Publications

Publications

​1. Fu, Y., Land, M., Kavlashvili, T., Cui, R., Kim, M., DeBitetto, E., Lieber, T., Ryu, K. W., Choi, E., Masilionis, I., Saha, R., Takizawa, M., Baker, D., Tigano, M., Lareau, C. A., Reznik, E., Sharma, R., Chaligne, R., Thompson, C. B., … Sfeir, A. (2025). Engineering mtDNA deletions by reconstituting end joining in human mitochondria. Cell, 188(10), 2778-2793.e21. https://doi.org/10.1016/j.cell.2025.02.009

2. Fung, T. S., Ryu, K. W., & Thompson, C. B. (2025). Arginine: At the crossroads of nitrogen metabolism. The EMBO Journal, 44(5), 1275–1293. https://doi.org/10.1038/s44318-025-00379-3

3. Ryu, K. W., Fung, T. S., Baker, D. C., Saoi, M., Park, J., Febres-Aldana, C. A., Aly, R. G., Cui, R., Sharma, A., Fu, Y., Jones, O. L., Cai, X., Pasolli, H. A., Cross, J. R., Rudin, C. M., & Thompson, C. B. (2024). Cellular ATP demand creates metabolically distinct subpopulations of mitochondria. Nature, 635(8039), 746–754. https://doi.org/10.1038/s41586-024-08146-w

4. Cai, X., Ng, C. P., Jones, O., Fung, T. S., Ryu, K. W., Li, D., & Thompson, C. B. (2023). Lactate activates the mitochondrial electron transport chain independently of its metabolism. Molecular Cell, 83(21), 3904-3920.e7. https://doi.org/10.1016/j.molcel.2023.09.034

5. Challa, S.*, Ryu, K. W.*, Whitaker, A. L., Abshier, J. C., Camacho, C. V., & Kraus, W. L. (2022). Development and characterization of new tools for detecting poly(ADP-ribose) in vitro and in vivo. eLife, 11, e72464. https://doi.org/10.7554/eLife.72464

6. Challa, S., Khulpateea, B. R., Nandu, T., Camacho, C. V., Ryu, K. W., Chen, H., Peng, Y., Lea, J. S., & Kraus, W. L. (2021). Ribosome ADP-ribosylation inhibits translation and maintains proteostasis in cancers. Cell, 184(17), 4531-4546.e26. https://doi.org/10.1016/j.cell.2021.07.005

7. Zhu, J., Schwörer, S., Berisa, M., Kyung, Y. J., Ryu, K. W., Yi, J., Jiang, X., Cross, J. R., & Thompson, C. B. (2021). Mitochondrial NADP(H) generation is essential for proline biosynthesis. Science, 372(6545), 968–972. https://doi.org/10.1126/science.abd5491

8. Huang, D., Camacho, C. V., Setlem, R., Ryu, K. W., Parameswaran, B., Gupta, R. K., & Kraus, W. L. (2020). Functional Interplay between Histone H2B ADP-Ribosylation and Phosphorylation Controls Adipogenesis. Molecular Cell, 79(6), 934-949.e14. https://doi.org/10.1016/j.molcel.2020.08.002

9. Ryu, K. W., Nandu, T., Kim, J., Challa, S., DeBerardinis, R. J., & Kraus, W. L. (2018). Metabolic regulation of transcription through compartmentalized NAD+ biosynthesis. Science, 360(6389), eaan5780. https://doi.org/10.1126/science.aan5780

10. Luo, X.*, Ryu, K. W.*, Kim, D.-S., Nandu, T., Medina, C. J., Gupte, R., Gibson, B. A., Soccio, R. E., Yu, Y., Gupta, R. K., & Kraus, W. L. (2017). PARP-1 Controls the Adipogenic Transcriptional Program by PARylating C/EBPβ and Modulating Its Transcriptional Activity. Molecular Cell, 65(2), 260–271. https://doi.org/10.1016/j.molcel.2016.11.015

11. Ryu, K. W., & Kraus, W. L. (2016). Who Put the “A” in ATP? Generation of ATP from ADP-Ribose in the Nucleus for Hormone-Dependent Gene Regulation. Molecular Cell, 63(3), 349–351. https://doi.org/10.1016/j.molcel.2016.07.018​

12. Kil, I. S., Ryu, K. W., Lee, S. K., Kim, J. Y., Chu, S. Y., Kim, J. H., Park, S., & Rhee, S. G. (2015). Circadian Oscillation of Sulfiredoxin in the Mitochondria. Molecular Cell, 59(4), 651–663. https://doi.org/10.1016/j.molcel.2015.06.031

13. Ryu, K. W., Kim, D.-S., & Kraus, W. L. (2015). New Facets in the Regulation of Gene Expression by ADP-Ribosylation and Poly(ADP-ribose) Polymerases. Chemical Reviews, 115(6), 2453–2481. https://doi.org/10.1021/cr5004248

14. Kil, I. S., Lee, S. K., Ryu, K. W., Woo, H. A., Hu, M.-C., Bae, S. H., & Rhee, S. G. (2012). Feedback Control of Adrenal Steroidogenesis via H2O2-Dependent, Reversible Inactivation of Peroxiredoxin III in Mitochondria. Molecular Cell, 46(5), 584–594. https://doi.org/10.1016/j.molcel.2012.05.030

15. Zhang, T., Berrocal, J. G., Yao, J., DuMond, M. E., Krishnakumar, R., Ruhl, D. D., Ryu, K. W., Gamble, M. J., & Kraus, W. L. (2012). Regulation of Poly(ADP-ribose) Polymerase-1-dependent Gene Expression through Promoter-directed Recruitment of a Nuclear NAD+ Synthase. Journal of Biological Chemistry, 287(15), 12405–12416. https://doi.org/10.1074/jbc.M111.304469

Published papers, studies and books from the Ryu Lab team.

