Skip to main content
NCBI home page
Medicine logoLink to Medicine
. 2026 Jul 3;105(27):e49635. doi: 10.1097/MD.0000000000049635

The causal relationship between the palmitoylation gene ZDHHC13 and ulcerative colitis: A Mendelian randomization study implicating CD62L-monocyte AC

Yanjie Chen a,b, Min Luo b, Ke Li a,*
PMCID: PMC13337070  PMID: 42410861

Abstract

This study explores the potential mechanisms between palmitoylation and ulcerative colitis (UC) through Mendelian randomization, bioinformatics analysis combined with eQTL and protein quantitative trait loci. This study selected a dataset of 5034 UC patients from the Finnish database and conducted Mendelian randomization analysis with palmitoylation target genes to explore the causal relationships between the two. Sensitivity and pleiotropy tests were performed alongside bioinformatics analysis to screen for the best target genes, ensuring the robustness of the results. Finally, immune cells were included for mediation analysis between palmitoylation and UC to explore potential mechanisms. Through Mendelian randomization analysis combined with sensitivity and pleiotropy tests, 5 target genes related to palmitoylation were identified to have a significant causal relationship with UC. Subsequent bioinformatics analysis confirmed ZDHHC13 and PPT1 as potential gene targets. By including immune cells in the mediation analysis, it was ultimately found that there is a potential mechanism involving ZDHHC13, CD62L- monocyte AC, and UC. There is a significant causal relationship between palmitoylation and UC. Furthermore, the palmitoylation gene ZDHHC13 can regulate CD62L- monocyte AC immune cells, inhibiting the occurrence of UC.

Keywords: CD62L- monocyte AC, Palmitoylation, ulcerative colitis, ZDHHC 13

1. Introduction

Ulcerative colitis (UC) is the most common inflammatory bowel disease globally, characterized by chronic inflammation and ulceration of the colonic mucosa. It is an autoimmune disease associated with genetic susceptibility, dysregulation of immune responses, and dysbiosis of the gut microbiota.[1] This disease significantly reduces the quality of life of patients and markedly increases the risk of developing colorectal cancer, making it one of the modern challenging diseases listed by the World Health Organization. Additionally, patients with UC may experience extraintestinal manifestations affecting other organs such as the joints, skin, eyes, liver, gallbladder, and mucous membranes.[2,3] The exact mechanism of UC development is still unclear; however, most studies suggest that it results from a combination of factors including genetically determined mucosal immunity, host susceptibility, and the gut microbiome environment.[4] With the advancement of intestinal immunology, immune responses and their role in the pathogenesis of UC have garnered increasing attention. The development of UC is primarily determined by genetic susceptibility, and inflammatory responses resulting from immune dysregulation may be a key pathogenic mechanism. The gastrointestinal tract harbors the largest reservoir of macrophages and neutrophils in the human body, and mucosal innate immune responses play a critical role in the initiation and progression of UC.[5]

Protein palmitoylation, referred to as palmitoylation, is a reversible lipid posttranslational modification catalyzed by the zinc-finger DHHC-type (ZDHHC) protein family. De-palmitoylation, the reverse reaction, is catalyzed by palmitoyl-protein thioesterases (PPT), including acyl-protein thioesterases (APT1/2), PPT1/2, or proteins 17A/B/C (ABHD17A/B/C) that contain α/β hydrolase domain.[6] Therefore, further exploring the potential targets of palmitoylation modifications in the pathogenesis of UC is of practical significance.

In this research, we will combine a review of gene expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) related to palmitoylation modification gene information, along with data from genome-wide association studies (GWAS) on UC populations. We will then employ Mendelian randomization (MR) causal inference to identify potential targets of palmitoylation modification in the pathogenesis of UC, further validate the robustness of these targets using bioinformatics techniques, and ultimately conduct mediation analysis in immune cells to explore the mechanistic role of palmitoylation in the development of UC.

