Race and Ethnicity, Socioeconomic Factors, and Epigenetic Age Acceleration in Survivors of Childhood Cancer.

Importance: Current research in epigenetic age acceleration (EAA) is limited to non-Hispanic White individuals. It is imperative to improve inclusivity by considering racial and ethnic minorities in EAA research. Objective: To compare non-Hispanic Black with non-Hispanic White survivors of childhood cancer by examining the associations of EAA with cancer treatment exposures, potential racial and ethnic disparity in EAA, and mediating roles of social determinants of health (SDOH). Design, Setting, and Participants: In this cross-sectional study, participants were from the St Jude Lifetime Cohort, which was initiated in 2007 with ongoing follow-up. Eligible participants included non-Hispanic Black and non-Hispanic White survivors of childhood cancer treated at St Jude Children's Research Hospital between 1962 and 2012 who had DNA methylation data. Data analysis was conducted from February 2023 to May 2024. Exposure: Three treatment exposures for childhood cancer (chest radiotherapy, alkylating agents, and epipodophyllotoxin). Main Outcomes and Measures: DNA methylation was generated from peripheral blood mononuclear cell-derived DNA. EAA was calculated as residuals from regressing Levine or Horvath epigenetic age on chronological age. SDOH included educational attainment, annual personal income, and the socioeconomic area deprivation index (ADI). General linear models evaluated cross-sectional associations of EAA with race and ethnicity (non-Hispanic Black and non-Hispanic White) and/or SDOH, adjusting for sex, body mass index, smoking, and cancer treatments. Adjusted least square means (ALSM) of EAA were calculated for group comparisons. Mediation analysis treated SDOH as mediators with average causal mediation effect (ACME) calculated for the association of EAA with race and ethnicity. Results: Among a total of 1706 survivors including 230 non-Hispanic Black survivors (median [IQR] age at diagnosis, 9.5 [4.3-14.3] years; 103 male [44.8%] and 127 female [55.2%]) and 1476 non-Hispanic White survivors (median [IQR] age at diagnosis, 9.3 [3.9-14.6] years; 766 male [51.9%] and 710 female [48.1%]), EAA was significantly greater among non-Hispanic Black survivors (ALSM = 1.41; 95% CI, 0.66 to 2.16) than non-Hispanic White survivors (ALSM = 0.47; 95% CI, 0.12 to 0.81). Among non-Hispanic Black survivors, EAA was significantly increased among those exposed to chest radiotherapy (ALSM = 2.82; 95% CI, 1.37 to 4.26) vs those unexposed (ALSM = 0.46; 95% CI, -0.60 to 1.51), among those exposed to alkylating agents (ALSM = 2.33; 95% CI, 1.21 to 3.45) vs those unexposed (ALSM = 0.95; 95% CI, -0.38 to 2.27), and among those exposed to epipodophyllotoxins (ALSM = 2.83; 95% CI, 1.27 to 4.40) vs those unexposed (ALSM = 0.44; 95% CI, -0.52 to 1.40). The association of EAA with epipodophyllotoxins differed by race and ethnicity (ß for non-Hispanic Black survivors, 2.39 years; 95% CI, 0.74 to 4.04 years; ß for non-Hispanic White survivors, 0.68; 95% CI, 0.05 to 1.31 years) and the difference was significant (1.77 years; 95% CI, 0.01 to 3.53 years; P for interaction = .049). Racial and ethnic disparities in EAA were mediated by educational attainment (

Health-related quality of life and DNA methylation-based aging biomarkers among survivors of childhood cancer.