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Publications

Publications

Adipokines, Immunity, and Infection. Joshi S, Patel A, Raja R, Rajagopalan KN. Endocrinology. 2026 Feb 3:bqag013. doi: 10.1210/endocr/bqag013. Epub ahead of print. PMID: 41631715.

FGF21 acting on the noradrenergic nervous system protects against influenza virus infection. Fan W, Zhang Y, Gautron L, Thomas DG, Stout-Delgado HW, Schenck EJ, Gwatiringa T, Rajagopalan KN*, Mangelsdorf DJ, Kliewer SA*. Proc Natl Acad Sci U S A. 2025 Sep 30;122(39):e2522045122. Epub 2025 Sep 25.

Leptin and melanocortin signalling in the response to infection. Nat Rev Endocrinol.
Fan RR, Beckham JD, Rajagopalan K.N. Nat Rev Endocrinol. 2026 Feb;22(2):92-101. doi: 10.1038/s41574-025-01184-y. Epub 2025 Sep 22.

Triglycerides are an important fuel reserve for synapse function in the brain.
Kumar M, Wu Y, Knapp J, Pontius CL, Park D, Witte RE, McAllister R, Gupta K, Rajagopalan KN, De Camilli P, Ryan TA. Nat Metab. 2025 Jul;7(7):1392-1403. Epub 2025 Jul 1.

Leptin signaling maintains autonomic stability during severe influenza infection in mice.
Muñoz-Rojas AR, Wang AC, Pomeranz LE, Reizis EL, Stout-Delgado HW, Miranda IC, Rajagopalan K, Gwatiringa T, Fan RR, Huda AA, Maskey N, Olumuyide RP, Patel AS, Friedman JM, Mathis D, Rajagopalan KN. J Clin Invest. 2024 Oct 31;135(1):e182550.

A randomized double-blind controlled trial of convalescent plasma in adults with severe COVID-19
O'Donnell MR, Grinsztejn B, Cummings MJ, Justman JE, Lamb MR, Eckhardt CM, Philip NM, Cheung YK, Gupta V, João E, Pilotto JH, Diniz MP, Cardoso SW, Abrams D, Rajagopalan KN, Borden SE, Wolf A, Sidi LC, Vizzoni A, Veloso VG, Bitan ZC, Scotto DE, Meyer BJ, Jacobson SD, Kantor A, Mishra N, Chauhan LV, Stone EF, Dei Zotti F, La Carpia F, Hudson KE, Ferrara SA, Schwartz J, Stotler BA, Lin WW, Wontakal SN, Shaz B, Briese T, Hod EA, Spitalnik SL, Eisenberger A, Lipkin WI. J Clin Invest. 2021 Jul 1;131(13):e150646.

Depletion of H3K36me2 recapitulates epigenomic and phenotypic changes induced by the H3.3K36M oncohistone mutation.
*Rajagopalan, KN, *Chen, X, *Weinberg, DN, Allis, CD, Lu, C.. Proc Natl Acad Sci U S A. 2021 Mar 2;118(9):e2021795118. (*denotes equal contribution)

Body mass index and risk of intubation or death in SARS-CoV-2 infection: a retrospective cohort study.
Anderson MR, Geleris J, Anderson DR, Zucker J, Nobel YR, Freedberg D, Small-Saunders J, Rajagopalan KN, Greendyk R, Chae SR, Natarajan K, Roh D, Edwin E, Gallagher D, Podolanczuk A, Barr RG, Ferrante AW, Baldwin MR. Body mass index and risk of intubation or death in SARS-CoV-2 infection: a retrospective cohort study. Ann Intern Med. 2020 Nov 17;173(10):782-790. Epub 2020 Jul 29.

Evaluating the efficacy and safety of human anti-SARS-CoV2 convalescent plasma in severely ill adults with COVID-19: A structured summary of a study protocol for a randomized control trial.
Eckhardt CM, Cummings MJ, Rajagopalan KN, Borden S, Bitan ZC, Wolf A, Kantor A, Briese T, Meyer BJ, Jacobson SD, Scotto D, Mishra N, Philip NM, Stotler BA, Schwartz J, Shaz B, Spitalnik SL, Eisenberger A, Hod EA, Justman J, Cheung K, Lipkin WI, O'Donnell MR. Trials. 2020 Jun 8;21(1):499.

