MethylDetectR: a software for methylation-based health profiling

Childhood exposure to danger increases Black youths' alcohol consumption, accelerated aging, and cardiac risk as young adults: A test of the incubation hypothesis

Using the dual-pathway framework (Beach et al., a), we tested a Neuro-immune Network (NIN) hypothesis: i.e., that chronically elevated inflammatory processes may have delayed (i.e., incubation) effects on young adult substance use, leading to negative health outcomes. In a sample of 449 participants in the Family and Community Health Study who were followed from age 10 to age 29, we examined a non-self-report index of young adult elevated alcohol consumption (EAC). By controlling self-reported substance use at the transition to adulthood, we were able to isolate a significant delayed (incubation) effect from childhood exposure to danger to EAC (β = -.157, p = .006), which contributed to significantly worse aging outomes. Indirect effects from danger to aging outcomes via EAC were: GrimAge (IE = .010, [.002, .024]), Cardiac Risk (IE = -.004, [-.011, -.001]), DunedinPACE (IE = .002, [.000, .008]). In exploratory analyses we examined potential sex differences in effects, showing slightly stronger incubation effects for men and slightly stronger effects of EAC on aging outcomes for women. Results support the NIN hypothesis that incubation of immune pathway effects contributes to elevated alcohol consumption in young adulthood, resulting in accelerated aging and elevated cardiac risk outcomes via health behavior.

Impact of combined exercise on blood DNA methylation and physical health in older women with obesity

This study examined the effects of a 14-week combined exercise program on blood DNA methylation (DNAm) and its potential biological pathways in normal-weight, overweight, and obese older women. A total of 41 participants were assessed at baseline, 7 weeks, and 14 weeks into the training. Their whole-blood DNAm profiles were measured using the Infinitum MethylationEPIC BeadChip, alongside physical and biochemical health evaluations. The results showed notable health improvements, with decreases in blood pressure and cholesterol levels in the overweight and obese groups. Blood triglycerides were reduced only in the overweight group. Physical performance also improved across all groups. At 14 weeks, 1,043 differentially methylated positions (DMPs) were identified, affecting 744 genes. The genes were linked to biological processes, such as cellular metabolism, with significant pathway enrichment related to oxidative phosphorylation and chemical carcinogenesis. Additionally, the overweight group experienced significant reductions in methylation levels at eight lipogenesis-related genes. Protein EpiScore analysis revealed decreased levels of CCL11, VEGFA, and NTRK3 proteins at 14 weeks compared to baseline. Despite these significant molecular changes, there was no observable difference in DNAm age after the intervention. This study highlights how combined exercise can modify DNAm patterns in older women, particularly in lipogenesis-related genes, but suggests that further research is needed to understand the full implications for biological ageing.

Salivary DNA methylation derived estimates of biological aging, cellular frequency and protein expression as predictors of oral mucositis severity and survival in head and neck cancer patients

BACKGROUND

Oral mucositis is a painful and debilitating condition that occurs in the majority of head and neck cancer patients receiving radiation and/or chemotherapy. While some patient and treatment related factors are known to contribute to the incidence and severity of disease, reliable biomarkers remain elusive. In the following study, we investigated the association of salivary DNA methylation derived biological aging, cellular frequency and protein concentration measures with the severity of oral mucositis and overall survival in a cohort of head and neck cancer (HNC) patients (n = 103).

METHODS

DNA methylation profiling was performed on saliva samples obtained prior to treatment. Biological aging measures included Horvath2, PhenoAge, FitAge and GrimAge, and cellular frequency included epithelial and specific immune cell populations.

RESULTS

Severe mucositis (i.e. grade 3 or 4) occurred in nearly half of patients. For malignant HNC patients (n = 84), every 1-SD increase in GrimAge was associated with 2.62-times risk of severe mucositis (95 % CI: 1.38, 5.57), while a 1-SD increase in monocyte frequency was associated with a decreased risk (OR [95 %CI]: 0.40 [0.18, 0.80]). Over a median follow-up of 53 months, 39 of 103 participants died. Six protein scores (TNFSF14, GCSF, MATN3, GDF8, nCDase, TNF-β) were associated with survival at q < 0.15.

CONCLUSION

We provide evidence that the risk-related biological aging measure GrimAge may be a useful predictor of mucositis severity in HNC patients. Salivary monocyte frequency may be protective against mucositis, and this measure could be used as a predictive biomarker while also providing clues into the pathobiology of the disease.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Blood-based multivariate methylation risk score for cognitive impairment and dementia

INTRODUCTION

The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection.

METHODS

In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts.

RESULTS

We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59).

DISCUSSION

Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk.

HIGHLIGHTS

We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

Epigenetic disease markers in primary sclerosing cholangitis and primary biliary cholangitis-methylomics of cholestatic liver disease

BACKGROUND

The epigenome, the set of modifications to DNA and associated molecules that control gene expression, cellular identity, and function, plays a major role in mediating cellular responses to outside factors. Thus, evaluation of the epigenetic state can provide insights into cellular adaptions occurring over the course of disease.