BACKGROUND: Childhood cancer survivors are at high risk for morbidity and mortality and poor patient-reported outcomes, typically health-related quality of life (HRQOL). However, associations between DNA methylation-based aging biomarkers and HRQOL have not been evaluated. METHODS: DNA methylation was generated with Infinium EPIC BeadChip on blood-derived DNA (median for age at blood draw = 34.5 years, range = 18.5-66.6 years), and HRQOL was assessed with age at survey (mean = 32.3 years, range = 18.4-64.5 years) from 2206 survivors in the St Jude Lifetime Cohort. DNA methylation-based aging biomarkers, including epigenetic age using multiple clocks (eg, GrimAge) and others (eg, DNAmB2M: beta-2-microglobulin; DNAmADM: adrenomedullin), were derived from the DNAm Age Calculator (https://dnamage.genetics.ucla.edu). HRQOL was assessed using the Medical Outcomes Study 36-Item Short-Form Health Survey to capture 8 domains and physical and mental component summaries. General linear models evaluated associations between HRQOL and epigenetic age acceleration (EAA; eg, EAA_GrimAge) or other age-adjusted DNA methylation-based biomarkers (eg, ageadj_DNAmB2M) after adjusting for age at blood draw, sex, cancer treatments, and DNA methylation-based surrogate for smoking pack-years. All P values were 2-sided. RESULTS: Worse HRQOL was associated with greater EAA_GrimAge (physical component summaries: ß = -0.18 years, 95% confidence interval [CI] = -0.251 to -0.11 years; P = 1.85 × 10-5; and 4 individual HRQOL domains), followed by ageadj_DNAmB2M (physical component summaries: ß = -0.08 years, 95% CI = -0.124 to -0.037 years; P = .003; and 3 individual HRQOL domains) and ageadj_DNAmADM (physical component summaries: ß = -0.082 years, 95% CI = -0.125 to -0.039 years; P = .002; and 2 HRQOL domains). EAA_Hannum (Hannum clock) was not associated with any HRQOL. CONCLUSIONS: Overall and domain-specific measures of HRQOL are associated with DNA methylation measures of biological aging. Future longitudinal studies should test biological aging as a potential mechanism underlying the association between poor HRQOL and increased risk of clinically assessed adverse health outcomes.

Cancer germline predisposing variants and late mortality from subsequent malignant neoplasms among long-term childhood cancer survivors: a report from the St Jude Lifetime Cohort and the Childhood Cancer Survivor Study.

BACKGROUND: Carriers of cancer predisposing variants are at an increased risk of developing subsequent malignant neoplasms among those who have survived childhood cancer. We aimed to investigate whether cancer predisposing variants contribute to the risk of subsequent malignant neoplasm-related late mortality (5 years or more after diagnosis). METHODS: In this analysis, data were included from two retrospective cohort studies, St Jude Lifetime Cohort (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), with prospective follow-up of patients who were alive for at least 5 years after diagnosis with childhood cancer (ie, long-term childhood cancer survivors) with corresponding germline whole genome or whole exome sequencing data. Cancer predisposing variants affecting 60 genes associated with well-established autosomal-dominant cancer-predisposition syndromes were characterised. Subsequent malignant neoplasms were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 4.03 with modifications. Cause-specific late mortality was based on linkage with the US National Death Index and systematic cohort follow up. Fine-Gray subdistribution hazard models were used to estimate subsequent malignant neoplasm-related late mortality starting from the first biospecimen collection, treating non-subsequent malignant neoplasm-related deaths as a competing risk, adjusting for genetic ancestry, sex, age at diagnosis, and cancer treatment exposures. SJLIFE (NCT00760656) and CCSS (NCT01120353) are registered with ClinicalTrials.gov. FINDINGS: 12 469 (6172 male and 6297 female) participants were included, 4402 from the SJLIFE cohort (median follow-up time since collection of the first biospecimen 7·4 years [IQR 3·1-9·4]) and 8067 from the CCSS cohort (median follow-up time since collection of the first biospecimen 12·6 years [2·2-16·6]). 641 (5·1%) of 12 469 participants carried cancer predisposing variants (294 [6·7%] in the SJLIFE cohort and 347 [4·3%] in the CCSS cohort), which were significantly associated with an increased severity of subsequent malignant neoplasms (CTCAE grade ≥4 vs grade <4: odds ratio 2·15, 95% CI 1·18-4·19, p=0·0085). 263 (2·1%) subsequent malignant neoplasm-related deaths (44 [1·0%] in the SJLIFE cohort; and 219 [2·7%] in the CCSS cohort) and 426 (3·4%) other-cause deaths (103 [2·3%] in SJLIFE; and 323 [4·0%] in CCSS) occurred. Cumulative subsequent malignant neoplasm-related mortality at 10 years after the first biospecimen collection in carriers of cancer predisposing variants was 3·7% (95% CI 1·2-8·5) in SJLIFE and 6·9% (4·1-10·7) in CCSS versus 1·5% (1·0-2·1) in SJLIFE and 2·1% (1·7-2·5) in CCSS in non-carriers. Carrying a cancer predisposing variant was associated with an increased risk of subsequent malignant neoplasm-related mortality (SJLIFE: subdistribution hazard ratio 3·40 [95% CI 1·37-8·43]; p=0·0082; CCSS: 3·58 [2·27-5·63]; p<0·0001). INTERPRETATION: Identifying participants at increased risk of subsequent malignant neoplasms via genetic counselling and clinical genetic testing for cancer predisposing variants and implementing early personalised cancer surveillance and prevention strategies might reduce the substantial subsequent malignant neoplasm-related mortality burden. FUNDING: American Lebanese Syrian Associated Charities and US National Institutes of Health.

