Causal Relationship and Potential Common Pathogenic Mechanisms Between Alopecia Areata and Related Cancer

Introduction

Alopecia areata (AA) is an autoimmune skin disorder where patients suffering from AA were characterized by hair loss in focal regions, such as the complete scalp, including eyelashes and eyebrows, or even any hair-bearing surface.^1–3 The clinical presentation of AA can range from small patches of hair loss to widespread involvement of the scalp or the entire body.^1,3 Statistically, AA has affected nearly 2% of the general population, regardless of ethnic groups, genders, and age-based groups.^1,4 While the exact pathogenesis of AA remains unclear, it is believed that the collapse of the immune privilege of the hair follicle caused by immunological mechanism plays a fundamental role in AA progression.² Genetic factors and environment factors (including immunology, oxidative stress, microbiome, and allergy) contribute to the pathogenesis of AA.^2,5,6 Traditional treatment options for AA mainly refer to the usage of corticosteroids (intralesional, topical or systemic), immunosuppressants such as methotrexate are supplementary treatments for recalcitrant and extensive AA.⁷ Besides, Janus kinase (JAK) inhibitors, Tumor necrosis factor-α (TNF-α) inhibitors (such as adalimumab and etanercept) were considered as new treatment strategies for AA.^8–10 It is important to note that while treatments for AA are of limited efficacy or are associated with potential side effects, many patients experience unpredictable cycles of hair loss and regrowth, with some cases being persistent and extensive.^1,2

Studies also reported that AA is associated with various other disorders. For instance, AA greatly impacts the quality of life for patients, lead to the development of psychological disorders such as anxiety and depression.¹¹ Atopic diathesis including asthma, atopic dermatitis, allergic rhinitis and allergic conjunctivitis were more prevalent in patients with AA compared with matched control subjects.¹² A systematic review indicated that patients with AA were more likely to suffer from thyroid diseases, psychiatric diseases, vitamin D deficiency, ophthalmic abnormalities.¹³

Mendelian randomization (MR) utilizes one or more genetic variants as instrumental variables (IVs) based on genome-wide association studies (GWAS). MR studies can infer the causal effects of exposure on an outcome. Recently, MR analysis also reported the causal relationship between AA and other diseases. For instance, MR analysis showed that AA was associated with an increased risk of myocardial infarction (MI).¹⁴ Similarly, AA could causally increase the risk of major depression disorder (MDD) and anxiety.¹⁵ However, to our knowledge, no study has yet investigated the causal effect of AA on the risk of cancer using Mendelian randomization. Our investigation aimed to explore the AA variants as instrumental variables for cancer risk utilizing two-sample MR, screen the gene sets and characteristic crosstalk genes of AA and related cancer.

Materials and Methods

Study Design

According to the MR framework (Figure 1), three key assumptions are included: (1) Relevance Assumption: Single nucleotide polymorphisms (SNPs) that are substantially linked to exposures (AA) are used as Instrumental variables (IVs). (2) Independence Assumption: These SNPs (IVs) should not show any correlation with the relevant confounding factor. (3) Exclusivity Assumption: These SNPs (IVs) should affect outcomes (different subtypes of cancers) only through its effect on exposure.^16–19

Figure 1 Flowchart schematic diagram followed by the MR analysis’ principal of this study.

Data Sources

We utilized summary data associated with AA and 17 subtypes of cancers from MRC Integrative Epidemiology Unit Open GWAS database (https://gwas.mrcieu.ac.uk). Accession numbers finn-b-L12_ALOPECAREATA for AA, 289 cases and 211,139 controls, information of different subtypes of cancers were detailed in Table 1, summary data were accessed from IEU Open GWAS project database (https://gwas.mrcieu.ac.uk). Our study was conducted by secondary analysis of data from other studies, all participants or their family members have provided informed written consent in the original studies.

