNSCs according to the published protocols36,37 with some minor modifications as described in our recent study.38 In brief, brains of mouse embryos (embryonic day 13.5 (E13.5), C57BL/6) were dissected under microscope to obtain neural stem cells from the ventricular zone (VZ) and sub-ventricular zone (SVZ) tissues. Details about isolation and culturing of mNSCs are provided in supplementary material.
Knockdown Experiments
The short hairpin RNAs (shRNAs) targeting mouse Tmem180 were designed using BLOCK-iT™ RNAi Designer (https://rnaidesigner.thermofisher.com/rnaiexpress/sort.do↗) (supplementary table 1). Detailed procedures were provided in supplementary methods.
Proliferation Assays of mNSCs
Proliferation assays (including EdU incorporation and CCK-8) were performed as previously described38 and detailed procedures were provided in supplementary methods.
Differentiation of mNSCs Into Neurons and Astrocyte Cells
The mNSCs cells were seeded onto the 24-well plates at a density of 2 × 105 cells/well (pre-coated with laminin [SIGMA, Cat.No: L2020-1mg]) and cultured in proliferation medium. After one day, the proliferation medium was replaced with differentiation medium. Differentiation assays were performed as previously described38 and detailed procedures were provided in supplementary methods.
Immunofluorescence Staining
Detailed procedures about immunofluorescence staining are provided in. The primary and secondary antibodies used in this study were provided in. supplementary material supplementary material
Real-Time Quantitative PCR
RNA was extracted with TRIzol RNA Isolation Reagents (Life technologies, 15596018) according to the manufacturer’s instructions. Detailed information about procedures and analyses of qPCR are provided in the. Primers sequences are listed in. supplementary methods supplementary table 1
Transcriptome Analysis
Detailed procedures about transcriptome analysis (RNA sequencing) are provided in. supplementary material
Results
TWAS and SMR Integrative Analyses in EAS Identifiedas a Schizophrenia Risk Gene TMEM180
To prioritize candidate genes whose expression alterations may confer risk of schizophrenia, several integrative analyses have been performed.18,22,23,25,27,31,32,39,40 However, most of the integrative analyses were conducted in populations of European ancestry. In this study, we performed integrative analyses using genome-wide associations of schizophrenia (22 778 schizophrenia cases and 35 362 controls) and eQTL data (162 individuals) from populations of EAS ancestry.11,30 We first conducted a TWAS31 in EAS and identified 4 transcriptome-wide significant risk genes (including TMEM180, ACTR1A, SFXN2, and MAD1L1) for schizophrenia (corrected by Bonferroni multiple comparison testing) (table 1), and TMEM180 showed the most significant association (TWAS P = 2.89 × 10–14). SNP rs2902544 showed significant association with schizophrenia and TMEM180 expression (figure 1a). Of note, functional annotation suggested that rs2902544 may be a functional variant (supplementary figure 1). We further performed another integrative analysis (ie, SMR32) by using the same GWAS and eQTL data as the TWAS analysis. SMR integrative analysis identified 2 schizophrenia risk genes (SFXN2 and TMEM180) (corrected by Bonferroni multiple comparison testing) (table 2). Nevertheless, HEIDI (heterogeneity in dependent instruments) test32 showed that SFXN2 could not pass heterogeneity test (PHEIDI < 0.05), suggesting that the association between SFXN2 and schizophrenia might due to linkage or pleiotropic effect (rather than causal effect). Thus, the only significant risk gene identified by SMR is TMEM180 (P = 6.04 × 10–5). Collectively, both TWAS and SMR integrative analyses supported that TMEM180 was significantly associated with schizophrenia.