Epigenetic Age in Peripheral Blood Among Children, Adolescent, and Adult Survivors of Childhood Cancer.

Importance: Certain cancer therapies are risk factors for epigenetic age acceleration (EAA) among survivors of childhood cancer, and EAA is associated with chronic health conditions (CHCs). However, small numbers of younger survivors (aged <20 years) previously evaluated have limited the ability to calculate EAA among this age group. Objective: To evaluate the change rate of epigenetic age (EA) and EAA in younger compared with older survivors and the possible association of EAA with early-onset obesity (aged <20 years), severity/burden of CHCs, and late mortality (>5 years from cancer diagnosis). Design, Setting, and Participants: Study participants were from the St Jude Lifetime Cohort, initiated in 2007 with ongoing follow-up. The present study was conducted from April 17, 2022, to March 23, 2023. Survivors in this cohort of European ancestry with DNA methylation data were included. Cross-sectional annual changes in EA and EAA were compared across 5 different chronologic age groups: age 0 to 9 (children), 10 to 19 (adolescents), 20 to 34 (younger adults), 35 to 49 (middle-aged adults), and greater than or equal to 50 (older adults) years. Logistic regression evaluated the association between EAA and early-onset obesity or severity/burden of CHCs. Cox proportional hazards regression assessed the association between EAA and late mortality. Main Outcomes and Measures: Early-onset obesity, severity/burden of CHCs (graded using the Common Terminology Criteria for Adverse Events (grade 1, mild; 2, moderate; 3, severe/disabling; 4, life-threatening) and were combined into high vs low severity/burden based on frequency and grade), and late mortality were the outcomes based on follow-up until April 2020. Expanded DNA methylation profiling increased the number of survivors younger than 20 years (n = 690). Epigenetic age was calculated primarily using the Levine clock, and EAA was derived from least squares regression of EA against chronologic age and was standardized to a z score (Levine EEA). Results: Among 2846 participants (median age, 30.3 [IQR, 9.3-41.5] years; 53% males), the cross-sectional annual change in EA_Levine was higher in children (1.63 years) and adolescents (1.14 years), and the adjusted least-squares mean of Levine EEA was lower in children (-0.22 years) and older adults (-1.70 years). Each 1-SD increase in Levine EEA was associated with increased risk of developing early-onset obesity (odds ratio [OR], 1.46; 95% CI, 1.19-1.78), high severity/burden of CHCs (OR, 1.13; 95% CI, 1.03-1.24), and late mortality (hazard ratio, 1.75; 95% CI, 1.35-2.26). Conclusions and Relevance: The findings of this study suggest that EAA measured in children and adolescent survivors of childhood cancer is associated with early-onset obesity, severity/burden of all CHCs, and late mortality. Evaluating EAA may help identify survivors of childhood cancer at increased risk for early-onset obesity, morbidity in general, and mortality.

Distinct DNA methylation signatures associated with blood lipids as exposures or outcomes among survivors of childhood cancer: a report from the St. Jude lifetime cohort.

