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Identification of novel proteins in inflammatory bowel disease based on the gut-brain axis: a multi-omics integrated analysis

Clinical Proteomics volume 21, Article number: 59 (2024) Cite this article

Abstract

Background

The gut-brain axis has garnered increasing attention, with observational studies suggesting its involvement in the disease activity and progression of inflammatory bowel disease (IBD), but the precise mechanisms remain unclear.

Materials and methods

In this study, we aimed to investigate “novel proteins” underlying IBD in the brain using a comprehensive multi-omics analysis approach. We performed integrated analyses of proteomics and transcriptomics in the human prefrontal cortex (PFC) tissue, coupled with genome-wide association studies (GWAS) of IBD, crohn’s disease (CD), and ulcerative colitis (UC). This included performing protein-wide association studies (PWAS), transcriptome-wide association studies (TWAS), Mendelian randomization (MR), and colocalization analysis to identify brain proteins associated with IBD and its subtypes.

Results

PWAS analyses identified and confirmation 9, 9, and 6 brain proteins strongly associated with IBD, CD, and UC, respectively. Subsequent MR analyses revealed that increased abundance of GPSM1, AUH, TYK2, SULT1A1, and FDPS, along with corresponding gene expression, led to decreased risk of IBD. For CD, increased abundance of FDPS, SULT1A1, and PDLIM4, along with corresponding gene expression, also decreased CD risk. Regarding UC, only increased abundance of AUH, along with corresponding gene expression, was significantly associated with decreased UC risk. Further TWAS and colocalization analyses at the transcriptome level supported strong associations of SULT1A1 and FDPS proteins with reduced risk of IBD and CD.

Conclusion

The two “novel proteins,” SULT1A1 and FDPS, are strongly associated with IBD and CD, elucidating their causal relationship in reducing the risk of IBD and CD. This provides new clues for identifying the pathogenesis and potential therapeutic targets for IBD and CD.

Introduction

Inflammatory bowel disease (IBD) represents a chronic inflammation of the gastrointestinal tract, encompassing two main clinical entities: Crohn’s disease (CD) and ulcerative colitis (UC). IBD is characterized by a relapsing and remitting course of gastrointestinal symptoms such as rectal bleeding, abdominal pain, and diarrhea [1] The incidence of IBD is steadily increasing in regions like North America, Oceania, and Europe [2]. However, despite ongoing research efforts, the exact etiology of IBD remains incompletely understood, and there is currently no curative therapy available. Additionally, issues such as medication resistance and adverse drug reactions underscore the urgent need for novel therapeutic approaches [3].

In recent years, the intricate and extensive relationship between IBD and the nervous system has garnered increasing attention, leading to the conceptualization of the gut-brain axis (GBA). Evidence suggests a bidirectional interaction between GBA and IBD [4, 5], with meta-analyses supporting these findings [6]. Numerous studies have implicated psychological stress in modulating intestinal permeability, motility, sensitivity, gut microbiota composition, as well as promoting the development and reactivation of intestinal inflammation [7,8,9], ultimately influencing the course of IBD [10]. Intestinal inflammation is also believed to alter brain activity and behavior through GBA regulation, potentially triggering psychiatric and neurodegenerative disorders [11,12,13]. Consequently, there is increasing interest in understanding the impact of the nervous system on IBD pathogenesis and exploring IBD therapeutic strategies based on the GBA concept [14].

Genetic susceptibility is a hallmark of IBD, with early genetic studies indicating a relative risk of over fivefold for first-degree relatives of IBD patients compared to the general population [15]. Significant advancements in IBD genetics have been achieved with the rapid development of genomic technologies such as whole-exome sequencing and genome-wide association studies (GWAS), identifying over 240 risk loci that shed light on various pathogenic mechanisms involving bacterial recognition, inflammation, immunity, and autophagy [16]. However, our understanding of the genetic and proteomic associations with IBD in the central nervous system remains limited, hindered by challenges in conducting relevant animal experiments. Integration of GWAS data with multidimensional quantitative trait locus (QTL) data holds promise for identifying specific genes or proteins underlying IBD pathogenesis [17].Previous research has explored therapeutic targets for inflammatory bowel disease using drug-target Mendelian randomization (MR) [18], while other scholars have utilized Summary data-based MR (SMR) analysis to investigate therapeutic targets related to important pathological mechanisms like endoplasmic reticulum stress in UC and CD [19]. However, research on the genetic and proteomic associations with IBD in the central nervous system based on the gut-brain axis remains limited.

