About

Rajat Deo, MD, MTR, is a Professor of Medicine in the Department of Cardiovascular Medicine at the Hospital of the University of Pennsylvania. He serves as a cardiologist within the Department of Athletics at Penn Medicine and is the Director of the Penn Arrhythmia Genetics Program. His educational background includes a Bachelor of Science in Biology from the Massachusetts Institute of Technology, an M.D. from the University of Michigan Medical School, and a Masters of Science in Translational Research from the University of Pennsylvania's Perelman School of Medicine. His research and clinical interests focus on cardiovascular electrophysiology, arrhythmia genetics, and translational research related to cardiac arrhythmias.

Research topics

• Medicine
• Internal medicine
• Cardiology
• Endocrinology
• Intensive care medicine
• Virology
• Surgery

Selected publications

• Quantitative Vector Screening to Improve Sensing and Reduce Inappropriate Shocks With the Subcutaneous Implantable Cardioverter Defibrillator

  Circulation Arrhythmia and Electrophysiology · 2026-04-20 · 1 citations

  article

  BACKGROUND: The subcutaneous implantable cardioverter defibrillator (S-ICD) offers protection from sudden cardiac death without transvenous leads. Although contemporary techniques and programming have reduced inappropriate shocks, high rates persist in certain populations. The objective of this study was to evaluate the impact of a novel quantitative vector screening (QVS) protocol on the incidence of sensing-related complications and inappropriate shocks in patients undergoing S-ICD implantation. METHODS: We analyzed 223 consecutive patients who underwent S-ICD implantation at the Hospital of the University of Pennsylvania from December 2018 to July 2025. Traditional vector screening was used before 2023. In 2023, we implemented QVS, which incorporated quantitative sensing scores for each candidate and raised the threshold for S-ICD implantation. The primary end point was time to first inappropriate shock or under-sensed ventricular arrhythmia. Secondary outcomes included SMART Pass deactivation and need for device revision. Outcomes were reported as survival analyses. RESULTS: During preimplant screening, the QVS protocol reduced patient eligibility from 96% to 83%. The median follow-up after implant was 42 months (interquartile range, 48) in the traditional vector screening arm and 18 months (interquartile range, 15) in the QVS arm. The primary end point of time to first inappropriate shock or under-sensed ventricular arrhythmia was longer in the QVS arm (log-rank, P =0.02). There were 23 primary end point events among 145 patients in the traditional vector screening arm (5.2 per 100 patient-years [95% CI, 3.1–7.4]) and 2 primary end point events among 78 patients in the QVS arm (1.8 per 100 patient-years [95% CI, 0.01–4.38]). CONCLUSIONS: Implementation of a novel S-ICD screening protocol with stricter eligibility thresholds reduced sensing-related complications, particularly inappropriate shocks.

  PublisherDOI

• Sex-specific omics scores of sex hormones and associations with metabolic and sleep disorders

  medRxiv · 2026-04-28

  articleOpen access

  Introduction: Sex hormones shape biological sex differences and alter the onset and severity of sleep and metabolic diseases in a sex-specific manner. To better understand relationships and underlying mechanisms, we develop summary proteomics and metabolomics scores for sex hormones and investigate their associations with sleep and metabolic disorders. Methods: We used proteome-(n= 3680) and metabolome-wide (n= 1649) data from the baseline exam of the Multi-Ethnic Study of Atherosclerosis (MESA) cohort to develop female- and male-specific omics scores for sex hormones including total (Total T), bioavailable (Bio T), and free (Free T) testosterone, estradiol (E2) and sex hormone binding protein (SHBG). Each omics dataset was randomly split assigning 80% of participants to a training dataset and the remaining 20% to a test dataset. We applied linear regression with bootstrap standard errors, adjusting for age, BMI, self-reported race/ethnicity and study site, to identify sex hormone-associated proteins and metabolites (i.e FDR< .05). Lasso penalized regression was then used to select independent features, from which weighted protein (ProtS) and metabolite scores (MetS) were constructed as weighted sums, and examined in the validation dataset. Subsequently, we conducted sex-stratified association analysis of the validated omics scores using data from MESA baseline, exams 4 (proteomics) and 5 (proteomics, metabolomics) with sleep and metabolic phenotypes, timepoints where sex hormones were not measured. Results: All constructed omics scores were significantly associated with their corresponding hormones in the test dataset. Higher omics scores of SHBG and lower omics scores of Free T were associated with lower diabetes risk in both sexes; and higher E2 scores with higher incident hypertension risk only in men. In males, Total T had protective diabetes associations, whereas in females they were linked to greater risk. Similarly, higher ProtS-Free T and lower ProtS-SHBG were associated with increased risk for OSA in both sexes. Finally, higher E2 scores were associated with higher risk of insomnia only in males. Conclusions: Summary omics-based scores reveal sex-specific cross-sectional associations with sleep and incident metabolic disorders. These findings highlight the potential of these omics proxies to improve risk stratification and generate insights into mechanisms linking sex hormones with disease.

