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Article

Indicators of HSV1 Infection, ECM–Receptor Interaction, and Chromatin Modulation in a Nuclear Family with Schizophrenia

by
Yen-Chen Huang
,
Lieh-Yung Ping
,
Shih-Hsin Hsu
,
Hsin-Yao Tsai
and
Min-Chih Cheng
*
Department of Psychiatry, Yuli Branch, Taipei Veterans General Hospital, Hualien 98142, Taiwan
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2023, 13(9), 1392; https://doi.org/10.3390/jpm13091392
Submission received: 10 August 2023 / Revised: 5 September 2023 / Accepted: 13 September 2023 / Published: 18 September 2023
(This article belongs to the Section Mechanisms of Diseases)
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Abstract

:
Schizophrenia (SCZ) is a complex psychiatric disorder with high heritability; identifying risk genes is essential for deciphering the disorder’s pathogenesis and developing novel treatments. Using whole-exome sequencing, we screened for mutations within protein-coding sequences in a single family of patients with SCZ. In a pathway enrichment analysis, we found multiple transmitted variant genes associated with two KEGG pathways: herpes simplex virus 1 (HSV1) infection and the extracellular matrix (ECM)–receptor interaction. When searching for rare variants, six variants, SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E, segregated with SCZ. A bioinformatic analysis showed that three of these mutated genes were associated with chromatin modulation. We found that HSV1 infection, ECM–receptor interaction pathways, and epigenetic mechanisms may contribute to the pathogenesis of SCZ in certain families. The identified polygenetic risk factors from the sample family provide distinctive underlying biological mechanisms of the pathophysiology of SCZ and may be useful in clinical practice and patient care.

1. Introduction

Schizophrenia (SCZ) is a chronic debilitating mental disorder characterized by abnormal perception, thought disturbances, bizarre behavior, and cognitive deficits [1]. This disorder affects approximately 1% of the general population worldwide. Genetic factors play a critical role in its etiology; the heritability of SCZ has been estimated at 70–80%, with numerous transmitted variants possibly involved [2]. However, discovering genes directly responsible for SCZ is challenging because of its genetic complexity and the epigenetic mechanisms involved, which possibly act as downstream effectors of environmental signals [3].
The current hypotheses of the genetic basis for SCZ include rare deleterious mutations with large clinical penetrance in some patients, psychosis in families, or the addition of multiple common polymorphisms with minor effects [4,5]. Identifying common and rare variants associated with SCZ could increase our understanding of the neurobiology of psychiatric disorders. In this regard, a genome-wide association (GWAS) study identified 108 SCZ-associated genetic loci [4]. Additionally, multiple rare or ultrarare variants, such as loss-of-function, missense, and chromosomal abnormalities, have been associated with SCZ [5,6]. These studies indicate that the genetic underpinnings of SCZ are very complex and heterogeneous. One strategy to better understand the etiology of this disorder is through a family-based analysis of the contribution of rare and common genetic variants to the disorder with whole-exome sequencing (WES) [7,8,9].
Here, we discovered variants in protein-coding sequences in a schizophrenic family with WES, which we confirmed with Sanger sequencing. The identified variants in the familial form of SCZ could provide a new landscape of the genetic architecture and alternative treatment targets for SCZ.

2. Materials and Methods

2.1. Sample Family Recruitment

The sample family was a nuclear family, including an unaffected father and a mother, son, and daughter with SCZ. All subjects were Han Chinese from Taiwan. The unaffected father and the two children were recruited for the WES experiment. All affected family members were diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria. The study was approved by the ethics committee of the Antai Tian-Sheng Memorial Hospital Institutional Review Board; written informed consent was obtained after all procedures were fully explained to the participants.

2.2. WES

Genomic DNA was prepared from white blood cells (WBCs) using a Gentra Puregene Blood Kit (QIAGEN). The quality of the genomic DNA was assessed on a NanoDrop One spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The 260/280 ratio for genomic DNA was ~1.8. The DNA library was prepared using 1 μg of genomic DNA from each sample using an xGenTM Exome Research Panel V2 (IDT, San Diego, CA, USA) following the manufacturer’s protocols with added index codes to attribute sequences to each sample. The library quality was assessed on a Qubit 4.0 fluorometer and Agilent bioanalyzer system. Sequencing was conducted on an Illumina NovaSeq 6000 platform to generate paired 150 bp reads, and the read coverage depth was 22×. The paired-end reads were analyzed for mapping to the human reference genome using the Burrows–Wheeler Aligner (v2.2.1) with default settings. The aligned reads were subsequently processed with a Genome Analysis ToolKit (GATK) (v4.2.1.0), including MarkDuplicates and Base Quality Score Recalibration. Variant calling for single-nucleotide variants (SNVs) and small insertion/deletion mutations was performed using a HaplotypeCaller. High-confidence variants were then obtained with the standard GATK Variant Quality Score Recalibration tool and annotated with ANNOVAR (v2020), SnpEff (v4.3), and VEP (v100.4); the data were then integrated using an in-house algorithm. Copy-number variations and structural variations were called using Control-FREEC (v11.6) and Manta (v1.6.0); next, the variants were annotated with AnnotSV (v3.0.9).