In this study, we aim to investigate novel proteins underlying IBD in the brain using a comprehensive multi-omics approach. Firstly, we integrate two sets of protein quantitative trait locus (pQTL) data obtained from human brain tissue and summary statistics from IBD GWAS to conduct a proteome-wide association study (PWAS) to identify proteins associated with IBD. Subsequently, we employ two-sample MR analysis to confirm causal relationships between significant proteins and their upstream mRNA and utilize genetic colocalization analysis to assess the probability of two traits sharing the same causal variants. Finally, we validate the association of key proteins at the mRNA level through transcriptome-wide association analysis (TWAS). Proteins passing all these tests will be identified as novel players in the pathogenesis of IBD (Fig. 1).

Fig. 1
figure 1

Research flow chart. IBD: Inflammatory Bowel Disease; CD: Crohn’s Disease; UC: Ulcerative Colitis; PWAS: Proteome-wide association studies; TWAS: Transcriptome-wide association studies; pQTL: protein Quantitative Trait Loci; eQTL: expression Quantitative Trait Loci

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Materials and methods

Data sources

Human brain proteomics data

For this study, a total of four sets of QTL datasets were utilized as genetic instrumental variables, consisting of two pQTL and two eQTL datasets. Both pQTL datasets underwent the same quality control procedures to identify and control for clinical covariates (i.e., age, sex, and final clinical diagnosis of cognitive status) before estimating protein weights. Further details regarding sample description, proteomic analysis, quality control, and statistical analysis are available in the original publications.

pQTL in the discovery PWAS: The discovery dataset was obtained from Wingo et al.‘s study conducted at the Banner Sun Health Research Institute (Banner) [20], comprising 198 individuals of European ancestry diagnosed with either Alzheimer’s disease (AD) or normal cognition. Following quality control, a subset of 152 individuals with dorsal lateral prefrontal cortex (dlPFC) tissue samples was selected for quantitative assessment of 11,518 proteins, with roughly balanced gender distribution (87 females, 65 males), and an average age at death of 85 years.

pQTL in the confirmation PWAS: The validation dataset ROSMAP, also developed by Wingo et al. [21], originated from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) cohorts, recruiting 391 individuals from two longitudinal clinical-pathological studies on aging and AD. After quality control, the analysis included dlPFC tissue samples from 376 individuals of European ancestry.

Human brain transcriptomics data

The eQTL dataset from PsychENCODE was generated from the prefrontal cortex (PFC) of 1,378 human individuals [22], incorporating 2,542,908 single nucleotide polymorphism(SNP)-gene expression pairs adjusted for 50 PEER factors. Summarized data can be downloaded from the SMR website (https://cnsgenomics.com/software/smr/#eQTLsummarydata).

eQTL in the verification TWAS: The transcriptomic data for TWAS in this study were sourced from the CommonMind Consortium (CMC), utilizing postmortem dlPFC tissue samples from 452 individuals of European ancestry. Genotyping of samples was performed using the Illumina Infinium HumanOmniExpress Exome array, and gene expression was mapped to human Ensembl genes using TopHat v.2.0.9 and Bowtie v.2.1.0 after phasing and imputation. We selected the cis-eQTL dataset, and detailed information regarding quality control, data adjustment, and normalization procedures can be found in the study by Fromer et al. [23]. The summarized statistical data above is from publicly available websites and does not include any personal identifying information of participants, therefore, no additional ethical approval is required for this study.

GWAS summary data

We included GWAS summary data for IBD and its two major subtypes, sourced from the International IBD Genetics Consortium (IIBDGC) [24], comprising 15 European ancestry cohorts. The overall IBD dataset included 12,882 cases and 21,770 controls, while CD comprised 5,956 cases and 14,927 controls, and UC comprised 6,968 cases and 20,464 controls. Cases included in the IIBDGC were diagnosed using standard clinical, endoscopic, and histopathological criteria. The summary statistics data for GWAS is sourced from publicly available websites and does not contain any personal identifying information of participants. Therefore, no additional ethical approval is required for this study.