Table 1 Information of GWAS Summary Data Source Included in the Study

Instrumental Variables (IVs) Selection

Related IVs for MR analysis followed particular principles: SNPs should be associated with exposures at the locus-wide significance level: P-value <5e-06. In addition, linkage disequilibrium (LD) coefficient r² should be less than 0.001, not closely related (clumping window more than 10,000 kb) to ensure exposure instrument independence. We used the F statistic to measure the strength of the IVs, the values of F-statistics were more than 10.^16–19

MR Analysis

Causal associations between AA and cancers were determined utilizing MR analysis. In the exposure-outcome analysis, we employed MR with more than two SNPs serving as IVs. Our MR analysis using each of the five methods: inverse variance-weighted (IVW) was performed as the primary statistical analysis method in our MR analysis for evaluating causal effects, besides, weighted median, and MR-Egger, simple mode, weighted mode were utilized.^16–19

The heterogeneity of the chosen SNPs was evaluated using Cochrane’s Q test, a P-value of more than 0.05 suggested the lack of heterogeneity. The random effects model was used once significant heterogeneity has been identified. We evaluated the possible bias from horizontal pleiotropy using the weighted median and MR-Egger regression in order to gauge the robustness of the IVW method. The MR-PRESSO (MR-Pleiotropy RESidual Sum and Outlier) test was used to appraise outliers that might have been influenced by horizontal pleiotropy. The causal-effect estimates for individual variants were displayed using Scatter plot. Thereafter, we performed a “leave-one-out” analysis to examine the stability of the results in the context of a single SNP’s influence and presented the findings in a forest plot.^16–19

All statistical analysis were conducted in R software (Version 4.3.2) using the TwoSampleMR package (Version 0.5.8). The statistical significance level is P-value <0.05. Pooled ORs (odds ratio) with 95% confidence interval (CI) were calculated.

Acquisition the Related Genes

Disease-related genes were obtained from The GeneCards database (https://www.genecards.org/), using the key word “alopecia areata” and causal related cancers. Intersection of the disease genes were used to obtain the crosstalk genes.

Enrichment Analysis of Crosstalk Genes

The R software packages “org.Hs.eg.db” and “clusterProfiler” were used to enrich the obtained crosstalk genes of AA and related cancers in the Gene Ontology (GO) categories of molecular function (MF), biological process (BP), and cellular component (CC). Thereafter, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the obtained crosstalk genes in AA and related cancers. Adjust P-value <0.05 was used as a filtering condition.

Results

Instrumental Variables

According to the quality control principle as mentioned, 12 SNPs related with AA were adopted as Instrumental variables (IVs). The SNPs included in the exposure data are detailed in Supplementary Table S1.

MR Analysis

We conducted the two-sample MR analysis between AA and 17 subtypes of cancers. The IVW MR analysis demonstrated that AA has a causal relationship with hepatic bile duct cancer (HBDC, OR = 0.944, 95% CI = 0.896–0.994, P-value = 0.030, Table 2) and colorectal cancer (CRC, OR = 0.981, 95% CI = 0.963–0.999, P-value = 0.046, Table 3), respectively. Interestingly, AA play protective roles in both HBDC and CRC. No causal association between AA and other cancers was observed (Figure 2). Using the MR-Egger, the relationship between AA and HBDC, CRC was visualized, respectively (Figure 3a and b).

Table 2 Causal Relationship Between AA and HBDC

Table 3 Causal Relationship Between AA and CRC

Figure 2 Forest plot of Mendelian randomization analysis for Alopecia areata on 17 subtypes of cancers risk. OR, odds ratio; CI, confidence interval; * P-value <0.05.

Figure 3 Scatter plots showing significant causal effects. (a) Alopecia areata on Hepatic bile duct cancer; (b) Alopecia areata on Colorectal cancer.

Sensitivity Analysis

According to the analysis of Cochran’s Q test, our IVW-MR analysis results demonstrated no evidence of heterogeneity among the reported results. Furthermore, the MR-Egger regression analysis results provided evidence that there exists no significant horizontal pleiotropy in our MR analysis, and MR-PRESSO analysis indicated that no outliers were identified (Table 4). The symmetric funnel plot (Figure 4) indicated no evidence of horizontal pleiotropy. We also conducted leave-one-out method to identify and delete abnormal instrumental variables (Figure 5). The results showed the robustness of our results. These results suggest that the MR analysis results were relatively stable.