![Expression quantitative trait loci andexpression analyses. (a) The schizophrenia risk allele of rs1902544 is associated with lowerexpression in EAS (effect size (beta) = 0.182). (b)expression was significantly down-regulated in schizophrenia cases compared with controls (with the effect size [Cohen’s] of 1.22). TMEM180 TMEM180 TMEM180 d](https://europepmc.org/articles/PMC8379544/bin/sbab032f0001.jpg.jpg "Click to view full size")
Expression quantitative trait loci andexpression analyses. (a) The schizophrenia risk allele of rs1902544 is associated with lowerexpression in EAS (effect size (beta) = 0.182). (b)expression was significantly down-regulated in schizophrenia cases compared with controls (with the effect size [Cohen’s] of 1.22). TMEM180 TMEM180 TMEM180 d
| Gene | CHR | Best.GWAS.IDa | A1 | A2 | ORb | eQTL IDc | TWAS.Zd | TWAS.P |
|---|---|---|---|---|---|---|---|---|
| TMEM180 | 10 | rs4147157 | A | G | 0.89 | rs2902544 | −7.603 | 2.89e-14 |
| ACTR1A | 10 | rs4147157 | A | G | 0.89 | rs284860 | −5.2973 | 1.18e-7 |
| SFXN2 | 10 | rs4147157 | A | G | 0.89 | rs2902548 | 5.0379 | 4.71e-7 |
| MAD1L1 | 7 | rs10239050 | A | G | 1.07 | rs1107592 | 4.647 | 0.00000337 |
| Gene | Chr | Top SNP | Top SNP_Chr | A1 | A2 | ORa | HEIDI_Pb | SMR_P |
|---|---|---|---|---|---|---|---|---|
| SFXN2 | 10 | rs2902548 | 10 | T | C | 0.92 | 0.00227 | 0.00000252 |
| TMEM180 | 10 | rs17114641 | 10 | T | G | 1.1 | 0.0822 | 0.0000604 |
Risk Allele of rs2902544 was Associated With LowerExpression TMEM180
Our TWAS analysis showed that rs2902544 was simultaneously associated with schizophrenia (P = 3.45 × 10–13) and TMEM180 expression (P = 2.88 × 10−10) in EAS (table 1), suggesting that genetic variation may confer schizophrenia risk by regulating TMEM180 mRNA expression. Further analysis showed that the risk allele (ie, C allele) of rs2902544 was associated with lower TMEM180 expression (figure 1a), implying that risk variants might contribute to schizophrenia risk through down-regulating TMEM180.
Down-Regulation ofin Schizophrenia Cases Compared With Controls TMEM180
As stated above, TWAS and eQTL analyses of rs2902544 predicted down-regulation of TMEM180 in schizophrenia cases compared with controls (table 1). We then examined TMEM180 mRNA expression changes between schizophrenia cases and controls using the expression data from Sun et al. (Chinese sample).35 Consistent with the prediction of integrative analyses, we found that TMEM180 was significantly down-regulated in the blood samples of schizophrenia cases compared with controls (P = 8.63 × 10–4) (figure 1b), with an effect size (Cohen’s d) of 1.22.
We further explored TMEM180 mRNA expression in brains of schizophrenia cases and controls using expression data from the PsychENCODE.41 Again, TMEM180 was significantly down-regulated in the brains of schizophrenia cases compared with controls (P = 1.87 × 10–5), with an effect size (Cohen’s d) of 0.906. These consistent results from different samples and tissues suggested that dysregulation of TMEM180 might play a role in schizophrenia.
Knockdown ofAffected Proliferation of Mouse Neural Stem Cells Tmem180
Although the pathophysiology of schizophrenia remains largely unknown, multiple lines of evidence (including genetic42 and functional studies27,43–45) support the neurodevelopmental hypothesis, which posits that schizophrenia is mainly attributed to abnormal brain development.46–50 To mimic the effect of TMEM180 down-regulation on neurodevelopment, we used the mouse neural stem model, which was frequently used in studying the role of schizophrenia risk genes in neurodevelopment.27,43–45 We validated the identity of isolated mNSCs using well-characterized markers, including PAX6, NESTIN and SOX2 (figures 2a–e). We designed 2 shRNAs to knockdown Tmem180 expression in mNSCs and RT-qPCR showed that Tmem180 was significantly down-regulated by the shRNAs (figure 2f). Both EdU and CCK-8 assays showed that Tmem180 knockdown promoted proliferation of mNSCs significantly (figures 2g–i), indicating that Tmem180 has a role in regulating proliferation of NSCs.