2.3. Mutation Validation with PCR-Based Sequencing

All PCR primer sequences were designed using the Primer3 website (http://bioinfo.ut.ee/primer3-0.4.0/primer3/, accessed on 10 August 2022), and the primer sequences, optimal annealing temperatures, and size of each amplicon are available on request. In a standard PCR reaction, genomic DNA (50 ng) was amplified in a reaction volume of 25 μL containing 2× PCR buffer for KOD FX, 2 mM dNTPs, and 1.0 U/μL of KOD FX (TOYOBO Co., Ltd., Osaka-Shi, Japan). The PCR cycling condition consisted of an initial denaturation at 95 °C for 5 min, followed by 30 cycles of 95 °C for 1 min, and an optimal annealing temperature of each target for 1 min and 72 °C for 1 min. For sequencing, aliquots of PCR products were purified using an Illustra™ ExoProStar™ 1-Step Kit (GE Healthcare Bio-Sciences, Piscataway, NJ, USA) and sequenced using a BigDye™ Terminator v3.1 Cycle Sequencing Kit on a SeqStudio DNA Analyzer (Thermo Fisher Scientific) according to the manufacturer’s protocols. The identified mutations were verified with repeated PCR and sequencing in both directions.

2.4. Bioinformatic Analysis

The variant coding effect was checked using publicly available prediction programs: Polyphen-2 (http://genetics.bwh.harvard.edu/pph2/, accessed on 8 August 2022), SIFT (http://sift.bii.a-star.edu.sg/, accessed on 8 August 2022), and CADD (https://cadd.gs.washington.edu/, accessed on 8 August 2022). We also determined whether the mutations were documented in the public databases gnomAD (https://gnomad.broadinstitute.org/, accessed on 8 August 2022) and Taiwan BioBank (https://taiwanview.twbiobank.org.tw, accessed on 8 August 2022). For the pathway analysis, genes with identified variants were uploaded to the database for annotation, visualization, and integrated discovery (DAVID v6.8, https://david.ncifcrf.gov/tools.jsp, accessed on 1 August 2022) using the official gene symbol method. Genes with identified variants associated with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were highlighted and annotated [10].

3. Results

3.1. Clinical Manifestations of SCZ in the Study Family

Figure 1 shows the nuclear family with an unaffected father (I:1), a mother with SCZ (I:2), a son with SCZ (II:1), and a daughter with SCZ (II:2). The SCZ seemed to be transmitted following a dominant inheritance pattern. At the time of the study, the father (I-1) was 61 years old and had no history of psychiatric disorders. The mother (I-2) died in an accident ten years ago. The elder son (II-1) was 30 years old and was born full-term without remarkable events. He began experiencing psychotic symptoms at the age of 14 years. His psychotic symptoms included auditory hallucinations, bizarre behavior, and aggressive behavior toward his family. He had no history of illicit drug abuse, head injury, or seizure attack. He had poor insight and poor drug adherence. As a result, he was hospitalized in psychiatric wards several times due to the relapse of his symptoms. He led a lazy lifestyle with poor socio-occupational functioning. Finally, he was admitted to a psychiatric day ward for long-term rehabilitation. The younger sister (II-2) was 29 years old and manifested auditory hallucinations, bizarre delusions (about aliens and gods), bizarre behaviors, persecutory delusion, and psychomotor agitation from the age of 20 years when she was diagnosed with SCZ. She had marked positive symptoms with multiple relapses, partly due to poor compliance with medication. Later, she did not respond very well to antipsychotic drugs; therefore, clozapine was prescribed in combination with other antipsychotics. She was finally hospitalized in a chronic psychiatric ward due to unremitted psychotic symptoms and poor family support. The clinical findings for the patients are shown in Supplementary Table S1.

3.2. WES Analysis

A WES analysis was conducted on peripheral WBC samples from the three family members (I:1, II:1, and II:2), and the reads were mapped against the hg38 human reference genome. The statistics of the sequencing reads and the number of identified variants after variant calling for SNVs are listed in Supplementary Table S2. A list of complete variants in the study samples is available on request. Next, the identified variants were further filtered to exclude non-protein-modifying variants.

