Proteomic Age Acceleration in Multiple Sclerosis Precedes Symptom Onset and Associates with Severity
Siavoshi, F.; Candia, J.; Ladakis, D. C.; Dewey, B. E.; Filippatou, A.; Smith, M. D.; Sotirchos, E. S.; Saidha, S.; Prince, J. L.; Abdelhak, A.; Mowry, E. M.; Calabresi, P. A.; Walker, K. A.; Fitzgerald, K. C.; Bhargava, P.
Show abstract
Biological aging is accelerated in people with multiple sclerosis, but whether such acceleration occurs during the pre-symptomatic phase or varies by organ system is understudied. We analyzed two independent proteomics datasets profiled using distinct platforms: the Johns Hopkins cohort profiled using the SomaScan platform (348 multiple sclerosis/49 age-matched controls) and the Department of Defense cohort profiled using the Olink platform (134 multiple sclerosis/79 age-matched controls), including 117 pre-symptomatic samples from people with multiple sclerosis (median lead time: 4.0 years), to estimate systemic and organ-specific proteomic age gaps using established clocks in pre-symptomatic and symptomatic phases, and assess their associations with severity. In the Johns Hopkins cohort, people with multiple sclerosis demonstrated acceleration of systemic ({beta}=2.2, 95% CI 1.2-3.2, P<0.001, FDR<0.001), brain ({beta}=1.7, 95% CI 0.6-2.7, P=0.003, FDR=0.01), muscle ({beta}=2.5, 95% CI 1.3-3.7, P<0.001, FDR<0.001), and immune age ({beta}=1.8, 95% CI 0.6-2.9, P=0.003, FDR=0.01), with findings reproduced in the Department of Defense cohort for systemic ({beta}=0.7, 95% CI 0.0-1.4, P=0.04, FDR=0.34) and brain age (3.2 years, 95% CI 2.1-4.3, P<0.001, FDR<0.001). Proteomic age acceleration was evident prior to symptom onset [systemic: ({beta}=1.0, 95% CI 0.4-1.7, P=0.002, FDR=0.02); brain: ({beta}=2.4, 95% CI 1.2-3.7, P<0.001, FDR=0.002)], whereas no immune age acceleration was detected before or after onset. Higher systemic age gap was associated with greater global Age-Related Multiple Sclerosis Severity Score ({beta}=0.14, 95% CI 0.05-0.24, P=0.005, FDR=0.03) and slower walking speed ({beta}=0.02, 95% CI 0.01-0.03, P=0.006, FDR=0.04), while higher muscle age gap was associated with greater global Age-Related Multiple Sclerosis Severity Score ({beta}=0.17, 95% CI 0.10-0.24, P<0.001, FDR<0.001), poorer manual dexterity ({beta}=0.28, 95% CI 0.04-0.52, P=0.03, FDR=0.30), slower walking speed ({beta}=0.02, 95% CI 0.01-0.03, P=0.002, FDR=0.02), lower peripapillary retinal nerve fiber layer ({beta}= -0.26, 95% CI -0.41 to -0.10, P=0.001, FDR=0.02) and ganglion cell-inner plexiform layer thicknesses ({beta}= -0.35; 95% CI -0.65 to -0.05; P=0.02, FDR=0.30). Higher brain age gap was associated with several imaging measures, including lower whole-brain ({beta}= -0.002, 95% CI -0.003 to -0.001, P=0.002, FDR=0.02), and lower peripapillary retinal nerve fiber layer thickness ({beta}= -0.21, 95% CI -0.39 to -0.03, P=0.02, FDR=0.10). Proteomic age acceleration in multiple sclerosis is detectable years before symptom onset and distinct organ-specific aging signatures are associated with disease severity. Proteomic aging may provide a biologically informative marker of early disease processes and a clinically relevant readout of disease heterogeneity.
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