  PublisherDOI

• Senescence protein signatures predict dementia risk with causal implication for TBCA: a two-cohort study

  Research Square · 2026-03-26

  preprintOpen access
  PublisherOA PDFDOI

• Discovery and Validation of SVEP1 and Other Novel Cardiovascular Biomarkers For Patients with Kidney Failure On Maintenance Hemodialysis

  medRxiv · 2026-04-24

  articleOpen access

  ABSTRACT Background Patients with kidney failure undergoing maintenance hemodialysis suffer high rates of major adverse cardiovascular events(MACE) that are not accurately predicted by traditional cardiovascular risk models. There is an urgent need to identify novel, modifiable cardiovascular risk factors for these patients. Methods We analyzed associations of 6287 circulating proteins with MACE among 1048 participants undergoing hemodialysis in the Chronic Renal Insufficiency Cohort(CRIC) (14-year follow-up) with validation in the Predictors of Arrhythmic and Cardiovascular Risk in End-Stage Renal Disease study(PACE) (7-year follow-up). In both cohorts, proteins were measured shortly after dialysis initiation and one year later. We compared protein-based risk models derived by elastic net regression to the Pooled Cohort Equations(PCE) optimized for these cohorts(Refit PCE), and to an Expanded Refit PCE that included Troponin T and N-terminal pro-B-type natriuretic peptide. Results In CRIC, 149 proteins were associated with MACE at false discovery rate&lt;0.05. Among 22 proteins significant at Bonferroni p&lt;8×10 -6 , proteins that validated in PACE included Sushi von Willebrand factor type A EGF and pentraxin domain-containing protein 1(SVEP1), Complement component C7, R-spondin 4, Tenascin, Fibulin-3 and Fibulin-5. Complement pathways were prominent in network analyses. SVEP1 surpassed other markers by statistical significance, with CRIC HR per log 2 1.8 (p=2.1×10 -12 ) and HR per annual doubling 1.6 (p=6.8×10 -6 ). For 2-year MACE, AUC(95%CI) for SVEP1 alone was 0.72(0.59, 0.84) in CRIC, and 0.73(0.63, 0.81) in PACE. SVEP1 surpassed the Expanded Refit PCE in CRIC (0.61 (0.48, 0.73)) (p=0.038). In the pooled CRIC + PACE cohort, SVEP1 AUC(95%CI) (0.79(0.70, 0.88)) surpassed Refit PCE (0.61(0.51, 0.72)) (p=0.004). Conclusions SVEP1, a 390 kDa protein unlikely to be renally cleared, surpassed over 6000 other proteins and by itself outperformed traditional clinical risk models in predicting MACE in two populations of patients undergoing maintenance hemodialysis. Future studies should provide mechanistic insights behind these findings. Key Points: Patients with kidney failure undergoing hemodialysis have 20-fold higher cardiovascular mortality compared to the general population, and conventional risk factors have low prognostic utility for these patients. By applying large-scale circulating proteomics in two independent hemodialysis cohorts, we have discovered &gt;20 novel proteins that predict major adverse cardiovascular events(MACE). Sushi von Willebrand factor type A EGF and pentraxin domain-containing protein 1(SVEP1) surpassed &gt;6000 individual proteins and clinical factors for predicting MACE.

  PublisherOA PDFDOI

• Proteomic-based Aging Clocks and MRI Markers of Cerebral Small Vessel Disease: ARIC and MESA