3.3. Autosomal Dominant Analysis and Rare Mutation Identification

An autosomal dominant transmission analysis identified 951 protein-altering variants (within 736 genes) in the two affected children (II:1 and II:2) absent in the unaffected father (I:1) (Supplementary Table S3). Furthermore, 736 genes were uploaded to the DAVID database for pathway analysis. According to the DAVID analysis (after multiple tests), multiple genes were associated with the following two KEGG pathways: herpes simplex virus 1 (HSV1) infection (hsa05168) and the extracellular matrix (ECM)–receptor interaction (hsa04512) (Table 1). The detailed genetic and bioinformatic information of the variants identified in these two KEGG pathways is listed in Table 1.
Among the 951 protein-altering variants segregated with SCZ, 55 had MAFs < 0.5% in the gnomAD and Taiwan BioBank databases, of which six variants (SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E) were not reported in either of the two databases (Table 2). Sanger sequencing confirmed the presence of these six rarely transmitted protein-altering variants in the sample family (Figure 2).

4. Discussion

Identifying the specific genetic susceptibility and polygenetic risk factors for a family with SCZ is essential for establishing the molecular diagnosis, providing insight into the pathogenesis, and guiding the personalized treatment for each affected patient [11]. In this case, to search for the genetic underpinnings, we conducted a WES analysis of a nuclear family with an unaffected father, a son with SCZ, and a daughter with SCZ. Because the mother with SCZ died in an accident ten years ago, we did not collect her sample for the WES analysis. Given that this sample family is a classical SCZ family with a dominant inheritance pattern, we conducted an autosomal dominant transmission analysis to identify protein-altering variants in the two affected children but absent in the unaffected father. After the autosomal dominant analysis, we found multiple transmitted variant genes associated with two KEGG pathways: HSV1 infection and the ECM–receptor interaction. In addition, we detected six variants (SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E) absent in the gnomAD and Taiwan BioBank databases, which indicated that these coding variants may be ultrarare and confer a risk for SCZ in this sample family. Among these ultrarare variants, three (CYP2E1p.T376S, NAT10p.E811D, and CBX2p.S520C) may be associated with epigenetic mechanisms in the pathogenesis of SCZ. The above polygenetic risk factors we identified from the sample family provide distinctive underlying biological mechanisms for the pathophysiology of SCZ and may be helpful in clinical practice and patient care.
Accumulating evidence from genetic and epidemiologic studies demonstrates that the link between immunological processes and neuropsychiatric disorders has increased [12,13,14]. For example, an inflammatory state in the brain plays a role in developing neuropsychiatric disorders [12]. A meta-analysis observed a positive association between non-neurological autoimmune disorders and psychosis [15]. Furthermore, previous research highlighted a potential role for the immune system in autism spectrum disorder [14]. Thus, it seems there is a role of immune systems in neuropsychiatric disorders, and understanding how they interact can improve our understanding of neuropsychiatric disorders and give rise to alternative treatments in psychiatry. Serological evidence has demonstrated that exposure to the neurotropic virus HSV1 is associated with cognitive deficits in individuals with SCZ [16,17]. In addition, neuroanatomic studies have revealed reduced brain gray matter volumes among patients with SCZ exposed to HSV1 compared with healthy subjects [18,19,20]. Moreover, cognitive impairment in patients with SCZ could be associated with HSV1 infection due to the ability of HSV1 to infect neurons in brain areas involved in working memory and executive functions [21]. Thus, HSV1 could contribute to the psychotic symptoms, behavioral abnormalities, and cognitive impairment that characterize SCZ. However, given the high worldwide prevalence of HSV1 infection, it may act additively or interact with other factors, such as genetic variation [22]. For example, Prasad et al. observed that differences in gray matter variations in the prefrontal cortex among HSV1-exposed patients with SCZ and healthy controls were related to an exonic polymorphism of the MHC class I polypeptide-related sequence B gene [23]. In the present findings, multiple missense variants segregated with SCZ were associated with the HSV1 infection pathway. Taken together, we speculate that a specific genetic susceptibility to HSV1 infection may contribute to the development of SCZ. However, the associations between these gene variants and HSV1 infection are complex. Further research is needed to fully understand the relationships between these gene variants and HSV1 infection.
ECM molecules, derived from neurons and glial cells, are located in extracellular space, and brain-ECM-interaction molecules are involved in synaptogenesis and GABAergic, glutamatergic, and dopaminergic neurotransmission [24]. The brain ECM plays multiple roles in brain development, shaping synaptic plasticity, stability, cognitive flexibility, context discrimination, as well as the physiology and pathology of the central nervous system (CNS) [25]. For example, research has demonstrated the contribution of extracellular glycans and glycoconjugates, major constituents of the neural ECM, to the etiology and pathogenesis of idiopathic autism spectrum disorders and other pervasive neurodevelopmental disorders [26]. Several lines of evidence point to the involvement of the ECM in the pathophysiology of neuropsychiatric disorders such as autism, SCZ, and Alzheimer’s disease, suggesting possible etiological mechanisms linking the ECM and neuropsychiatric disorders [26,27,28]. The pathophysiology of SCZ is characterized by substantial alterations and a functional impact of the ECM’s composition and integrity [25,27,28]. Studies have demonstrated some ECM-related genes potentially associated with SCZ in animal models [6,29,30,31]. For example, a study demonstrated that patients with SCZ presented significantly lower levels of four brain ECM proteins (Lumican, a secreted acidic protein rich in cysteine, Nidogen-1, and Fibronectin) than healthy volunteers, suggesting that the brain ECM and its components are potential pharmacological targets to treat SCZ [29]. Fraser extracellular matrix complex subunit 1 (FRAS1) encodes an ECM protein that appears to regulate epidermal–basement membrane adhesion and organogenesis during development [30]. The ECM was disorganized in cortical and subcortical areas in Fras1 knockout mice, which exhibited many behavioral defects, including impaired egocentric spatial memory and aberrant olfactory learning and memory [31]. De novo mutations in an ECM gene, LAMA2, were described in patients with SCZ [6]. In addition, our previous study identified that the genetic deletion of an SCZ-susceptible gene, an activity-regulated cytoskeleton-associated protein, disturbed multiple genes involved in the ECM [32]. Here, we identified multiple missense variants within ECM-related genes transmitted by a mother with SCZ. These findings point toward associations between SCZ and multiple missense mutations within ECM-related genes, consistent with previous reports implicating a pathophysiological dysregulation of the brain ECM proteins in SCZ.
Although twin and adoption studies indicate that SZ has a genetic component with heritability [33], environmental influences are an alternative explanation for the non-hereditary portion of schizophrenia [3,34]. Epigenetic modifications, which possibly act as downstream effectors of environmental signals, not only play a regulatory role in cell differentiation and the development of the brain but also as a mechanism underlying behavioral changes [35]. Research has demonstrated that epigenetic alterations, such as altered DNA methylation, histone modifications, and RNA interference, may provide an alternative explanation for the pathogenesis of SCZ [36]. In the present study, we identified three ultrarare variants in three epigenetic-associated genes (CYP2E1, NAT10, and CBX2) that may be associated with the pathogenesis of SCZ. The cytochrome P450 family 2 subfamily E member 1 (CYP2E1) gene encodes a member of the cytochrome P450 superfamily, being considered an oxidative-stress-related gene [37]. CYP2E1 enzyme expression is differently influenced by epigenetic variation such as DNA methylation [38]. DNA methylation levels in the promoter of the CYP2E1 gene have been associated with SCZ and tardive dyskinesia [39]. In fact, a Chinese case–control study revealed that two CYP2E1 SNPs were associated with SCZ [40]. Thus, it should be noted that (epi)genetic variations of the CYP2E1 gene play a role in SCZ. Further, N-acetyltransferase 10 (NAT10) is involved in epigenetic events, including histone acetylation and mRNA modification [41,42]. Recently, Guo and colleagues found that NAT10 elevation in hippocampal neurons was related to anxiety- and depression-like behavior [43]. Finally, Chromobox 2 (CBX2) encodes a component of the polycomb multiprotein complex, which is required to maintain the transcriptionally repressive state of many genes throughout development via chromatin remodeling and histone modification [44]. Gu and colleagues reported that CBX2 inhibits neurite development by interacting with neuro-associated genes [45]. Thus, we suggest that aberrant chromatin modulation and histone modifications due to CYP2E1, NAT10, and CBX2 mutations may have contributed to the pathogenesis of SCZ in this family, but an additional functional study is required.
This study had the following limitations. First, we performed a whole-exome analysis in only one family. The present data may represent a specific genetic background in the sample family. Second, because we did not investigate whole-genome sequencing, several potentially valuable regions, such as non-protein-coding regions, were not sequenced.

5. Conclusions

We hypothesize that multiple coding variants in two KEGG pathways (HSV1 infection and the ECM–receptor interaction) indirectly affect the etiology of SCZ. With respect to rare variants, we hypothesize that damaging coding variants associated with epigenetic mechanisms are associated with SCZ, followed by ultra-rarely transmitted variants, given the evidence that newly arising mutations are enriched for more harmful mutation types. This present study provides insights with potential benefits for treating SCZ.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/jpm13091392/s1, Table S1: Clinical findings of the sample family; Table S2: Summary of whole-exome sequencing statistics and variants found in study samples; Table S3: Identified protein-altering variants in two affected children (II:1 and II:2) absent in the unaffected father (I:1).