knockdown promotes proliferation of mNSCs significantly. (a–e) Immunofluorescence staining showed that the isolated mNSCs express 3 well-characterized markers for NSCs, including SOX2, PAX6, and NESTIN, indicating that the cells were NSCs. (f) Expression ofin mNSCs was significantly knocked-down by the designed shRNAs. (g) EdU incorporation assay showed that EdU(red) cells were significantly increased inknocked-down cells compared with controls. DAPIwas used to stain the nucleus (blue). (h) The quantification results of the EdU incorporation assay. (i) CCK-8 assay revealed that theknockdown significantly promote proliferation of NSCs. Data showed at 3 time points, 24, 48 and 72 hours. Two-tailedwas used to compare if the difference was significant. n = 3 for,= 3 (EdU positive cells were counted from 6 independent immunostaining images for each sample) for,= 9 for. Data are represented as mean ± SD. *< .05; **< .01; ***< .001. Tmem180 Tmem180 Tmem180 Tmem180 Student’s t test n n P P P + + f g i
Knockdown ofAffected Differentiation of mNSCs Into Neuronal and Astrocyte Cells Tmem180
In the early stage of neurodevelopment, the NSCs first undergo serial proliferation and self-renewal in the ventricular zone (VZ) and sub-ventricular zone (SVZ) to generate numbers of NSCs and neural progenitor cells.51 With the progress of development, these NSCs and neural progenitors migrate outside and differentiate into different types of neural cells and astrocyte cells. To further explore the role of TMEM180 in neurodevelopment, we next investigated the role of TMEM180 in neural differentiation. Compared with control NSCs, we found that the proportion of GFAP positive astrocytes cells (GFAP+) was significantly decreased in Tmem180 knockdown group (figures 3a and 3b). By contrast, the proportion of MAP2 positive neuronal cells (MAP2+) was significantly increased (figures 3c and 3d). We validated the impact of Tmem180 knockdown on neural differentiation with RT-qPCR. Consistent with the immunostaining results, RT-qPCR showed that Tmem180 knockdown significantly altered the expression of GFAP and MAP2, with the same effect direction as observed in immunostaining assays (figures 3f and 3g). Collectively, these results demonstrate the important role of TMEM180 in regulating neural differentiation.
knockdown affects differentiation of mNSCs. (a) Representative immunofluorescence staining images for GFAPastrocyte cells (green) and DAPI(blue). (b) Quantification for the ratio of GFAP positive astrocyte cells inknockdown and controls mNSCs. The ratio of GFAP positive astrocyte cells was significantly decreased inknockdown group compared to control group, indicating that the differentiation of mNSCs into astrocyte cells were impaired. (c) Representative immunofluorescence staining images for MAP2neurons (green) and DAPI(blue). (d) Quantification for the ratio of MAP2 positive neurons inknockdown and controls NSCs. The ratio of MAP2 positive astrocyte cells was significantly increased inknockdown group compared to control group, indicating that the differentiation of NSCs into neurons were enhanced. (f,g) RT-qPCR results showed thatknockdown significantly affected the relative expression level ofand. pLKO.1-EGFP was used as controls (ie, these cells were transfected with random shRNAs and EGFP). Two-tailedwas used to compare if the difference was significant.= 3 (GFAP positive cells were counted from 8 independent immunostaining images for each sample) for= 3 (MAP2 positive cells were counted from 6 independent immunostaining images for each sample) for*< .05; **< .01. Tmem180 Tmem180 Tmem180 Tmem180 Tmem180 Tmem180 GFAP MAP2 Student’s t test n n P P + + + + a, c.