Statistical analysis

The PWAS and TWAS analyses were conducted by integrating GWAS data for IBD and its two subtypes with two sets of brain proteomics data (discovery and confirmation) and one set of transcriptomic data obtained from brain tissue using the FUSION pipeline (http://gusevlab.org/projects/fusion/). We conducted PWAS analysis to discover and validate brain proteomes associated with IBD. Given that proteins are translated from mRNA, we also explored genes associated with IBD at the transcriptome (mRNA) level by TWAS [25]. Specifically, we first calculated weights for the proteome and transcriptome separately using FUSION. Subsequently, PWAS and TWAS analyses were performed by computing the linear sum of independent SNP z-scores multiplied by weights to combine the genetic effects of IBD and its subtypes (GWAS z-scores) with pre-computed weights. Proteins identified in the discovery dataset and replicated in the confirmation dataset were considered “potential proteins” associated with IBD. To ensure the reliability of FUSION mapping and control for potential effects of multiple testing on PWAS results, we implemented over 10,000 permutations to correct for population stratification and inflation or deflation of the empirical null distribution in GWAS, applying the false discovery rate (FDR) using the Benjamini-Hochberg (BH) method with permutation proteins with FDR-adjusted P < 0.05 were considered significant. Conditional quantile–quantile (Q–Q) plots were used to visualize FDR P-values to assess enrichment of pleiotropy and shared risk loci for genes associated with IBD. Additionally, due to structural complexity, the major histocompatibility complex (MHC) region on chromosome 6 was excluded from the analysis. The linkage disequilibrium reference panel commonly used for this study comprised 1,190,321 HapMap SNPs from 489 individuals of European ancestry in the 1000 Genomes Project.

Mendelian randomization analysis

MR is a genetic method that investigates causal relationships between exposure and outcome using SNPs significantly associated with exposure, closely correlated with genetic instrumental variables (IVs) across the entire genome. This study adheres to the STROBE-MR guidelines [26]. In this study, IVs for exposure were derived from the eqtl and pqtl datasets, representing proteins “associated protein” with significant associations with IBD and its subtypes tested through double verification in PWAS (discovery and confirmation). We selected SNPs with genome-wide significance (P < 5 × 10− 8) for these genes and aggregated them within 10 MB distance with LD R2 ≤ 0.001 as IVs. Next, IVs were extracted from GWAS summary data for outcome traits (IBD and its two subtypes) and harmonized in exposure and outcome GWAS datasets. Generally, MR effects were evaluated using the inverse variance-weighted (IVW) method. However, after clumping, most pQTLs or eQTLs had only one SNP, at which point the “Wald ratio” method was used for MR assessment. Proteins were deemed “vital protein” if both eQTLs and pQTLs were causally associated with IBD and its subtypes. The aforementioned algorithm was implemented using the “Twosample MR” R package.

Colocalization analysis

We further conducted colocalization analysis using the colco.abf function in the R package “Coloc” to assess the likelihood of shared causal signals between risk loci for IBD and its subgroups and pQTLs or eQTLs. “Coloc” employs Bayesian algorithms to generate posterior probabilities for five mutually independent variables, where posterior probability PPH3 + PPH4 > 0.8 is typically interpreted as colocalization [27]. The combined significance from PWAS, MR, colocalization, and TWAS analyses greatly ensured the accuracy of the impact of “vital protein” on IBD and ultimately identified “novel protein”.

Results

Discovery and confirmation PWAS for IBD

In the discovery phase of PWAS (Banner), we identified 14 proteins whose levels in the brain were significantly associated with (P ≤ 0.05/1147 = 4.36E-05) susceptibility to IBD. Among these 14 proteins, the minimum absolute Z-value was 4.51, and the minimum P-value was 6.63E-06. Subsequently, independent confirmatory PWAS using a different reference brain proteome (ROSMAP) replicated 9 genes (P ≤ 0.05/1761 = 2.84E-05), accounting for a high proportion of 64.3% (Table 1; Fig. 2A; Additional file1 Table S1).

Table 1 Results of PWAS and co-localization analysis identifying Brain proteins Associated with IBD and its subtypes
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For CD, in the discovery PWAS (Banner), we found 14 proteins whose levels were associated with susceptibility to CD (P ≤ 0.05/1147 = 4.36E-05). Among these 14 proteins, the minimum absolute Z-value was 4.13, and the minimum P-value was 3.69E-05. Subsequently, independent confirmatory PWAS replicated 9 genes (P ≤ 0.05/1761 = 2.84E-05), accounting for a high proportion of 64.3% (Table 1; Fig. 2B; Additional file1 Table S2).