The histone mark H3K36me2 recruits DNMT3A and shapes the intergenic DNA methylation landscape.
Weinberg DN, Papillon-Cavanagh S, Chen H, Yue Y, Chen X, Rajagopalan KN, Horth C, McGuire JT, Xu X, Nikbakht H, Lemiesz AE, Marchione DM, Marunde MR, Meiners MJ, Cheek MA, Keogh MC, Bareke E, Djedid A, Harutyunyan AS, Jabado N, Garcia BA, Li H, Allis CD, Majewski J, Lu C.Nature. 2019 Sep;573(7773):281-286. Epub 2019 Sep 4.

Metabolic plasticity maintains proliferation in pyruvate dehydrogenase deficient cells.
Rajagopalan KN, Egnatchik RA, Calvaruso MA, Wasti AT, Padanad MS, Boroughs LK, Ko B, Hensley CT, Acar M, Hu Z, Jiang L, Pascual JM, Scaglioni PP, DeBerardinis RJ. Cancer Metab. 2015 Jun 29:3:7. eCollection 2015.

Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. 
Marin-Valencia I, Yang C, Mashimo T, Cho S, Baek H, Yang XL, Rajagopalan KN, Maddie M, Vemireddy V, Zhao Z, Cai L, Good L, Tu BP, Hatanpaa KJ, Mickey BE, Matés JM, Pascual JM, Maher EA, Malloy CR, Deberardinis RJ, Bachoo RM. Cell Metab. 2012 Jun 6;15(6):827-37.

Role of glutamine in cancer: therapeutic and imaging implications.
Rajagopalan KN, and DeBerardinis RJ. J Nucl Med. 2011 Jul;52(7):1005-8. Epub 2011 Jun 16.

Haem oxygenase is synthetically lethal with the tumor suppressor fumarate hydratase.
Frezza C, Zheng L, Folger O, Rajagopalan KN, MacKenzie ED, Jerby L, Micaroni M, Chaneton B, Adam J, Hedley A, Kalna G, Tomlinson IP, Pollard PJ, Watson DG, Deberardinis RJ, Shlomi T, Ruppin E, Gottlieb E. Nature. 2011 Aug 17;477(7363):225-8.

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Publications

Publications

View All Publications on My Bibliography

Nguyen T.P., Fang M., Kim J., Wang B., Lin E., Khivansara V., Barrows N., Rivera-Cancel G., Goralski M., Cervantes C.L., Xie S., Peterson J.M., Povedano J.M., Antczak M.I., Posner B.A., McFadden D.G., Ready J.M., De Brabander J.K., Nijhawan D. Inducible mismatch repair streamlines forward genetic approaches to target identification of cytotoxic small molecules. (2023) Cell Chem Biol. 2023 Aug 14:S2451-9456(23)00245-3. doi: 10.1016/j.chembiol.2023.07.017

Povedano J.M., Li V., Lake K.E., Bai X., Rallabandi R., Kim J.,Xie Y., De Brabander J.K., and McFadden D.G. TK216 targets microtubules in Ewing sarcoma cells. (2022) Cell Chem Biol. Aug 18;29(8):1325-1332.e4. doi: 10.1016/j.chembiol.2022.06.002.

Povedano J. M., Rallabandi R., Bai X., Ye X., Liou J., Chen H., Kim J., Xie Y., Posner B., Rice L., De Brabander J.K., and McFadden D.G. A Multipronged Approach Establishes Covalent Modification of β-Tubulin as the Mode of Action of Benzamide Anti-Cancer Toxins. (2020) J Med Chem. DOI: 10.1021/acs.jmedchem.0c01482.

Povedano J.M., Liou J., Wei D., Srivatsav A., Kim J., Xie Y., Nijhawan D., and McFadden D.G. Engineering forward genetics into cultured cancer cells for chemical target identification. (2019) Cell Chem Biol. Jul 11; 26:1-7. PMID: 31303577

Povedano J. M., Martinez P., Serrano R., Tejera Á., Gómez-López G., Bobadilla M., Flores J.M., Bosch F., and Blasco M.A. Therapeutic effects of telomerase in mice with pulmonary fibrosis induced by damage to the lungs and short telomeres. (2018) eLife. Jan 30;7. pii: e31299. doi: 10.7554/eLife.31299.

Bär C., Povedano J. M., Serrano R., Popkes M., Benitez-Buelga C., Formentinin I., Bobadilla M., Bosch F., and Blasco M. A. Telomerase gene therapy rescues telomere length, bone marrow aplasia and survival in a mouse model of aplastic anemia. (2016) Blood. 127(14):1770-9. doi: 10.1182/blood-2015-08-667485.