2. Methods

2.1. Research design

We have summarized 31 palmitoylation target genes from the above review. Based on this, we will extract the pQTL genes related to palmitoylation from the UK Biobank Protein Phenotype Project (UKB-PPP) and the eQTL genes from the eQTLGen database. First, after selecting eQTL at the gene level and pQTL as instrumental variables at the protein level, we will conduct MR analysis using data on UC from FinnGen. Further screening will be conducted to identify palmitoylation genes that reach the significance threshold after sensitivity and horizontal pleiotropy testing, in order to determine potential palmitoylation targets related to UC. Then, we will validate the robustness of the palmitoylation targets in UC patients through bioinformatics analysis, ultimately incorporating immune cells for mediation analysis to explore the potential mechanisms between palmitoylation and UC.

2.2. Data sources

Firstly, the eQTLs data is derived from the eQTLGen consortium (https://eqtlgen.org/), which includes 15,673 genes from 31,684 healthy European ancestry blood samples[7]; the pQTL data comes from the UKB-PPP (http://ukb-ppp.gwas.eu).[8] Secondly, the GWAS data for UC patients is sourced from the FinnGen database (https://www.finngen.fi/en/access_results), which includes 5034 UC patients and 371,530 healthy controls. The bioinformatics analysis is based on the GEO database (https://www.ncbi.nlm.nih.gov/geo/), selecting the gene chip (GSE87466) for result validation, which includes 87 UC patients and 21 healthy controls. This study is based on publicly available datasets, all of which have been approved by the relevant institutional review boards.

2.3. Mendelian randomization analysis

To ensure the exclusivity and correlation of genetic variations, this study conducted strict quality control and screening on the aggregated data from GWAS of exposure factors (palmoylation-related genes or traits).In the initial stage, we will extract single nucleotide polymorphisms (SNPs) that are significantly associated with the exposure factors as potential instrumental variables (IVs). To address the issue that the traditional genome-wide significance threshold (P < 1.0 × 10−8) might lead to insufficient number of instrumental variables, and to balance the statistical power, we adopted a more lenient but still widely accepted significance threshold (P < 1.0 × 10−5)[9] to ensure the feasibility of the subsequent multi-angle validation analysis. After selecting the initial SNPs, in order to eliminate the bias caused by linkage disequilibrium, we set strict parameters (r2 < 0.001, clustering distance = 10000kb) to ensure that the selected SNPs are independent of each other and to avoid duplicate counting due to genetic associations. Ensure the consistency of the effect alleles by comparing the exposed data with the outcomes and the SNPs of intermediate allele frequencies. Furthermore, in this study, the R software (version4.3.3) and the “TwoSampleMR” package were used to conduct a two-sample Mendelian randomization analysis. The inverse variance weight (IVW) method is adopted as the main causal effect estimation model. IVW is equivalent to conducting a weighted meta-analysis of the Wald ratios of each SNP. Under the assumption that all instrumental variables are effective (there is no horizontal multiplicity), it provides the most accurate causal estimation value. Furthermore, to ensure the robustness of the results, we concurrently employed MR-Egger regression and weighted median method for supplementary verification. To further verify the core assumptions of the MR analysis and the credibility of the evaluation results, we employed Cochran Q test, MR-Egger intercept test, and MR-PRESSO global test for verification.[10]

2.4. Bioinformatics validation

In this study, the dataset will be extracted from the GEO database using “Homo sapiens” and “Expression profiling by array” as selection criteria, analyzing the gene chip (GSE87466) in conjunction with the identified potential targets to validate the expression levels of palmitoylation target genes in patients with UC.

2.5. Mediation analysis

Based on the aforementioned bioinformatics analysis, this study will validate the expression levels of palmitoylation target genes in patients with UC and further explore the potential mechanisms among immune cells, palmitoylation, and UC. We will conduct a mediation analysis by incorporating immune cells that have a significant causal relationship with UC and palmitoylation genes, building upon the initial phase of MR analysis. The calculation of the mediation effect ratio is based on the formula β (A) * β (B)/ β (Total),[11] where β (A) is the effect value of the mediator and the palmitoylation gene, β (B) is the effect value of the mediator and UC, and β (Total) is the effect of the palmitoylation gene on UC. A higher proportion of the mediation effect indicates a more favorable result.

