1 / 25

Kristen Krysko , MD Neuroimmunology Clinical Research Fellow

Leukocyte telomere length is associated with disability progression in multiple sclerosis independent of chronological age. Kristen Krysko , MD Neuroimmunology Clinical Research Fellow University of California, San Francisco

tamas
Télécharger la présentation

Kristen Krysko , MD Neuroimmunology Clinical Research Fellow

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Leukocyte telomere length is associated with disability progression in multiple sclerosis independent of chronological age Kristen Krysko, MD Neuroimmunology Clinical Research Fellow University of California, San Francisco Kristen M. Krysko, Roland G. Henry, Bruce Cree, Jue Lin, UCSF MS-EPIC Team, Stacy Caillier, Adam Santaniello, Chao Zhao, Refujia Gomez, Carolyn Bevan, Dana Smith, William Stern, Gina Kirkish, Stephen L. Hauser, Jorge R. Oksenberg, Jennifer S. Graves

  2. Disclosures This study was funded by the National Multiple Sclerosis Society (NMSS RG-1607-25103 PI J Graves). I am supported by a Sylvia Lawry award from the National Multiple Sclerosis Society and a Biogen MS fellowship grant. Dr. Graves has received recent grant and clinical trial support from the National MS Society, Race to Erase MS, UCSF CTSI RAP program, Biogen, and Genentech. She has received honoraria from Biogen, Novartis and Genzyme for education events. 

  3. Background: Aging and MS progression • Factors leading to progression in MS are not fully understood • Older chronological age associated with faster time to disability milestones(Confavreux & Vukusic 2006; Freilich et al. 2017; Tutuncu et al. 2013; Scalfari et al. 2011) • Biological aging may contribute to neurodegeneration in MS • Decline in remyelination capacity(Chari et al. 2003; Sim et al 2002) • Altered immunologic response with age (Rawji et al 2016; Shaw et al 2013)

  4. Background: Telomeres • Telomeres contain proteins and nucleotide repeats at the ends of chromosomes that shorten with each cell division • Telomere shortening accelerated by oxidative stress and DNA damage (Blackburn, Epel, Lin 2015) • Shortened telomeres seen in: • Cardiovascular disease (Haycock et al 2014) • Dementia (Forero et al 2016) • Autoimmune disease (lupus, rheumatoid arthritis) (Georgin-Lavialle et al 2010) • Primary progressive multiple sclerosis (Guan J-Z et al 2015)

  5. Objective • To assess whether biological aging as measured by leukocyte telomere length (LTL) is associated with clinical disability and brain volume in MS independent of chronological age and disease duration Cumulative cell division over lifetime Telomerase activity Biological Aging: Decreased repair Immune changes DNA Damage Response MS disability accumulation Telomere shortening Environmental stress Genetic factors

  6. Methods: Design • Cohort study of adults with MS or CIS in the EPIC study at UCSF to evaluate cross-sectional and longitudinal associations • 516 of 517 in the original cohort were included (DNA available at baseline) • Nested case-control study to evaluate association of change in LTL with disability and MRI metrics longitudinally • 23 converting to SPMS during follow-up with DNA available • Matched 1:1 on baseline age, sex, disease duration, EDSS to those who remained with relapsing MS

  7. Methods: Measures Leukocyte telomere length (LTL) – T/S ratio • Yearly: • EDSS (primary outcome) • MSFC • MRI brain volumes Baseline Subset of 46 with LTL measured at multiple timepoints LTL LTL LTL

  8. Methods: Statistical Analyses • Cross-sectional analysis of baseline data for association of LTL with EDSS and secondary outcomes (n=516) • Linear regression models • Analysis of 23 matched pairs • Mixed models to assess association of change in LTL with change in outcomes • Longitudinal analysis of entire cohort using baseline LTL as a predictor (n=516) • Mixed models with interaction term between LTL and visit

  9. Baseline Characteristics (n=516)

  10. Analyses • Cross-sectional analysis of baseline data for association of LTL with EDSS and secondary outcomes (n=516) • Linear regression models • Analysis of 23 matched pairs • Mixed models to assess association of change in LTL with change in outcomes • Longitudinal analysis of entire cohort using baseline LTL as a predictor (n=516) • Mixed models with interaction term between LTL and visit

  11. Baseline Cross-sectional Analysis (n=516)  linear regression coefficient;CI confidence interval; EDSS Expanded Disability Status Scale; MSFC multiple sclerosis functional composite; WM white matter; GM grey matter. an=516 for EDSS, n=511 for MSFC and n=515 for all other outcomes. bPer 0.2 unit decrease in mean T/S ratio (leukocyte telomere length). cAdjusted for chronological age, sex, and disease duration.

  12. Analyses • Cross-sectional analysis of baseline data for association of LTL with EDSS and secondary outcomes (n=516) • Linear regression models • Analysis of 23 matched pairs • Mixed models to assess association of change in LTL with change in outcomes • Longitudinal analysis of entire cohort using baseline LTL as a predictor (n=516) • Mixed models with interaction term between LTL and visit

  13. Longitudinal Analysis of subset of 23 pairs with LTL measured over time (n=46)  linear regression coefficient;CI confidence interval; EDSS Expanded Disability Status Scale; MSFC multiple sclerosis functional composite; WM white matter; GM grey matter. an=46 bPer 0.2 unit decrease in mean T/S ratio (leukocyte telomere length). cAdjusted for baseline chronological age, sex, and disease duration.