Table 4 Sensitivity Analysis of Our MR

Figure 4 Funnel plot of our Mendelian randomization study. (a) Alopecia areata on Hepatic bile duct cancer; (b) Alopecia areata on Colorectal cancer.

Figure 5 Results of “Leave-one-out” sensitivity analysis in our Mendelian randomization study. (a) Alopecia areata on Hepatic bile duct cancer; (b) Alopecia areata on Colorectal cancer.

Reversed MR

We also conducted the reversed MR. We identified 11 SNPs from HBDC, 76 SNPs from CRC (detailed in supplementary Tables S2 and S3). No significant results were detected when AA was conducted as the outcome (Tables 5 and 6). These results indicated that HBDC or CRC has no causal impact on AA.

Table 5 Reverse Causality Between HBDC and AA

Table 6 Reverse Causality Between CRC and AA

Crosstalk Genes and Enrichment Analysis

A total of 613 AA disease genes, 4892 hBDC disease genes, 12,806 CRC disease genes were obtained from the GeneCard, respectively. As shown in Figure 6a, considering the intersection of these diseases, 287 intersecting genes were obtained (Table S4 for details).

Figure 6 Disease genes and enrichment analysis. (a) intersecting genes between AA and causal related cancers; (b) biological process (BP); (c) cellular component (CC); (d) molecular function (MF); (e) Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment analysis. AA= Alopecia areata. HBDC= Hepatic bile duct cancer. CRC= Colorectal cancer.

GO enrichment results showed that the set of genes associated with inflammatory response, immune response, positive regulation of interleukin-6, interleukin-8, interleukin-10, interleukin-12 production, positive regulation of T cell proliferation, positive regulation of inflammatory response, the set of genes related to immune inflammation were significantly enriched among the crosstalk genes of AA, HBDC and CRC, as shown in Figure 6b-d. The KEGG enrichment results showed that Cytokine–cytokine receptor interaction, Th17 cell differentiation, Toll-like receptor signaling pathway, Janus kinase (JAK) signal transducer and activator of transcription (JAK-STAT) pathway signaling pathway, Intestinal immune network for IgA production, Tumor necrosis factor (TNF) signaling pathway were significantly enriched among the crosstalk genes of AA and causal related cancers, as shown in Figure 6e, Table S5 for details.

Discussion

We conducted a bidirectional MR analysis to investigate the causal relationship between AA and 17 subtypes of cancers. Our results showed that AA has a causal effect on HBDC and CRC, in contrast, HBDC or CRC has no causal impact on AA. Furthermore, these results provided evidence for a protective effect of AA on HBDC and CRC risk. To the best of our knowledge, this MR analysis is the first to investigate the causal relationship between AA and cancers.

HBDC (intrahepatic Cholangiocarcinoma, iCCA) accounts for 2% of all malignancies.²⁰ Anatomically, HBDC arises from the epithelium of the bile ducts (BD) and can involve any part of the biliary tract.^20,21 HBDC is the second most common cause of primary liver cancer, after hepatocellular carcinoma (HCC).²² Surgical resection is still the possible curative therapy for HBDC, while the anatomical location influences the surgical techniques employed.²² Radiotherapy in selected cases, and systemic chemotherapy also play a significant role in both curative and palliative cohort.^22,23 Generally, the prognosis of HBDC is poor, accordingly, one-year survival for HBDC was 25% and 5-year survival was 5% in Europe.²³

