The molecular subtypes of autoimmune diseases.

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

Comparative analysis of single-cell transcriptome reveals heterogeneity and commonality in the immune microenvironment of colorectal cancer and inflammatory bowel disease.

Background: During aging, chronic inflammation can promote tumor development and metastasis. Patients with chronic inflammatory bowel diseases (IBD) are at an increased risk of developing colorectal cancer (CRC). However, the molecular mechanism underlying is still unclear. Methods: We conducted a large-scale single-cell sequencing analysis comprising 432,314 single cells from 92 CRC and 24 IBD patients. The analysis focused on the heterogeneity and commonality of CRC and IBD with respect to immune cell landscape, cellular communication, aging and inflammatory response, and Meta programs. Results: The CRC and IBD had significantly different propensities in terms of cell proportions, differential genes and their functions, and cellular communication. The progression of CRC was mainly associated with epithelial cells, fibroblasts, and monocyte-macrophages, which displayed pronounced metabolic functions. In particular, monocyte-macrophages were enriched for the aging and inflammation-associated NF-κB pathway. And IBD was enriched in immune-related functions with B cells and T cells. Cellular communication analysis in CRC samples displayed an increase in MIF signaling from epithelial cells to T cells, and an increase in the efferent signal of senescence-associated SPP1 signaling from monocyte-macrophages. Notably, we also found some commonalities between CRC and IBD. The efferent and afferent signals showed that the pro-inflammatory cytokine played an important role. And the activity of aging and inflammatory response with AUCell analysis also showed a high degree of commonality. Furthermore, using the Meta programs (MPs) with the NMF algorithm, we found that the CRC non-malignant cells shared a substantial proportion of the MP genes with CRC malignant cells (68% overlap) and IBD epithelial cells (52% overlap), respectively. And it was extensively involved in functions of cell cycle and immune response, revealing its dual properties of inflammation and cancer. In addition, CRC malignant and non-malignant cells were enriched for the senescence-related cell cycle G2M phase transition and the p53 signaling pathway. Conclusion: Our study highlights the characteristics of aging, inflammation and tumor in CRC and IBD at the single-cell level, and the dual property of inflammation-cancer in CRC non-malignant cells may provide a more up-to-date understanding of disease transformation.

A review of disease risk prediction methods and applications in the omics era.

Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.

Effects of genetic variation on the structure of RNA and protein.

Changes in the structure of RNA and protein, have an important impact on biological functions and are even important determinants of disease pathogenesis and treatment. Some genetic variations, including copy number variation, single nucleotide variation, and so on, can lead to changes in biological function and increased susceptibility to certain diseases by changing the structure of RNA or protein. With the development of structural biology and sequencing technology, a large amount of RNA and protein structure data and genetic variation data resources has emerged to be used to explain biological processes. Here, we reviewed the effects of genetic variation on the structure of RNAs and proteins, and investigated their impact on several diseases. An online resource (http://www.onethird-lab.com/gems/) to support convenient retrieval of common tools is also built. Finally, the challenges and future development of the effects of genetic variation on RNA and protein were discussed.

Genome-wide identification of m6A-associated single nucleotide polymorphisms in complex diseases of nervous system.

N6-methyladenosine (m6A) is one of the most abundant chemical modifications on RNA and can affect the occurrence and development of diseases. Some studies have shown that the expressions of some m6A-related genes are significantly regulated by single nucleotide variants (SNV). However, the function of m6A-associated single nucleotide polymorphisms (m6A-SNP) remains unclear in multiple sclerosis (MS), Alzheimer's disease (AD) and Parkinson's disease (PD). Here, we identified the disease-associated m6A-SNPs by integrating genome-wide association study (GWAS) and m6A-SNPs from the RMVar database, and confirmed the relationship between these identified m6A-SNPs and their target genes in eQTL analysis and gene differential expression analysis. Finally, 26 genes corresponding to 20 m6A-SNPs with eQTL signals were identified and differentially expressed (P < 0.05) in MS, 15 genes corresponding to 12 m6A-SNPs (P < 1e-04) were differentially expressed in AD, and 27 PD-associated m6A-SNPs that regulated the expression of 31 genes were identified. There were 5 HLA genes with eQTL signals (HLA-DQB1, HLA-DRB1, HLA-DQA1, HLA-DQA2 and HLA-DQB1-AS1) to be detected in the three diseases. In summary, our study provided new insights into understanding the potential roles of these m6A-SNPs in disease pathogenesis as well as therapeutic target.