In the case of UC, in the discovery PWAS (Banner), we identified 9 proteins whose levels were associated with susceptibility to UC (P ≤ 0.05/1147 = 4.36E-05). Among these 9 proteins, the minimum absolute Z-value was 4.09, and the minimum P-value was 4.23E-05. Subsequently, independent confirmatory PWAS replicated 6 genes (P ≤ 0.05/1761 = 2.84E-05), accounting for a high proportion of 66.7% (Table 1; Fig. 2C; Additional file1 Table S3).

Fig. 2
figure 2

Manhattan plots of PWAS and TWAS for inflammatory bowel disease and its subtypes. Manhattan plots depict significant human brain proteins and genes discovered in PWAS and TWAS for IBD and its subtypes. Each point represents a single test of association between a gene and phenotype, plotted based on genomic position on the x-axis and Z-value on the y-axis. Statistically significant proteins and genes identified through analysis are plotted, with annotated regions denoting those that have been validated. Proteins identified in both discovery PWAS and confirmation PWAS are highlighted in red and blue fonts, with red representing Banner in discovery PWAS and blue representing ROSMAP in confirmation PWAS. Green font indicates genes significantly identified in TWAS analysis of proteins validated by PWAS. Subplots are labeled for IBD, CD, and UC

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Finally, consistent patterns were observed in all discovery and confirmation conditional Q-Q plots, showing significant upward deviation, indicating significant pleiotropic enrichment of dlPFC brain tissue proteins with IBD and related phenotypes (Fig. 3).

Fig. 3
figure 3

Conditional quantile-quantile plots. The dashed line represents the expected line under the null hypothesis, with leftward deviation indicating the degree of pleiotropic enrichment. (A) Conditional Q-Q plot summarizing PWAS/TWAS and IBD. (B) Conditional Q-Q plot summarizing PWAS/TWAS and CD. (C) Conditional Q-Q plot summarizing PWAS/TWAS and UC. IBD: Inflammatory Bowel Disease; CD: Crohn’s Disease; UC: Ulcerative Colitis

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MR analysis

Two-sample MR further confirms the causal relationship between the “Banner dataset” and “potential proteins” in brain proteomics and IBD and its subtypes. Using the “Wald ratio” method, 9 “associated proteins” were found to be causally associated with IBD, with most proteins reducing the risk of IBD. Specifically, an increase in abundance of INPP5E, GPSM1, AUH, LNPEP, GPX1, TYK2, SULT1A1, and FDPS led to a decrease in IBD risk, while only an increase in LSP1 abundance resulted in an increased risk of IBD. In CD, LIME1, LNPEP and MSTO1 did not have genome-wide significant SNPs (P<5 × 10− 8) and were therefore not included in MR analysis. However, the remaining 6 proteins were all causally associated with CD, with significant associations observed for an increase in abundance of GPX1, INPP5E, FDPS, SULT1A1, PDLIM4, and HINT1, resulting in a decrease in CD risk. As for UC, LIME1 did not have genome-wide significant SNPs, but the remaining 5 proteins were causally associated with IBD. Among these, an increase in abundance of GPX1, INPP5E, PANK4, and AUH was associated with a decrease in UC risk, while only an increase in the abundance of LSP1 is associated with an increased risk of UC (Table 2).

Table 2 Mendelian randomization analysis validating causal relationships at the proteomic level
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The PsychENCODE eQTL summary dataset was used to further examine whether these “associated proteins” remained causally associated with IBD at the gene (mRNA) level. Specifically, we validated transcriptomic data for 7, 3, and 3 proteins in IBD, CD, and UC, respectively. For IBD, the LSP1 gene did not show a significant causal relationship with IBD, while the AUH, TYK2, SULT1A1, FDPS, and GPSM1 genes exhibited the same direction of causal relationship as the expressed brain tissue proteins. In CD, 3 genes, FDPS, SULT1A1, and PDLIM4, showed the same direction of causal relationship as the expressed brain tissue proteins. For UC, only the AUH gene showed the same direction of causal relationship as the expressed brain tissue proteins, while the LSP1 and PANK4 genes did not show a significant causal relationship with UC (Table 3).

Table 3 Mendelian randomization analysis validating causal relationships at the transcriptomic level
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Colocalization and TWAS validation

Colocalization analysis was used to scan for shared pathogenic genes between IBD, CD, and UC in the above conclusions. The results showed that most of the proteins confirmed by PWAS shared causal variant drivers with IBD and its subgroups, with FDPS, GPX1, LNPEP, and SULT1A1 shared in IBD, FDPS, GPX1, HINT1, LNPEP, PDLIM4, and SULT1A1 shared in CD, and GPX1, LSP1, and PANK4 shared in UC. Finally, TWAS provided secondary validation for the “vital protein” SULT1A1 and FDPS, both strongly associated with IBD and CD, while other genes did not yield significant findings (Table 4; Fig. 4, Additional file1 Table S4). Notably, the genes SULT1A1 and FDPS, along with their expressed proteins, shared common causal variant drivers with IBD and CD, thus ultimately identified as “novel proteins”.

