Leukocyte telomere length is associated with disability progression in multiple sclerosis - PowerPoint Presentation

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Leukocyte telomere length is associated with disability progression in multiple sclerosis independent of chronological age

Kristen Krysko, MDNeuroimmunology Clinical Research FellowUniversity of California, San FranciscoKristen 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

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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. 

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Background: Aging and MS progression

Factors leading to progression in MS are not fully understoodOlder 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 MSDecline in remyelination capacity (Chari et al. 2003; Sim et al 2002)Altered immunologic response with age (

Rawji et al 2016; Shaw et al 2013)

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Background: Telomeres

Telomeres contain proteins and nucleotide repeats at the ends of chromosomes that shorten with each cell divisionTelomere 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)

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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 durationTelomere shortening

DNA Damage Response

Biological Aging:

Decreased repair

Immune changes

MS disability accumulation

Telomerase activity

Genetic factors

Cumulative cell division over lifetime

Environmental stress

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Methods: Design

Cohort study of adults with MS or CIS in the EPIC study at UCSF to evaluate cross-sectional and longitudinal associations516 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 longitudinally23 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

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Methods: Measures

BaselineLeukocyte telomere length (LTL) – T/S ratio

Yearly:

EDSS (primary outcome)

MSFC

MRI brain volumes

Subset of 46 with LTL measured at multiple timepoints

LTL

LTL

LTL

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Methods: Statistical AnalysesCross-sectional analysis of baseline data for association of LTL with EDSS and secondary outcomes (n=516)

Linear regression modelsAnalysis of 23 matched pairs Mixed models to assess association of change in LTL with change in outcomesLongitudinal analysis of entire cohort using baseline LTL as a predictor (n=516)Mixed models with interaction term between LTL and visit

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Baseline Characteristics (n=516)

 Characteristic Cohort (n=516)Age, mean years (SD)42.6 (9.8)

Female sex, n (%)

354 (68.6)

Disease duration, median years (range)

6 (0-45)

Smoking status, n (%)

Current

Former

Never

 

64 (12.4)

157 (30.5)

295 (57.2)

MS subtype, n (%)

RRMS

CIS

SPMS

PPMS

PRMS

Unclear

 367 (71.1)

80 (15.5)47 (9.1)17 (3.3)4 (0.8)1 (0.2)

Leukocyte telomere length, mean T/S ratio (SD)

0.97 (0.18)

EDSS, median (range)1.5 (0.0-7.0)

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Analyses

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

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Baseline Cross-sectional Analysis (n=516)

 OutcomeaUnadjusted

Adjustedc



b

95% CI

p-value



b

95% CI

p-value

Disability score (EDSS)

0.41

0.27 to 0.56

<0.001

0.27

0.13 to 0.42

<0.001

MSFC z-score

-0.09

-0.16 to -0.03

0.006

-0.05

-0.12 to 0.02

0.13

Total brain volume, mm

3

-22.3

-30.6 to -14.0

<0.001

-7.4

-14.7 to -0.10

0.047

Total WM volume, mm

3

-7.4

-11.5 to -3.3

<0.001

-4.0

-8.0 to -0.04

0.048

Total GM volume, mm

3

-14.7

-20.1 to -9.2

<0.001

-3.4

-7.8 to 1.0

0.13

Cortical GM volume, mm

3

-12.9

-17.5 to -8.3

<0.001

-3.1

-6.8 to 0.61

0.10



linear regression coefficient;

CI confidence interval; EDSS Expanded Disability Status Scale; MSFC multiple sclerosis functional composite; WM white matter; GM grey matter.

a

n=516 for EDSS, n=511 for MSFC and n=515 for all other outcomes.

b

Per

0.2 unit decrease in mean T/S ratio (leukocyte telomere length).

cAdjusted for chronological age, sex, and disease duration.

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Analyses

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

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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=46bPer 0.2 unit decrease in mean T/S ratio (leukocyte telomere length).cAdjusted for baseline chronological age, sex, and disease duration.