Epigenome-wide methylation haplotype association analysis identified HLA-DRB1, HLA-DRB5 and HLA-DQB1 as risk factors for rheumatoid arthritis.

The aim of this study was to compare nonrandom associations between physically adjacent single methylation polymorphism loci among rheumatoid arthritis (RA) and normal subjects for investigating RA-risk methylation haplotypes (meplotype). With 354 ACPA-positive RA patients and 335 normal controls selected from a case-control study based on Swedish population, we conducted the first RA epigenome-wide meplotype association study using our software EWAS2.0, mainly including (i) converted the ß value to methylation genotype (menotype) data, (ii) identified methylation disequilibrium (MD) block, (iii) calculated frequent of each meplotypes in MD block and performed case-control association test and (iv) screened for RA-risk meplotypes by odd ratio (OR) and p-values. Ultimately, 545 meplotypes on 334 MD blocks were identified significantly associated with RA (p-value < .05). These meplotypes were mapped to 329 candidate genes related to RA. Subsequently, combined with gene optimization, eight RA-risk meplotypes were identified on three risk genes: HLA-DRB1, HLA-DRB5 and HLA-DQB1. Our results reported the relationship between DNA methylation pattern on HLA-DQB1 and the risk of RA for the first time, demonstrating the co-demethylation of 'cg22984282' and 'cg13423887' on HLA-DQB1 gene (meplotype UU, p-value = 2.90E - 6, OR = 1.68, 95% CI = [1.35, 2.10]) may increase the risk of RA. Our results demonstrates the potential of methylation haplotype analysis to identify RA-related genes from a new perspective and its applicability to the study of other disease.

RABC: Rheumatoid Arthritis Bioinformatics Center.

Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.

Identification of novel meQTLs strongly associated with rheumatoid arthritis by large-scale epigenome-wide analysis.

Rheumatoid arthritis (RA) is highly heritable, and previous studies have suggested that genetic variation may affect susceptibility to RA by altering epigenetic modifications (e.g. DNA methylation). Here we examined how genetic variation influences DNA methylation (DNAm) in RA by integrating individual genetic variation and DNAm data. Epigenome-wide meQTL (methylation quantitative trait loci) analysis was performed on 354 RA patients and 335 controls, scanning 30,101,744 relationships between 62 SNPs and 485,512 DNA methylation sites. Two regulatory relationship pairs (FDR < 0.05) showed very strong associations with RA risk. One was rs10796216-cg00475509, and the DNAm decreased by 0.0168 per addition of allele rs10796216-A. The other was rs6546473-cg13358873, for which a 0.0365 reduction of DNAm at cg13358873 was observed for each addition of allele rs6546473-A, and lower DNAm was found to be significantly associated with RA risk (P = 2.0407e-28). Moreover, both pairs of meQTL showed a strong regulatory relationship only in RA samples, so they can be subsequently considered as risk markers for RA. In conclusion, our integrated analysis of genetic and epigenetic variation suggests that genetic variation may affect the risk of RA by regulating DNA methylation levels. Alterations of DNAm at cg00475509 and cg13358873 loci conferred by rs10796216-A and rs6546473-A allele may suggest a potential risk for RA. Our results deepen our understanding of the genetic and epigenetic mechanisms of RA and provide novel associations that can be further investigated in future studies.

Ribosomal protein L22-like1 (RPL22L1) mediates sorafenib sensitivity via ERK in hepatocellular carcinoma.

Precision medicine in hepatocellular carcinoma (HCC) relies on validated biomarkers that help subgroup patients for targeted treatment. Here, we identified a novel candidate oncogene, ribosomal protein L22-like1 (RPL22L1), which was markedly elevated in HCC, contributed to HCC malignancy and adverse patient survival. Functional studies indicated RPL22L1 overexpression accelerated cell proliferation, migration, invasion and sorafenib resistance. Mechanism studies revealed that RPL22L1 activated ERK to induce atypical epithelial-to-mesenchymal transition (EMT) progress. Importantly, the ERK inhibitor (ERKi) could potentiate sorafenib efficiency in RPL22L1-high HCC cells. In summary, these data uncover RPL22L1 is a potential marker to guide precision therapy for utilizing ERKi to enhance the sorafenib efficacy in RPL22L1-high HCC patients.

