AHRR DNA methylation for clinical risk stratification—how far are we?

Hypomethylation of a specific cytosine-phosphate-guanine (CpG) site (cg05575921) in the aryl hydrocarbon receptor repressor (AHRR) gene of leukocytes has been investigated in several studies for use as a biomarker reflecting smoking exposure to predict occurrence of smoking-related illness. We and others have found that reduced AHRR methylation is predictive of future lung cancer diagnosis, also after adjustment for detailed smoking history by elaborated questionnaires (1,2). Furthermore, AHRR hypomethylation is predictive of other smoking-related diagnoses such as chronic obstructive pulmonary disease (COPD) exacerbation (2), lung function decline (3), peripheral artery disease (PAD) and aortic aneurysm (AA) (4), and impaired fetal growth in smoking mothers (5). In a study by Tsuboi et al. recently published in Cancer Epidemiology Biomarkers & Prevention, the ability of AHRR methylation for predicting cancer mortality was investigated in 795 Japanese individuals receiving an annual health check-up (6). The authors found that compared to never-smokers, current smokers with AHRR methylation below 60% had increased hazard ratio of death from any cause, death due to any cancer, and death due to lung cancer, regardless of cumulative smoking history [>/<20 pack-years (PY)]. For current smokers with an AHRR methylation above 60% no elevated mortality risk was found compared to never-smokers regardless of PY stratum. Also, for former smokers, AHRR methylation seemed to be more associated with risk of death from any cause and lung cancer mortality than time since quitting. Moreover, for former smokers with low AHRR methylation, all-cause mortality and lung cancer mortality resembled those for current smokers regardless of time since quitting.

These findings are in line with previous studies showing that AHRR methylation is superior to smoking history in predicting smoking-related mortality (2,7,8). The study also recapitulates some of the well-known characteristics of AHRR methylation in relation to smoking exposure. One of these is the correlation between hypomethylation of AHRR and cumulative smoking, which is not linear but shows an initial steep decrease in methylation by increasing PY to about 30 PY, after which the decrease in methylation levels off and reaches a plateau (9). Similarly, the study finds a reversion of AHRR methylation primarily in the first 10 years of smoking cessation after which the increase diminishes as also noted previously (2,10). As such, the study confirms the dynamics of AHRR methylation found in other, primarily European and American adult populations, in a Japanese population. As the study finds that AHRR methylation can stratify smokers according to their risk of cancer mortality better than the current practice using cumulative smoking, the authors conclude that AHRR methylation may identify individuals at risk who might be overlooked by questionnaire-based smoking history.

The vast majority of promising biomarkers shown to hold clinical validity never transition into broad clinical use (11). Establishing clinical utility before transition, is expensive and difficult. It requires large prospective studies examining the biomarker in the well-defined clinical context in which it is believed to add value in clinical decision making (12). In the case of AHRR methylation, we find that several key requirements are already fulfilled for broader clinical use, while other important questions must be answered before implementing the measurement into clinical practice, as outlined below.

Analytical validity

In the study by Tsuboi et al., AHRR methylation is measured by pyrosequencing, while other studies use bisulfite-polymerase chain reaction (PCR) or Illumina HumanMethylationEPIC BeadArray. These techniques are suitable to evaluate AHRR methylation on outcomes in large population studies, but do not hold the required precision to be used when addressing the individual patient for clinical decision making. A study compared pyrosequencing to digital droplet PCR (ddPCR) for evaluation of single site methylation changes in a clinical context, found high variation between pyrosequencing runs, whereas ddPCR results were highly reproducible (13). This is in line with experience from our lab in which ddPCR analysis of AHRR methylation shows a very high precision with a coefficient of variation of 0.7% (unpublished results).

Sample collection and transportation is easy as AHRR methylation is measured in leukocyte deoxyribonucleic acid (DNA) and therefore blood samples can be stored and shipped at room temperature once they are drawn into a tube with anticoagulant ethylenediaminetetraacetic acid (EDTA). We believe that all the above-mentioned techniques may be practically applied for AHRR methylation measurement in a clinical context, but the ddPCR based analyses are particularly attractive because of their high precision. We have a workflow from sample to answer which can be done in 4–5 days at about half the costs of a blood-based vitamin B12 deficiency work-up, dependent on the laboratory logistics.