  medRxiv · 2026-04-04

  articleOpen access

  Background: This study investigates whether proteomic aging clocks (PACs) are associated with cerebral small vessel disease (CSVD). Methods: We included participants from two US community-based cohorts: the Atherosclerosis Risk in Communities (ARIC) Study and the Multi-Ethnic Study of Atherosclerosis (MESA) Study. These analyses leveraged PACs that were developed in ARIC using proteomics measured by SomaScan in midlife (Visit 2; mean age 56 y; n=1,486) and late-life (Visit 5; mean age 76 y; n=1,496), trained on chronological age. Proteomic age acceleration (PAA) was calculated as residuals from regressing PACs on chronological age. 3T brain MRI data were collected in late-life. We examined associations of PAA with log-transformed white matter hyperintensity (WMH) volume using linear regression and with the presence of microbleeds, and subcortical, lacunar, and cortical infarcts using logistic regression. Associations of PACs with WMH volume and microbleeds were tested in MESA using proteins measured at Exam 1 (mean age 57 y; n=932) and Exam 5 (mean age 66 y; n=934). All associations were quantified per 5-year increase in PAA. All models were adjusted for demographics and cardiovascular risk factors. Results: In ARIC, higher midlife PAA was associated with greater WMH volume (percent difference: 25% [95% CI: 13%, 39%]) and higher odds of subcortical infarcts (OR: 1.24 [1.02, 1.51]). Late-life PAA was associated with all CSVD markers: WMH volume (percent difference: 20% [8%, 34%]), cerebral microbleeds (OR: 1.40 [1.15, 1.69]), subcortical (OR: 1.80 [1.47, 2.22]), lacunar (OR: 1.80 [1.46, 2.23]), and cortical infarcts (OR: 1.39 [1.07, 1.82]). In MESA, higher late-life PAA was associated with greater WMH volume (28% [3%, 58%]) but not with microbleeds. Conclusion: Accelerated proteomic aging is associated with a higher prevalence of MRI markers of CSVD, most predominantly in late-life. Understanding this relationship may help stratify those at higher risk of CSVD at an early stage.

  PublisherOA PDFDOI

• Medication Costs for Dofetilide: Comparison of Insurance Copayments Versus Generic Pricing Through Cost Plus Drug Company

  Circulation · 2026-03-16

  article
  PublisherDOI

• T-FIX: Text-Based Explanations with Features Interpretable to eXperts

  ArXiv.org · 2025-11-06

  preprintOpen access

  As LLMs are deployed in knowledge-intensive settings (e.g., surgery, astronomy, therapy), users are often domain experts who expect not just answers, but explanations that mirror professional reasoning. Yet evaluating whether an LLM "thinks like an expert" remains difficult: existing approaches rely on per-example expert annotation, making them costly, hard to scale, and tied to a single notion of correct reasoning within each domain. To address this gap, we introduce T-FIX, a unified evaluation framework that operationalizes expert alignment as a desired attribute of LLM-generated explanations. T-FIX spans seven scientific tasks across three domains, with each task evaluated against expert-defined criteria that capture domain-grounded reasoning rather than generic explanation quality. Our framework enables automatic, personalizable evaluation of expert alignment that generalizes to unseen explanations without ongoing expert involvement. Code is available at https://github.com/BrachioLab/FIX-2/.

  PublisherOA PDFDOI

• Proteomic discovery analysis of quantitatively assessed emphysema in the general population. The MESA Lung Study

  Respiratory Research · 2025-07-04 · 1 citations

  articleOpen access

  Abstract Background Pulmonary emphysema occurs frequently in older adults, often without airflow limitation. Its presence predicts symptoms, respiratory hospitalizations and deaths, and all-cause mortality. Proteomics may provide further insights into emphysema pathogenesis and inform therapeutic targets. Objective We performed a proteomic discovery analysis of percent emphysema on computed tomography (CT) in a population-based, multiethnic sample from the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study. Replication was performed in two chronic obstructive pulmonary disease (COPD)-based studies, the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) and the Genetic Epidemiology of COPD (COPDGene) Study. Methods MESA recruited participants from the general population in 2000–02. The MESA Lung Study performed full-lung CT scans in 2010–12. Percent emphysema was defined as the percentage of lung voxels &lt; -950 Hounsfield units. Over 7,200 plasma aptamers were measured via SomaScan. Cross-sectional linear and least absolute shrinkage and selection operator (LASSO) regression models were adjusted for demographics, anthropometrics, smoking, renal function, and scanner parameters. Statistical significance was defined as a false discovery rate p-value &lt; 0.05. Gene Ontology (GO)/Reactome enrichment analyses were performed. LASSO-selected proteins’ predictive performance was evaluated. Results Among 2,504 participants in the MESA Lung Study, mean age was 69.4 years, 1,291 had ever smoked, and median percent emphysema-like lung was 1.4%. In total, 1,234 aptamers were significantly associated with percent emphysema in the MESA Lung Study, and 35 replicated in the SPIROMICS and COPDGene Studies. Novel associations included protein family with sequence similarity (FAM) 177A1, syntenin-2, ubiquitin carboxyl-terminal hydrolase 25, and uncharacterized protein C20orf173. Previously identified emphysema-associated proteins included soluble advanced glycosylation end product-specific receptor (sRAGE), protein S100-A12, high mobility group protein B1, and roundabout homolog 2. Enrichment analyses identified 40 GO biological processes, including chemokine production and regulation and cell–cell adhesion and regulation, and two Reactome pathways, including RAGE signaling. In tenfold cross-validation, novel proteins were largely retained by LASSO (R 2 = 5.4%), improved overall model performance (R 2 = 24.8%), and uniquely explained greater variance in percent emphysema. Conclusions This analysis in a general population sample identified novel and previously characterized proteins whose functional roles were validated by GO/Reactome enriched pathways, offering new insights into emphysema pathophysiology and therapeutics.