3. Results

3.1. eQTL/pQTL screening for palmitoylation target genes

By integrating pQTL genes from the UKB-PPP related to palmitoylation and eQTL genes from eQTLGen, we identified a total of 31 target genes from 1556 genes in pQTL and 15,673 genes in eQTL. Among these, 22 were selected from eQTL and 1 from pQTL (Figs 1 and 2).

Figure 1.

Figure 1.

Open in a new tab

Intersection target genes of palmitoylation in eQTL. eQTL = expression quantitative trait loci.

Figure 2.

Figure 2.

Open in a new tab

Intersection target genes of palmitoylation in pQTL. pQTL = protein quantitative trait loci.

3.2. Causal association between palmitoylation modification and UC

The dataset from the Finnish database (finngen_R9_K11_UC_STRICT2) was selected for the MR analysis related to palmitoylation genes, primarily focusing on the IVW results, which indicated that 4 target genes showed significant causal relationships in eQTL: PPT2 (P = .009, OR = 1.934 (1.177, 3.175)), ZDHHC1 (P = .049, OR = 2.156 (1.002, 4.639)), ZDHHC13 (P = .016, OR = 2.156 [1.002, 4.639]), ZDHHC18 (P<.001, OR = 2.156 [1.002, 4.639]); In the pQTL analysis, the target gene PPT1 showed a significant causal relationship with the following results: (P = .009, OR = 1.189 [1.044, 1.355]) (Fig. 3). After further testing for heterogeneity, pleiotropy, and sensitivity analysis, we excluded the ZDHHC target genes. The remaining genes showed no detectable horizontal pleiotropy, indicating that the results are robust (Table 1).

Figure 3.

Figure 3.

Open in a new tab

Mendelian randomization analysis of palmitoylation genes and UC. CI = confidence interval, OR = odds ratio, UC = ulcerative colitis.

Table 1.

MR sensitivity analysis results of palmitoylation genes and UC.

Gene Cochran Q MR-PRESSO MR-Pleiotropy
Q-value P-value P-value Intercept P-value
PPT1 8.111 .703 .663 0.004 .802
PPT2 3.361 .499 .607 0.098 .528
ZDHHC1 0.894 .827 - -0.039 .708
ZDHHC13 17.371 .565 .618 0.011 .526
ZDHHC18 13.530 .700 .749 -0.005 .689
Open in a new tab

3.3. Bioinformatics validation of palmitoylation targets

After excluding the palmitoylation target gene ZDHHC1, bioinformatics analysis was conducted on the remaining target genes: PPT1, PPT2, ZDHHC13, and ZDHHC18. The GSE87466 gene chip was selected as the validation dataset, and the results indicated that the expression levels of the 4 gene groups were statistically significant. However, based on the previous MR analysis, it was found that the logic for the target genes PPT2 and ZDHHC18 was inconsistent, leading to the decision to retain only PPT1 and ZDHHC13 (Fig. 4). This indicates that the downregulation of ZDHHC13 or the upregulation of PPT1 may promote the onset of UC.

Figure 4.

Figure 4.

Open in a new tab

Expression levels of palmitoylation genes in UC population. UC = ulcerative colitis.

3.4. Immune cell mediated analysis

In the aforementioned MR analysis and bioinformatics analysis, we ultimately determined that ZDHHC13 and PPT1 have a significant causal relationship with UC, and further incorporated immune cell mediation analysis between UC, ZDHHC13, and PPT1. We ultimately identified 16 types of immune cells that have potential mediating effects in UC (Fig. 5), further mediation analysis results showed that PPT1 did not mediate the influence of immune cells on UC, while ZDHHC13 could mediate the inhibition of UC by 7 types of immune cells (Fig. 6), with the regulation of CD62L- monocyte AC immune cells having an impact of approximately 52% (Table 2).