Another common challenge is lack of standardization of biochemical assays used in laboratories and resulting inability to compare results between different hospital labs. Again, the ddPCR-based methods seem attractive: by shipping blood samples to another laboratory, we found a very high degree of agreement between the two labs using similar reagent kits and equipment for DNA isolation, bisulphite conversion and ddPCR (R²=0.999, 0.05% relative bias). Varying the different analytical steps, we found very low relative biases (DNA extraction: 1.8%, bisulfite conversion: 3.1% and droplet detection: 1.2%). These comparisons indicate that AHRR methylation by ddPCR is a very robust analysis with results which can be compared across different laboratories, in particular if similar bisulfite conversion methods are used.

Clinical validity

The most important and difficult aspect of transitioning a biomarker into a clinical setting in which it provides value, is probably choosing and testing the biomarker in the most appropriate clinical situation. In line with the conclusions by Tsuboi et al., we also believe that the objective AHRR methylation adds considerably to lung cancer risk stratification compared to subjective smoking history attained. Within the context of lung cancer risk stratification, we see some possible clinical situations in which AHRR methylation could be tested. First is the use of AHRR methylation in selecting participants for image-based lung cancer screening. Currently eligibility criteria include age, cumulative PY and time since quitting, but the study by Tsuboi et al., along with other previous studies, have shown that individuals with the same cumulative smoking can have very different lung cancer risk as stratified by AHRR methylation (1,2,14), although other disagree (15). We have previously found that adding AHRR methylation to current eligibility criteria may improve specificity by excluding participants with the lowest risk (16). Second, AHRR methylation may be used to evaluate the probability of lung cancer for patients known to be at risk, such as those with chronic obstructive disorder (17) or with long-term cough (18) to reduce the number of computed tomography (CT) scans conducted in these patient categories. Third, AHRR methylation may be included in the risk assessment once a lung nodule is found, either as a result of lung cancer screening or incidentally on a chest CT scan on other indications. Similarly, in other cancers for which smoking is an important causal risk factor, such as bladder cancer, laryngeal cancer, pharyngeal cancer, and esophageal cancer, AHRR methylation may add to the ongoing work to develop risk stratification models (19-21).

In addition to being carcinogenic, smoking also increases the risk of developing cardiovascular disease (CVD). The recent study by Tsuboi et al. did not find a significant association between AHRR hypomethylation and CVD, as has been found in previous studies (22). This may be due to the relatively limited number of participants in the current study compared to previous epidemiological investigations showing a clear correlation (23). We have investigated the association between AHRR methylation and future diagnosis of PAD or AA in 11,332 individuals from the Danish population (4). We found a stepwise increase in the risk of both PAD and AA by progressive hypomethylation after adjusting for self-reported cumulative PY, and years of smoking cessation (4). As such, AHRR methylation might be able to improve currently used CVD risk prediction tools. Since a blood draw to assess lipid status is already a part of these predictive algorithms, a blood test for AHRR methylation would not require additional procedures or visits for patients.

Clinical utility

Regardless of the clinical situation, immediate smoking cessation is always the best intervention for current smokers. This, however, has proven to be difficult and AHRR methylation might be helpful in motivating patients. Once the smoker has quitted, AHRR methylation might be particularly helpful in reinforcement and monitoring of the remaining risk level.

As an objective long-term measure of past smoking behavior, AHRR methylation might be useful in the management of diseases for which smoking contributes with a large part of causality: lung cancer, COPD, PAD, nicotine dependence, smoking dependence in pregnancy, etc. (Figure 1). For each disease, the added predictive information of an AHRR methylation measurement must be determined compared to subjective smoking information alone. The AHRR methylation might be valuable alone or might only be valuable as a part of a comprehensive risk model together with other relevant disease risk information or in combination with other methylation markers predictive of lung cancer. Any risk model should be validated externally before use. Also, it should be defined how the AHRR methylation measurement is thought to influence dedicated patient pathways for the given disease (stratification and/or monitoring of risk, indication for intervention, etc.).