Table 4 Transcriptomic levels of brain proteins associated with inflammatory bowel disease and its subtypes in TWAS-Based secondary validation PWAS analysis
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Fig. 4
figure 4

Co-localization analysis plot. Illustration of co-localization results validated through PWAS, MR, and TWAS in IBD and CD. The upper and lower portions of the figure represent sections for IBD and CD, respectively. Annotations denote: (A) IBD-associated SULT1A1 protein from discovery pQTLs data; (B) IBD-associated SULT1A1 gene from PsychENCODE eQTLs data; (C) IBD-associated FDPS protein from discovery pQTLs data; (D) IBD-associated FDPS gene from PsychENCODE eQTLs data; (E) CD-associated SULT1A1 protein from discovery pQTLs data; (F) CD-associated SULT1A1 gene from PsychENCODE eQTLs data; (G) CD-associated FDPS protein from discovery pQTLs data; (H) CD-associated FDPS gene from PsychENCODE eQTLs data

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Discussion

This study represents the first comprehensive exploration of the genetic correlations between IBD and its two subtypes with the brain proteins. The current study has several strengths. Firstly, the design of discovery and validation based on two sets of proteomic data from the PFC enhances the robustness of our investigative findings, preliminarily identifying “potential proteins” associated with IBD and its subtypes. These findings were then validated at the protein and mRNA levels through MR, assessing their causal associations, followed by colocalization analysis evaluating causal variant drivers. Finally, TWAS based on mRNA data from the PFC was utilized to further validate genes associated with IBD and its subtypes among these candidate proteins. Our results indicate that 9 “associated proteins” and their “associated genes” are causally associated with IBD, with 6 causally associated with CD and 5 with UC. Colocalization analysis suggests the presence of common causal variants among them. Through TWAS secondary validation, only SULT1A1 and FDPS, these two “novel proteins,” passed all the aforementioned rigorous criteria, demonstrating strong associations with reduced risk of IBD and CD. These findings represent historical firsts, robustly unveiling new proteins associated with the brain in relation to IBD and CD, potentially serving as critical links between the brain and IBD/CD, or even as potential therapeutic targets.

Currently, the increasing incidence of IBD is partly attributed to rapid urbanization, industrialization, and the Westernization of lifestyle, placing individuals in prolonged high-stress environments. Additionally, dietary changes contribute to the heightened risk of IBD [4]. Furthermore, stress-induced mental disorders may increase intestinal permeability via the GBA, facilitating the translocation of gut bacteria to peripheral lymphoid organs, triggering innate immune responses, and inducing local gastrointestinal inflammation. Moreover, stress can alter visceral hypersensitivity, motility [28, 29], and involve pathways such as the gut-brain axis, central nervous system responses, and stress pathways (hypothalamic-pituitary-adrenal axis), as well as pathways involving gastrointestinal hormones (e.g., corticotropin-releasing factor) [30], Understanding and managing patients with overlapping disorders of gut-brain interaction), all of which are potential mechanisms promoting the occurrence of IBD. Compared to UC patients, individuals with CD may be more susceptible to psychological factors, exacerbating their condition [31]. This partly explains why this study ultimately identified brain proteins associated with CD rather than UC.

The PFC tissue selected in this study is closely associated with human emotion and mood, which is crucial for chronic stress-induced depressive and anxiety-like behaviors [32]. Prior to this, many key targets and proteins related to emotional disorders have been identified from human brain PFC tissue [33,34,35]. Based on the concept of the “ GBA ”, we aimed to explore new targets and proteins associated with IBD to aid in the research and development of new drugs.