Povedano J. M., Martinez P., Flores J. M., Mulero F., and Blasco M. A. Telomere dysfunction in lung alveolar type II cells is sufficient to trigger progressive pulmonary fibrosis in mice. (2015) Cell Rep. 12 (2), 286-99.

publications from the Povedano Selfa research lab

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Publications

Publications

Journal Publications

  • Maciel C, Tayaba M, Zou Q, Untrained Network for Super-resolution for Non-contrast-enhanced Wholeheart MRI Acquired using Cardiac-triggered REACT (SRNN-REACT), Current Medical Imaging. 2024 Nov. 8: 1-11. Link
  • Erdem S, Greil GF, Hussain MT, Zou Q. A novel non-contrast agent–enhanced 3D whole-heart magnetic resonance sequence for congenital heart disease patients: the REACT Study. Pediatric Radiology. 2024 Nov 6:1-1. Link
  • Maciel C, Zou Q. Dynamic MRI interpolation in temporal direction using an unsupervised generative model. Computerized Medical Imaging and Graphics. 2024 Oct 1;117:102435. Link
  • Andrews A, Doctor P, Gaur L, Greil FG, Hussain T, Zou Q. Manifold-based denoising for Ferumoxytol-enhanced 3D cardiac cine MRI. Mathematical Biosciences and Engineering: MBE. 2024 Feb 1;21(3):3695-712. Link
  • Zou Q. Motion-resolved 3D Pulmonary MRI Reconstruction using Sinusoidal Representation Networks. Current Medical Imaging. 2024 Jan 1;20:1-7. Link
  • Zou Q, Priya S, Nagpal P, Jacob M. Joint cardiac T1 mapping and cardiac cine using manifold modeling. Bioengineering. 2023 Mar 9;10(3):345. Link
  • Zou Q, Ahmed AH, Dzelebdzic S, Hussain T. Free-breathing and ungated cardiac MRI reconstruction using a deep kernel representation. Applied Sciences. 2023 Feb 10;13(4):2281. Link
  • Zou Q, Miller Z, Dzelebdzic S, Abadeer M, Johnson KM, Hussain T. Time-Resolved 3D cardiopulmonary MRI reconstruction using spatial transformer network. Mathematical Biosciences and Engineering. 2023;20(9):15982-98. Link
  • Zou Q, Ahmed AH, Nagpal P, Priya S, Schulte RF, Jacob M. Variational manifold learning from incomplete data: application to multislice dynamic MRI. IEEE transactions on medical imaging. 2022 Jul 11;41(12):3552-61. Link
  • Zou Q, Torres LA, Fain SB, Higano NS, Bates AJ, Jacob M. Dynamic imaging using motion-compensated smoothness regularization on manifolds (MoCo-SToRM). Physics in medicine & biology. 2022 Jul 4;67(14):144001. Link
  • Ahmed AH, Zou Q, Nagpal P, Jacob M. Dynamic imaging using deep bi-linear unsupervised representation (DEBLUR). IEEE transactions on medical imaging. 2022 Apr 18;41(10):2693-703. Link
  • Zou Q. An image inpainting model based on the mixture of Perona–Malik equation and Cahn–Hilliard equation. Journal of Applied Mathematics and Computing. 2021 Jun;66(1):21-38. Link
  • Zou Q, Ahmed AH, Nagpal P, Kruger S, Jacob M. Dynamic imaging using a deep generative SToRM (Gen-SToRM) model. IEEE transactions on medical imaging. 2021 Mar 15;40(11):3102-12. Link
  • Zou Q, Jacob M. Recovery of surfaces and functions in high dimensions: sampling theory and links to neural networks. SIAM journal on imaging sciences. 2021;14(2):580-619. Link
  • Zou Q. A PDE model for smooth surface reconstruction from 2D parallel slices. IEEE Signal Processing Letters. 2020 Jun 5;27:1015-9. Link
  • Zou Q, Poddar S, Jacob M. Sampling of planar curves: Theory and fast algorithms. IEEE Transactions on Signal Processing. 2019 Nov 20;67(24):6455-67. Link
  • Qi F, Zou Q, Guo BN. The inverse of a triangular matrix and several identities of the Catalan numbers. Applicable Analysis and Discrete Mathematics. 2019 Oct 1;13(2):518-41. Link

Publications before the year of 2019 are om. See my Google Scholar page for publications before 2019.