METHODS

We performed epigenome-wide association studies of primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) using the Illumina MethylationEPIC Bead Chip.

RESULTS

We found evidence of increased epigenetic age acceleration and differences in predicted immune cell composition in patients with PSC and PBC. Epigenetic profiles demonstrated differences in predicted protein levels including increased levels of tumor necrosis factor receptor superfamily member 1B in patients with cirrhotic compared to noncirrhotic PSC and PBC. Epigenome-wide association studies of PSC discovered strongly associated 5'-C-phosphate-G-3' sites in genes including vacuole membrane protein 1 and SOCS3, and epigenome-wide association studies of PBC found strong 5'-C-phosphate-G-3' associations in genes including NOD-like receptor family CARD domain containing 5, human leukocyte antigen-E, and PSMB8. Analyses identified disease-associated canonical pathways and upstream regulators involved with immune signaling and activation of macrophages and T-cells. A comparison of PSC and PBC data found relatively little overlap at the 5'-C-phosphate-G-3' and gene levels with slightly more overlap at the level of pathways and upstream regulators.

CONCLUSIONS

This study provides insights into methylation profiles of patients that support current concepts of disease mechanisms and provide novel data to inspire future research. Studies to corroborate our findings and expand into other -omics layers will be invaluable to further our understanding of these rare diseases with the goal to improve and individualize prognosis and treatment.

Unveiling the epigenetic impact of vegan vs. omnivorous diets on aging: insights from the Twins Nutrition Study (TwiNS)

BACKGROUND

Geroscience focuses on interventions to mitigate molecular changes associated with aging. Lifestyle modifications, medications, and social factors influence the aging process, yet the complex molecular mechanisms require an in-depth exploration of the epigenetic landscape. The specific epigenetic clock and predictor effects of a vegan diet, compared to an omnivorous diet, remain underexplored despite potential impacts on aging-related outcomes.

METHODS

This study examined the impact of an entirely plant-based or healthy omnivorous diet over 8 weeks on blood DNA methylation in paired twins. Various measures of epigenetic age acceleration (PC GrimAge, PC PhenoAge, DunedinPACE) were assessed, along with system-specific effects (Inflammation, Heart, Hormone, Liver, and Metabolic). Methylation surrogates of clinical, metabolite, and protein markers were analyzed to observe diet-specific shifts.

RESULTS

Distinct responses were observed, with the vegan cohort exhibiting significant decreases in overall epigenetic age acceleration, aligning with anti-aging effects of plant-based diets. Diet-specific shifts were noted in the analysis of methylation surrogates, demonstrating the influence of diet on complex trait prediction through DNA methylation markers. An epigenome-wide analysis revealed differentially methylated loci specific to each diet, providing insights into the affected pathways.

CONCLUSIONS

This study suggests that a short-term vegan diet is associated with epigenetic age benefits and reduced calorie intake. The use of epigenetic biomarker proxies (EBPs) highlights their potential for assessing dietary impacts and facilitating personalized nutrition strategies for healthy aging. Future research should explore the long-term effects of vegan diets on epigenetic health and overall well-being, considering the importance of proper nutrient supplementation.

TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT05297825.

The Molecular Biology of Midgut Neuroendocrine Neoplasms

Midgut neuroendocrine neoplasms (NENs) are one of the most common subtypes of NEN, and their incidence is rising globally. Despite being the most frequently diagnosed malignancy of the small intestine, little is known about their underlying molecular biology. Their unusually low mutational burden compared to other solid tumors and the unexplained occurrence of multifocal tumors makes the molecular biology of midgut NENs a particularly fascinating field of research. This review provides an overview of recent advances in the understanding of the interplay of the genetic, epigenetic, and transcriptomic landscape in the development of midgut NENs, a topic that is critical to understanding their biology and improving treatment options and outcomes for patients.

An overview of DNA methylation-derived trait score methods and applications

Microarray technology has been used to measure genome-wide DNA methylation in thousands of individuals. These studies typically test the associations between individual DNA methylation sites ("probes") and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.

Epigenetics and ADHD: Reflections on Current Knowledge, Research Priorities and Translational Potential

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating neurodevelopmental disorder influenced by both genetic and environmental factors, typically identified in the school-age years but hypothesized to have developmental origins beginning in utero. To improve current strategies for prediction, prevention and treatment, a central challenge is to delineate how, at a molecular level, genetic and environmental influences jointly shape ADHD risk, phenotypic presentation, and developmental course. Epigenetic processes that regulate gene expression, such as DNA methylation, have emerged as a promising molecular system in the search for both biomarkers and mechanisms to address this challenge. In this Current Opinion, we discuss the relevance of epigenetics (specifically DNA methylation) for ADHD research and clinical practice, starting with the current state of knowledge, what challenges we have yet to overcome, and what the future may hold in terms of methylation-based applications for personalized medicine in ADHD. We conclude that the field of epigenetics and ADHD is promising but is still in its infancy, and the potential for transformative translational applications remains a distant goal. Nevertheless, rapid methodological advances, together with the rise of collaborative science and increased availability of high-quality, longitudinal data make this a thriving research area that in future may contribute to the development of new tools for improved prediction, management, and treatment of ADHD.