  PublisherOA PDFDOI

• Abstract 4360980: Evaluating Gaps in Cardiac Rhythm Monitoring Completion in a Post-Stroke Population

  Circulation · 2025-11-03

  articleSenior author

  Background: Cardiac rhythm monitoring is a mainstay of secondary stroke prevention. Despite this, prior studies have highlighted gaps in real-world monitoring after stroke. Objective: To assess whether failure to complete cardiac monitoring is associated with worse clinical outcomes in patients (pts) who have had an acute ischemic stroke or TIA. Methods: We evaluated 891 stroke pts who were prescribed ambulatory cardiac rhythm monitoring between 2019-2023. Electronic health records identified those who completed (≥ 3 days) and did not complete (&lt; 3 days) wear. We also obtained census tract-level CDC/ATSDR Social Vulnerability Index (SVI) data for each patient. Residential addresses were geocoded in ArcGIS Pro (ESRI) and linked to overall SVI scores, which represent national percentile rankings (range 0-1). Higher values indicate greater social vulnerability. Cox proportional hazards models evaluated the associations between monitor completion and the risk for recurrent strokes, cardiovascular events, and deaths. Results: Of 891 post-stroke pts, 229 (26%) did not complete cardiac monitoring. Compared to the monitored group, pts who did not complete monitoring were more likely to be Black and have hypertension, diabetes, and Medicaid or no insurance. Median SVI rank was significantly higher in non-monitored pts (0.83 vs. 0.58, p &lt;0.001), indicating higher social vulnerability. After a median follow-up of 970 days [IQR 413, 1265], there were 325 events. The non-monitored group had a higher unadjusted risk of clinical events than the monitored group (Figure 1). After multivariable adjustment for age, sex, hypertension, diabetes, hyperlipidemia, smoking, prior stroke, heart failure, and coronary heart disease, non-monitored pts had a higher risk of recurrent stroke (HR 1.52, 95% CI [1.02, 2.25]), cardiovascular events (HR 1.50, 95% CI [1.00, 2.25]), and all-cause mortality (HR 2.79, 95% CI [1.81, 4.31]). In stratified analysis, failure to complete monitoring was independently associated with an increased risk of the combined endpoint in both the most socially vulnerable (SVI Quartile 4) (adjusted HR 1.54, 95% CI [1.08, 2.19]) and less vulnerable (SVI Quartiles 1-3) (HR 2.14, 95% CI [1.39, 3.27]) pts. Conclusions: Failure to complete cardiac monitoring is associated with worse post-stroke outcomes. While more socially vulnerable pts are less likely to complete monitoring, monitoring is associated with better outcomes across highly and less vulnerable populations.

  PublisherDOI

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

  npj Digital Medicine · 2025-11-13

  articleOpen access

  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

Recent grants

• NIH Grant K23DK089118

  NIH · $617k · 2015

• Identifying Modifiable Biomarkers/Mediators for Cardiovascular Disease in Chronic Kidney Disease

  NIH · $1.9M · 2016–2024

Frequent coauthors

• Michael G. Shlipak

  University of California, San Francisco

  485 shared

• Ronit Katz

  University of Washington

  245 shared

• David S. Siscovick

  Tufts University

  240 shared

• Bryan Kestenbaum

  University of Washington

  237 shared

• Michel Chonchol

  University of Colorado Anschutz Medical Campus

  223 shared

• Nona Sotoodehnia

  University of Washington

  208 shared

• Bruce M. Psaty

  205 shared

• Emelia J. Benjamin

  Boston Medical Center

  196 shared

Education

• Masters of Science in Translational Research

  University of Pennsylvania

  2011

• MD, Medicine

  University of Michigan

  2001

• SB

  Massachusetts Institute of Technology

  1996