About

Carsten C. Skarke is an Adjunct Associate Professor of Medicine (Experimental Therapeutics) at the University of Pennsylvania's Perelman School of Medicine. He holds the Robert L.. McNeil, Jr Fellow in Translational Medicine and serves as the Director of the CTSA Translational Research Internship Program at the Institute for Translational Medicine and Therapeutics (ITMAT). His research expertise centers on translational chronobiology and the human chronobiome, studying oscillatory functional networks in humans under basal and perturbed conditions, and how these networks are modulated by sex, age, and disease. His work involves time-specific deep phenotyping using multiomics, clinical, and remote sensing outputs, with a focus on understanding circadian rhythms and their impact on health outcomes, including postoperative care and digital health technologies. Skarke has contributed to the understanding of the formation of bioactive lipids from fish oils in humans and has challenged existing dogmas regarding inflammation resolution. Additionally, he is dedicated to training the next generation of clinical translational scientists through mentored programs for high school, undergraduate, and medical students, and has pioneered science communication through the ITMAT Artist-in-Residency program to foster public trust and accessible narratives around scientific discovery.

Research topics

• Medicine
• Biology
• Pharmacology
• Internal medicine
• Chemistry

Selected publications

• TracMyAir: Smartphone-enabled spatiotemporal estimates for inhaled doses of particulate matter and ozone to personalize health outcomes

  medRxiv · 2026-02-16

  articleOpen accessSenior authorCorresponding

  Abstract Accurate quantification of individual exposure to air pollutants remains a major challenge in environmental health, as fixed-site monitoring fails to account for mobility, indoor environments, and physiological variability. We deployed TracMyAir, a smartphone-based digital health platform designed to generate time-resolved, personalized exposure and inhaled dose estimates for PM 2.5 and ozone under real-world conditions. In an exploratory study of 18 adults contributing more than 1,500 participant-hours, the platform integrated smartphone geolocation, regulatory (AirNow) and community-based (PurpleAir) air quality data, building infiltration modeling, microenvironment classification, and wearable-derived physical activity metrics to compute eight tiers of hourly exposure estimates, culminating in individualized inhaled dose. Hourly dose estimates derived from smartphone-and smartwatch-based step counts were concordant (Spearman correlation p =0.97–0.98), while heart rate–based estimates yielded greater variability and higher mean values ( p =0.82–0.92). Exposure explained 51–73% of variance in inhaled dose of PM 2.5 and 68–84% of ozone, suggesting that physiological-based modeling approaches improve hyperlocal estimates of personal pollutant burden. Substantial inter-and intra-individual variability reflect dynamic microenvironmental transitions and activity patterns. Modeled doses based on regulatory and community sensor networks were strongly correlated ( R =0.84), with community sensors located closer to participants on average, supporting the feasibility of integrating dense, low-cost monitoring networks. No consistent association was observed between outdoor pollutant levels and neighborhood socioeconomic status in this cohort. These findings demonstrate the feasibility of a scalable, smartphone-centered digital health approach for hyperlocal exposure and inhaled dose modeling. By leveraging ubiquitous consumer devices and existing air quality networks, TracMyAir enables personalized environmental exposure assessment with potential applications in epidemiology, population health, and precision environmental medicine.

  PublisherOA PDFDOI

• Art as a multiplier of science communication

  Journal of Clinical and Translational Science · 2026-01-01

  articleOpen accessSenior author

  Clinical and translational science faces persistent challenges in public trust, effective communication, and siloed knowledge structures. Addressing these issues requires innovative educational and engagement strategies. We present an artist-in-residency program immersed into an undergraduate pathway program to integrate artwork as a tool to enhance science communication, foster public engagement, and build a resilient translational science workforce. Through structured art-science-community interactions, this initiative demonstrates how artistic practice builds a new collaborative communication framework for linking early-career scientists, clinical translational research faculty, and the broader community. The conceptual novelty of our science-art initiative promises to break communication barriers, increase public trust, and develop new, accessible science narratives.