Figure 5.

Figure 5.

Open in a new tab

Mediation analysis results of UC and immune cells. CI = confidence interval, OR = odds ratio, UC = ulcerative colitis.

Figure 6.

Figure 6.

Open in a new tab

Mediation analysis results of palmitoylation of ZDHHC13 gene and immune cells. CI = confidence interval, OR = odds ratio.

Table 2.

Mediation analysis results.

Exposure Mediator Total effect (Beta) A (Beta) B (Beta) Indirect effect (Beta) Mediation effect/Total effect
ZDHHC13 CD62L- monocyte AC −0.0544 0.2046 −0.2661 −0.0502 0.5202
ZDHHC13 CD62L- monocyte %monocyte −0.0288 0.2847 −0.1013 −0.0758 0.2755
ZDHHC13 Myeloid DC AC 0.0291 0.1847 0.1576 −0.1338 −0.2781
ZDHHC13 Myeloid DC %DC 0.0264 0.1617 0.1634 −0.1311 −0.2525
ZDHHC13 CD62L- myeloid DC AC 0.0163 0.1613 0.1011 −0.1210 −0.1558
ZDHHC13 CD62L- CD86+myeloid DC AC 0.0118 0.1368 0.0863 −0.1165 −0.1128
ZDHHC13 Plasmacytoid DC %DC 0.0289 −0.1713 −0.1688 −0.1336 −0.2762
Open in a new tab

4. Discussion

Protein palmitoylation is a reversible lipid modification primarily catalyzed by the zinc-finger containing palmitoyl S-acyltransferase (PAT) family, specifically the DHHC (Asp-His-His-Cys) type (ZDHHC).[12] Palmitoylation can target several immune regulatory factors by altering their transport, stability, and protein-protein interactions, thereby influencing immune responses.[13] Relevant experimental studies have demonstrated that ZDHHC12 can target the NLRP3 inflammasome for palmitoylation modification, thereby promoting NLRP3 degradation through the chaperone-mediated autophagy pathway,[14] revealing the potential advantages of palmitoylation modification in the treatment of inflammatory autoimmune diseases. UC is an inflammatory bowel disease characterized by chronic inflammatory changes and ulcer formation in the colonic mucosa, and it is also an autoimmune disease associated with genetic susceptibility, dysregulated immune responses, and gut microbiota imbalance.[15] Jinting Li research[16] indicates that the palmitoylation of STAT3 directly affects the integrity of the intestinal mucosa under colitis conditions, while 2’-fucosyllactose (2’-FL) can promote the restoration of the intestinal mucosal barrier and inhibit the inflammation of UC by suppressing the palmitoylation and phosphorylation of STAT3. Although the aforementioned studies have indicated that palmitoylation plays a significant role in the integrity of the intestinal mucosa, the mechanistic connection between palmitoylation and UC still requires further exploration. In this study based on eQTL, pQTL, and GWAS large sample data, we identified 5 palmitoylation target genes that have a significant causal association with the onset of UC after conducting Mendelian randomization analysis to minimize biases. To further verify the robustness of these results and explore potential molecular mechanisms, we conducted bioinformatics analyses on the relevant target genes and included immune cells for mediation analysis, ultimately determining that ZDHHC13 can inhibit the potential pathogenesis of UC by regulating CD62L- monocyte AC.

ZDHHC13, also known as HIP14-like protein (HIP14L), is a member of the ZDHHC family, primarily located in the membrane part of the cell. It is the second protein acyltransferase (PAT) identified in the ZDHHC family that mediates HTT palmitoylation.[17] ZDHHC13 has various complex physiological and pathological functions, including regulating mitochondrial function, palmitoylation modification, Mg2+ ion transport, postnatal skeletal development, skin barrier function, and germ layer differentiation.[18] Existing studies have found that ZDHHC13 plays an important role in the onset and progression of osteoporosis,[19] atopic dermatitis,[20] and melanoma.[21] It is noteworthy that ZDHHC13 has significant characteristics in repairing the mucosal barrier, a finding that provides a novel approach for the prevention and treatment of UC.