Regulated Schizophrenia-Associated Pathways TMEM180
To further investigate the biological and signaling pathways regulated by TMEM180, we performed transcriptome analysis. We conducted RNA-Seq to examine the impact of Tmem180 knockdown on global gene expression profiling in mNSCs. We identified 654 genes (supplementary table 2) that were differentially expressed (fold change > 1.5 and adjusted P < .05) in Tmem180 knockdown mNSCs (compared with controls) (figure 4a). We selected 5 genes (including Nptx1, Ywhah, Gabra2, Col26a1, and Slc6a9) (figure 4b) to validate the results of RNA-seq using RT-qPCR (figures 4c–g), and the selection criteria of these 5 genes were as follows: First, these 5 genes were from the top 30 differentially expressed genes (based on RNA-seq). Second, these genes are abundantly expressed (https://www.proteinatlas.org/↗)52 (supplementary figure 2) and have pivotal roles in the human brain.52–65 Detailed information about the roles of these genes in the central nervous system was provided in the supplementary methods. Taken together, these lines of evidence indicated the important role of the potential target genes of TMEM180 in brain development and psychiatric disorders, suggesting that TMEM180 may confer risk of schizophrenia through regulating these genes.
We next performed GO analysis to explore if the 654 differentially expressed genes were enriched in specific biological categories or signaling pathways. Our GO analysis showed that the differentially expressed genes were mainly enriched in biological processes associated with schizophrenia, including action potential,66 learning or memory,67,68 cognition,69–71 synaptic transmission, etc (figure 4h). In addition, KEGG pathway analysis showed that the dysregulated genes were significantly enriched in schizophrenia-associated signaling pathways, including ECM-receptor interaction,72 cAMP signaling pathway,73 glutamatergic synapse, synaptic vesicle cycle,74–77 GABAergic synapse,78,79 etc (figure 4i). Collectively, our transcriptome analysis showed that TMEM180 may contribute to schizophrenia by regulating these biological processes and signaling pathways.
regulates schizophrenia-associated biological processes and pathways. (a) Expression heatmap of all differentially expressed genes (= 654) identified inknockdown NSCs compared with controls. (b) Heatmap plot of the top 30 differentially expressed genes. (c–g) qPCR validation of RNA-Seq results. Five genes (marked by red color in) were selected for qPCR verification. All of the 5 genes that showed differential expression by RNA-Seq were validated by RT-qPCR, indicating the reliability of RNA-Seq. (h,i) GO and KEGG analyses of the differentially expressed genes. Pathways marked with red color were previously reported to be associated with schizophrenia.values were calculated by Two-tailedwas used for statistical test.= 3 for*< .05; **< .01. Tmem180 n Tmem180 P Student’s t test n P P b c–g,
Discussion
In this study, we identified TMEM180 as a schizophrenia risk gene through integrating genome-wide associations and eQTL data from EAS. We provided convergent lines of evidence that support dysregulation of TMEM180 might have a role in schizophrenia. First, our TWAS and SMR integrative analyses suggested that TMEM180 is schizophrenia risk gene whose down-regulation may have a role in schizophrenia. Of note, previous TWAS studies21,60 using GWAS associations and brain eQTL data of Europeans did not identify TMEM180 as a schizophrenia risk gene (supplementary table 3), indicating the necessity and importance of performing integrative analysis using GWAS and eQTL data from non-European populations. Second, consistent with the prediction of integrative analyses, mRNA expression analysis showed that TMEM180 was significantly down-regulated in peripheral blood of schizophrenia cases compared with controls in EAS sample. Third, TMEM180 also showed a significant down-regulation in brains of schizophrenia cases compared with controls in European sample from the PsychENCODE,22 further supporting the potential involvement of TMEM180 in schizophrenia. Fourth, we found that Tmem180 knockdown affected proliferation and differentiation of NSCs, indicating that Tmem180 is required for normal proliferation and differentiation of NSCs. These results also suggested that TMEM180 may contribute to susceptibility of schizophrenia by affecting neurodevelopment. Finally, transcriptome analysis demonstrated that Tmem180 regulates schizophrenia-associated pathways, including pathways related to synaptic transmission, memory and cognition.
