research – Jaron Arbet, Ph.D.

Interests

Machine learning and predictive modeling
High-dimensional “Big Data”
Variable selection
Multi-omics cancer data integration
Robust nonparametric statistics

Publications

1. Jones, L. W., Lavery, J. A., Tsai, B. L., Moskowitz, C. S., Lee, C. P., Harrison, J., Michalski, M. G., Stoeckel, K., Graham, C., Iyengar, N. M., Bhanot, U., Linkov, I., Jain, M., Jochelson, M. S., Monetti, M., Seewaldt, V. L., Pilewskie, M. L., Pribil, P., Zhu, C., Arbet, J., Mangino, D. A., & Boutros, P. C. (2025). A co-clinical trial of exercise therapy in breast cancer prevention. Clinical Cancer Research, OF1–OF11. https://doi.org/10.1158/1078-0432.ccr-24-4298

2. Tohi, Y., Sahrmann, J. M., Arbet, J., Kato, T., Lee, L. S., Peacock, M., Ginsburg, K., Pavlovich, C., Carroll, P., Bangma, C. H., Sugimoto, M., & Boutros, P. C. (2025). De-escalation of monitoring in active surveillance for prostate cancer: Results from the GAP3 consortium. European Urology Oncology, 8(2), 347–354. https://doi.org/10.1016/j.euo.2024.07.006

3. Xu, X., Zhu, H., Hugh-White, R., Livingstone, J., Eng, S., Zeltser, N., Wang, Y., Pajdzik, K., Chen, S., Houlahan, K. E., Luo, W., Liu, S., Xu, X., Sheng, M., Guo, W. Y., Arbet, J., Song, Y., Wang, M., Zeng, Y., Wang, S., Zhu, G., Gao, T., Chen, W., Ci, X., Xu, W., Xu, K., Orain, M., Picard, V., Hovington, H., Bergeron, A., … He, H. H. (2025). The landscape of N6-methyladenosine in localized primary prostate cancer. Nature Genetics, 57(4), 934–948. https://doi.org/10.1038/s41588-025-02128-y

4. Weiner, A. B., Agrawal, R., Wang, N. K., Sonni, I., Li, E. V., Arbet, J., Zhang, J. J. H., Proudfoot, J. A., Hong, B. H., Davicioni, E., Kane, N., Valle, L. F., Kishan, A. U., Pra, A. D., Ghadjar, P., Sweeney, C. J., Nickols, N. G., Karnes, R. J., Shen, J., Rettig, M. B., Czernin, J., Ross, A. E., Lee Kiang Chua, M., Schaeffer, E. M., Calais, J., Boutros, P. C., & Reiter, R. E. (2024). Molecular hallmarks of prostate-specific membrane antigen in treatment-naïve prostate cancer. European Urology, 86(6), 579–587. https://doi.org/10.1016/j.eururo.2024.09.005

5. Lippitt, W., Carlson, N. E., Arbet, J., Fingerlin, T. E., Maier, L. A., & Kechris, K. (2024). Limitations of clustering with PCA and correlated noise. Journal of Statistical Computation and Simulation, 94(10), 2291–2319. https://doi.org/10.1080/00949655.2024.2329976

6. Ni, K., Rogowitz, E., Farahmand, A. K., Kaizer, L. K., Arbet, J., Cunningham, C. R., Thomas, E. A., & Saxon, D. R. (2024). Weight loss outcomes in a veterans affairs pharmacotherapy-based weight management clinic. Journal of the Endocrine Society, 8(5). https://doi.org/10.1210/jendso/bvae042

7. Greca, A. L., Grau, L., Arbet, J., Liao, L. M., Sosa, J. A., Haugen, B. R., & Kitahara, C. M. (2023). Anthropometric, dietary, and lifestyle factors and risk of advanced thyroid cancer: The NIH‐AARP diet and health cohort study. Clinical Endocrinology, 99(6), 586–597. https://doi.org/10.1111/cen.14970

8. Gamallat, Y., Choudhry, M., Li, Q., Rokne, J. G., Alhajj, R., Abdelsalam, R., Ghosh, S., Arbet, J., Boutros, P. C., & Bismar, T. A. (2023). Serrate RNA effector molecule (SRRT) is associated with prostate cancer progression and is a predictor of poor prognosis in lethal prostate cancer. Cancers, 15(10), 2867. https://doi.org/10.3390/cancers15102867