Conference publications and Abstracts

  • Doctor P, Fares M, Greil G, Hussain T, Zou Q, Utility of 3 Dimensional Ferumoxytol-enhanced Magnetic Resonancy Angiography using non-Cartesian Ultra-short Echo Time in Pediatric and Congenital Heart Diseases: Just in a minute, SCMR 2025.
  • Stebbings S, Erdem S, Greil GF, Hussain MT, Zou Q. Free-running 3D whole-heart angiography and cine in less than 2 minutes: A feasibility study. SCMR 2025.
  • Jack A, Erdem S, Greil GF, Hussain MT, Zou Q. Magnetization-Transfer-Contrast Based Free-Breathing, Non-Contrast-Enhanced Whole-Heart MRI for Better Vascular Visualization. SCMR 2025.
  • Young D, Hussain T, Q. Zou Q. UTE Imaging for Rapid Whole-Body Central Vascular Access Assessment in Children and Young Adults Undergoing Cardiac Surgery, ISMRM 2024.
  • Erdem S, Miah T, Hussain T, Greil G, Zou Q. Comparing 3D Cardiovascular MR Angiography with 3D bSSFP Whole Heart Imaging in Congenital Heart Diseases: A REACT Study. ISMRM 2024.
  • Maciel C, Zou Q, Unsupervised Neural Network for Super-Resolving Non-Contrast-Enhanced Whole-Heart MRI Using REACT, ISMRM 2024.
  • Miah T, Fares M, Greil G, Hussain T, Zou Q. An Innovative Approach to Cardiac MRI Stent Imaging Using UTE. SCMR 2024. Link
  • Miah T, Gunda R, Greil G, Hussain T, Zou Q. Feasibility Study of Using T1-TFE Sequence with Ferumoxytol Contrast for Cardiac Function Assessment. SCMR 2024. Link
  • Dzelebdzic S, Hussain T, Sood A, Zou Q. Lung Water Density Measurements in Biventricular and Single Ventricle Physiology Using a 3D Ultrashort Echo Time Sequence (UTE). SCMR 2024. Link
  • Zou Q, Chabiniok R, Greil G, Hussain T, Right ventricle segmentation using a narrowband level set method in cardiac MRI, SCMR 2023.
  • Zou Q, Dzelebdzic S, Hussain T, Deep kernel method for free-breathing and ungated cardiac MRI reconstruction, ISMRM 2023.
  • Zou Q, Priya S, Nagpal P, Jacob M, Joint cardiac T1 mapping and cardiac cine using a deep manifold framework, ISMRM 2023.
  • Zou Q, Dzelebdzic S, Hussain T, Deep Kernel Method for Dynamic MRI Reconstruction, IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2023. Link
  • Zou Q, Priya S, Nagpal P, Jacob M, Deep Generative Model for Joint Cardiac T1 Mapping and Cardiac Cine, IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2023. Link
  • Rusho RZ, Zou Q, Alam W, Erattakulangara S, Jacob M, Lingala SG, Accelerated pseudo-3D dynamic speech imaging using unsupervised deep variational manifold learning, 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. Link
  • Zou Q, Ahmed AH, Nagpal P, S. Priya, Schulte RF, Jacob M, Joint alignment and reconstruction of multislice dynamic MRI using variational manifold learning, IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2022. Link
  • Zou Q, Torres L, Fain S, Jacob M, Dynamic imaging using motion-compensated smoothness regularization on manifolds (MoCo-SToRM), IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2022. Link
  • Zou Q, Ahmed AH, Nagpal P, S. Priya, Schulte RF, Jacob M, Alignment and joint recovery of multi-slice free-breathing cardiac cine using manifold learning, ISMRM 2022.
  • Zou Q, Torres L, Fain S, Jacob M, High-resolution dynamic 3D UTE Lung MRI using motion-compensated manifold learning, ISMRM 2022.
  • Rusho RZ, Zou Q, Jacob M, Lingala SG, Accelerated time aligned multi-slice speech MRI using a generative manifold model, ISMRM 2022.
  • Zou Q, Ahmed AH, Nagpal P, Kruger S, Jacob M, Deep Generative SToRM model for dynamic imaging, IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2021. Link
  • Zou Q, Ahmed AH, Nagpal P, Schulte RF, Jacob M, Deep generative manifold model: a novel approach for free-breathing dynamic MRI, ISMRM 2021.
  • Zou Q, Ahmed AH, Nagpal P, Schulte RF, Jacob M, Alignment & joint recovery of multi-slice cine MRI data using deep generative manifold model, ISMRM 2021.
  • Zou Q, Jacob M, Sampling of surfaces and learning functions in high dimensions, The International Conference on Acoustics, Speech, & Signal Processing (IEEE ICASSP) 2020. Link
  • Zou Q, Learning Functions Using Data-Dependent Regularization: Representer Theorem Revisited, International Conference on Computational Science (ICCS) 2020. Link

publications for Zou Lab

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Publications

Publications

Heart Failure with Preserved Ejection Fraction and Geriatric Cardiology

  1. Segar M, Patel K, Ayers C, Basit M, Tang Wilson W. H, Willett D, Berry J, Grodin J, Pandey A. Phenomapping of patients with heart failure with preserved ejection fraction using machine learning-based unsupervised cluster analysis. European Journal of Heart Failure 2020;22 (1):148-158.
  2. Pandey A, Yanamala N, Kagiyama N, Segar M, Tokodi M, Cho Jung Sun, Sengupta P. Deep- learning Models for the Echocardiographic Assessment of Diastolic Dysfunction: Development and Validation in NHLBI-Funded Heart Failure Clinical Trials. JACC: Cardiovascular Imaging 2021 Oct;14(10):1887-1900.
  3. Kitzman, D. W., Upadhya, B., & Pandey, A. (2023). Rate-Adaptive Pacing for Heart Failure With Preserved Ejection Fraction. JAMA, 329(10), 797–799. doi: 10.1001/jama.2023.1053
  4. Pandey, A., Kitzman, D. W., Nelson, M. B., Pastva, A. M., Duncan, P., Whellan, D. J., Mentz, R. J., Chen, H., Upadhya, B., & Reeves, G. R. (2023). Frailty and Effects of a Multidomain Physical Rehabilitation Intervention Among Older Patients Hospitalized for Acute Heart Failure: A Secondary Analysis of a Randomized Clinical Trial. JAMA Cardiology, 8(2), 167–176. doi:10.1001/jamacardio.2022.4903
  5. Pandey, A., Shah, S. J., Butler, J., Kellogg, D. L., Jr, Lewis, G. D., Forman, D. E., Mentz, R. J., Borlaug, B. A., Simon, M. A., Chirinos, J. A., Fielding, R. A., Volpi, E., Molina, A. J. A., Haykowsky, M. J., Sam, F., Goodpaster, B. H., Bertoni, A. G., Justice, J. N., White, J. P., Ding, J., … Kitzman, D. (2021). Exercise Intolerance in Older Adults With Heart Failure With Preserved Ejection Fraction: JACC State-of-the-Art Review. Journal of the American College of Cardiology, 2021 Sep 14;78(11):1166-1187. doi: 10.1016/j.jacc.2021.07.014.