Author Contributions

Conceptualization, Y.-C.H., L.-Y.P. and M.-C.C.; methodology, S.-H.H., H.-Y.T. and M.-C.C.; formal analysis, S.-H.H., H.-Y.T. and M.-C.C.; investigation, Y.-C.H., L.-Y.P., S.-H.H., H.-Y.T. and M.-C.C.; resources, L.-Y.P. and M.-C.C.; writing—original draft preparation, Y.-C.H. and M.-C.C.; writing—review and editing, M.-C.C.; funding acquisition, M.-C.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Yuli Branch, Taipei Veterans General Hospital, Taiwan, grant number VHYL108-008.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the Antai Medical Care Cooperation, Antai Tian-Sheng Memorial Hospital (approval number: 18-144-A).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The raw data are available upon the request of the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Jpm 13 01392 g001
Figure 1. Pedigree of the sample family. Circles and squares denote females and males, respectively. Black color indicates family members with SCZ. The arrow indicates the proband.
Figure 1. Pedigree of the sample family. Circles and squares denote females and males, respectively. Black color indicates family members with SCZ. The arrow indicates the proband.
Jpm 13 01392 g001
Jpm 13 01392 g002
Figure 2. Results of Sanger sequencing of the six ultrarare variants (SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E) identified in this study. The blue box indicates the position of the identified missense mutations.
Figure 2. Results of Sanger sequencing of the six ultrarare variants (SLC6A19p.L541R, CYP2E1p.T376S, NAT10p.E811D, N4BP1p.L7V, CBX2p.S520C, and ZNF460p.K190E) identified in this study. The blue box indicates the position of the identified missense mutations.
Jpm 13 01392 g002
Table 1. Protein-altering variants in the HSV1 infection pathway and ECM–receptor interactions observed in the sample family under the autosomal dominant inheritance model.
Table 1. Protein-altering variants in the HSV1 infection pathway and ECM–receptor interactions observed in the sample family under the autosomal dominant inheritance model.
GeneCoding: Amino Acid Changers NumberPublic Database MAFIn Silico Analysis
gnomADTaiwan BioBankSIFT Polyphen-2CADDraw/phred
Herpes Simplex Virus 1 Infection Pathway #
ZNF573:NM_001172692c.A1303G:p.M435Vrs30957260.8310.3895TB−0.073/0.943
ZNF177:NM_001172651c.C335T:p.T112Mrs22176520.610.408TB−0.13/0.718
ZNF177:NM_001172651c.A1363T:p.I455Frs22307520.5660.4DB0.744/8.855
ZNF132:NM_003433c.C755T:p.P252Lrs14657890.5470.296TB0.265/3.882
ZNF132:NM_003433c.G608A:p.G203Drs11229550.1740.0615TB−1.234/0.002
ZNF891:NM_001277291c.G1375C:p.V459Lrs21739700.1890.1555TB1.398/15.07
ZNF571:NM_001321272c.A1777G:p.K593Ers169738900.01480.062TP2.087/19.92
SP100:NM_001080391c.T2477C:p.M826Trs8362370.7970.4545TB−1.434/0.001
ZNF790:NM_001242800c.A902G:p.Q301Rrs37457750.2730.245DB0.255/3.759
ZNF44:NM_001353551c.A394G:p.T132Ars118791680.1810.301DB0.955/11.05
ZNF529:NM_001145650c.T337G:p.L113Vrs29124440.6940.489TB−0.538/0.099
ZNF527:NM_032453c.A638G:p.H213Rrs44520750.2720.304DB−0.35/0.245
ZNF229:NM_00127851c.G1966A:p.G656Rrs14345790.270.3265DP2.495/22.4
