Vidyani Suryadevara

All Publications

• SenNet recommendations for detecting senescent cells in different tissues. Nature reviews. Molecular cell biology Suryadevara, V., Hudgins, A. D., Rajesh, A., Pappalardo, A., Karpova, A., Dey, A. K., Hertzel, A., Agudelo, A., Rocha, A., Soygur, B., Schilling, B., Carver, C. M., Aguayo-Mazzucato, C., Baker, D. J., Bernlohr, D. A., Jurk, D., Mangarova, D. B., Quardokus, E. M., Enninga, E. A., Schmidt, E. L., Chen, F., Duncan, F. E., Cambuli, F., Kaur, G., Kuchel, G. A., Lee, G., Daldrup-Link, H. E., Martini, H., Phatnani, H., Al-Naggar, I. M., Rahman, I., Nie, J., Passos, J. F., Silverstein, J. C., Campisi, J., Wang, J., Iwasaki, K., Barbosa, K., Metis, K., Nernekli, K., Niedernhofer, L. J., Ding, L., Wang, L., Adams, L. C., Ruiyang, L., Doolittle, M. L., Teneche, M. G., Schafer, M. J., Xu, M., Hajipour, M., Boroumand, M., Basisty, N., Sloan, N., Slavov, N., Kuksenko, O., Robson, P., Gomez, P. T., Vasilikos, P., Adams, P. D., Carapeto, P., Zhu, Q., Ramasamy, R., Perez-Lorenzo, R., Fan, R., Dong, R., Montgomery, R. R., Shaikh, S., Vickovic, S., Yin, S., Kang, S., Suvakov, S., Khosla, S., Garovic, V. D., Menon, V., Xu, Y., Song, Y., Suh, Y., Dou, Z., Neretti, N. 2024

  Abstract

  Once considered a tissue culture-specific phenomenon, cellular senescence has now been linked to various biological processes with both beneficial and detrimental roles in humans, rodents and other species. Much of our understanding of senescent cell biology still originates from tissue culture studies, where each cell in the culture is driven to an irreversible cell cycle arrest. By contrast, in tissues, these cells are relatively rare and difficult to characterize, and it is now established that fully differentiated, postmitotic cells can also acquire a senescence phenotype. The SenNet Biomarkers Working Group was formed to provide recommendations for the use of cellular senescence markers to identify and characterize senescent cells in tissues. Here, we provide recommendations for detecting senescent cells in different tissues based on a comprehensive analysis of existing literature reporting senescence markers in 14 tissues in mice and humans. We discuss some of the recent advances in detecting and characterizing cellular senescence, including molecular senescence signatures and morphological features, and the use of circulating markers. We aim for this work to be a valuable resource for both seasoned investigators in senescence-related studies and newcomers to the field.

  View details for DOI 10.1038/s41580-024-00738-8

  View details for PubMedID 38831121

  View details for PubMedCentralID 5643029

• Detecting High-Dose Methotrexate-Induced Brain Changes in Pediatric and Young Adult Cancer Survivors Using [18F]FDG PET/MRI: A Pilot Study. Journal of nuclear medicine : official publication, Society of Nuclear Medicine Baratto, L., Singh, S. B., Williams, S. E., Spunt, S. L., Rosenberg, J., Adams, L., Suryadevara, V., Iv, M., Daldrup-Link, H. 2024