  14. Analyses • Cross-sectional analysis of baseline data for association of LTL with EDSS and secondary outcomes (n=516) • Linear regression models • Analysis of 23 matched pairs • Mixed models to assess association of change in LTL with change in outcomes • Longitudinal analysis of entire cohort using baseline LTL as a predictor (n=516) • Mixed models with interaction term between LTL and visit

  15. Predicted EDSS over time by baseline LTL (n=516) Baseline difference in EDSS by LTL p=0.001 LTL by year interaction p=0.09 Shaded areas represent 95% CI.

  16. Summary of findings • In cross-sectional study of >500 MS patients, LTL is associated with EDSS and total brain volume • Longitudinal changes in LTL are associated with changes in EDSS over time

  17. Strengths and Limitations • Novel investigation of the ultimate biological clock on disability progression • Large cohort of well characterized patients • Cross-sectional and longitudinal analyses using robust statistical models • DNA availability limited ability to measure LTL in all individuals over time • Low power to detect associations in the subset of 46 individuals

  18. Conclusions • Our marker of biological aging was associated with MS disability • Aging-related processes may contribute to MS progression • Oxidative stress, decline in remyelination capacity, altered immune function • Co-morbidities and lifestyle factors may contribute • Targeting aging-related processes may be a therapeutic strategy

  19. Acknowledgements UCSD/UCSF Jennifer S Graves Blackburn Lab Elizabeth Blackburn Jue Lin Dana Smith UCSF Neurology Jorge Oksenberg Stephen L Hauser Roland G Henry Bruce Cree Stacy Caillier Adam Santaniello Chao Zhao Refujia Gomez Carolyn Bevan William Stern Gina Kirkish UCSF EPIC Team UCSF Thesis Committee Emmanuelle Waubant Ann Lazar Charles McCulloch Kristine Yaffe Funded by National Multiple Sclerosis Society (NMSS RG-1607-25103 PI J Graves. Fellowship funded by the NMSS (FP-1605-08753 (Krysko)).

  20. Thank you

  21. References Confavreux C, Vukusic S. Age at disability milestones in multiple sclerosis. Brain J Neurol. 2006;129(Pt 3):595-605. Freilich J, Manouchehrinia A, Trusheim M, et al. Characterization of annual disease progression of multiple sclerosis patients: A population-based study. MultSclerHoundmills Basingstoke Engl. May 2017:1352458517706252. Tutuncu M, Tang J, Zeid NA, et al. Onset of progressive phase is an age-dependent clinical milestone in multiple sclerosis. MultSclerHoundmills Basingstoke Engl. 2013;19(2):188-198. Scalfari A, Neuhaus A, Daumer M, Ebers GC, Muraro PA. Age and disability accumulation in multiple sclerosis. Neurology. 2011;77(13):1246-1252. Chari DM, Crang AJ, Blakemore WF. Decline in rate of colonization of oligodendrocyte progenitor cell (OPC)-depleted tissue by adult OPCs with age. J NeuropatholExp Neurol. 2003;62(9):908-916. Sim FJ, Zhao C, Penderis J, Franklin RJM. The age-related decrease in CNS remyelination efficiency is attributable to an impairment of both oligodendrocyte progenitor recruitment and differentiation. J Neurosci Off J SocNeurosci. 2002;22(7):2451-2459. Rawji KS, Mishra MK, Michaels NJ, Rivest S, Stys PK, Yong VW. Immunosenescence of microglia and macrophages: impact on the ageing central nervous system. Brain. 2016;139(3):653-661. Shaw AC, Goldstein DR, Montgomery RR. Age-dependent dysregulation of innate immunity. Nat Rev Immunol. 2013;13(12):875-887. Blackburn EH, Epel ES, Lin J. Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection. Science. 2015;350(6265):1193-1198. Haycock PC, Heydon EE, Kaptoge S, Butterworth AS, Thompson A, Willeit P. Leucocyte telomere length and risk of cardiovascular disease: systematic review and meta-analysis. BMJ. 2014;349:g4227. Forero DA, González-Giraldo Y, López-Quintero C, Castro-Vega LJ, Barreto GE, Perry G. Meta-analysis of Telomere Length in Alzheimer’s Disease. J Gerontol A Biol Sci Med Sci. 2016;71(8):1069-1073. Georgin-Lavialle S, Aouba A, Mouthon L, et al. The telomere/telomerase system in autoimmune and systemic immune-mediated diseases. Autoimmun Rev. 2010;9(10):646-651. Guan J-Z, Guan W-P, Maeda T, Guoqing X, GuangZhi W, Makino N. Patients with multiple sclerosis show increased oxidative stress markers and somatic telomere length shortening. Mol Cell Biochem. 2015;400(1-2):183-187.

  22. Extra slides

  23. Disease duration Chronological Age Sex Leukocyte Telomere Length (LTL) Biological Age MS disability Evaluated as potential confounders: Smoking, HLA-DRB1*15:01 status

  24. Longitudinal Analysis of entire cohort using baseline LTL as a predictor (n=516)  linear regression coefficient at visit 1;CI confidence interval; EDSS Expanded Disability Status Scale; MSFC multiple sclerosis functional composite; WM white matter; GM grey matter. an=516 for EDSS and brain volume metrics, n=514 for MSFC. bPer 0.2 unit decrease in mean T/S ratio (leukocyte telomere length). cAdjusted for baseline chronological age, sex, and disease duration.

  25. Predicted MRI brain volume over time by baseline LTL (n=516) Baseline difference in brain volume by LTL p=0.006 LTL by year interaction p=0.60

More Related