  PublisherOA PDFDOI

• Age and the Diurnal Oscillatory Features of the Human Chronobiome

  medRxiv · 2026-01-23 · 2 citations

  article1st authorCorresponding

  The molecular clock regulates diverse aspects of human biology. As people age, diurnal rhythms deteriorate, most evidently in the daytime napping and nighttime waking of older individuals. To understand how temporal deconsolidation of oscillatory networks could contribute to age-related disease expression, we studied the chronobiome at unprecedented depth in young and old apparently healthy individuals. Transomic integration segregated age groups and identified candidate mechanisms by which oscillatory function might contribute to age dependent distinctions. In an orthogonal approach, we validated as true cyclers many proteins identified in the UK Biobank as predictors of health and disease outcomes. Here, age-specific alterations in the cycling proteome across disease phenotypes is consistent with our hypothesis that deconsolidated circadian programs associate with increased susceptibility to age-related disease.

  PublisherDOI

• Disrupted Diurnal Phase Variation in Circulating Factors as a Predictor of Disease and Mortality

  medRxiv · 2026-01-22 · 1 citations

  article

  Abstract Maintaining normal diurnal rhythms is critical for human health, yet due to limited longitudinal sampling, the oscillatory patterns of most circulating molecular factors and their alteration in pathology remain poorly characterized. Here, we used large-scale cross-sectional UK Biobank plasma data to identify daytime (diurnal phase) oscillations in more than 3,200 biomarkers. Most plasma components exhibited significant oscillatory patterns, including 98% of lipoproteins, 90% of complete blood count measures, and 56% of proteins. We further validated the enrichment of proteomic oscillations in an independent 48-hour serial sampling cohort. Approximately 25% of oscillatory biomarkers displayed sex-specific patterns, particularly hormones, phosphate regulators, immune mediators, and muscle proteins. Remodeling of oscillatory patterns was associated with pathological states, with many alterations detectable years before clinical diagnosis. We derived a composite time-of-day deviation risk score (TOD-RS) strongly associated with all-cause mortality (HR=1.40 per SD, p < 1 × 10 −16 ). These findings highlight the pervasive nature of daytime oscillatory regulation, its disruption in disease, and the potential use of oscillatory biomarkers for risk stratification and early disease detection.

  PublisherDOI

• Critically ill patients with a reverse blood pressure dipping phenotype at increased risk for delirium and death

  Scientific Reports · 2025-11-18 · 2 citations

  articleOpen accessSenior author

  The ICU environment is disruptive to a patient's biological rhythms where sleep-wake cycles are often desynchronized from the environmental day-night changes. This puts patients at increased risk to develop delirium with consequent fiscal pressure for the health care system. An underappreciated dimension is how time-specific patient phenotypes in the critical care environment relate to clinical outcomes. We set out to analyze how rhythmic components (or the lack thereof) in physiological data streams sampled at high resolution in the ICU were associated with the future incidence of delirium and death. To offer cues for further interrogation into mechanism and risk prognosis, we examined differences in 24-hour fluctuations of clinical labs in ICU patient populations at risk. Rhythmic components using dipping ratios and JTK_CYCLE statistics were derived from 24-hour blood pressure and heart rate measurements available from ICU patient admissions recorded in the MIMIC IV database. Logistic adjusted regression models assessed the association between disrupted vital sign rhythms and the future incidence of delirium during the same hospital admission and death. Aggregation of numeric clinical lab measurements across the first 24 h from all patient admissions allowed modeling of rhythmic patterns and subsequent association studies to link potential biochemical mechanisms to perturbed vital sign rhythms and adverse ICU outcomes. Patients with reverse blood pressure dipping were at a 40% higher risk to have a diagnosis of delirium (Odds Ratio: 1.38, 95% CI 1.13-1.71) and a 13% increased risk of death (Odds Ratio: 1.13, 95% CI 1.02-1.26). Compared to the patient population with nocturnal blood pressure dip, reverse dippers showed 24-hour biochemistry profiles suggestive of altered circadian programs specifically in clinical parameters of renal, metabolic, and hemostatic function. Reverse blood pressure dipping can be an early sign for the future development of delirium in the ICU and is accompanied by disrupted biorhythms across multiple organ systems. Dampened and reversed heart rate and blood pressure rhythms are associated with a higher risk for death in ICU patients. Considering the inclusion of these risk factors in preventive care may improve patient outcomes and reduce burden on the health care system.

