Amarnath Singh, PhD

Research Program: Cancer Prevention and Population Sciences Faculty Rank: Postdoctoral Research Fellow Campus: University of Arkansas for Medical Sciences College: College of Public Health Department: College of Public health

Cancer Research Interest

• Disease Site Focus: Breast, Prostate, Thoracic/ Lung
• Research Focus Area: Carcinogenesis, Health Disparities, Diagnosis/ Prognosis, Informatics, Prevention
• Type of Research: Population Sciences, Clinical, Translational
• Research Keywords: Metabolomics, Epigenetics, Multiomics, Transcriptomics, Lipidomics, Public health, Exposome
• Research Interest Statement: Research Statement My research program focuses on how environmental exposures and modifiable behaviors “get under the skin” to shape cancer risk, treatment toxicity, and survivorship outcomes through measurable molecular changes. I integrate epigenomics (DNA methylation and epigenetic clocks), metabolomics/lipidomics, and exposure biomarkers to (1) identify early, minimally invasive markers of risk and prognosis, (2) illuminate biological mechanisms linking exposures to disease phenotypes, and (3) advance strategies to reduce health disparities in medically underserved and high-risk populations. Across my work, a consistent theme is that chemical exposures including tobacco toxicants, volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and metals such as arsenic—are associated with molecular signatures of dysregulated immune signaling, endocrine disruption, mitochondrial/oxidative stress, and accelerated biological aging, all of which are relevant to carcinogenesis and treatment-related complications. Scientific contributions and impact Epigenetic aging and early-onset cancer: minimally invasive methylation biomarkers in underserved population. A major contribution of my work is demonstrating that epigenetic aging is meaningfully linked to aggressive or early-onset cancer phenotypes, using accessible biospecimens and population-based cohorts. In the Arkansas Rural Community Health (ARCH) study, I profiled salivary DNA methylation using the Illumina EPIC array and showed that early-onset breast cancer (diagnosis <50 years) is associated with distinct methylomic signatures and consistently higher epigenetic age acceleration (EAA) across multiple clocks. Differentially methylated positions and regions mapped to genes implicated in immune regulation, transcriptional control, neuroendocrine signaling, and oncogenic pathways, and enrichment analyses highlighted cellular senescence and cancer-related signaling (e.g., FoxO/MAPK and breast cancer pathways). This work advances the field by establishing saliva as a feasible, noninvasive matrix for methylation-based risk stratification, linking early-onset disease to accelerated biological aging as a plausible integrative marker of cumulative exposures and physiological stress, and providing urgently needed molecular data from a rural, medically underserved, agricultural-state cohort where environmental exposures and barriers to care may compound risk. Multi-omics signatures of tobacco exposure connect chemistry exposure to biological aging in cancer patients Another core contribution is my integration of DNA methylation, epigenetic clocks and untargeted metabolomics to connect exposure biomarkers with biological aging phenotypes in clinically relevant populations. In men with prostate cancer (PCa), I demonstrated that current smoking was associated with accelerated epigenetic aging (especially Grim-mAA and DunedinPACE) alongside canonical smoking-associated methylation changes (e.g., AHRR and other established loci). Importantly, I showed that smoking-related xenobiotic metabolites (e.g., aromatic hydrocarbon metabolites and related sulfate conjugates) track with epigenetic age acceleration, supporting a coherent exposure → internal dose → molecular aging pathway. This multi-omics framework strengthens causal plausibility by tying chemical burden to epigenetic consequences in individuals already affected by cancer. Extending this exposure biology into disparities-focused research, I also identified metabolomic signatures of smoking associated with aggressive prostate cancer, emphasizing patterns in African American men and demonstrating race-relevant differences in smoking-related metabolic features and predictors of aggressiveness. Together, these studies provide molecular evidence to support targeted interventions (e.g., cessation programs and risk monitoring) that may reduce smoking-related cancer inequities. Environmental metals and epigenetic regulation: arsenic-associated methylation changes in rural women Recognizing rural environmental exposures as an under-studied driver of health inequities, I examined salivary arsenic and DNA methylation in ARCH participants (breast cancer survivors and cancer-free women). I observed strong associations between arsenic and methylation profiles, including changes in genes relevant to apoptosis and signaling pathways. This work positions arsenic as a plausible endocrine-disrupting exposure with measurable epigenetic consequences and reinforces the utility of saliva-based exposure assessment paired with epigenomics. Biomarkers for chemotherapy safety: metabolomics for early prediction of doxorubicin-induced cardiotoxicity A further translational contribution of my work is in treatment toxicity prediction. Using serial plasma samples from breast cancer patients receiving doxorubicin, I applied untargeted metabolomics and statistical/machine learning approaches to identify metabolic features distinguishing patients who develop doxorubicin-induced cardiotoxicity (DIC) from those who do not—detectable at baseline and after the first cycle. The identification of a reduced metabolite set with strong predictive performance supports a practical direction for early-risk biomarkers that could be integrated into survivorship care and precision oncology workflows to prevent irreversible cardiac injury. Mechanistic insight into lung toxicity from smoking and electronic cigarettes using integrated biomarkers To address urgent public health questions about inhaled toxicants, I contributed to a set of studies leveraging bronchoscopy-derived biospecimens, urinary biomarkers, and molecular assays to characterize pulmonary effects of smoking and vaping. Across these projects, I linked urinary VOC and PAH metabolites with lung immune cell infiltrates, inflammatory cytokines, and airway gene expression, identifying exposure–response relationships consistent with oxidative stress and inflammatory signaling. I also helped characterize lung lipid alterations associated with smoking and ECIG use, showing that smoking is associated with broader and stronger disruption of lipid homeostasis (including changes in saturated lipids and sphingolipid-related classes), while ECIG effects appear smaller in magnitude but not negligible. These integrated findings support the concept that urinary exposure biomarkers can serve as early indicators of biological impact in the lung, enabling translational monitoring approaches for risk assessment. Overall significance Collectively, my studies advance an exposure-to-disease framework in which environmental toxicants and behaviors shape cancer risk and outcomes through molecular aging, immune dysregulation, endocrine signaling changes, and metabolic reprogramming. This work is significant because it produces minimally invasive biomarkers (saliva, urine, and plasma) that can be deployed in large cohorts and underserved settings, leverages multi-omics integration to strengthen inference and biological plausibility, addresses disparities by focusing on rural populations and African American men, and spans both etiology (risk and aggressiveness) and clinical translation (treatment toxicity prediction). Future directions Building on this foundation, my near-term research direction is to develop validated, multi-omics exposure–aging signatures that can predict aggressive cancer phenotypes and adverse treatment outcomes while guiding prevention and survivorship strategies. Key next steps include replicating and validating saliva-based methylation and epigenetic age acceleration markers for early-onset breast cancer and environmental metal exposure in larger rural and diverse cohorts; applying causal modeling and mediation analyses to test whether metabolite burdens and epigenetic aging mediate exposure–cancer relationships; developing integrated risk prediction tools combining exposure biomarkers (VOCs/PAHs/metals), epigenetic clocks, and metabolomics to stratify risk for aggressive disease and cardiotoxicity; and advancing implementation-oriented biomarker development emphasizing feasibility in community and resource-limited settings, aligned with NIH priorities in prevention, health equity, and translational science. My long-term goal is to enable actionable precision prevention and survivorship care by transforming exposure biology into reliable, equitable biomarkers that improve cancer outcomes and reduce disparities.

Contact Information

• Email Address: ASingh@uams.edu