The most important risk factor for chronic disease, cancer, and death is chronological age [1], and it acts as a barometer for the various biological changes that occur over the life course [2]. DNA methylation (DNAm) plays an important role in transcription control and alters consistently with age [3]. Horvath and collaborators define a DNA methylation clock (DNAm clock) as a set of CpGs whose methylation status is used with a regression algorithm to estimate the biological age of a DNA sample obtained from an individual [4]. Current views regarding the significance of epigenetic clock metrics suggest that DNAm clocks capture aging-related epigenetic modifications that are widespread and indicative of genomic, cell biology, and tissue changes that occur throughout life. These molecular changes could lead to a more precise and high-resolution knowledge of age-related disease and physiology, according to a recent review by Bell et al., 2019 [5]. Patients with HIV infection and Down syndrome have been found to have accelerated DNAm aging [3]. In addition, a large body of literature has identified DNAm as one of the key mechanisms underlying the association between aging and cancer [6, 7], showing epigenetic age acceleration might represent an early event in the development of cancerous cells and could be utilized to predict cancer risk and cancer incidence [8].
Several DNAm clocks have been proposed in the literature [4, 5]. These predictors are trained on data from different platforms and tissues, hence some variability between their predictions has been reported [5]. The clock reported by Hannum et al. [9] relied on 71 CpGs from the Illumina 450 K array, using DNA obtained from human peripheral blood samples. Horvath et al. proposed a “pan-tissue” DNAm clock [10] comprised of a subset of 353 CpGs present in the Illumina 27 k array. Recently, DNAm clocks have been proposed that are trained on age-related and disease phenotypes, such as the “PhenoAge” DNA methylation clock [4] or the “Grim Age” clock [11]. While these clocks lead to a stronger prediction on lifespan and healthspan, they are not solely based on methylation signals but require more information such as age-related biochemical measures or smoking related habits [11].
Hereditary nonpolyposis colorectal cancer (HNPCC), also known as Lynch syndrome, represents around 5% of colorectal cancers (CRC) and, it is transmitted in an autosomal dominant manner. Carriers of the different Lynch Syndrome-associated mutations in DNA mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2 [12]) have a significantly higher risk of developing colorectal cancer in first-degree. Moreover, these patients also have a higher risk of developing other tumor types, as endometrial adenocarcinoma, affecting at least to one female relative in 50% of Lynch syndrome pedigrees, stomach, small intestine, liver, biliary tract, brain, and ovary cancers, as well as transition cell carcinoma in ureters and renal pelvis. The average age of CRC detection in carriers of any of these mutations is in the mid 40 s to early 50 s, in contrast to the 60 years average age of onset for other sporadic CRC patients [13].
Colonoscopic and gynecological monitoring is recommended for patients with a germinal mutation in MMR genes [14, 15]. Healthy carriers of Lynch Syndrome-associated mutations are subject to a psychological burden by the knowledge that a cancer lesion is likely to emerge at any time. Physicians monitoring the health of these individuals need reliable metrics of imminent cancer risk to be able to prioritize care for the most severely affected individuals. Here we show data suggesting that DNA methylation metrics in general, and the epigenetic clock in particular, may be of utility in monitoring imminent cancer risk in healthy carriers of Lynch Syndrome-associated mutations.