  PublisherOA PDFDOI

• Quantifying Sleep-Wake Rhythms in the Hospital Environment with Digital Technologies

  npj Digital Medicine · 2025-11-22

  preprintOpen access1st author

  Postoperative clinical care is prone to circadian desynchronization that may influence health outcomes. In an exploratory, feasibility-oriented and signal-exploration effort, we collected 1.8 million data points using 11 remote sensors during preoperative, in-hospital and post-discharge settings in 13 elective cardiac surgery patients (5.2% enrolled from 252 screened). We found that room traffic continued during nighttime with ≥1 visit/h. Sound levels exceeded the recommended 45 dBA threshold (51.9 ± 3.3 vs. 48.3 ± 4.2 dBA during nighttime). Brightness dropped at night (89.9 ± 87.7 to 3.7 ± 9.8 lux), but bright light exposures occurred. Ambient room temperature lacked sleep-inducing diurnal variability. Behavioral-physiological rhythms were disrupted and phase-shifted during hospitalization. Time awake during night hours increased from 10.7 ± 7.9% preoperatively to 34.8 ± 29.1% in-hospital. Cognitive function scores decreased (26.8 ± 2.8 points preoperatively to 24.7 ± 3.9 points in-hospital) with 31% of patients developing transient mild impairment. These data will inform the design of a controlled trial seeking to modify circadian/diurnal disruptors to enhance patient outcomes. Clinicaltrials.gov NCT05828680, November 21, 2022.

  PublisherDOI

• Predictors of Supplemental Opioid Use After Third Molar Extraction

  medRxiv · 2025-07-18

  preprintOpen access

  Objectives: Non-steroidal anti-inflammatory drugs (NSAIDs) are recommended as first-line analgesics following third molar extraction, but some patients require supplemental opioids for pain management. The objective of this study was to identify demographic and clinical factors that predicted supplemental opioid use following third molar extraction in patients treated with an evidence-based analgesic regimen. Methods: Healthy adults underwent surgical extraction of partial or full bony impacted mandibular third molar. When pain intensity was ≥4/10, participants were given ibuprofen 400 mg (N=59) or placebo (N=26) in a randomized, double-blind design. After 4h, all participants transitioned to open-label ibuprofen 400 mg + acetaminophen 500 mg, with oxycodone 5 mg available for breakthrough pain. Analgesic use was documented for the first week after extraction. Predictors of supplemental opioid use in addition to ibuprofen + acetaminophen were evaluated by logistic regression. Results: Ibuprofen + acetaminophen provided adequate analgesia in most of the 85 participants, with 17 participants (20%) using supplemental oxycodone in the first week after extraction. Female sex (OR: 6.770; 95% CI: 1.657-35.57; p=0.013) and higher body mass index (BMI) (OR: 1.253; 95% CI: 1.052-1.525; p=0.016) were associated with increased odds of supplemental opioid use, while higher difficulty index (Pederson score) slightly decreased the odds of supplemental opioid use (OR: 0.852; 95% CI: 0.724-0.993; p=0.043). Adding pre-surgery neutrophil counts improved model fit, with higher neutrophil counts associated with lower odds of supplemental opioid use (OR: 0.435; 95% CI: 0.212-0.775; p=0.011). Conclusions: Female sex, higher BMI, and pre-surgery neutrophil counts were predictors of supplemental opioid use in patients treated with an evidence-based analgesic regimen. Greater surgical difficulty of third molar extraction does not increase the likelihood of supplemental opioid use.