Epigenetic and Proteomic Biomarkers of Elevated Alcohol Use Predict Epigenetic Aging and Cell-Type variation Better Than Self-Report

Excessive alcohol consumption (EAC) has a generally accepted effect on morbidity and mortality, outcomes thought to be reflected in measures of epigenetic aging (EA). As the association of self-reported EAC with EA has not been consistent with these expectations, underscoring the need for readily employable non-self-report tools for accurately assessing and monitoring the contribution of EAC to accelerated EA, newly developed alcohol consumption DNA methylation indices, such as the Alcohol T Score (ATS) and Methyl DetectR (MDR), may be helpful. To test that hypothesis, we used these new indices along with the carbohydrate deficient transferrin (CDT), concurrent as well as past self-reports of EAC, and well-established measures of cigarette smoking to examine the relationship of EAC to both accelerated EA and immune cell counts in a cohort of 437 young Black American adults. We found that MDR, CDT, and ATS were intercorrelated, even after controlling for gender and cotinine effects. Correlations between EA and self-reported EAC were low or non-significant, replicating prior research, whereas correlations with non-self-report indices were significant and more substantial. Comparing non-self-report indices showed that the ATS predicted more than four times as much variance in EA, CDT4 cells and B-cells as for both the MDR and CDT, and better predicted indices of accelerated EA. We conclude that each of the non-self-report indices have differing predictive capacities with respect to key alcohol-related health outcomes, and that the ATS may be particularly useful for clinicians seeking to understand and prevent accelerated EA. The results also underscore the likelihood of substantial underestimates of problematic use when self-report is used and a reduction in correlations with EA and variance in cell-types.

Do Loneliness and Per Capita Income Combine to Increase the Pace of Biological Aging for Black Adults across Late Middle Age?

In a sample of 685 late middle-aged Black adults (M age at 2019 = 57.17 years), we examined the effects of loneliness and per capita income on accelerated aging using a newly developed DNA-methylation based index: the DunedinPACE. First, using linear, mixed effects regression in a growth curve framework, we found that change in DunedinPACE was dependent on age, with a linear model best fitting the data (b = 0.004, p < 0.001), indicating that average pace of change increased among older participants. A quadratic effect was also tested, but was non-significant. Beyond the effect of age, both change in loneliness (b = 0.009, p < 0.05) and change in per capita income (b = -0.016, p < 0.001) were significantly associated with change in DunedinPACE across an 11-year period, accounting for significant between person variability observed in the unconditional model. Including non-self-report indices of smoking and alcohol use did not reduce the association of loneliness or per capita income with DunedinPACE. However, change in smoking was strongly associated with change in DunedinPACE such that those reducing their smoking aged less rapidly than those continuing to smoke. In addition, both loneliness and per capita income were associated with DunedinPACE after controlling for variation in cell-types.

A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events

BACKGROUND

Recent evidence highlights the epidemiological value of blood DNA methylation (DNAm) as surrogate biomarker for exposure to risk factors for non-communicable diseases (NCD). DNAm surrogate of exposures predicts diseases and longevity better than self-reported or measured exposures in many cases. Consequently, disease prediction models based on blood DNAm surrogates may outperform current state-of-the-art prediction models. This study aims to develop novel DNAm surrogates for cardiovascular diseases (CVD) risk factors and develop a composite biomarker predictive of CVD risk. We compared the prediction performance of our newly developed risk score with the state-of-the-art DNAm risk scores for cardiovascular diseases, the 'next-generation' epigenetic clock DNAmGrimAge, and the prediction model based on traditional risk factors SCORE2.

RESULTS

Using data from the EPIC Italy cohort, we derived novel DNAm surrogates for BMI, blood pressure, fasting glucose and insulin, cholesterol, triglycerides, and coagulation biomarkers. We validated them in four independent data sets from Europe and the USA. Further, we derived a DNAmCVDscore predictive of the time-to-CVD event as a combination of several DNAm surrogates. ROC curve analyses show that DNAmCVDscore outperforms previously developed DNAm scores for CVD risk and SCORE2 for short-term CVD risk. Interestingly, the performance of DNAmGrimAge and DNAmCVDscore was comparable (slightly lower for DNAmGrimAge, although the differences were not statistically significant).

CONCLUSIONS

We described novel DNAm surrogates for CVD risk factors useful for future molecular epidemiology research, and we described a blood DNAm-based composite biomarker, DNAmCVDscore, predictive of short-term cardiovascular events. Our results highlight the usefulness of DNAm surrogate biomarkers of risk factors in epigenetic epidemiology to identify high-risk populations. In addition, we provide further evidence on the effectiveness of prediction models based on DNAm surrogates and discuss methodological aspects for further improvements. Finally, our results encourage testing this approach for other NCD diseases by training and developing DNAm surrogates for disease-specific risk factors and exposures.