Ten Years of EWAS.

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

EWASdb: epigenome-wide association study database.

DNA methylation, the most intensively studied epigenetic modification, plays an important role in understanding the molecular basis of diseases. Furthermore, epigenome-wide association study (EWAS) provides a systematic approach to identify epigenetic variants underlying common diseases/phenotypes. However, there is no comprehensive database to archive the results of EWASs. To fill this gap, we developed the EWASdb, which is a part of 'The EWAS Project', to store the epigenetic association results of DNA methylation from EWASs. In its current version (v 1.0, up to July 2018), the EWASdb has curated 1319 EWASs associated with 302 diseases/phenotypes. There are three types of EWAS results curated in this database: (i) EWAS for single marker; (ii) EWAS for KEGG pathway and (iii) EWAS for GO (Gene Ontology) category. As the first comprehensive EWAS database, EWASdb has been searched or downloaded by researchers from 43 countries to date. We believe that EWASdb will become a valuable resource and significantly contribute to the epigenetic research of diseases/phenotypes and have potential clinical applications. EWASdb is freely available at http://www.ewas.org.cn/ewasdb or http://www.bioapp.org/ewasdb.

Genome-wide haplotype association study identifies risk genes for non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related death worldwide. Most lung cancer is non-small cell lung cancer (NSCLC), in which malignant cells form in the lung epithelium. Mutations in multiple genes and environmental factors both contribute to NSCLC, and although some NSCLC susceptibility genes have been characterized, the pathogenesis of this disease remains unclear. To identify genes conferring NSCLC risk and determine their associated pathological mechanism, we combined genome-wide haplotype associated analysis with gene prioritization using 224,677 SNPs in 37 NSCLC cell lines and 116 unrelated European individuals. Five candidate genes were identified: ESR1, TGFBR1, INSR, CDH3, and MAP3K5. All of these have previously been implicated in NSCLC, with the exception of CDH3, which can therefore be considered a novel indicator of NSCLC risk. Functional annotation confirmed the relationship between these five genes and NSCLC. Our findings are indicative of the underlying pathological mechanisms of NSCLC and provide information to support future directions in diagnosing and treating NSCLC.

EWAS: epigenome-wide association study software 2.0.

Motivation: With the development of biotechnology, DNA methylation data showed exponential growth. Epigenome-wide association study (EWAS) provide a systematic approach to uncovering epigenetic variants underlying common diseases/phenotypes. But the EWAS software has lagged behind compared with genome-wide association study (GWAS). To meet the requirements of users, we developed a convenient and useful software, EWAS2.0. Results: EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our 'population epigenetic framework' and can perform: (i) epigenome-wide single marker association study; (ii) epigenome-wide methylation haplotype (meplotype) association study and (iii) epigenome-wide association meta-analysis. Users can use EWAS2.0 to execute chi-square test, t-test, linear regression analysis, logistic regression analysis, identify the association between epi-alleles, identify the methylation disequilibrium (MD) blocks, calculate the MD coefficient, the frequency of meplotype and Pearson's correlation coefficients and carry out meta-analysis and so on. Finally, we expect EWAS2.0 to become a popular software and be widely used in epigenome-wide associated studies in the future. Availability and implementation: The EWAS software is freely available at http://www.ewas.org.cn or http://www.bioapp.org/ewas.

Recombinant Gallid herpesvirus 2 with interrupted meq genes confers safe and efficacious protection against virulent field strains.

