Chemotherapy-induced acceleration of DNA methylation-based biological age in breast cancer.

Breast cancer is the most common cancer diagnosed in women and is often treated with chemotherapy. Although previous studies have demonstrated increasing biological age in patients who receive chemotherapy, evaluation of this association with DNA methylation-based markers of biological ageing may provide novel insight into the role of chemotherapy on the ageing process. We therefore sought to investigate the association between chemotherapy and markers of biological ageing as estimated from DNA methylation in women with breast cancer. DNA methylation profiling was performed on peripheral blood collected from 18 patients before and after the first cycle of chemotherapy using the Infinium HumanMethylation450 BeadChip. Six markers of biological age acceleration were estimated from DNA methylation levels. Multiple linear regression analyses were performed to evaluate the association between each metric of biological age acceleration and chemotherapy. After adjusting for chronological age and race, intrinsic epigenetic age acceleration (p = 0.041), extrinsic epigenetic age acceleration (p = 0.050), PhenoAge acceleration (p = 0.001), GrimAge acceleration (p < 0.001), and DunedinPACE (p = 0.006) were significantly higher and telomere length (p = 0.027) was significantly lower following the first cycle of chemotherapy compared to before treatment initiation. These results demonstrate greater biological ageing as estimated from DNA methylation following chemotherapy in women with breast cancer. Our findings illustrate that cytotoxic therapies may modulate the ageing process among breast cancer patients and may also have implications for age-related health conditions in cancer survivors.

Time to relapse in chronic lymphocytic leukemia and DNA-methylation-based biological age.

Chronic lymphocytic leukemia (CLL) is a mature B cell neoplasm with a predilection for older individuals. While previous studies have identified epigenetic signatures associated with CLL, whether age-related DNA methylation changes modulate CLL relapse remains elusive. In this study, we examined the association between epigenetic age acceleration and time to CLL relapse in a publicly available dataset. DNA methylation profiling of 35 CLL patients prior to initiating chemoimmunotherapy was performed using the Infinium HumanMethylation450 BeadChip. Four epigenetic age acceleration metrics (intrinsic epigenetic age acceleration [IEAA], extrinsic epigenetic age acceleration [EEAA], PhenoAge acceleration [PhenoAA], and GrimAge acceleration [GrimAA]) were estimated from blood DNA methylation levels. Linear, quantile, and logistic regression and receiver operating characteristic curve analyses were conducted to assess the association between each epigenetic age metric and time to CLL relapse. EEAA (p = 0.011) and PhenoAA (p = 0.046) were negatively and GrimAA (p = 0.040) was positively associated with time to CLL relapse. Simultaneous assessment of EEAA and GrimAA in male patients distinguished patients who relapsed early from patients who relapsed later (p = 0.039). No associations were observed with IEAA. These findings suggest epigenetic age acceleration prior to chemoimmunotherapy initiation is associated with time to CLL relapse. Our results provide novel insight into the association between age-related DNA methylation changes and CLL relapse and may serve has biomarkers for treatment relapse, and potentially, treatment selection.

Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning.

Background Existing studies on cardiovascular diseases (CVDs) often focus on individual-level behavioral risk factors, but research examining social determinants is limited. This study applies a novel machine learning approach to identify the key predictors of county-level care costs and prevalence of CVDs (including atrial fibrillation, acute myocardial infarction, congestive heart failure, and ischemic heart disease). Methods and Results We applied the extreme gradient boosting machine learning approach to a total of 3137 counties. Data are from the Interactive Atlas of Heart Disease and Stroke and a variety of national data sets. We found that although demographic composition (eg, percentages of Black people and older adults) and risk factors (eg, smoking and physical inactivity) are among the most important predictors for inpatient care costs and CVD prevalence, contextual factors such as social vulnerability and racial and ethnic segregation are particularly important for the total and outpatient care costs. Poverty and income inequality are the major contributors to the total care costs for counties that are in nonmetro areas or have high segregation or social vulnerability levels. Racial and ethnic segregation is particularly important in shaping the total care costs for counties with low poverty rates or social vulnerability level. Demographic composition, education, and social vulnerability are consistently important across different scenarios. Conclusions The findings highlight the differences in predictors for different types of CVD cost outcomes and the importance of social determinants. Interventions directed toward areas that have been economically and socially marginalized may aid in reducing the impact of CVDs.