Big Data, Risk Prediction and Epidemiology

  1. Segar, M. W., Patel, K. V., Vaduganathan, M., Caughey, M. C., Jaeger, B. C., Basit, M., Willett, D., Butler, J., Sengupta, P. P., Wang, T. J., McGuire, D. K., & Pandey, A. (2021). Development and validation of optimal phenomapping methods to estimate long-term atherosclerotic cardiovascular disease risk in patients with type 2 diabetes. Diabetologia, 64(7), 1583–1594. doi: 10.1007/s00125-021-05426-2
  2. Pandey, A., & Adedinsewo, D. (2022). The Future of AI-Enhanced ECG Interpretation for Valvular Heart Disease Screening. Journal of the American College of Cardiology, 80(6), 627–630. doi: 10.1016/j.jacc.2022.05.034
  3. Segar, M. W., Khan, M. S., Patel, K. V., Vaduganathan, M., Kannan, V., Willett, D., Peterson, E., Tang, W. H. W., Butler, J., Everett, B. M., Fonarow, G. C., Wang, T. J., McGuire, D. K., & Pandey, A. (2022). Incorporation of natriuretic peptides with clinical risk scores to predict heart failure among individuals with dysglycaemia. European journal of heart failure, 24(1), 169–180. doi: 10.1002/ejhf.2375
  4. Segar, M. W., Jaeger, B. C., Patel, K. V., Nambi, V., Ndumele, C. E., Correa, A., Butler, J., Chandra, A., Ayers, C., Rao, S., Lewis, A. A., Raffield, L. M., Rodriguez, C. J., Michos, E. D., Ballantyne, C. M., Hall, M. E., Mentz, R. J., de Lemos, J. A., & Pandey, A. (2021). Development and Validation of Machine Learning-Based Race-Specific Models to Predict 10-Year Risk of Heart Failure: A Multicohort Analysis. Circulation, 143(24), 2370–2383. doi: 10.1161/CIRCULATIONAHA.120.053134
  5. Mosley JD, Gupta DK, Tan J, Yao J, Wells QS, Shaffer CM, Kundu S, Robinson-Cohen C, Psaty BM, Rich SS, Post WS, Guo X, Rotter JI, Roden DM, Gerszten RE, Wang TJ. Predictive accuracy of a polygenic risk score compared with a clinical risk score for incident coronary heart disease. JAMA. 2020;323:627-635. doi: 10.1001/jama.2019.21782