Gallid herpesvirus 2 (GaHV-2) continuously evolves, which reduces the effectiveness of existing vaccines. To construct new GaHV-2 candidate vaccines, LMS, which is a virulent GaHV-2 field strain isolated from diseased chicken flocks in Southwest China in 2007, was modified such that both copies of its meq oncogene were partially deleted. The resulting virus, i.e., rMSΔmeq, was characterized using PCR and sequencing. To evaluate the safety and protective efficacy of rMSΔmeq, specific pathogen-free (SPF) chickens were inoculated with 2000 plaque forming units (pfu) and 20,000pfu of rMSΔmeq immediately after hatching. All birds grew well during the experimental period, and none of the challenged chickens developed Marek's disease-associated lymphoma. In addition, the rMSΔmeq- and CVI988/Rispens-vaccinated SPF chickens were challenged with 1000 pfu and 5000 pfu of the representative virulent GaHV-2 Md5 strain and 1000 pfu of the variant GaHV-2 strains LCC or LTS. The results showed that the rMSΔmeq strain provided complete protection, which was similar to that provided by the CVI988/Rispens vaccine (protective index (PI) of 95.5) when challenged with a conventional dose of the Md5 strain. However, rMSΔmeq provided a PI of 90.9 when challenged with 5000 pfu of the Md5 strain, which was significantly higher than that provided by the CVI988/Rispens vaccine (54.5). rMSΔmeq provided a PI of 86.4 against LCC, which was equal to that provided by the CVI988/Rispens vaccine (81.8). In addition, rMSΔmeq provided a PI of 100 against LTS, which was significantly higher than that provided by the CVI988/Rispens vaccine (68.2). Altogether, the rMSΔmeq virus provided efficient protection against representative and variant GaHV-2 strains. In conclusion, the rMSΔmeq virus is a safe and effective vaccine candidate for the prevention of Marek's disease and is effective against the Chinese variant GaHV-2 strains.

Co-Infection with Marek's Disease Virus and Reticuloendotheliosis Virus Increases Illness Severity and Reduces Marek's Disease Vaccine Efficacy.

Marek's disease virus (MDV) and reticuloendotheliosis virus (REV) cause Marek's disease (MD) and reticuloendotheliosis (RE), respectively. Co-infection with MDV and REV is common in chickens, causing serious losses to the poultry industry. However, experimental studies of such co-infection are lacking. In this study, Chinese field strains of MDV (ZW/15) and REV (JLR1501) were used as challenge viruses to evaluate the pathogenicity of co-infection and the influence of MD vaccination in chickens. Compared to the MDV-challenged group, the mortality and tumor rates increased significantly by 20.0% (76.7 to 96.7%) and 26.7% (53.3 to 80.0%), in the co-challenged group, respectively. The protective index of the MD vaccines CVI988 and 814 decreased by 33.3 (80.0 to 47.7) and 13.3 (90.0 to 76.7), respectively. These results indicated that MDV and REV co-infection significantly increased disease severity and reduced the vaccine efficacy. The MDV genome load showed no difference in the feather pulps and spleen, and pathogenicity-related MDV gene expression (meq, pp38, vIL-8, and ICP4) in the spleen significantly increased at some time points in the co-challenged group. Clearly, synergistic pathogenicity occurred between MDV and REV, and the protective efficacy of existing MD vaccines was attenuated by co-infection with Chinese field MDV and REV strains.

A Chinese Variant Marek's Disease Virus Strain with Divergence between Virulence and Vaccine Resistance.

Marek's disease (MD) virus (MDV) has been evolving continuously, leading to increasing vaccination failure. Here, the MDV field strain BS/15 was isolated from a severely diseased Chinese chicken flock previously vaccinated with CVI988. To explore the causes of vaccination failure, specific-pathogen free (SPF) chickens vaccinated with CVI988 or 814 and unvaccinated controls were challenged with either BS/15 or the reference strain Md5. Both strains induced MD lesions in unvaccinated chickens with similar mortality rates of 85.7% and 80.0% during the experimental period, respectively. However, unvaccinated chickens inoculated with BS/15 exhibited a higher tumor development rate (64.3% vs. 40.0%), but prolonged survival and diminished immune defects compared to Md5-challenged counterparts. These results suggest that BS/15 and Md5 show a similar virulence but manifest with different pathogenic characteristics. Moreover, the protective indices of CVI988 and 814 were 33.3 and 66.7 for BS/15, and 92.9 and 100 for Md5, respectively, indicating that neither vaccine could provide efficient protection against BS/15. Taken together, these data suggest that MD vaccination failure is probably due to the existence of variant MDV strains with known virulence and unexpected vaccine resistance. Our findings should be helpful for understanding the pathogenicity and evolution of MDV strains prevalent in China.