ZNF229:NM_00127851c.C991T:p.R331Crs121513380.2740.3365TP1.057/12.32
ZNF568:NM_001204839c.G1696C:p.G566Rrs13637530.570.3325TB−0.68/0.048
ZNF302:NM_001012320c.A266G:p.Y89Crs22906520.3030.234TP2.082/19.88
ZNF565:NM_001366190c.G140T:p.G47Vrs757661770.003560.102TB−0.092/0.863
ZNF543:NM_213598c.C163G:p.P55Ars65100570.5280.295TB0.407/5.505
ZNF268:NM_001165887c.A220T:p.M74Lrs619606700.1820.137TB−0.68/0.049
ZNF268:NM_001165881c.G2579C:p.R860Trs626445410.1820.137DB2.755/22.9
ZNF300:NM_052860c.5_7del:p.M2delrs723321880.0273170.038NANAN/A
ZIM3:NM_052882c.A1135G:p.I379Vrs48014330.4510.363TP1.731/17.24
ZIM3:NM_052882c.T205A:p.L69Mrs48012000.450.363TP0.283/4.096
ZIM3:NM_052882c.G82A:p.E28Krs23701340.1430.2665TP0.174/2.83
ZNF584:NM_001318002c.C298T:p.R100Crs2007799560.0001050.0615TB0.202/3.141
ZNF584:NM_001363680c.C289T:p.P97Srs116687890.1780.061TB−0.063/0.991
ZNF484:NM_001007101c.G1397A:p.G466Drs37396020.02390.2785DP2.451/22.3
ZNF440:NM_152357c.A371G:p.N124Srs4278800.5150.3965DB0.11/2.181
ZNF440:NM_152357c.G1561A:p.G521Rrs1179988130.003850.0755DB1.105/12.82
ZNF285:NM_001291491c.G158A:p.S53Nrs25710890.1920.362TB−0.604/ 0.071
ZNF460:NM_001330622c.A568G:p.K190ENDNDNDDP3/23.4
ZNF284:NM_001037813c.369_371del:p.S124delrs1399001310.4733220.3493NANAN/A
ZNF382:NM_001256838c.C1637T:p.T546Mrs617321800.1620.188TB0.854/9.938
ZNF180:NM_001278508c.C740G:p.S247Crs18978200.5320.59DB1.601/16.38
ZNF180:NM_001278508c.C192G:p.C64Wrs22535630.5170.5765DP1.158/13.3
ZNF180:NM_001278508c.T122C:p.V41Ars25711080.6920.697TB0.209/3.23
ZNF57:NM_001319083c.C572A:p.T191Nrs22889580.4180.6085TB−1.136/0.003
ZNF816:NM_001202456c.C485T:p.S162Lrs110842100.09290.2365TB−0.468/0.138
ZNF30:NM_001099437c.A1202G:p.Y401Crs7657460.1880.403DP1.728/17.22
ZNF439:NM_001348724c.C1013G:p.A338Grs729942140.0230.08DB0.772/9.12
ZNF317:NM_00119079c.G57T:p.Q19Hrs37521990.1540.117TB0.43/5.76
ZNF416:NM_001353405c.C284T:p.S95Lrs1513248980.0009520.035TP0.947/10.97
ZNF735:NM_001159524c.C670A:p.H224Nrs43204340.2240.2575TB−1.599/0.001
ZNF875:NM_001329773c.G1358T:p.S453Irs37457650.2780.318TB−0.005/1.302
ZNF460:NM_001330622c.A568G:p.K190ENDNDNDDP3/23.4
ZNF333:NM_001352243c.C917T:p.A306Vrs37646260.3570.5945TB0.635/7.848
TLR3:NM_00326c.C1234T:p.L412Frs37752910.2360.361DP2.844/23.1
IFNAR1:NM_000629c.G502C:p.V168rs22571670.1560810.354TP1.153/13.25
ECM–receptor interaction pathway $
LAMA2:NM_000426c.G1856A:p.R619Hrs38166650.2572270.0725TB−1.085/0.004
LAMA2:NM_00107982c.C7748T:p.A2583Vrs22298480.3705350.587TP4.105/27.8
VWF:NM_000552c.G6104A:p.G2035Drs1868066740.0001570.0045TB0.811/9.502
ITGA4:NM_000885c.G2633A:p.R878Qrs11436760.2882300.8475TB−0.899/0.014
LAMC3:NM_006059c.C1564T:p.P522Srs8694570.2827280.2955TB0.839/9.786
LAMC3:NM_006059c.A1631G:p.E544Grs109013330.4771130.471TB2.173/20.7
LAMC3:NM_006059c.C2308G:p.R770Grs37395100.8450.6075TB−0.095/0.851
LAMC3:NM_006059c.A3244G:p.S1082Grs22751400.2437870.663TB0.421/5.661
LAMA4:NM_001105206c.G5443A:p.V1815Irs37342920.0017400.0755DP3.647/25.2
DMP1:NM_001079911c.A157T:p.S53Crs100190090.2810.4205DP3.056/23.5
HMMR:NM_001142557c.G737A:p.R246Hrs23030780.0378070.04TB0.075/1.873
FRAS1:NM_001166133c.T1396A:p.L466Irs125040810.3508180.3855TP2.658/22.7