 

Outcome

a

Unadjusted

Adjusted

c



b

95% CI

p-value



b

95% CI

p-value

Disability score (EDSS)

0.31

0.05 to 0.57

0.021

0.34

0.08 to 0.61

0.012

MSFC z-score

0.07

-0.03 to 0.17

0.15

0.08

-0.02 to 0.18

0.10

Total brain volume, mm

3

-9.1

-20.6 to 2.4

0.12

-6.2

-17.6 to 5.2

0.29

Total WM volume, mm

3

-3.4

-10.7 to 3.8

0.35

-2.4

-9.7 to 4.9

0.52

Total GM volume, mm

3

-4.4

-11.3 to 2.6

0.22

-2.7

-9.3 to 4.0

0.44

Cortical GM volume, mm

3

-0.55

-6.2 to 5.1

0.85

0.13

-5.4 to 5.7

0.96

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Analyses

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

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Predicted EDSS over time by baseline LTL (n=516)

Baseline difference in EDSS by LTL p=0.001LTL by year interaction p=0.09Shaded areas represent 95% CI.

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Summary of findingsIn 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

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Strengths and Limitations

Novel investigation of the ultimate biological clock on disability progressionLarge cohort of well characterized patientsCross-sectional and longitudinal analyses using robust statistical modelsDNA availability limited ability to measure LTL in all individuals over timeLow power to detect associations in the subset of 46 individuals

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Conclusions

Our marker of biological aging was associated with MS disabilityAging-related processes may contribute to MS progressionOxidative stress, decline in remyelination capacity, altered immune functionCo-morbidities and lifestyle factors may contributeTargeting aging-related processes may be a therapeutic strategy

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Acknowledgements

Funded by National Multiple Sclerosis Society (NMSS RG-1607-25103 PI J Graves. Fellowship funded by the NMSS (FP-1605-08753 (Krysko)).UCSD/UCSFJennifer S Graves

Blackburn LabElizabeth BlackburnJue

Lin

Dana Smith

UCSF Neurology

Jorge

Oksenberg

Stephen L Hauser

Roland G Henry

Bruce Cree

Stacy

Caillier

Adam

Santaniello

Chao Zhao

Refujia

Gomez

Carolyn BevanWilliam Stern

Gina Kirkish

UCSF EPIC TeamUCSF Thesis Committee

Emmanuelle WaubantAnn Lazar

Charles McCullochKristine Yaffe

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Thank you

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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. Mult Scler Houndmills 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.

Mult Scler Houndmills 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 Neuropathol

Exp 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 Soc Neurosci. 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.

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Extra slides

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Leukocyte Telomere Length (LTL)

Biological AgeMS disability

Chronological Age

Sex

Disease duration

Evaluated as potential confounders: Smoking,

HLA-DRB1*15:01

status

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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.

 

Outcome

a

Unadjusted

Adjusted

c

 

 

Interaction

 

 

Interaction



b

95% CI

p-value

Visit by LTL p-value



b

95% CI

p-value

Visit by LTL p-value

Disability score (EDSS)

0.41

0.27 to 0.56

<0.001

0.09

0.25

0.11 to 0.39

0.001

0.09

MSFC z-score

-0.09

-0.16 to -0.02

0.008

0.44

-0.05

-0.12 to 0.02

0.15

0.42

Total brain volume, mm

3

-22.5

-31.1 to -14.0

<0.001

0.58

-10.5

-18.0 to -3.0

0.006

0.60

Total WM volume, mm

3

-7.5

-11.8 to -3.2

0.001

0.71

-4.3

-8.4 to -0.14

0.043

0.71

Total GM volume, mm

3

-14.8

-20.3 to -9.2

<0.001

0.19

-6.4

-11.0 to -1.9

0.006

0.21

Cortical GM volume, mm

3

-12.9

-17.7 to -8.2

<0.001

0.02

-5.9

-9.8 to -2.1

0.003

0.02

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Predicted MRI brain volume over time by baseline LTL (n=516)

Baseline difference in brain volume by LTL p=0.006LTL by year interaction p=0.60