Characterization of a Gallid herpesvirus 2 strain with novel reticuloendotheliosis virus long terminal repeat inserts.

A bacterial artificial chromosome clone, designated LCY, was constructed from a Gallid herpesvirus 2 (GaHV-2) isolate from a GaHV-2 and reticuloendotheliosis virus co-infected clinical sample. The LCY GaHV-2 insert was sequenced and found to consist of 175,319 nucleotides. LCY GaHV-2 open reading frames (ORFs) had a high sequence identity to those of reference strains. The major difference was that two REV long terminal repeats (LTRs), in the same direction, were inserted at the internal repeat short (IRs)/unique short (Us) and Us/terminal repeat short (TRs) junctions. In addition, the a-like sequence and UL36 were different from other strains. Phylogenetic analysis revealed that LCY was closely related to pandemic strains in China. A pathogenicity study and a vaccination-challenge test were performed on LCY and the reference strain, GA. The results showed that LCY induced gross Marek's disease (MD) lesions and mortality in 71.4 and 7.1% of chickens, respectively, which are lower rates than those observed for the reference strain GA (85.7 and 35.7%). The commercially available CVI988 vaccine provided complete protection against LCY and GA (100%). These results showed that the isolate exhibited lower pathogenicity in SPF chickens. This study revealed that a novel pattern of LTR inserts was found in the strain LCY and that the strain was of low virulence. The present work expands the available genetic information for GaHV-2 and will be useful for the control of MD in China.

The shared and specific mechanism of four autoimmune diseases.

Interaction between genetic and epigenetic mechanisms may lead to autoimmune diseases. The features of these diseases show familial aggregation. The generality and specificity are keys to studying pathogenesis and etiology of them. This research integrated data of genetics and epigenetics, to find disease-related genes based on the levels of expression and regulation, and explored then to the shared and specific mechanism of them by analyzing shared and specific pathways of common four autoimmune diseases, including Type 1 Diabetes Mellitus (T1D), Multiple Sclerosis (MS), Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE). The results showed that Lysosome and Fc gamma R-mediated phagocytosis are shared pathways of the four diseases. It means that the occurrence and development of them may associate with lysosomes and phagocytosis. And there were 2 pathways are shared pathways of three diseases, ribosome pathway associated with susceptibility to MS, RA and SLE, and Pathogenic Escherichia coli infection associated with susceptibility to T1D, MS and RA; 9 pathways are shared pathways of two diseases. The corporate underlying causes of these diseases may be these shared pathways activated. Furthermore, we found that T1D-related specific pathways (Insulin signaling,etc.) were 9, MS (Proteasome,etc.) is also 9, RA and SLE is 10 and 6 respectively. These pathways could help us to reveal shared and specific mechanisms of the four diseases.

Genetic evolution of Gallid herpesvirus 2 isolated in China.

Gallid herpesvirus 2 (GaHV-2), which causes Marek's disease in chickens and has caused extensive economic losses, has recently evolved increased virulence in China. To better understand the genetic basis of the pathogenic characteristics changed and increased virulence, we sequenced the genomes of six new GaHV-2 strains (LCC, LTS, WC/1203, JL/1404, CC/1409, and HS/1412) isolated from chickens with failed immunisation as well as one previously isolated Chinese GaHV-2 strain, J-1. Based on a multiple sequence alignment, several characteristic point mutations were detected in the open reading frames of the Chinese isolates. In addition, two deletions and an insertion were identified at the unique short region and terminal repeat short region junctions in Chinese isolates, and the insertion was a characteristic of the new Chinese isolates. According to a phylogenetic analysis, the GaHV-2 genome diverged substantially over the last two decades in China. Based on the internal repeat long region, the new isolates were closely related to very virulent or very virulent plus strains. Additionally, the new Chinese isolates diverged from the previously isolated strains J-1 and 814. In conclusion, our results provide evidence that Chinese GaHV-2 strains contain characteristic sequences, especially the new isolates. The observed genetic divergence in the new Chinese GaHV-2 strains over the last two decades may be related to observed changes in pathogenic characteristics and virulence.

Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD.