Assessing the causal role of epigenetic clocks in the development of multiple cancers: a Mendelian randomization study
- University of Bristol, United Kingdom
- University of Edinburgh, United Kingdom
- University of California, Los Angeles, United States
- Imperial College London, United Kingdom
- University of Ioannina, Greece
- Fred Hutchinson Cancer Research Center, United States
- University of Melbourne, Australia
- Cancer Prevention Institute of California, United States
Abstract
Background: Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.
Methods: We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (9 single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs) and GrimAge (4 SNPs) on multiple cancers (i.e., breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N=34,710), and for cancer from the UK Biobank (N cases=2,671-13,879; N controls=173,493-372,016), FinnGen (N cases=719-8,401; N controls=74,685-174,006) and several international cancer genetic consortia (N cases=11,348-122,977; N controls=15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.
Results: Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR=1.12 per year increase in GrimAge acceleration, 95%CI 1.04-1.20, p=0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR=1.15, 95%CI 1.09-1.21, p=0.006), than rectal cancer (IVW OR=1.05, 95%CI 0.97-1.13, p=0.24). Results were less consistent for associations between other epigenetic clocks and cancers.
Conclusions: GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.
Funding: FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.
Data availability
Summary statistics for epigenetic age acceleration measures of HannumAge, Intrinsic HorvathAge, PhenoAge and GrimAge were downloaded from: https://datashare.ed.ac.uk/handle/10283/3645. Summary statistics for international cancer genetic consortiums were obtained from their respective data repositories. Colorectal cancer data were obtained following the submission of a written request to the GECCO committee, which may be contacted by email at kafdem@fredhutch.org/upeters@fredhutch.org. Breast, ovarian, prostate and lung cancer data were accessed via MR-Base (http://app.mrbase.org/), which holds complete GWAS summary data from BCAC, OCAC, PRACTICAL and ILCCO. Breast cancer subtype data were obtained from BCAC and can be downloaded from: http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas-summary-associations-breast-cancer-risk-2020/. Data on breast and ovarian cancer in BRCA1 and BRCA2 carriers were obtained from CIMBA and can be downloaded from: http://cimba.ccge.medschl.cam.ac.uk/oncoarray-complete-summary-results/. Prostate cancer subtype data are not publicly available through MR-Base but can be accessed upon request. These data are managed by the PRACTICAL committee, which may be contacted by email at practical@icr.ac.uk. FinnGen data is publicly available and can be accessed here: https://www.finngen.fi/en/access_results. UK Biobank data can be accessed through the MR-Base platform. Parental history of cancer data were obtained from the UK Biobank study under application #15825 and can be accessed via an approved application to the UK Biobank (https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access). GWAS data for negative control outcomes and potential confounders were obtained via the MR-Base platform (GWAS IDs for negative control outcomes: "ukb-b-19560", "ukb-b-533"; GWAS IDs for confounders: "ukb-b-10831", "ukb-b-13702", "ukb-b-6134", "ieu-a-1239", "ukb-b-5779", "ieu-a-835", "ieu-a-61"). GWAS data for measured telomere length used in bidirectional MR analyses were also obtained via the MR-Base platform (GWAS ID: "ieu-b-4879").
-
European-ancestries meta-analysis summary statistics: Hannum (645.4Mb)Edinburgh DataShare doi:10.7488/ds/2834.
-
European-ancestries meta-analysis summary statistics: IEAA (645.7Mb)Edinburgh DataShare doi:10.7488/ds/2834.
-
European-ancestries meta-analysis summary statistics: GrimAge (645.7Mb)Edinburgh DataShare doi:10.7488/ds/2834.
-
European-ancestries meta-analysis summary statistics: PhenoAge (645.7Mb)Edinburgh DataShare doi:10.7488/ds/2834.
-
Breast cancer (Combined Oncoarray; iCOGS; GWAS meta analysis)IEU OpenGWAS, ieu-a-1126.
-
High grade serous ovarian cancerIEU OpenGWAS, ieu-a-1121.
-
Low grade serous ovarian cancerIEU OpenGWAS, ieu-a-1122.
-
Invasive mucinous ovarian cancerIEU OpenGWAS, ieu-a-1123.
-
Endometrioid ovarian cancerIEU OpenGWAS, ieu-a-1125.
-
Malignant neoplasm of breast (all cancers excluded)FinnGen public data r5, finngen_R5_C3_BREAST_EXALLC.gz.
-
Malignant neoplasm of bronchus and lung (all cancers excluded)FinnGen public data r5, finngen_R5_C3_BRONCHUS_LUNG_EXALLC.gz.
-
Colorectal cancer (all cancers excluded)FinnGen public data r5, finngen_R5_C3_COLORECTAL_EXALLC.gz.
-
Malignant neoplasm of ovary (all cancers excluded)FinnGen public data r5, finngen_R5_C3_OVARY_EXALLC.gz.
-
Malignant neoplasm of prostate (all cancers excluded)FinnGen public data r5, finngen_R5_C3_PROSTATE_EXALLC.gz.
-
Time spent doing vigorous physical activityIEU OpenGWAS, ukb-b-13702.
-
Age completed full time educationIEU OpenGWAS, ukb-b-6134.
Article and author information
Author details
Fernanda Morales Berstein
George Davey Smith
Riccardo E Marioni
Funding
Wellcome Trust (224982/Z/22/Z)
- Fernanda Morales Berstein
Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5)
- George Davey Smith
Cancer Research UK (C18281/A29019)
- Caroline L Relton
Cancer Research UK (C18281/A29019)
- George Davey Smith
Alzheimer's Society (AS-PG-19b-010)
- Riccardo E Marioni
National Institutes of Health (U01 AG-18-018,PI: Steve Horvath)
- Riccardo E Marioni
de Pass Vice Chancellor's Research Fellow at the University of Bristol
- Rebecca C Richmond
Cancer Research UK (C18281/A29019)
- Konstantinos K Tsilidis
Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228)
- Konstantinos K Tsilidis
Cancer Research UK (C18281/A29019)
- Philip C Haycock
Cancer Research UK (C18281/A29019)
- Richard M Martin
NIHR Biomedical Research Centre at University Hospitals Bristol
- Richard M Martin
Weston NHS Foundation Trust
- Richard M Martin
NIHR Senior Investigator (NIHR202411)
- Richard M Martin
Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5)
- Caroline L Relton
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: This research did not require ethical approval as it used secondary, genome-wide association data from studies that obtained informed consent from all participants and ethical approval from review boards and/or ethics committees.
Copyright
© 2022, Morales Berstein et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,401
- views
-
- 742
- downloads
-
- 54
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Assessing the causal role of epigenetic clocks in the development of multiple cancers: a Mendelian randomization study
eLife 11:e75374.
https://doi.org/10.7554/eLife.75374
Further reading
-
- Cancer Biology
- Genetics and Genomics
Tyrosine kinases play a crucial role in cell proliferation and survival and are extensively investigated as targets for cancer treatment. However, the efficacy of most tyrosine kinase inhibitors (TKIs) in cancer therapy is limited due to resistance. In this study, we identify a synergistic combination therapy involving TKIs for the treatment of triple negative breast cancer. By employing pairwise tyrosine kinase knockout CRISPR screens, we identify FYN and KDM4 as critical targets whose inhibition enhances the effectiveness of TKIs, such as NVP-ADW742 (IGF-1R inhibitor), gefitinib (EGFR inhibitor), and imatinib (ABL inhibitor) both in vitro and in vivo. Mechanistically, treatment with TKIs upregulates the transcription of KDM4, which in turn demethylates H3K9me3 at FYN enhancer for FYN transcription. This compensatory activation of FYN and KDM4 contributes to the resistance against TKIs. FYN expression is associated with therapy resistance and persistence by demonstrating its upregulation in various experimental models of drug-tolerant persisters and residual disease following targeted therapy, chemotherapy, and radiotherapy. Collectively, our study provides novel targets and mechanistic insights that can guide the development of effective combinatorial targeted therapies, thus maximizing the therapeutic benefits of TKIs.
-
- Genetics and Genomics
- Neuroscience
The central complex (CX) plays a key role in many higher-order functions of the insect brain including navigation and activity regulation. Genetic tools for manipulating individual cell types, and knowledge of what neurotransmitters and neuromodulators they express, will be required to gain mechanistic understanding of how these functions are implemented. We generated and characterized split-GAL4 driver lines that express in individual or small subsets of about half of CX cell types. We surveyed neuropeptide and neuropeptide receptor expression in the central brain using fluorescent in situ hybridization. About half of the neuropeptides we examined were expressed in only a few cells, while the rest were expressed in dozens to hundreds of cells. Neuropeptide receptors were expressed more broadly and at lower levels. Using our GAL4 drivers to mark individual cell types, we found that 51 of the 85 CX cell types we examined expressed at least one neuropeptide and 21 expressed multiple neuropeptides. Surprisingly, all co-expressed a small molecule neurotransmitter. Finally, we used our driver lines to identify CX cell types whose activation affects sleep, and identified other central brain cell types that link the circadian clock to the CX. The well-characterized genetic tools and information on neuropeptide and neurotransmitter expression we provide should enhance studies of the CX.