FRAS1:NM_001166133c.A2060G:p.D687Grs3455130.4250.4485TB0.327/4.597
FRAS1:NM_001166133c.C2450T:p.A817Vrs68357690.4338170.197TB0.351/4.87
FRAS1:NM_001166133c.G3406A:p.E1136Krs125121640.2421340.207TP1.844/18.06
TNN:NM_022093c.C3467T:p.A1156Vrs20720360.1145640.178DB0.296/4.24
COL6A2:NM_001849c.G2039A:p.R680Hrs10429170.4783960.43DP3.684/25.3
COL9A1:NM_001377290c.A1133G:p.Q378Rrs11350560.3828330.2785TB0.922/10.68
TNR:NM_003285c.G382T:p.A128Srs22398190.2415530.514TB1.383/14.97
COL6A6:NM_001102608c.G5216A:p.R1739Qrs168304940.0955440.1835DB2.068/19.77
# Fold enrichment: 2.0736; Bonferroni: 0.0101; Benjamini: 0.0093; FDR: 0.0093. $ Fold enrichment: 4.0982; Bonferroni: 0.0184; Benjamini: 0.0093; FDR: 0.0093; MAF: minor allele frequency; ND: not documented; NA: not applicable; T: tolerated; D: damaging; B: benign; P: probably or possibly damaging.
Table 2. Protein-altering variants with minor allele frequency (MAF) < 0.5% observed in the sample family under the autosomal dominant inheritance model.
Table 2. Protein-altering variants with minor allele frequency (MAF) < 0.5% observed in the sample family under the autosomal dominant inheritance model.
GeneCoding: Amino Acid Changers NumberPublic Database MAFIn Silico Analysis
gnomADTaiwan BioBankSIFT Polyphen-2CADDraw/phred
SSX2IP:NM_001166294c.G1492C:p.G498Rrs1914482930.00029000.001648DP1.85/18.1
SPAG17:NM_206996c.A4837G:p.N1613Drs2005621170.000080070.000660TB0.468/6.162
STYXL2:NM_001080426c.C91T:p.R31Xrs3772457100.000056640.001318NANA7.113/37
ZNF648:NM_001009992c.T1105C:p.C369Rrs7650640280.000057090.000668DP3.636/25.2
RGSL1:NM_001137669c.T226C:p.F76Lrs14039310740.00004728NDDP3.83/26
EMILIN1:NM_007046c.G2366A:p.R789Qrs5666203720.00007649NDTP3.552/24.9
ARHGEF33:NM_001145451c.C484G:p.P162Ars1905873240.00012000.000989TP2.677/22.8
USP34:NM_014709c.A3444G:p.I1148Mrs7698082280.000076530.002307TB1.537/15.97
CLEC4F:NM_001258027c.1421delA:p.K474Sfs*44rs7818708180.000035350.000330NANANA
STEAP3:NM_001008410c.G982A:p.A328Trs3766352820.00002651NDTP0.49/6.395
MYO7B:NM_001080527c.A694C:p.I232Lrs5591700470.00011760.001979DP3.607/25.1
USF3:NM_001009899c.A934G:p.T312Ars1922134730.00010330.000659TB0.336/4.707
FIP1L1:NM_001134938c.1225_1226del:p.R413Gfs*3rs1436716590.000160NDNANANA
NDST3:NM_004784c.A2027T:p.E676Vrs7579552010.000031880.000330TB2.585/22.6
UCP1:NM_021833c.G242A:p.G81Ers5558001040.00012720.000659DP3.426/24.5
SLC6A19:NM_001003841c.T1622G:p.L541Rrs1176698743NDNDDP3.562/24.9
CENPK:NM_001349368c.G487A:p.V163Irs7690170860.000087670.001649TP2.989/23.4
DMGDH:NM_013391c.T2324G:p.L775Rrs2014161830.000003992NDDP4.262/29.2
ZFYVE16:NM_001284237c.C2189T:p.T730Irs1408236340.00006367NDTB1.397/15.06
SLC22A4:NM_003059c.442_443del:p.L148Vfs*131rs7652478500.000019880.000330NANANA
TCOF1:NM_000356c.C122T:p.A41Vrs561805930.0029660.003DP1.682
CRYBG1:NM_001624c.G166C:p.E56Qrs2017890820.00051890.002444DP3.799/25.8
COL10A1:NM_000493c.T788C:p.I263Trs2004617890.000088760.000989TB0.282/4.078
CREB5:NM_001011666c.G671T:p.G224Vrs1427160670.00029030.006338DP4.015/27.1
SEMA3E:NM_001178129c.G1552A:p.V518Irs2007799560.00016670.003626TB1.179/13.47
ATP6V1B2:NM_001693c.C7A:p.L3Mrs2010571590.00013010.001252TP2.71/22.8
