Erratum to: DNA methylation age of human tissues and cell types

I recently described an epigenetic biomarker of aging based on DNA methylation (DNAm) levels [1]. Unfortunately, I made a software coding error in my analysis of the cancer data, but not of the non-cancer tissue data. The error effectively added an offset term to the age estimates. All of my results from [1] that involve non-cancerous tissue or cancer cell lines remain valid but I have to report some corrections for the cancer tissue data. In particular, I have to retract the statement that cancer is associated with an increased DNA methylation age (i.e. positive age acceleration) in most cancer types. In fact, while some cancer types show positive age acceleration, others exhibit negative age acceleration. I deeply regret this software coding error. The error arose from me using the wrong age calibration function for the cancer tissue data sets, which led to a systematic over-estimation of DNA methylation age (Figure 1). Figure 1 Evaluating the effect of the error on the DNAm age estimate in the cancer samples. The old, incorrect estimate of DNAm age (y-axis) versus the correct estimate (x-axis). Note that the two estimates are highly correlated (r = 0.98), which ... Fortunately, all of the other statements about cancer remain intact since the coding error effectively added an offset term to predicted age that changed little with chronological age (Figure 1). I am comforted by the fact that most of the reported results for cancer become even more significant, including the following. First, the results for cancer tissues are now more congruent with those obtained for cancer cell lines (which remain unchanged). Second, the age predictor leads to a much lower error in cancer tissues (now 16 years). Third, the results for TP53 become more significant, that is TP53 mutations are associated with lower age acceleration in colorectal cancer. As a result of this error, the following Figures and Additional files are incorrect in the published paper, and correct versions are presented here: Figure seven in the original publication; Figure 2 here: Age acceleration versus number of somatic mutations in the TCGA data. Figure 2 Age acceleration versus number of somatic mutations in the TCGA data. Mutation data from TCGA were used to count the number of mutations per cancer sample. A) Age acceleration versus (log transformed) mutation count per sample across all cancers. Note ... Figure eight in the original publication; Figure 3 here: Age acceleration in breast cancer. Figure 3 Age acceleration in breast cancer. Panels in the first column (A,E,I,M) show that estrogen receptor positive breast cancer samples have increased age acceleration in four independent data sets. Panels in the second column (B,F,J) show the same result ... Figure nine in the original publication; Figure 4 here: Age acceleration in colorectal cancer, glioblastoma multiforme and acute myeloid leukemia. Figure 4 Age acceleration in colorectal cancer, GBM and AML. A-F) report results for colorectal cancer. Mean age acceleration (y-axis) in colorectal cancer versus mutation status (denoted by +) in A) BRAF, B) TP53, C) K-RAS. D) Promoter hyper methylation of the ... Additional file twelve in the original publication; Additional file 1 here: Description of cancer data sets. Additional file thirteen in the original publication; Additional file 2 here: DNAm versus chronological age in cancer. Additional file fourteen in the original publication; Additional file 3 here: Age acceleration versus tumor grade and stage. Additional file fifteen in the original publication; Additional file 4 here: Age acceleration versus mutation count status in breast cancer. Additional file sixteen in the original publication; Additional file 5 here: Selected significant gene mutations versus age acceleration. Additional file seventeen in the original publication; Additional file 6 here: Effect of TP53 mutation on age acceleration. Below, for sections of the original paper that are affected by the error, I explain how the corrected results are different from those that were reported.