Immune imbalance, as one of the important mechanisms in the pathogenesis of UC, has a significant impact on the outcomes and prognosis of patients with UC. We incorporated 730 types of immune cells (accession numbers from GCST0001391 to GCST0002121) into a mediation analysis between palmitoylation and UC, ultimately selecting CD62L- monocyte AC immune cells as the mediating mechanism by which ZDHHC13 influences the progression of UC. CD62L- monocyte AC refers to a specific type of monocyte, where CD62L is an adhesion molecule that facilitates the migration of leukocytes to lymph nodes.[22] This molecule expression can identify functionally distinct memory B cell subsets in mice and is involved in important pathways during memory B cell subset development, mediating immune responses.[23] CD62L+ monocytes not only serve as precursors of macrophages, but also the locally derived macrophages can expand the effector cell pool through proliferation, promoting their polarization into different functional phenotypes. The intervention of macrophage polarization is an important and necessary condition for immune regulation in the treatment of IBD.[24] In studies identifying pathogenic Th17 characteristics in mesenteric lymph nodes of patients with Crohn disease and UC, memory Th cell subsets are further divided into CD62L low effector memory (TEM) and CD62L high central memory (TCM), with TEM cells significantly outnumbering TCM cells in inflamed gut tissue.[25] This is consistent with our findings that the immune regulatory function of monocytes is diminished when CD62L is lacking, showing a low expression state of CD62L during the pathogenesis of UC. Based on relevant studies, antibody-drug conjugates can achieve this through strategic selection of payloads such as topoisomerase inhibitors or olisopim. Modern anti-resistance antitumor proteins can induce immunogenic cell death or apoptosis, and are expected to become a new direction for immune-targeted therapy in UC.[26] Although the results of this study reveal the potential application of the ZDHHC13 palmitoylation target gene in the treatment of UC, further experiments and clinical studies are needed to validate its potential value.

In this study, we first combined Mendelian randomization, bioinformatics, and eQTL/pQTL data to analyze the potential mechanisms between palmitoylation and UC, showcasing innovation in research methods and mechanisms, as well as clinical significance. Interestingly, we also discovered the potential application of the palmitoylation target genes ZDHHC13 and CD62L-monocyte AC in UC. Specifically, the palmitoylated gene ZDHHC13 was found to be able to inhibit the occurrence of UC by regulating the helper immune response mediated by CD62L+ monocytes. Therefore, the recognition of the ZDHHC13-CD62L+ monocyte axis provides a new molecular bridge for understanding the clinical immunopathology of UC. The most significant clinical translational value of this study lies in the possibility it has demonstrated that ZDHHC13 can serve as a new therapeutic target for UC. However, this study still has certain limitations: First, due to the differences in allele frequencies, linkage disequilibrium structures, and environmental exposures among different races, the genetic effects of the palmitoylation gene may exhibit race-specificity. Therefore, the conclusions of this study only represent the causal effects in the European population. In the future, cross-race GWAS data are needed to verify the universality of these findings, and cross-species meta-analysis should be conducted to enhance the statistical power. Secondly, the palmoylation-related genes involved in this study, as an emerging molecular phenotype, have complex regulatory mechanisms, and the direct measurement data of specific protein palmoylation levels in the currently available GWAS data is limited. Therefore, the findings of this study need to be functionally verified at the cellular level (such as functional experiments of palmoylation site mutants) and in animal models (such as the observation of colitis phenotypes after specific gene knockout) to clarify the specific molecular pathways. Thirdly, to ensure sufficient statistical power, this study relaxed the screening threshold for instrumental variables. Although this increased the number of available SNPs to support various sensitivity analyses, it also introduced the potential risk of weak instrumental variable bias. Future studies can adopt more rigorous co-localization analysis to distinguish the true causal signals from the false positive associations caused by linkage disequilibrium. Fourth, in this study, we strictly followed the core assumptions of Mendelian randomization for the selection of instrumental variables. However, due to the biological complexity of the genes related to palmitoylation, it is still difficult to completely rule out potential horizontal pleiotropy.