TMEM180 is also known as MFSD13A (Major Facilitator Superfamily Domain Containing13A) and it encodes a transmembrane protein which contains 12 transmembrane domains.80 Previous studies have showed that TMEM180 knockdown (with siRNAs) promotes proliferation of the human pancreatic cancer cells.81 In addition, TMEM180 is highly expressed in colorectal cancer cells80 and it may be a new marker for colorectal cancer.82,83 To date, the exact function of TMEM180 is still unclear and we know little about the role of TMEM180 in brain and schizophrenia pathogenesis. Our transcriptome sequencing showed that synaptic transmission and neuronal related pathways were significantly affected by Tmem180 knockdown, suggesting that TMEM180 may have a pivotal role in the brain. The potential roles of TMEM180 in the brain are discussed in the supplementary discussion and related data are provided in supplementary figures 3–5.
Recent integrative analyses have linked schizophrenia risk variants to genes,18,21,23,25,27,32,60 thus providing a starting point for further functional characterization and mechanism dissection. These integrative analyses not only translated the genetic associations into risk genes,24 but also provided potential insights into schizophrenia pathogenesis. As the genome-wide associations and eQTL data used for integrative analyses were primarily from populations of Europeans, there is a necessity to look at the other continental populations in consideration of the population genetic heterogeneity. Fortunately, recent studies have begun to dissect the genetic architecture of schizophrenia in other populations, including populations of EAS,9,11 African and Latino ancestries.17 These studies provided important biological insights into the genetic etiology of schizophrenia and are well complementary to the GWASs conducted in European populations. In this study, we reported the first integrative analysis on schizophrenia using genome-wide associations and eQTL data of EAS. Our study identifies TMEM180 as a novel risk gene for schizophrenia and provides a complementary scheme to the integrative studies performed in European populations. Of note, the original study by Lam et al. suggested that ACTR1A might be the responsible gene at this locus as ACTR1A is the gene nearest the top association (the lead or index) variant at this locus.11 Our study highlights that the gene nearest the top association cannot be simply presumed to harbor the causal variations. The risk or causal variants may confer schizophrenia risk through regulating expression of distal genes (rather than the nearest gene). Interestingly, we noticed that TMEM180 did not show significant association with schizophrenia in previous GWAS10 (supplementary figure 6a) and integrative studies of schizophrenia (supplementary tables 3 and 4) (using European),21,22,25 suggesting the potential population specificity of this risk gene. Finally, the frequency of the risk allele (C) of rs2902544 also showed differences in Europeans and East Asians (supplementary figure 7), implying differential power to detect this association across ancestries, and either random drift or possibly positive selection favoring the minor allele in out-of-Africa populations.
Our study also suggests ancestry-specific findings diverge and converge across modalities in schizophrenia. Detailed discussions on this are provided in the. supplementary discussion
There are several limitations of this study. First, the sample size of schizophrenia GWAS included in this study was still relatively small compared to integrative studies performed in European,22,25 which may limit the identification of more promising candidate risk genes for schizophrenia. Second, as no brain eQTL data was available for EAS, we used eQTL data from the lymphoblastoid cell lines (as a surrogate) for integrative analysis. Considering that schizophrenia is a mental disorder that is mainly originated from abnormal brain development and function, it is ideal to use eQTL data from brain tissues to conduct integrative analysis. Using eQTL data from non-brain tissues for integrative analyses may miss important information. In fact, only a significant gene (ie, TMEM180) was identified in our study. The relatively small sample size included in EAS GWAS and the using of non-brain eQTL data may be the major reasons for the identification of only one significant gene in our study. Further investigations with larger sample size and using of brain eQTL data (of EAS) will help to validate this result and to identify more risk genes. Third, though our integrative analyses suggested that genetic variants may confer schizophrenia risk by regulating TMEM180 expression, the functional risk variants (or causal variants) and how these functional variants regulate TMEM180 expression remain unknown. Finally, despite our study revealed that TMEM180 may have a role in neurodevelopment, currently we still do not know the exact role of TMEM180 in brain development and schizophrenia. Further in vivo functional studies are needed to demonstrate how TMEM180 confer risk of schizophrenia.
In summary, we performed a schizophrenia integrative analysis using genetic associations and eQTL data from EAS. Our study identified TMEM180 as a novel schizophrenia risk gene whose expression alternation may have a role in schizophrenia. Further functional study will elucidate the role and mechanisms of TMEM180 in schizophrenia.