Figure 1 AHRR methylation might be useful in the clinical management of diseases for which smoking contributes with a large fraction of the causality (lung cancer, aortic aneurism, smoking in pregnancy, peripheral artery disease). The measurement might contribute to risk monitoring, motivation for quitting and risk stratification dependent on the disease and clinical pathway. AHRR, aryl hydrocarbon receptor repressor.

Conclusions

The recent study by Tsuboi et al. published in Cancer Epidemiology Biomarkers & Prevention, confirms previous reports showing advantage of using AHRR methylation for predicting smoking-related disease such as lung cancer and all cancer mortality even when taking self-reported smoking history into account. Analysis of AHRR methylation, with a feasible and high-precision technology such as ddPCR, has proven analytical validity and also clinical validity in predicting development of smoking-related disease such as lung cancer. Before assessment of clinical utility can be assessed, appropriate cut-offs or incorporations into risk models should be specified to allow for appropriate external validation.

Perhaps the time has come to move from exploration of AHRR methylation and into prospective studies with prespecified use of the AHRR methylation and tested with sufficient stringency and statistical power.

Answering the question in the title, we are approaching the use of AHRR methylation for lung cancer risk stratification, while the framework and clinical utility in other diseases remain to be established.

Acknowledgments

We thank Rikke Fredslund Andersen, molecular biologist at Department of Clinical Biochemistry, Lillebaelt Hospital, University Hospital of Southern Denmark for conducting the comparisons of ddPCR analysis of AHRR methylation referred to in this editorial.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Cancer Epidemiology. The article has undergone external peer review.

Peer Review File: Available at https://ace.amegroups.com/article/view/10.21037/ace-2026-1-0013/prf

Funding: This work was supported by the Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital and the Independent Research Fund Denmark (grant No. 1030-00055B).

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://ace.amegroups.com/article/view/10.21037/ace-2026-1-0013/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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References