BACKGROUND: DNA methylation (DNAm) plays an important role in lipid metabolism, however, no epigenome-wide association study (EWAS) of lipid levels has been conducted among childhood cancer survivors. Here, we performed EWAS analysis with longitudinally collected blood lipid data from survivors in the St. Jude lifetime cohort study. METHODS: Among 2052 childhood cancer survivors of European ancestry (EA) and 370 survivors of African ancestry (AA), four types of blood lipids, including high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides (TG), were measured during follow-up beyond 5-years from childhood cancer diagnosis. For the exposure EWAS (i.e., lipids measured before blood draw for DNAm), the DNAm level was an outcome variable and each of the blood lipid level was an exposure variable; vice versa for the outcome EWAS (i.e., lipids measured after blood draw for DNAm). RESULTS: Among EA survivors, we identified 43 lipid-associated CpGs in the HDL (n = 7), TC (n = 3), and TG (n = 33) exposure EWAS, and 106 lipid-associated CpGs in the HDL (n = 5), LDL (n = 3), TC (n = 4), and TG (n = 94) outcome EWAS. Among AA survivors, we identified 15 lipid-associated CpGs in TG exposure (n = 6), HDL (n = 1), LDL (n = 1), TG (n = 5) and TC (n = 2) outcome EWAS with epigenome-wide significance (P < 9 × 10-8). There were no overlapping lipids-associated CpGs between exposure and outcome EWAS among EA and AA survivors, suggesting that the DNAm changes of different CpGs could be the cause or consequence of blood lipid levels. In the meta-EWAS, 12 additional CpGs reached epigenome-wide significance. Notably, 32 out of 74 lipid-associated CpGs showed substantial heterogeneity (Phet < 0.1 or I2 > 70%) between EA and AA survivors, highlighting differences in DNAm markers of blood lipids between populations with diverse genetic ancestry. Ten lipid-associated CpGs were cis-expression quantitative trait methylation with their DNAm levels associated with the expression of corresponding genes, out of which seven were negatively associated. CONCLUSIONS: We identified distinct signatures of DNAm for blood lipids as exposures or outcomes and between EA and AA survivors, revealing additional genes involved in lipid metabolism and potential novel targets for controlling blood lipids in childhood cancer survivors.

Hepatic retinoic acid receptor alpha mediates all-trans retinoic acid's effect on diet-induced hepatosteatosis.

All-trans retinoic acid (AtRA) is an active metabolite of vitamin A that influences many biological processes in development, differentiation, and metabolism. AtRA functions through activation of retinoid acid receptors (RARs). AtRA is shown to ameliorate hepatic steatosis, but the underlying mechanism is not well understood. In this study, we investigated the role of hepatocyte RAR alpha (RARα) in mediating the effect of AtRA on hepatosteatosis in mice. Hepatocyte-specific Rarα-/- (L-Rarα-/- ) mice and their control mice were fed a chow diet, high-fat diet (HFD), or a high-fat/cholesterol/fructose (HFCF) diet. Some of the mice were also treated with AtRA. Loss of hepatocyte RARα-induced hepatosteatosis in chow-fed aged mice and HFD-fed mice. AtRA prevented and reversed HFCF diet-induced obesity and hepatosteatosis in the control mice but not in L-Rarα-/- mice. Furthermore, AtRA reduced hepatocyte fatty acid uptake and lipid droplet formation, dependent on hepatocyte RARα. Our data suggest that hepatocyte RARα plays an important role in preventing hepatosteatosis and mediates AtRA's effects on diet-induced hepatosteatosis.

Automated Isoform Diversity Detector (AIDD): a pipeline for investigating transcriptome diversity of RNA-seq data.

BACKGROUND: As the number of RNA-seq datasets that become available to explore transcriptome diversity increases, so does the need for easy-to-use comprehensive computational workflows. Many available tools facilitate analyses of one of the two major mechanisms of transcriptome diversity, namely, differential expression of isoforms due to alternative splicing, while the second major mechanism-RNA editing due to post-transcriptional changes of individual nucleotides-remains under-appreciated. Both these mechanisms play an essential role in physiological and diseases processes, including cancer and neurological disorders. However, elucidation of RNA editing events at transcriptome-wide level requires increasingly complex computational tools, in turn resulting in a steep entrance barrier for labs who are interested in high-throughput variant calling applications on a large scale but lack the manpower and/or computational expertise. RESULTS: Here we present an easy-to-use, fully automated, computational pipeline (Automated Isoform Diversity Detector, AIDD) that contains open source tools for various tasks needed to map transcriptome diversity, including RNA editing events. To facilitate reproducibility and avoid system dependencies, the pipeline is contained within a pre-configured VirtualBox environment. The analytical tasks and format conversions are accomplished via a set of automated scripts that enable the user to go from a set of raw data, such as fastq files, to publication-ready results and figures in one step. A publicly available dataset of Zika virus-infected neural progenitor cells is used to illustrate AIDD's capabilities. CONCLUSIONS: AIDD pipeline offers a user-friendly interface for comprehensive and reproducible RNA-seq analyses. Among unique features of AIDD are its ability to infer RNA editing patterns, including ADAR editing, and inclusion of Guttman scale patterns for time series analysis of such editing landscapes. AIDD-based results show importance of diversity of ADAR isoforms, key RNA editing enzymes linked with the innate immune system and viral infections. These findings offer insights into the potential role of ADAR editing dysregulation in the disease mechanisms, including those of congenital Zika syndrome. Because of its automated all-inclusive features, AIDD pipeline enables even a novice user to easily explore common mechanisms of transcriptome diversity, including RNA editing landscapes.