Accelerated Epigenetic Age Among Women with Invasive Cervical Cancer and HIV-Infection in Nigeria.

Background: Invasive cervical cancer (ICC) is a serious public health burden in Nigeria, where human immunodeficiency virus (HIV) remains highly prevalent. Previous research suggested that epigenetic age acceleration (EAA) could play a role in detection of HIV-associated ICC. However, little research has been conducted on this topic in Africa where the population is most severely affected by HIV-associated ICC. Here, we investigated the association between ICC and EAA using cervical tissues of ICC-diagnosed Nigerian women living with HIV. Methods: We included 116 cervical tissue samples from three groups of Nigerian women in this study: (1) HIV+/ICC+ (n = 39); (2) HIV+/ICC- (n = 53); and (3) HIV-/ICC + (n = 24). We utilized four DNA methylation-based EAA estimators; IEAA, EEAA, GrimAA, and PhenoAA. We compared EAA measurements across the 3 HIV/ICC groups using multiple linear regression models. We also compared EAA between 26 tumor tissues and their surrounding normal tissues using paired t-tests. We additionally performed a receiver operating characteristics (ROC) curve analysis to illustrate the area under the curve (AUC) of EAA in ICC. Results: We found the most striking associations between HIV/ICC status and PhenoAge acceleration (PhenoAA). Among HIV-positive women, PhenoAA was on average 13.4 years higher in women with ICC compared to cancer-free women (P = 0.005). PhenoAA was 20.7 and 7.1 years higher in tumor tissues compared to surrounding normal tissues among HIV-positive women (P = 0.009) and HIV-negative women (P = 0.284), respectively. We did not find substantial differences in PhenoAA between HIV-positive and HIV-negative women with ICC. Conclusion: PhenoAA is associated with ICC in HIV-infected women in our study. Our findings suggest that PhenoAA may serve as a potential biomarker for further risk stratification of HIV-associated ICC in Nigeria and similar resource-constrained settings.

DNA methylation of individual repetitive elements in hepatitis C virus infection-induced hepatocellular carcinoma.

BACKGROUND: The two most common repetitive elements (REs) in humans, long interspersed nuclear element-1 (LINE-1) and Alu element (Alu), have been linked to various cancers. Hepatitis C virus (HCV) may cause hepatocellular carcinoma (HCC) by suppressing host defenses, through DNA methylation that controls the mobilization of REs. We aimed to investigate the role of RE methylation in HCV-induced HCC (HCV-HCC). RESULTS: We studied methylation of over 30,000 locus-specific REs across the genome in HCC, cirrhotic, and healthy liver tissues obtained by surgical resection. Relative to normal liver tissue, we observed the largest number of differentially methylated REs in HCV-HCC followed by alcohol-induced HCC (EtOH-HCC). After excluding EtOH-HCC-associated RE methylation (FDR < 0.001) and those unable to be validated in The Cancer Genome Atlas (TCGA), we identified 13 hypomethylated REs (11 LINE-1 and 2 Alu) and 2 hypermethylated REs (1 LINE-1 and 1 Alu) in HCV-HCC (FDR < 0.001). A majority of these REs were located in non-coding regions, preferentially enriched with chromatin repressive marks H3K27me3, and positively associated with gene expression (median correlation r = 0.32 across REs). We further constructed an HCV-HCC RE methylation score that distinguished HCV-HCC (lowest score), HCV-cirrhosis, and normal liver (highest score) in a dose-responsive manner (p for trend < 0.001). HCV-cirrhosis had a lower score than EtOH-cirrhosis (p = 0.038) and HCV-HCC had a lower score than EtOH-HCC in TCGA (p = 0.024). CONCLUSIONS: Our findings indicate that HCV infection is associated with loss of DNA methylation in specific REs, which could implicate molecular mechanisms in liver cancer development. If our findings are validated in larger sample sizes, methylation of these REs may be useful as an early detection biomarker for HCV-HCC and/or a target for prevention of HCC in HCV-positive individuals.