MTSS1:NM_001363300c.G1181A:p.R394Qrs7806738470.000019900.000330DP3.739/25.6
EXD3:NM_017820c.C707T:p.A236Vrs3707484380.00015870.000660TB−0.38/0.212
KIAA1217:NM_001282769c.T1169G:p.V390Grs7803716890.000060110.000330DP4.244/29.1
SORBS1:NM_001290296c.C649G:p.R217Grs3717847910.00028120.001995DB0.928/10.74
CYP2E1:NM_000773c.C1127G:p.T376SNDNDNDDB1.605/16.41
NAT10:NM_001144030c.G2433T:p.E811DNDNDNDDP3.284/24.1
PACSIN3:NM_001184974c.C82T:p.R28Wrs1859369790.00040140.002970DP4.48/32
OR8K5:NM_001004058c.C821A:p.A274Drs2019965410.000051770.000989DP1.472/15.55
VWF:NM_000552c.G6104A:p.G2035Drs1868066740.00040340.003626TB0.811/9.502
SLC39A5:NM_001135195c.C1517T:p.T506Mrs22935110.00074470.004293TB−0.791/0.027
DNAH3:NM_00134788c.G10796A:p.R3599Hrs7504871560.00014850.001320DP2.868/23.1
PRSS53:NM_001039503c.C1004T:p.A335Vrs1883428960.00051280.003955TB0.433/5.786
N4BP1:NM_153029c.C19G:p.L7VNDNDNDTP2.527/22.5
CBX2:NM_005189c.C1559G:p.S520CNDNDNDDP4.002/27
GDF15:NM_004864c.G763A:p.A255Trs7798655100.000008450NDDP2.955/23.3
ZNF784:NM_203374c.C298A:p.P100Trs5586254950.00026100.004529DB1.118/12.94
NLRP13:NM_001321057c.C2764G:p.P922Ars1812746360.00018050.004285TB0.173/2.827
PEG3:NM_001369735c.G1736A:p.S579Nrs5321733820.000095510.000989TP3.266/24
ZNF460:NM_001330622c.A568G:p.K190ENDNDNDDP3/23.4
C20orf96:NM_080571c.C58G:p.Q20Ers7568432780.000025030.001978DP1.474/15.57
SALL4:NM_001318031c.T1262G:p.L421Wrs7583734110.0001061NDDP3.88/26.2
ZNF831:NM_178457c.G3106A:p.A1036Trs7495435850.00013200.000330TB0.618/7.683
MCM3AP:NM_003906c.T5555C:p.M1852Trs1825651170.00027570.004614TB0.393/5.345
IL17RA:NM_001289905c.G1817A:p.G606Ers7616195260.00014680.003067TP−0.335/0.264
AIFM3:NM_001018060c.A151C:p.T51Prs7533627050.000099960.003014TB0.363/5.011
MYO18B:NM_001318245c.G5399A:p.R1800Qrs3712832190.000046490.000659DP4.151/28.2
ELFN2:NM_052906c.G62A:p.R21Hrs3687818610.00014280.002125TB0.686/8.33
SCUBE1:NM_173050c.G2146A:p.G716Srs5500157840.00012390.000342TB−0.44/0.159
SCUBE1:NM_173050c.G2141A:p.R714Hrs5356504370.000037030.000341DP3.831/26
MAF: minor allele frequency; ND: not documented; NA: not applicable; T: tolerated; D: damaging; B: benign; P: probably or possibly damaging.
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Huang, Y.-C.; Ping, L.-Y.; Hsu, S.-H.; Tsai, H.-Y.; Cheng, M.-C. Indicators of HSV1 Infection, ECM–Receptor Interaction, and Chromatin Modulation in a Nuclear Family with Schizophrenia. J. Pers. Med. 2023, 13, 1392. https://doi.org/10.3390/jpm13091392

AMA Style

Huang Y-C, Ping L-Y, Hsu S-H, Tsai H-Y, Cheng M-C. Indicators of HSV1 Infection, ECM–Receptor Interaction, and Chromatin Modulation in a Nuclear Family with Schizophrenia. Journal of Personalized Medicine. 2023; 13(9):1392. https://doi.org/10.3390/jpm13091392

Chicago/Turabian Style

Huang, Yen-Chen, Lieh-Yung Ping, Shih-Hsin Hsu, Hsin-Yao Tsai, and Min-Chih Cheng. 2023. "Indicators of HSV1 Infection, ECM–Receptor Interaction, and Chromatin Modulation in a Nuclear Family with Schizophrenia" Journal of Personalized Medicine 13, no. 9: 1392. https://doi.org/10.3390/jpm13091392

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