  Abstract

  Significant improvements in treatments for children with cancer have resulted in a growing population of childhood cancer survivors who may face long-term adverse outcomes. Here, we aimed to diagnose high-dose methotrexate-induced brain injury on [18F]FDG PET/MRI and correlate the results with cognitive impairment identified by neurocognitive testing in pediatric cancer survivors. Methods: In this prospective, single-center pilot study, 10 children and young adults with sarcoma (n = 5), lymphoma (n = 4), or leukemia (n = 1) underwent dedicated brain [18F]FDG PET/MRI and a 2-h expert neuropsychologic evaluation on the same day, including the Wechsler Abbreviated Scale of Intelligence, second edition, for intellectual functioning; Delis-Kaplan Executive Function System (DKEFS) for executive functioning; and Wide Range Assessment of Memory and Learning, second edition (WRAML), for verbal and visual memory. Using PMOD software, we measured the SUVmean, cortical thickness, mean cerebral blood flow (CBFmean), and mean apparent diffusion coefficient of 3 different cortical regions (prefrontal cortex, cingulate gyrus, and hippocampus) that are routinely involved during the above-specified neurocognitive testing. Standardized scores of different measures were converted to z scores. Pairs of multivariable regression models (one for z scores < 0 and one for z scores > 0) were fitted for each brain region, imaging measure, and test score. Heteroscedasticity regression models were used to account for heterogeneity in variances between brain regions and to adjust for clustering within patients. Results: The regression analysis showed a significant correlation between the SUVmean of the prefrontal cortex and cingulum and DKEFS-sequential tracking (DKEFS-TM4) z scores (P = 0.003 and P = 0.012, respectively). The SUVmean of the hippocampus did not correlate with DKEFS-TM4 z scores (P = 0.111). The SUVmean for any evaluated brain regions did not correlate significantly with WRAML-visual memory (WRAML-VIS) z scores. CBFmean showed a positive correlation with SUVmean (r = 0.56, P = 0.01). The CBFmean of the cingulum, hippocampus, and prefrontal cortex correlated significantly with DKEFS-TM4 (all P < 0.001). In addition, the hippocampal CBFmean correlated significantly with negative WRAML-VIS z scores (P = 0.003). Conclusion: High-dose methotrexate-induced brain injury can manifest as a reduction in glucose metabolism and blood flow in specific brain areas, which can be detected with [18F]FDG PET/MRI. The SUVmean and CBFmean of the prefrontal cortex and cingulum can serve as quantitative measures for detecting executive functioning problems. Hippocampal CBFmean could also be useful for monitoring memory problems.

  View details for DOI 10.2967/jnumed.123.266760

  View details for PubMedID 38575193

• Musculoskeletal imaging of senescence. Skeletal radiology Daldrup-Link, H. E., Suryadevara, V., Tanyildizi, Y., Nernekli, K., Tang, J. H., Meade, T. J. 2024

  Abstract

  Senescent cells play a vital role in the pathogenesis of musculoskeletal (MSK) diseases, such as chronic inflammatory joint disorders, rheumatoid arthritis (RA), and osteoarthritis (OA). Cellular senescence in articular joints represents a response of local cells to persistent stress that leads to cell-cycle arrest and enhanced production of inflammatory cytokines, which in turn perpetuates joint damage and leads to significant morbidities in afflicted patients. It has been recently discovered that clearance of senescent cells by novel "senolytic" therapies can attenuate the chronic inflammatory microenvironment of RA and OA, preventing further disease progression and supporting healing processes. To identify patients who might benefit from these new senolytic therapies and monitor therapy response, there is an unmet need to identify and map senescent cells in articular joints and related musculoskeletal tissues. To fill this gap, new imaging biomarkers are being developed to detect and characterize senescent cells in human joints and musculoskeletal tissues. This review article will provide an overview of these efforts. New imaging biomarkers for senescence cells are expected to significantly improve the specificity of state-of-the-art imaging technologies for diagnosing musculoskeletal disorders.

  View details for DOI 10.1007/s00256-024-04585-8

  View details for PubMedID 38329533

  View details for PubMedCentralID 5785239

• Spatial mapping of cellular senescence: emerging challenges and opportunities. Nature aging Gurkar, A. U., Gerencser, A. A., Mora, A. L., Nelson, A. C., Zhang, A. R., Lagnado, A. B., Enninful, A., Benz, C., Furman, D., Beaulieu, D., Jurk, D., Thompson, E. L., Wu, F., Rodriguez, F., Barthel, G., Chen, H., Phatnani, H., Heckenbach, I., Chuang, J. H., Horrell, J., Petrescu, J., Alder, J. K., Lee, J. H., Niedernhofer, L. J., Kumar, M., Konigshoff, M., Bueno, M., Sokka, M., Scheibye-Knudsen, M., Neretti, N., Eickelberg, O., Adams, P. D., Hu, Q., Zhu, Q., Porritt, R. A., Dong, R., Peters, S., Victorelli, S., Pengo, T., Khaliullin, T., Suryadevara, V., Fu, X., Bar-Joseph, Z., Ji, Z., Passos, J. F. 2023

  Abstract

  Cellular senescence is a well-established driver of aging and age-related diseases. There are many challenges to mapping senescent cells in tissues such as the absence of specific markers and their relatively low abundance and vast heterogeneity. Single-cell technologies have allowed unprecedented characterization of senescence; however, many methodologies fail to provide spatial insights. The spatial component is essential, as senescent cells communicate with neighboring cells, impacting their function and the composition of extracellular space. The Cellular Senescence Network (SenNet), a National Institutes of Health (NIH) Common Fund initiative, aims to map senescent cells across the lifespan of humans and mice. Here, we provide a comprehensive review of the existing and emerging methodologies for spatial imaging and their application toward mapping senescent cells. Moreover, we discuss the limitations and challenges inherent to each technology. We argue that the development of spatially resolved methods is essential toward the goal of attaining an atlas of senescent cells.