Colorectal cancer (CRC) accounts for about 10% of all diagnosed cancers and cancer-related deaths worldwide each year.^24,25 It is the second most common cancer in women and the third most common in men. Women have a lower incidence and mortality rate compared to men, with rates approximately 25% lower.²⁵ The incidence of CRC worldwide is predicted to increase to 2.5 million new cases in 2035.^25,26 Risk factors such as obesity, lack of physical exercise, and smoking contribute to the increased risk of developing CRC. Treatments for CRC include endoscopic resection (for some early cancers) and surgical local excision, radiotherapy and systemic therapy, such as chemotherapy, targeted therapy, and immunotherapy.^25,27

MR analysis has reported several factors associated with HBDC or CRC. Ulcerative colitis (UC) patients could increase the incidences of HBDC,²⁸ in addition, specific gut microbiota and metabolites have causal relationship with HBDC.²⁹ Living habits were also demonstrated to have causal impact on liver cancer: sleep duration has a negative correlation with HBDC, in contrast, there was a positive correlation found between insomnia and nap during the day with HBDC.³⁰ Likewise, MR analysis also indicated alcohol consumption, higher body mass index (BMI), low 25-hydroxyvitamin D could increase the risk of CRC.^31–33

Observational studies have reported the relationship between AA and cancers.^34,35 Accordingly, AA decreased the risk of nonmelanoma skin cancer and melanoma.³⁴ Additionally, liver cancer, uterine, and cervix cancer were also significantly lower in patients with AA. In contrast, AA patients were more likely to suffer from lymphoma, breast cancer, kidney, and urinary bladder cancer.³⁵ However, our MR study did not find the causal relationship between AA and skin cancer, breast cancer, cervix cancer, lymphoma or urinary bladder cancer. Interestingly, a recent systematic review and meta-analysis conducted by Sophia Ly et al investigated the comorbid conditions associated with AA. The findings indicated that AA may serve as a protective factor against specific types of cancer, as individuals with AA demonstrated reduced odds of developing colorectal cancer (odds ratio [OR] 0.61, 95% confidence interval [CI] 0.42–0.89) and hepatocellular carcinoma (OR 0.37, 95% CI 0.25–0.56) in comparison to healthy control subjects. These outcomes provide additional corroboration for our findings.³⁶

To our known, no studies reported the relationship between AA and HBDC or CRC, our MR analysis uncovered new evidence suggesting the potential link between AA and these two cancers. Immune-related factors may be potential explanations for the protective role of AA in cancer progression. As mentioned, the pathophysiology of AA is not fully understood, while breaking down of the immune privilege of the hair follicles followed by autoimmune attack was believed to be the leading cause of AA.^35,37 On the other hand, upregulation of NKG2D ligands (NKG2DLs) compared with the infiltration of cytotoxic subset of CD8+NKG2D+ T cells in AA patient is the major pathogenesis of AA.^35,38 NKG2D and its ligand are known for their protective role in tumor immune surveillance, combined with the immune defense against tumors effect achieved by NK cells.³⁹ In our Enrichment Analysis, we also find immune-related inflammation was significantly enriched among the crosstalk genes of AA, HBDC and CRC. It should also be noted that, we also find that Th17 cell differentiation, Toll-like receptor signaling pathway, JAK-STAT signaling pathway, Intestinal immune network for IgA production, TNF signaling pathway were significantly enriched among the crosstalk genes, these pathways were related to immunity-inflammation procedure, regulating autoimmunity and cancer.^40–42 Meanwhile, the mechanism of how AA decreased the risk of HBDC and CRC remains uncertain.

There are several limitations to our study. First, due to the original GWAS statistics, we were unable to divide the cohorts or perform subgroup analyses. Second, our analysis only included individuals of the European population. Although using a single European population to investigate causal relationships can minimize population stratification bias, it is important to interpret these findings with caution regarding their applicability to other populations. Further research is required on the mechanism of how AA decreased HBDC and CRC risk.

Conclusion

In conclusion, our MR study has provided the first-ever evidence that AA has a causal impact on HBDC and CRC, AA decreased the risk of both HBDC and CRC. Besides, our results do not support a causal association between AA and other subtypes of cancers. Further studies focusing on AA may provide newer avenues for research in search of treatment targeted therapy in the treatment of HBDC and CRC.