5. Conclusion

In summary, our research found a significant causal association between palmitoylation and UC, revealing that the palmitoylation gene ZDHHC13 can regulate CD62L- monocyte AC immune cells to inhibit the potential mechanism of UC. This provides valuable insight for future studies aimed at treating UC through the modulation of palmitoylation.

Acknowledgments

We sincerely thank every author for their hard work and the guidance of the teachers of the Shengxin Madman team.

Author contributions

Data curation: Yanjie Chen.

Funding acquisition: Yanjie Chen, Ke Li.

Investigation: Yanjie Chen.

Resources: Yanjie Chen.

Software: Yanjie Chen.

Formal analysis: Min Luo.

Project administration: Min Luo.

Supervision: Min Luo.

Validation: Min Luo.

Visualization: Min Luo.

Conceptualization: Ke Li.

Methodology: Ke Li.

Writing – original draft: Yanjie Chen.

Writing – review & editing: Ke Li.

Abbreviations:

eQTL
expression quantitative trait loci
GWAS
Genome-wide association study
IVW
inverse variance weight
MR
Mendelian randomization
PPT
palmitoyl-protein thioesterases
pQTL
protein quantitative trait loci
SNP
single nucleotide polymorphism
UC
ulcerative colitis

This project is supported by the Hunan Provincial Natural Science Foundation General Project (2022JJ30448) and the Hunan University of Chinese Medicine Graduate Innovation Project (2024CX126).

This study is based on publicly published eQPL, pQTL, GWAS, and GEO data, which have been ethically approved in the aforementioned public databases; therefore, this research does not require ethical approval or informed consent.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

How to cite this article: Chen Y, Luo M, Li K. The causal relationship between the palmitoylation gene ZDHHC13 and ulcerative colitis: A Mendelian randomization study implicating CD62L-monocyte AC. Medicine 2026;105:27(e49635).

Contributor Information

Yanjie Chen, Email: 18876177903@163.com.

Min Luo, Email: 17789851255@163.com.