Explaining Pathogenicity of Congenital Zika and Guillain-Barré Syndromes: Does Dysregulation of RNA Editing Play a Role?

Previous studies of Zika virus (ZIKV) pathogenesis have focused primarily on virus-driven pathology and neurotoxicity, as well as host-related changes in cell proliferation, autophagy, immunity, and uterine function. It is now hypothesized that ZIKV pathogenesis arises instead as an (unintended) consequence of host innate immunity, specifically, as the side effect of an otherwise well-functioning machine. The hypothesis presented here suggests a new way of thinking about the role of host immune mechanisms in disease pathogenesis, focusing on dysregulation of post-transcriptional RNA editing as a candidate driver of a broad range of observed neurodevelopmental defects and neurodegenerative clinical symptoms in both infants and adults linked with ZIKV infections. The authors collect and synthesize existing evidence of ZIKV-mediated changes in the expression of adenosine deaminases acting on RNA (ADARs), known links between abnormal RNA editing and pathogenesis, as well as ideas for future research directions, including potential treatment strategies.

Shedding light on lipid metabolism in Kinetoplastida: A phylogenetic analysis of phospholipase D protein homologs.

Unicellular flagellates that make up the class Kinetoplastida include multiple parasites responsible for public health concerns, including Trypanosoma brucei and T. cruzi (agents of African sleeping sickness and Chagas disease, respectively), and various Leishmania species, which cause leishmaniasis. These diseases are generally difficult to eradicate, with treatments often having lethal side effects and/or being effective only during the acute phase of the diseases, when most patients are still asymptomatic. Phospholipid signaling and metabolism are important in the different life stages of Trypanosoma, including playing a role in transitions between stages and in immune system evasion, thus, making the responsible enzymes into potential therapeutic targets. However, relatively little is understood about how the pathways function in these pathogens. Thus, in this study we examined evolutionary history of proteins from one such signaling pathway, namely phospholipase D (PLD) homologs. PLD is an enzyme responsible for synthesizing phosphatidic acid (PA) from membrane phospholipids. PA is not only utilized for phospholipid synthesis, but is also involved in many other signaling pathways, including biotic and abiotic stress response. 37 different representative Kinetoplastida genomes were used for an exhaustive search to identify putative PLD homologs. The genome of Bodo saltans was the only one of surveyed Kinetoplastida genomes that encoded a protein that clustered with plant PLDs. The representatives from other Kinetoplastida species clustered together in two different clades, thought to be homologous to the PLD superfamily, but with shared sequence similarity with cardiolipin synthases (CLS), and phosphatidylserine synthases (PSS). The protein structure predictions showed that most Kinetoplastida sequences resemble CLS and PSS, with the exception of 5 sequences from Bodo saltans that shared significant structural similarities with the PLD sequences, suggesting the loss of PLD-like sequences during the evolution of parasitism in kinetoplastids. On the other hand, diacylglycerol kinase (DGK) homologs were identified for all species examined in this study, indicating that DGK could be the only pathway for the synthesis of PA involved in lipid signaling in these organisms due to genome streamlining during transition to parasitic lifestyle. Our findings offer insights for development of potential therapeutic and/or intervention approaches, particularly those focused on using PA, PLD and/or DGK related pathways, against trypanosomiasis, leishmaniasis, and Chagas disease.