  View details for DOI 10.1038/s43587-023-00446-6

  View details for PubMedID 37400722

• Thwarting Alzheimer's Disease through Healthy Lifestyle Habits: Hope for the Future. Neurology international Govindugari, V. L., Golla, S., Reddy, S. D., Chunduri, A., Nunna, L. S., Madasu, J., Shamshabad, V., Bandela, M., Suryadevara, V. 2023; 15 (1): 162-187

  Abstract

  Alzheimer's disease (AD) is a neurodegenerative disorder that slowly disintegrates memory and thinking skills. Age is known to be the major risk factor in AD, but there are several nonmodifiable and modifiable causes. The nonmodifiable risk factors such as family history, high cholesterol, head injuries, gender, pollution, and genetic aberrations are reported to expediate disease progression. The modifiable risk factors of AD that may help prevent or delay the onset of AD in liable people, which this review focuses on, includes lifestyle, diet, substance use, lack of physical and mental activity, social life, sleep, among other causes. We also discuss how mitigating underlying conditions such as hearing loss and cardiovascular complications could be beneficial in preventing cognitive decline. As the current medications can only treat the manifestations of AD and not the underlying process, healthy lifestyle choices associated with modifiable factors is the best alternative strategy to combat the disease.

  View details for DOI 10.3390/neurolint15010013

  View details for PubMedID 36810468

• MegaPro, a clinically translatable nanoparticle for in vivo tracking of stem cell implants in pig cartilage defects. Theranostics Suryadevara, V., Hajipour, M. J., Adams, L. C., Aissaoui, N. M., Rashidi, A., Kiru, L., Theruvath, A. J., Huang, C., Maruyama, M., Tsubosaka, M., Lyons, J. K., Wu, W. E., Roudi, R., Goodman, S. B., Daldrup-Link, H. E. 2023; 13 (8): 2710-2720

  Abstract

  Rationale: Efficient labeling methods for mesenchymal stem cells (MSCs) are crucial for tracking and understanding their behavior in regenerative medicine applications, particularly in cartilage defects. MegaPro nanoparticles have emerged as a potential alternative to ferumoxytol nanoparticles for this purpose. Methods: In this study, we employed mechanoporation to develop an efficient labeling method for MSCs using MegaPro nanoparticles and compared their effectiveness with ferumoxytol nanoparticles in tracking MSCs and chondrogenic pellets. Pig MSCs were labeled with both nanoparticles using a custom-made microfluidic device, and their characteristics were analyzed using various imaging and spectroscopy techniques. The viability and differentiation capacity of labeled MSCs were also assessed. Labeled MSCs and chondrogenic pellets were implanted into pig knee joints and monitored using MRI and histological analysis. Results: MegaPro-labeled MSCs demonstrated shorter T2 relaxation times, higher iron content, and greater nanoparticle uptake compared to ferumoxytol-labeled MSCs, without significantly affecting their viability and differentiation capacity. Post-implantation, MegaPro-labeled MSCs and chondrogenic pellets displayed a strong hypointense signal on MRI with considerably shorter T2* relaxation times compared to adjacent cartilage. The hypointense signal of both MegaPro- and ferumoxytol-labeled chondrogenic pellets decreased over time. Histological evaluations showed regenerated defect areas and proteoglycan formation with no significant differences between the labeled groups. Conclusion: Our study demonstrates that mechanoporation with MegaPro nanoparticles enables efficient MSC labeling without affecting viability or differentiation. MegaPro-labeled cells show enhanced MRI tracking compared to ferumoxytol-labeled cells, emphasizing their potential in clinical stem cell therapies for cartilage defects.