Biomarkers and Metabolomics

  1. Patel, K. V., Segar, M. W., Lavie, C. J., Kondamudi, N., Neeland, I. J., Almandoz, J. P., Martin, C. K., Carbone, S., Butler, J., Powell-Wiley, T. M., & Pandey, A. (2022). Diabetes Status Modifies the Association Between Different Measures of Obesity and Heart Failure Risk Among Older Adults: A Pooled Analysis of Community-Based NHLBI Cohorts. Circulation, 145(4), 268–278. doi: 10.1161/CIRCULATIONAHA.121.055830
  2. Pandey, A., Mehta, A., Paluch, A., Ning, H., Carnethon, M. R., Allen, N. B., Michos, E. D., Berry, J. D., Lloyd-Jones, D. M., & Wilkins, J. T. (2021). Performance of the American Heart Association/American College of Cardiology Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Self-reported Physical Activity Levels. JAMA cardiology, 6(6), 690–696. doi: 10.1001/jamacardio.2021.0948
  3. Segar M, Vaduganathan M, Patel KV, McGuire DK, Butler J, Fonarow GC, Basit M, Kannan V, Grodin JL, Everett B, Willett D, Berry J, Pandey A. Machine Learning to Predict the Risk of Incident Heart Failure Hospitalization Among Patients with Diabetes. Diabetes Care. 2019,42:2298-2306. doi: 10.2337/dc19-0587.
  4. Pandey A, Patel K, Vongpatanasin W, et al. Incorporation of Biomarkers into Risk Assessment for Allocation of Antihypertensive Medication According to the 2017 ACC/AHA High Blood Pressure Guideline: A Pooled Cohort Analysis. Circulation 2019;140(25):2076-2088 doi: 10.1161/CIRCULATIONAHA.119.043337.
  5. York, M. K., Gupta, D. K., Reynolds, C. F., Farber-Eger, E., Wells, Q. S., Bachmann, K. N., Xu, M., Harrell, F. E., Jr, & Wang, T. J. B-Type Natriuretic Peptide Levels and Mortality in Patients With and Without Heart Failure. Journal of the American College of Cardiology, 2018,71(19), 2079–2088. doi: 10.1016/j.jacc.2018.02.071
  6. Benson MD, Yang Q, Ngo D, Zhu Y, Shen D, Farrell LA, Sinha S, Keyes MJ, Vasan RS, Larson MG, Smith JG, Wang TJ*, Gerszten RE*. Genetic architecture of the cardiovascular risk proteome. Circulation. 2018; 137:1158-1172. doi: 10.1161/CIRCULATIONAHA.117.029536.
  7. Mosley JD, Benson MD, Smith JG, Melander O, Ngo D, Shaffer CM, Ferguson JF, Herzig MS, McCarty CA, Chute CG, Jarvik GP, Gordon AS, Palmer MR, Crosslin DR, Larson EB, Carrell DS, Kullo IJ, Pacheco JA, Peissig PL, Brilliant MH, Kitchner TE, Linneman JG, Namjou B, Williams MS, Ritchie MD, Borthwick KM, Kiryluk K, Mentch FD, Sleiman PM, Karlson EW, Verma SS, Zhu Y, Vasan RS, Yang Q, Denny JC, Roden DM, Gerszten RE*, Wang TJ*. Probing the virtual proteome to identify novel disease biomarkers. Circulation. 2018;138:2469-2481. doi: 10.1161/CIRCULATIONAHA.118.036063.
  8. Cheng S, Larson M, McCabe E, Murabito J, Rhee E, Ho J, Jacques PF, Ghorbani A, Magnusson M, Souza A, Diek A, Pierce K, Bullock K, O'Donnell C, Melander O, Clish C, Vasan R, Gerszten R, Wang T. Distinct metabolic signatures are associated with longevity in humans. Nature Comm. 2015;6:6791. doi: 10.1038/ncomms7791.
  9. Wang, T. J., Ngo, D., Psychogios, N., Dejam, A., Larson, M. G., Vasan, R. S., ... & Gerszten, R. E. 2-Aminoadipic acid is a biomarker for diabetes risk. The Journal of Clinical Investigation, 2013,123(10), 4309-4317. doi: 10.1172/JCI64801.
  10. Magnusson, Martin, Gregory D. Lewis, Ulrika Ericson, Marju Orho-Melander, Bo Hedblad, Gunnar Engström, Gerd Östling et al. A diabetes-predictive amino acid score and future cardiovascular disease. European heart journal 34, no. 26 (2013): 1982-1989. doi: 10.1093/eurheartj/ehs424.
  11. Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, Lewis GD, Fox CS, Jacques PF, Fernandez C, O’Donnell CJ, Carr SA, Mootha VK, Florez JC, Souza A, Melander O, Clish CB, Gerszten RE. Metabolite profiles and the risk of developing diabetes. Nature Medicine. 2011;17:448-53. doi: 10.1038/nm.2307. 
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Health Services and Disparities