1. Fasanelli F, Baglietto L, Ponzi E, et al. Hypomethylation of smoking-related genes is associated with future lung cancer in four prospective cohorts. Nat Commun 2015;6:10192. [Crossref] [PubMed]
2. Bojesen SE, Timpson N, Relton C, et al. AHRR (cg05575921) hypomethylation marks smoking behaviour, morbidity and mortality. Thorax 2017;72:646-53. [Crossref] [PubMed]
3. Kodal JB, Kobylecki CJ, Vedel-Krogh S, et al. AHRR hypomethylation, lung function, lung function decline and respiratory symptoms. Eur Respir J 2018;51:1701512. [Crossref] [PubMed]
4. Skov-Jeppesen SM, Kobylecki CJ, Jacobsen KK, et al. Aryl hydrocarbon receptor repressor (AHRR) methylation predicts risk of vascular disease: A cohort study of the general population. Int J Surg 2024;110:6953-61. [Crossref] [PubMed]
5. Xu R, Hong X, Zhang B, et al. DNA methylation mediates the effect of maternal smoking on offspring birthweight: a birth cohort study of multi-ethnic US mother-newborn pairs. Clin Epigenetics 2021;13:47. [Crossref] [PubMed]
6. Tsuboi Y, Yamada H, Fujii R, et al. AHRR DNA Methylation Levels in Leukocytes Identify People at Risk for Cancer Mortality Overlooked by Questionnaire-Based Smoking Indices. Cancer Epidemiol Biomarkers Prev. 2025;34:1836-43. [Crossref] [PubMed]
7. Philibert RA, Dogan MV, Mills JA, et al. AHRR Methylation is a Significant Predictor of Mortality Risk in Framingham Heart Study. J Insur Med 2019;48:79-89. [Crossref] [PubMed]
8. Tsuboi Y, Yamada H, Munetsuna E, et al. Increased risk of cancer mortality by smoking-induced aryl hydrocarbon receptor repressor DNA hypomethylation in Japanese population: A long-term cohort study. Cancer Epidemiol 2022;78:102162. [Crossref] [PubMed]
9. Kemp Jacobsen K, Johansen JS, Mellemgaard A, Bojesen SE. AHRR (cg05575921) methylation extent of leukocyte DNA and lung cancer survival. PLoS One 2019;14:e0211745. [Crossref] [PubMed]
10. Skov-Jeppesen SM, Kobylecki CJ, Jacobsen KK, Bojesen SE. Changing Smoking Behavior and Epigenetics: A Longitudinal Study of 4,432 Individuals From the General Population. Chest 2023;163:1565-75. [Crossref] [PubMed]
11. Diamantopoulos MA, Boti MA, Sarri T, Tounias G, Psychogyiou DD, Scorilas A. Regulation of biomarker analysis: what can be translated in the clinic? Expert Rev Mol Diagn 2025;25:647-64. [Crossref] [PubMed]
12. Ioannidis JPA, Bossuyt PMM. Waste, Leaks, and Failures in the Biomarker Pipeline. Clin Chem 2017;63:963-72. [Crossref] [PubMed]
13. Schlaich E, Hubens WHG, Eggermann T. First-time application of droplet digital PCR for methylation testing of the 11p15.5 imprinting regions. Mol Genet Genomic Med 2023;11:e2264. [Crossref] [PubMed]
14. Domingo-Relloso A, Joehanes R, Rodriguez-Hernandez Z, et al. Smoking, blood DNA methylation sites and lung cancer risk. Environ Pollut 2023;334:122153. [Crossref] [PubMed]
15. Grieshober L, Graw S, Barnett MJ, et al. AHRR methylation in heavy smokers: associations with smoking, lung cancer risk, and lung cancer mortality. BMC Cancer 2020;20:905. [Crossref] [PubMed]
16. Jacobsen KK, Schnohr P, Jensen GB, Bojesen SE. AHRR (cg05575921) Methylation Safely Improves Specificity of Lung Cancer Screening Eligibility Criteria: A Cohort Study. Cancer Epidemiol Biomarkers Prev 2022;31:758-65. [Crossref] [PubMed]
17. Bang Henriksen M, Hansen TF, Jensen LH, et al. Lung cancer among outpatients with COPD: a 7-year cohort study. ERJ Open Res 2024;
18. Hatlen P, Langhammer A, Carlsen SM, Salvesen Ø, Amundsen T. Self-reported cardiovascular disease and the risk of lung cancer, the HUNT study. J Thorac Oncol 2014;9:940-6. [Crossref] [PubMed]
19. Lee YA, Al-Temimi M, Ying JRisk Prediction Models for Head and Neck Cancer in the US Population From the INHANCE Consortium, et al. Am J Epidemiol 2020;189:330-42. [Crossref] [PubMed]
20. Jobczyk M, Stawiski K, Fendler W, et al. Validation of EORTC, CUETO, and EAU risk stratification in prediction of recurrence, progression, and death of patients with initially non-muscle-invasive bladder cancer (NMIBC): A cohort analysis. Cancer Med 2020;9:4014-25. [Crossref] [PubMed]
21. Khadhouri S, Gallagher KM, MacKenzie KR, et al. Developing a Diagnostic Multivariable Prediction Model for Urinary Tract Cancer in Patients Referred with Haematuria: Results from the IDENTIFY Collaborative Study. Eur Urol Focus 2022;8:1673-82. [Crossref] [PubMed]
22. Zhu L, Zhu C, Wang J, et al. The association between DNA methylation of 6p21.33 and AHRR in blood and coronary heart disease in Chinese population. BMC Cardiovasc Disord 2022;22:370. [Crossref] [PubMed]
23. Jones GT, Williams MJA, Khashram M, et al. A DNA Methylation Marker, cg05575921 (AHRR), Outperforms Self-Reported Smoking Exposure for Its Association With Cardiovascular Disease Prevalence. Nicotine Tob Res 2026;28:422-28. [Crossref] [PubMed]