  View details for DOI 10.7150/thno.82620

  View details for PubMedID 37215574

• NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health NATURE AGING Lee, P. J., Benz, C. C., Blood, P., Boerner, K., Campisi, J., Chen, F., Daldrup-Link, H., De Jager, P., Ding, L., Duncan, F. E., Eickelberg, O., Fan, R., Finkel, T., Furman, D., Garovic, V., Gehlenborg, N., Glass, C., Heckenbach, I., Joseph, Z., Katiyar, P., Kim, S., Koenigshoff, M., Kuchel, G. A., Lee, H., Lee, J., Ma, J., Ma, Q., Melov, S., Metis, K., Mora, A. L., Musi, N., Neretti, N., Passos, J. F., Rahman, I., Rivera-Mulia, J., Robson, P., Rojas, M., Roy, A. L., Scheibye-Knudsen, M., Schilling, B., Shi, P., Silverstein, J. C., Suryadevara, V., Xie, J., Wang, J., Wong, A., Niedernhofer, L. J., Wang, S., Anvari, H., Balough, J., Benz, C., Bons, J., Brenerman, B., Evans, W., Gerencser, A., Gregory, H., Hansen, M., Justice, J., Kapahi, P., Murad, N., O'Broin, A., Pavone, M., Powell, M., Scott, G., Shanes, E., Shankaran, M., Verdin, E., Winer, D., Wu, F., Adams, A., Blood, P. D., Bueckle, A., Cao-Berg, I., Chen, H., Davis, M., Filus, S., Hao, Y., Hartman, A., Hasanaj, E., Helfer, J., Herr, B., Bar Joseph, Z., Molla, G., Mou, G., Puerto, J., Quardokus, E. M., Ropelewski, A. J., Ruffalo, M., Satija, R., Schwenk, M., Scibek, R., Shirey, W., Sibilla, M., Welling, J., Yuan, Z., Bonneau, R., Christiano, A., Izar, B., Menon, V., Owens, D. M., Phatnani, H., Smith, C., Suh, Y., Teich, A. F., Bekker, V., Chan, C., Coutavas, E., Hartwig, M. G., Ji, Z., Nixon, A. B., Dou, Z., Rajagopal, J., Slavov, N., Holmes, D., Jurk, D., Kirkland, J. L., Lagnado, A., Tchkonia, T., Abraham, K., Dibattista, A., Fridell, Y., Howcroft, T., Jhappan, C., Montes, V., Prabhudas, M., Resat, H., Taylor, V., Kumar, M., Cigarroa, F., Cohn, R., Cortes, T. M., Courtois, E., Chuang, J., Dave, M., Domanskyi, S., Enninga, E., Eryilmaz, G., Espinoza, S. E., Gelfond, J., Kirkland, J., Kuo, C., Lehman, J. S., Aguayo-Mazzucato, C., Meves, A., Rani, M., Sanders, S., Thibodeau, A., Tullius, S. G., Ucar, D., White, B., Wu, Q., Xu, M., Yamaguchi, S., Assarzadegan, N., Cho, C., Hwang, I., Hwang, Y., Xi, J., Adeyi, O. A., Aliferis, C. F., Bartolomucci, A., Dong, X., DuFresne-To, M. J., Ikramuddin, S., Johnson, S. G., Nelson, A. C., Revelo, X. S., Trevilla-Garcia, C., Sedivy, J. M., Thompson, E. L., Robbins, P. D., Wang, J., Aird, K. M., Alder, J. K., Beaulieu, D., Bueno, M., Calyeca, J., Chamucero-Millaris, J. A., Chan, S. Y., Chung, D., Corbett, A., Gorbunova, V., Gowdy, K. M., Gurkar, A., Horowitz, J. C., Hu, Q., Kaur, G., Khaliullin, T. O., Lafyatis, R., Lanna, S., Li, D., Ma, A., Morris, A., Muthumalage, T. M., Peters, V., Pryhuber, G. S., Reader, B. F., Rosas, L., Sembrat, J. C., Shaikh, S., Shi, H., Stacey, S. D., St Croix, C., Wang, C., Wang, Q., Watts, A., Gu, L., Lin, Y., Rabinovitch, P. S., Sweetwyne, M. T., Artyomov, M. N., Ballentine, S. J., Chheda, M. G., Davies, S. R., DiPersio, J. F., Fields, R. C., Fitzpatrick, J. J., Fulton, R. S., Imai, S., Jain, S., Ju, T., Kushnir, V. M., Link, D. C., Ben Major, M., Oh, S. T., Rapp, D., Rettig, M. P., Stewart, S. A., Veis, D. J., Vij, K. R., Wendl, M. C., Wyczalkowski, M. A., Craft, J. E., Enninful, A., Farzad, N., Gershkovich, P., Halene, S., Kluger, Y., VanOudenhove, J., Xu, M., Yang, J., Yang, M., SenNet Consortium 2022; 2 (12): 1090-1100

  View details for DOI 10.1038/s43587-022-00326-5

  View details for Web of Science ID 000916582800010