9. Chan, T. W., Dodson, J. P., Arbet, J., Boutros, P. C., & Xiao, X. (2022). Single-cell analysis in lung adenocarcinoma implicates RNA editing in cancer innate immunity and patient prognosis. Cancer Research, 83(3), 374–385. https://doi.org/10.1158/0008-5472.can-22-1062

10. Grau, L., Arbet, J., Ostendorf, D. M., Blankenship, J. M., Panter, S. L., Catenacci, V. A., Melanson, E. L., & Creasy, S. A. (2022). Creating an algorithm to identify indices of sleep quantity and quality from a wearable armband in adults. Sleep Science, 15(03), 279–287. https://doi.org/10.5935/1984-0063.20220052

11. Creasy, S. A., Ostendorf, D. M., Blankenship, J. M., Grau, L., Arbet, J., Bessesen, D. H., Melanson, E. L., & Catenacci, V. A. (2022). Effect of sleep on weight loss and adherence to diet and physical activity recommendations during an 18-month behavioral weight loss intervention. International Journal of Obesity, 46(8), 1510–1517. https://doi.org/10.1038/s41366-022-01141-z

12. Lin, N. W., Arbet, J., Mroz, M. M., Liao, S.-Y., Restrepo, C. I., Mayer, A. S., Li, L., Barkes, B. Q., Schrock, S., Hamzeh, N., Fingerlin, T. E., Carlson, N. E., & Maier, L. A. (2022). Clinical phenotyping in sarcoidosis using cluster analysis. Respiratory Research, 23(1). https://doi.org/10.1186/s12931-022-01993-z

13. Okamoto, Y., Devoe, S., Seto, N., Minarchick, V., Wilson, T., Rothfuss, H. M., Mohning, M. P., Arbet, J., Kroehl, M., Visser, A., August, J., Thomas, S. M., Charry, L. L., Fleischer, C., Feser, M. L., Frazer?Abel, A. A., Norris, J. M., Cherrington, BrianD., Janssen, W. J., Kaplan, M. J., Deane, K. D., Holers, V. M., & Demoruelle, M. K. (2021). Association of sputum neutrophil extracellular trap subsets with IgA anti–citrullinated protein antibodies in subjects at risk for rheumatoid arthritis. Arthritis &Amp; Rheumatology, 74(1), 38–48. https://doi.org/10.1002/art.41948

14. Wood, C., Arbet, J., Amura, C. R., Nodine, P., Collins, M. R., Orlando, B. S., Mayer, D. C., Stein, D., & Anderson, J. (2021). Multicenter study evaluating nitrous oxide use for labor analgesia at high- and low-altitude institutions. Anesthesia &Amp; Analgesia, 134(2), 294–302. https://doi.org/10.1213/ane.0000000000005712

15. Nodine, P. M., Arbet, J., Jenkins, P. A., Rosenthal, L., Carrington, S., Purcell, S. K., Lee, S., & Hoon, S. (2021). Graduate nursing student stressors during the COVID-19 pandemic. Journal of Professional Nursing, 37(4), 721–728. https://doi.org/10.1016/j.profnurs.2021.04.008

16. Arbet, J., Zhuang, Y., Litkowski, E., Saba, L., & Kechris, K. (2021). Comparing statistical tests for differential network analysis of gene modules. Frontiers in Genetics, 12. https://doi.org/10.3389/fgene.2021.630215

17. Ostendorf, D. M., Blankenship, J. M., Grau, L., Arbet, J., Mitchell, N. S., Creasy, S. A., Caldwell, A. E., Melanson, E. L., Phelan, S., Bessesen, D. H., & Catenacci, V. A. (2021). Predictors of long‐term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis. Obesity Science &Amp; Practice, 7(5), 569–582. https://doi.org/10.1002/osp4.530

18. Reed, S. M., Arbet, J., & Staubli, L. (2021). Clinical nurse specialists in the united states registered with a national provider identifier. Clinical Nurse Specialist, 35(3), 119–128. https://doi.org/10.1097/nur.0000000000000592