References

  • [1].Lasa JS, Olivera PA, Danese S, Peyrin-Biroulet L. Efficacy and safety of biologics and small molecule drugs for patients with moderate-to-severe ulcerative colitis: a systematic review and network meta-analysis. Lancet Gastroenterol Hepatol. 2022;7:161–70. [DOI] [PubMed] [Google Scholar]
  • [2].Fabian O, Kamaradova K. Morphology of inflammatory bowel diseases (IBD). Cesk Patol. 2022;58:27–37. [PubMed] [Google Scholar]
  • [3].Bruner LP, White AM, Proksell S. Inflammatory bowel disease. Prim Care. 2023;50:411–27. [DOI] [PubMed] [Google Scholar]
  • [4].Nakase H, Sato N, Mizuno N, Ikawa Y. The influence of cytokines on the complex pathology of ulcerative colitis. Autoimmun Rev. 2022;21:103017. [DOI] [PubMed] [Google Scholar]
  • [5].Huang F, Zhang S, Li X, Huang Y, He S, Luo L. STAT3-mediated ferroptosis is involved in ulcerative colitis. Free Radic Biol Med. 2022;188:375–85. [DOI] [PubMed] [Google Scholar]
  • [6].Zhou B, Hao Q, Liang Y, Kong E. Protein palmitoylation in cancer: molecular functions and therapeutic potential. Mol Oncol. 2023;17:3–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Vosa U, Claringbould A, Westra HJ, et al. ; BIOS Consortium. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat Genet. 2021;53:1300–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Sun BB, Chiou J, Traylor M, et al. ; Alnylam Human Genetics. Plasma proteomic associations with genetics and health in the UK Biobank. Nature. 2023;622:329–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [9].Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27:1133–63. [DOI] [PubMed] [Google Scholar]
  • [10].Xu S, Liang J, Shen T, Zhang D, Lu Z. Causal links between immune cells and asthma: insights from a Mendelian randomization analysis. J Asthma. 2025;62:346–53. [DOI] [PubMed] [Google Scholar]
  • [11].Wang J, Yang M, Xu K, et al. The causal associations between growth factors and constipation: a two-sample Mendelian randomization study. Front Physiol. 2023;14:1204146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].Zhao M, He Z, Liu L, et al. Causal and mediating effects of lipid and facial aging: association study integrating GWAS, eQTL, mQTL, and pQTL data. Lipids Health Dis. 2024;23:342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13].Elliot Murphy R, Banerjee A. In vitro reconstitution of substrate S-acylation by the ZDHHC family of protein acyltransferases. Open Biol. 2022;12:210390. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Das T, Yount JS, Hang HC. Protein S-palmitoylation in immunity. Open Biol. 2021;11:200411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Wang L, Cai J, Zhao X, et al. Palmitoylation prevents sustained inflammation by limiting NLRP3 inflammasome activation through chaperone-mediated autophagy. Mol Cell. 2023;83:281–97.e10. [DOI] [PubMed] [Google Scholar]
  • [16].Le Berre C, Honap S, Peyrin-Biroulet L. Ulcerative colitis. Lancet. 2023;402:571–84. [DOI] [PubMed] [Google Scholar]
  • [17].Li J, Wei Y, Liu C, et al. 2’-Fucosyllactose restores the intestinal mucosal barrier in ulcerative colitis by inhibiting STAT3 palmitoylation and phosphorylation. Clin Nutr. 2024;43:380–94. [DOI] [PubMed] [Google Scholar]
  • [18].Huang K, Sanders SS, Kang R, et al. Wild-type HTT modulates the enzymatic activity of the neuronal palmitoyl transferase HIP14. Hum Mol Genet. 2011;20:3356–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [19].Zhang Y, Fan S, He L, Li L. The ZDHHC13/ZDHHC17 subfamily: from biological functions to therapeutic targets of diseases. Pharmacol Res. 2024;209:107418. [DOI] [PubMed] [Google Scholar]
  • [20].Song IW, Li WR, Chen LY, et al. Palmitoyl acyltransferase, ZDHHC13, facilitates bone mass acquisition by regulating postnatal epiphyseal development and endochondral ossification: a mouse model. PLoS One. 2014;9:e92194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Chen LY, Yang-Yen HF, Tsai CC, et al. Protein palmitoylation by ZDHHC13 protects skin against microbial-driven dermatitis. J Invest Dermatol. 2017;137:894–904. [DOI] [PubMed] [Google Scholar]
  • [22].Chen S, Han C, Miao X, et al. Targeting MC1R depalmitoylation to prevent melanomagenesis in redheads. Nat Commun. 2019;10:877. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Laidlaw BJ, Duan L, Xu Y, Vazquez SE, Cyster JG. The transcription factor Hhex cooperates with the corepressor Tle3 to promote memory B cell development. Nat Immunol. 2020;21:1082–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Zhu W, Chen Q, Li Y, Wan J, Li J, Tang S. HIF-1α-overexpressing mesenchymal stem cells attenuate colitis by regulating M1-like macrophages polarization toward M2-like macrophages. Biomedicines. 2023;11:825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Wang Y, Lu K, Xu Y, Xu S, Chu H, Fang X. Antibody-drug conjugates as immuno-oncology agents in colorectal cancer: targets, payloads, and therapeutic synergies. Front Immunol. 2025;16:1678907. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Bsat M, Chapuy L, Rubio M, et al. Differential pathogenic Th17 profile in mesenteric lymph nodes of Crohn’s disease and ulcerative colitis patients. Front Immunol. 2019;10:1177. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Medicine are provided here courtesy of Wolters Kluwer Health

RESOURCES