  PublisherOA PDFDOI

• Degree of Cyclooxygenase-2 Inhibition Modulates Blood Pressure Response

  Hypertension · 2025-12-29 · 1 citations

  articleOpen access

  BACKGROUND: Large clinical trials compared distinct nonsteroidal anti-inflammatory drugs in terms of their risk of adverse cardiovascular events. However, whether pharmacologically equipotent doses were used, that is, whether a similar degree of COX (cyclooxygenase)-2 inhibition was achieved, was not considered. We compared drug target inhibition and blood pressure (BP) response to celecoxib and naproxen. METHODS: Sixteen healthy participants were treated with celecoxib (200 mg/d), naproxen (500 mg/d), or placebo for 7 days in a double-blind, crossover design. The degree of COX inhibition was assessed ex vivo using established whole blood assays and in vivo by quantifying urinary metabolites of thromboxane A 2 (COX-1) and prostacyclin (COX-2). Ambulatory BP was measured throughout the final dosing interval. RESULTS: Both nonsteroidal anti-inflammatory drugs inhibited COX-2 activity relative to placebo, but naproxen inhibited COX-2 activity to a greater degree (62.9±21.7%) than celecoxib (35.7±25.2%; P <0.05). Similarly, naproxen treatment inhibited prostacyclin formation in vivo (48.0±24.9%) to a greater degree than celecoxib (26.7±24.6%; P <0.05). Naproxen significantly increased BP compared with celecoxib (mean arterial pressure, +2.5 [95% CI, 1.5–3.5] mm Hg; systolic BP, +4.0 [95% CI, 2.9–5.1] mm Hg; and diastolic BP, +1.8 [95% CI, 0.8–2.8] mm Hg; P <0.05 for all). The difference in systolic BP relative to placebo was associated with the degree of COX-2 inhibition ( P <0.05). CONCLUSIONS: Future studies should consider pharmacokinetic and pharmacodynamic properties, as well as patient-specific factors that may modulate the cardiovascular risk of nonsteroidal anti-inflammatory drug use. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02502006.

  PublisherOA PDFDOI

• Diurnal variation of wearable device-based heart rate variability in the Chronic Renal Insufficiency Cohort study

  npj Digital Medicine · 2025-11-13

  articleOpen access1st author

  Little is known about the prognostic value of continuous, out-of-clinic biometric monitoring of cardiovascular function in chronic kidney disease (CKD). In this study, a mean (±SD) of 50.3 ± 9.3 h of EKG recordings from wearable BioPatch devices was collected from 458 participants across seven Chronic Renal Insufficiency Cohort centers. Multivariable linear regression showed that diabetes was associated with 7.4 ms lower Standard Deviation of NN Intervals (SDNN) compared to non-diabetic participants (p = 0.001). Higher proteinuria (uPCR ≥ 0.2) was associated with 5.73 ms lower SDNN compared to lower proteinuria (p = 0.027). This study represents the largest dataset to date evaluating SDNN, a key heart rate variability metric using wearable EKG technology in CKD. Our findings highlight that specific clinical and demographic factors significantly influence HRV in this population. These results provide a critical foundation for future work to determine whether time-specific HRV metrics can serve as predictive biomarkers for cardiovascular risk and clinical outcomes in CKD.

  PublisherOA PDFDOI

• Sleep disorders as risk factors for calcific aortic stenosis.

  American Journal of Preventive Cardiology · 2025-03-09 · 3 citations

  articleOpen access

  Circadian disruption and sleep disorders have been shown to increase the risk for many cardiovascular diseases. Their association specifically with valvular heart disease, however, is inconclusive. In this study we test the association between sleep disorders and the future incidence of aortic stenosis using two large electronic health record (EHR) databases datasets (the TriNetX network and the All of Us study). We also explore biochemical data for potential mechanistic insights into that association. We fitted Cox proportional hazards models to quantify the risk of future incidence of AS in patients with sleep disorders. We also explored clinical laboratory test datasets for biochemical signals that might explain the association, running mediation analyses. In our fully adjusted Cox models, we find that having any sleep disorder increases the risk for the future incidence of AS (HR: 1.15 95% CI: 1.13-1.18). Changes in lipid profile mediate a proportion of that association. Sleep disorders are associated with an increased risk of AS incidence. That association is independent of classical cardiovascular risk factors even though dyslipidemia plays a large role in mediating this risk.

  PublisherDOI

Frequent coauthors

• Garret A. FitzGerald

  Translational Therapeutics (United States)

  61 shared

• Gregory R. Grant

  Translational Therapeutics (United States)

  60 shared

• Nicholas F. Lahens

  Translational Therapeutics (United States)

  55 shared

• Gerd Geißlinger

  Fraunhofer Institute for Translational Medicine and Pharmacology

  47 shared

• Jörn Lötsch

  Fraunhofer Institute for Translational Medicine and Pharmacology

  39 shared

• Shirley Zhang

  35 shared

• Antonijo Mrčela

  Translational Therapeutics (United States)

  33 shared

• Thomas G. Brooks

  29 shared

Labs

• Institute for Translational Medicine and Therapeutics (ITMAT)PI

Awards & honors

• Robert L. McNeil, Jr Fellow in Translational Medicine, Insti…