19. Rosenthal, L., Lee, S., Jenkins, P., Arbet, J., Carrington, S., Hoon, S., Purcell, S. K., & Nodine, P. (2021). A survey of mental health in graduate nursing students during the COVID-19 pandemic. Nurse Educator, 46(4), 215–220. https://doi.org/10.1097/nne.0000000000001013

20. Carpenter, C. M., Frank, D. N., Williamson, K., Arbet, J., Wagner, B. D., Kechris, K., & Kroehl, M. E. (2021). tidyMicro: A pipeline for microbiome data analysis and visualization using the tidyverse in r. BMC Bioinformatics, 22(1). https://doi.org/10.1186/s12859-021-03967-2

21. Ramakrishnan, V. R., Arbet, J., Mace, J. C., Suresh, K., Shintani Smith, S., Soler, Z. M., & Smith, T. L. (2021). Predicting olfactory loss in chronic rhinosinusitis using machine learning. Chemical Senses, 46. https://doi.org/10.1093/chemse/bjab042

22. Thomas, E. A., Zaman, A., Cornier, M.-A., Catenacci, V. A., Tussey, E. J., Grau, L., Arbet, J., Broussard, J. L., & Rynders, C. A. (2020). Later meal and sleep timing predicts higher percent body fat. Nutrients, 13(1), 73. https://doi.org/10.3390/nu13010073

23. Schmanski, A., Roberts, E., Coors, M., Wicks, S. J., Arbet, J., Weber, R., Crooks, K., Barnes, K. C., & Taylor, M. R. G. (2020). Research participant understanding and engagement in an institutional, self‐consent biobank model. Journal of Genetic Counseling, 30(1), 257–267. https://doi.org/10.1002/jgc4.1316

24. Arbet, J., Brokamp, C., Meinzen-Derr, J., Trinkley, K. E., & Spratt, H. M. (2020). Lessons and tips for designing a machine learning study using EHR data. Journal of Clinical and Translational Science, 5(1). https://doi.org/10.1017/cts.2020.513

25. Arbet, J., McGue, M., & Basu, S. (2020). A robust and unified framework for estimating heritability in twin studies using generalized estimating equations. Statistics in Medicine, 39(27), 3897–3913. https://doi.org/10.1002/sim.8564

26. Coleman-Minahan, K., Sheeder, J., Arbet, J., & McLemore, M. R. (2020). Interest in medication and aspiration abortion training among colorado nurse practitioners, nurse midwives, and physician assistants. Women’s Health Issues, 30(3), 167–175. https://doi.org/10.1016/j.whi.2020.02.001

27. Gance-Cleveland, B., Linton, A., Arbet, J., Stiller, D., & Sylvain, G. (2020). Predictors of overweight and obesity in childhood cancer survivors. Journal of Pediatric Oncology Nursing, 37(3), 154–162. https://doi.org/10.1177/1043454219897102

28. James-Allan, L. B., Arbet, J., Teal, S. B., Powell, T. L., & Jansson, T. (2019). Insulin stimulates GLUT4 trafficking to the syncytiotrophoblast basal plasma membrane in the human placenta. The Journal of Clinical Endocrinology &Amp; Metabolism, 104(9), 4225–4238. https://doi.org/10.1210/jc.2018-02778

29. Grinde, K. E., Arbet, J., Green, A., O’Connell, M., Valcarcel, A., Westra, J., & Tintle, N. (2017). Illustrating, quantifying, and correcting for bias in post-hoc analysis of gene-based rare variant tests of association. Frontiers in Genetics, 8. https://doi.org/10.3389/fgene.2017.00117

30. Arbet, J., McGue, M., Chatterjee, S., & Basu, S. (2017). Resampling-based tests for lasso in genome-wide association studies. BMC Genetics, 18(1). https://doi.org/10.1186/s12863-017-0533-3

31. Greco, B., Hainline, A., Arbet, J., Grinde, K., Benitez, A., & Tintle, N. (2015). A general approach for combining diverse rare variant association tests provides improved robustness across a wider range of genetic architectures. European Journal of Human Genetics, 24(5), 767–773. https://doi.org/10.1038/ejhg.2015.194