Through rigorous testing, including at the protein and mRNA levels, we have identified two proteins, SULT1A1 and FDPS, which consistently influence IBD in the same direction at various levels. SULT1A1 is a member of the human cytosolic sulfotransferase family, catalyzing the metabolism of 3’-phosphoadenosine-5’-phosphosulfate, thereby influencing neurotransmitter transmission [36]. Research indicates that SULT1A1 has two allosteric binding sites, one for catechins (natural polyphenolic compounds) and another for non-steroidal anti-inflammatory drugs, which are believed to be associated with migraine occurrence [37]. This discovery highlights the impact of SULT1A1 on the nervous system. Zhao et al. [38] suggested that SULT1A1 may contribute to improving intestinal inflammation and promoting intestinal barrier repair. Certainly, post-translational modifications (PTMs) of proteins, including neddylation, acetylation, glycosylation, and phosphorylation, also play significant roles in influencing IBD [39]. Ehrentraut SF [40] proposed that PTMs tightly regulate inflammation by altering the functional relevance of protein networks, which is a mechanism relevant to the onset of IBD. The role of SULT1A1 in the interaction between gut microbiota and host metabolism [41] may be influenced by PTMs. Specifically, a critical pathway in gut homeostasis involves the phosphorylation of IκBα and strict regulation of NF-κB activity [42, 43]. Activation of the NF-κB pathway occurs via IκBα phosphorylation, and inhibition of NF-κB activation depends on cullin deneddylation [42]. Notably, neddylation, a PTM, targets cullin proteins specifically [44], facilitating the conjugation of ubiquitin-modified proteins with their target substrates, thereby regulating various cellular processes. Research also indicates that inhibiting cullin 2 neddylation can modulate hypoxia-inducible factor (HIF) to alleviate mucosal inflammation [45, 46].

For FDPS protein, which is involved in the biosynthesis of cholesterol and the metabolism of steroids, and it participates in various crucial cellular functions related to the pathogenesis of tumors, cardiovascular diseases, and autoimmune diseases [47]. However, there is currently no evidence suggesting its association with IBD. Yet, exploring whether FDPS acts as an intermediary in communication between the brain and IBD, along with PTM effects, remains worthwhile. Additionally, this study identified some potential genes, although they did not show satisfactory results in the secondary validation TWAS analysis, they have been previously noted by other scholars. For example, LSP1 has been identified as a risk gene in UC and normal populations [48], consistent with our findings. The deficiency of GPX1 is also considered to be associated with the early inflammatory response of IBD [49]. INPP5E has been identified as a target gene for IBD-associated variations in previous GWAS analyses, and our study further links it to the brain-gut axis.

Despite the rigorous analyses conducted, there are still some noteworthy limitations. Firstly, the limited SNPs in the genetic landscape of brain proteomics stem from the relatively small samples in the original studies, potentially introducing bias into our investigation of the proteome. Similarly, issues arise in transcriptomic studies due to sample size limitations, which could be addressed by developing new databases. Additionally, while this study presents conclusions from both genetic and expressed protein levels, these conclusions are derived from statistical analyses and require further functional studies to validate our findings.

Conclusion

This study provides the first evidence, based on multi-omics data from the brain, supporting the strong associations and causal relationship between two novel proteins, SULT1A1 and FDPS, with IBD and CD, offering new insights into the pathogenesis and potential therapeutic targets for IBD and CD.

Data availability

The ROSMAP and Banner datasets, including weights and pQTL data, can be accessed at https://www.synapse.org/#!Synapse:syn23627957;GWAS summary data for IBD, CD, and UC are sourced from the International IBD Genetics Consortium and can be accessed at https://www.ibdgc.org/;The eQTL summary dataset from PsychENCODE can be found at https://cnsgenomics.com/software/smr/#eQTLsummarydata; The human brain transcriptome data for TWAS is sourced from the CommonMind Consortium and can be accessed at www.synapse.org/CMC.

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Acknowledgements

The authors thank all the participants and researchers who contributed and collected data.

Funding

This work is supported by grants from the Jiangxi University of Chinese Medicine Science and Technology Innovation Team Development Program (No. CXTD22011).

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Authors and Affiliations

  1. School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China

    Yifeng Xu & Zhaoqi Yan

  2. Affiliated Hospital of Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China

    Liangji Liu

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Contributions

XYF contributed to the conception and design of the study and data analysis. XYF and YZQ contributed to design of the study and wrote the first draft of the manuscript. LLJ contributed to the revision of the manuscript. All authors contributed to the article and approved the submitted version.

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Correspondence to Liangji Liu.

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Xu, Y., Yan, Z. & Liu, L. Identification of novel proteins in inflammatory bowel disease based on the gut-brain axis: a multi-omics integrated analysis. Clin Proteom 21, 59 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12014-024-09511-7

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Keywords

Clinical Proteomics

ISSN: 1559-0275