  1. Mentias, A., Peterson, E. D., Keshvani, N., Kumbhani, D. J., Yancy, C. W., Morris, A. A., Allen, L. A., Girotra, S., Fonarow, G. C., Starling, R. C., Alvarez, P., Desai, M. Y., Cram, P., & Pandey, A. Achieving Equity in Hospital Performance Assessments Using Composite Race-Specific Measures of Risk-Standardized Readmission and Mortality Rates for Heart Failure. Circulation, 2023 147(15), 1121–1133. doi: 10.1161/CIRCULATIONAHA.122.061995
  2. Mentias, A., Desai, M. Y., Keshvani, N., Gillinov, A. M., Johnston, D., Kumbhani, D. J., Hirji, S. A., Sarrazin, M. V., Saad, M., Peterson, E. D., Mack, M. J., Cram, P., Girotra, S., Kapadia, S., Svensson, L., & Pandey, A. Ninety-Day Risk-Standardized Home Time as a Performance Metric for Cardiac Surgery Hospitals in the United States. Circulation, 2022 146(17), 1297–1309. doi: 10.1161/CIRCULATIONAHA.122.059496
  3. Keshvani, N., Mehta, A., Alger, H. M., Rutan, C., Williams, J., Zhang, S., Young, R., Alhanti, B., Chiswell, K., Greene, S. J., DeVore, A. D., Yancy, C. W., Fonarow, G. C., & Pandey, A. Heart failure quality of care and in-hospital outcomes during the COVID-19 pandemic: findings from the Get With The Guidelines-Heart Failure registry. European Journal of Heart Failure, 2022 24(6), 1117–1128. doi: 10.1002/ejhf.2484
  4. Mentias, A., Keshvani, N., Desai, M. Y., Kumbhani, D. J., Sarrazin, M. V., Gao, Y., Kapadia, S., Peterson, E. D., Mack, M., Girotra, S., & Pandey, A. (2022). Risk-Adjusted, 30-Day Home Time After Transcatheter Aortic Valve Replacement as a Hospital-Level Performance Metric. Journal of the American College of Cardiology, 2022 79(2), 132–144. doi: 10.1016/j.jacc.2021.10.038
  5. Pandey, A., Keshvani, N., Zhong, L., Mentz, R. J., Piña, I. L., DeVore, A. D., Yancy, C., Kitzman, D. W., & Fonarow, G. C. Temporal Trends and Factors Associated With Cardiac Rehabilitation Participation Among Medicare Beneficiaries With Heart Failure. JACC. Heart Failure, 2021 9(7), 471–481. doi: 10.1016/j.jchf.2021.02.006
  6. Pandey, A., Keshvani, N., Vaughan-Sarrazin, M. S., Gao, Y., Fonarow, G. C., Yancy, C., & Girotra, S.. Evaluation of Risk-Adjusted Home Time After Hospitalization for Heart Failure as a Potential Hospital Performance Metric. JAMA Cardiology, 2021 6(2), 169–176. doi: 10.1001/jamacardio.2020.4928
  7. Jacobs, J. A., Addo, D. K., Zheutlin, A. R., Derington, C. G., Essien, U. R., Navar, A. M., Hernandez, I., Lloyd-Jones, D. M., King, J. B., Rao, S., Herrick, J. S., Bress, A. P., & Pandey, A. Prevalence of Statin Use for Primary Prevention of Atherosclerotic Cardiovascular Disease by Race, Ethnicity, and 10-Year Disease Risk in the US: National Health and Nutrition Examination Surveys, 2013 to March 2020. JAMA Cardiology, 2023. e230228. Advance online publication. doi: 10.1001/jamacardio.2023.0228
  8. Segar, M. W., Hall, J. L., Jhund, P. S., Powell-Wiley, T. M., Morris, A. A., Kao, D., Fonarow, G. C., Hernandez, R., Ibrahim, N. E., Rutan, C., Navar, A. M., Stevens, L. M., & Pandey, A. Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure. JAMA Cardiology, 2022. 7(8), 844–854. doi: 10.1001/jamacardio.2022.1900
  9. Mentias, A., Desai, M. Y., Vaughan-Sarrazin, M. S., Rao, S., Morris, A. A., Hall, J. L., Menon, V., Hockenberry, J., Sims, M., Fonarow, G. C., Girotra, S., & Pandey, A. Community-Level Economic Distress, Race, and Risk of Adverse Outcomes After Heart Failure Hospitalization Among Medicare Beneficiaries. Circulation 2022. 145(2), 110–121. doi: 10.1161/CIRCULATIONAHA.121.057756
  10. Rao, S., Hughes, A., Segar, M. W., Wilson, B., Ayers, C., Das, S., Halm, E. A., & Pandey, A. Longitudinal Trajectories and Factors Associated With US County-Level Cardiovascular Mortality, 1980 to 2014. JAMA Network Open, 2021. 4(11), e2136022. doi: 10.1001/jamanetworkopen.2021.36022
  11. Rao, S., Segar, M. W., Bress, A. P., Arora, P., Vongpatanasin, W., Agusala, V., Essien, U. R., Correa, A., Morris, A. A., de Lemos, J. A., & Pandey, A. (2020). Association of Genetic West African Ancestry, Blood Pressure Response to Therapy, and Cardiovascular Risk Among Self-Reported Black Individuals in the Systolic Blood Pressure Reduction Intervention Trial (SPRINT). JAMA Cardiology, 2020 Nov 13;6(4):388-398. doi: 10.1001/jamacardio.2020.6566.

Implementation Science and Electronic Health Record

  1. Wang T. J. The Polypill at 20 - What Have We Learned?. NEJM, 2022 387(11), 1034–1036. doi: 10.1056/NEJMe2210020
  2. Rao, S., Jamal Siddiqi, T., Khan, M. S., Michos, E. D., Navar, A. M., Wang, T. J., Greene, S. J., Prabhakaran, D., Khera, A., & Pandey, A. Association of polypill therapy with cardiovascular outcomes, mortality, and adherence: A systematic review and meta-analysis of randomized controlled trials. Progress in Cardiovascular Diseases, 2022 .73, 48–55. doi: 10.1016/j.pcad.2022.01.005
  3. Pandey, A., MacNamara, J., Sarma, S., Velasco, F., Kannan, V., Willard, J., Skinner, C., Keller, T., Basit, M., Levine, B., & Willett, D. (2019). Rapid-Cycle Implementation of a Multi-Organization Registry for Heart Failure with Preserved Ejection Fraction Using Health Information Exchange Standards. Studies in health technology and informatics, 2019 264, 1560–1561. doi: 10.3233/SHTI190534
  4. Muñoz D, Uzoije P, Reynolds C, Miller R, Walkley D, Pappalardo S, Tousey P, Munro H, Gonzales H, Song W, White C, Blot WJ, Wang TJ. Polypill for Cardiovascular Disease Prevention in an Underserved Population. N Engl J Med. 2019;381:1114-1123. doi: 10.1056/NEJMoa1815359.
  5. Muñoz D, Wang TJ. The Polypill Revisited: Why We Still Need Population-Based Approaches in the Precision Medicine Era. Circulation. 2019;140:1776-1778. doi: 10.1161/CIRCULATIONAHA.119.043491.
  6. Arora P, Song Y, Dusek J, Plotnikoff G, Sabatine M, Cheng S... Azzahir A, Strachan SM, O'Neill DC, Wolf M, Harrell F, Newton-Cheh C, Wang TJ. Vitamin D Therapy in Individuals with Pre-Hypertension or Hypertension: The DAYLIGHT Trial. Circulation. 2015; 131:254-62 doi: 10.1161/CIRCULATIONAHA.114.011732.

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