Socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis

Vasileiou, Eleni S; Filippatou, Angeliki; Maldonado, Daniela Pimentel; Kalaitzidis, Grigorios; Ehrhardt, Henrik; Lambe, Jeffrey; Saidha, Shiv; Sotirchos, Elias S.; Mowry, Ellen M.; Calabresi, Peter A.; Fitzgerald, Kathryn C.

doi:10.1093/brain/awab342

Cited by 23 publications

(17 citation statements)

References 44 publications

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“…Most previous studies on SES in the context of MS have focused on susceptibility rather than severity, and results have been conflicting . A few studies looking at severity have demonstrated correlation to postcode-based socioeconomic indices, similar to our findings. Only 1 of these studies accounted for DMT exposure, and all measured SES at or after diagnosis.…”

Section: Discussionmentioning

confidence: 99%

Premorbid Sociodemographic Status and Multiple Sclerosis Outcomes in a Universal Health Care Context

He,

Manouchehrinia,

Glaser

et al. 2023

JAMA Netw Open

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ImportanceMultiple sclerosis (MS) severity may be informed by premorbid sociodemographic factors.ObjectiveTo determine whether premorbid education, income, and marital status are associated with future MS disability and symptom severity, independent of treatment, in a universal health care context.Design, Setting, and ParticipantsThis nationwide observational cohort study examined data from the Swedish MS Registry linked to national population registries from 2000 to 2020. Participants included people with MS onset from 2005 to 2015 and of working age (aged 23 to 59 years) 1 year and 5 years preceding disease onset.ExposuresIncome quartile, educational attainment, and marital status measured at 1 and 5 years preceding disease onset.Main Outcome and MeasuresRepeated measures of Expanded Disability Status Scale (EDSS) scores and patient-reported Multiple Sclerosis Impact Scale (MSIS-29) scores. Models were adjusted for age, sex, relapses, disease duration, and treatment exposure. Secondary analyses further adjusted for comorbidity. All analyses were stratified by disease course (relapse onset and progressive onset).ResultsThere were 4557 patients (mean [SD] age, 37.5 [9.3] years; 3136 [68.8%] female, 4195 [92.1%] relapse-onset MS) with sociodemographic data from 1-year preonset of MS. In relapse-onset MS, higher premorbid income and education correlated with lower disability (EDSS, −0.16 [95% CI, −0.12 to −0.20] points) per income quartile; EDSS, −0.47 [95% CI, −0.59 to −0.35] points if tertiary educated), physical symptoms (MSIS-29 physical subscore, −14% [95% CI, −11% to −18%] per income quartile; MSIS-29 physical subscore, −43% [95% CI, −35% to −50%] if tertiary educated), and psychological symptoms (MSIS-29 psychological subscore, −12% [95% CI, −9% to −16%] per income quartile; MSIS-29 psychological subscore, −25% [95% CI, −17% to −33%] if tertiary educated). Marital separation was associated with adverse outcomes (EDSS, 0.34 [95% CI, 0.18 to 0.51]; MSIS-29 physical subscore, 35% [95% CI, 12% to 62%]; MSIS-29 psychological subscore, 25% [95% CI, 8% to 46%]). In progressive-onset MS, higher income correlated with lower EDSS (−0.30 [95% CI, −0.48 to −0.11] points per income quartile) whereas education correlated with lower physical (−34% [95% CI, −53% to −7%]) and psychological symptoms (−33% [95% CI, −54% to −1%]). Estimates for 5-years preonset were comparable with 1-year preonset, as were the comorbidity-adjusted findings.Conclusions and relevanceIn this cohort study of working-age adults with MS, premorbid income, education, and marital status correlated with disability and symptom severity in relapse-onset and progressive-onset MS, independent of treatment. These findings suggest that socioeconomic status may reflect both structural and individual determinants of health in MS.

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Section: Discussionmentioning

confidence: 99%

Premorbid Sociodemographic Status and Multiple Sclerosis Outcomes in a Universal Health Care Context

He,

Manouchehrinia,

Glaser

et al. 2023

JAMA Netw Open

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“…The GCIPL is a better biomarker of atrophy than peripapillary nerve fiber layer thickness because its loss can be detected much earlier. 17,31 Both the reviewers of MRI and OCTs were blinded to the clinical data.…”

Section: Methodsmentioning

confidence: 99%

“…15 This observation may be unique to particular parts of the CNS and does not necessarily apply to all CNS structures. Optical coherence tomography (OCT) imaging is a tool used to longitudinally quantify retinal neurodegeneration in MS, [16][17][18] and its measures have been shown to correlate with disability, 19,20 brain neurodegeneration, 21 and cortical lesions. 22 The brain cortex and retina have different cytoarchitectures, with a greater proportion of tissue volume in the retina coming from neurons/axons and greater heterogeneity of neuronal subtypes as well as the presence of oligodendrocytes in the cortex (Figure 2).…”

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confidence: 99%

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Differences in Age-related Retinal and Cortical Atrophy Rates in Multiple Sclerosis

et al. 2022

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Background and Objectives:The timing of neurodegeneration in MS remains unclear. It is critical to understand the dynamics of neuroaxonal loss if we hope to prevent or forestall permanent disability in MS. We therefore used a deeply phenotyped longitudinal cohort to assess and compare rates of neurodegeneration in retina and brain throughout the MS disease course.Methods:We analyzed 597 MS patients who underwent longitudinal OCT imaging annually for 4.5±2.4 years and 432 patients who underwent longitudinal MRI scans for 10±3.4 yrs, quantifying macular ganglion-cell–inner plexiform layer (GCIPL) volume and cortical gray matter (CGM) volume. To evaluate the rate of loss, linear mixed-effects modeling with subject-specific intercepts and slopes were fitted using restricted maximum likelihood estimation. The association between the slope of decline in the anatomical structure and the age of entry in the cohort (categorized by the MRI cohort’s age quartiles) was assessed by linear regression models.Results:The rate of CGM volume loss declined with increasing age of study entry (1.3%/year atrophy for the age of entry in the cohort <35 years; 1.1% for age >35 years and <41; 0.97% for age >41 years and <49; 0.9% for age >49 years) while the rate of GCIPL thinning was highest in patients in the youngest quartile, fell by more than 50% in the following age quartile, and then stabilized (0.7%/year thinning for the age of entry in the cohort <35 years; 0.29% for age >35 years and <41; 0.34% for age >41 years and <49; 0.33% for age >49 years).Conclusions:An age-dependent reduction in retinal and cortical volume loss rates during RRMS suggests deceleration in neurodegeneration in the earlier period of disease and further indicates that the period of greatest adaptive-immune-mediated inflammatory activity is also the period with the greatest neuroaxonal loss.

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“…Available data regarding the effect of socioeconomic status on MS disability outcomes indicate a relationship between greater deprivation at disease onset and greater disability even in countries with a universal health-care system, including a higher risk of reaching EDSS scores of 4.0 and 6.0 in Cox proportional hazards models 46,48 , faster retinal neurodegeneration 49 and onset of secondary progression 46 . Evidence also indicates that higher socioeconomic status in people with MS is associated with a lower burden of psychiatric symptoms and a higher likelihood of symptom recovery following mental health treatment 50,51 .…”

Section: Race and Ethnicitymentioning

confidence: 99%

Social determinants of health in multiple sclerosis

et al. 2022

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Social determinants of health are the conditions in which people are born, grow, live, work and age. These circumstances are the nonmedical factors that influence health outcomes. Evidence indicates that health behaviours, comorbidities and disease-modifying therapies all contribute to multiple sclerosis (MS) outcomes; however, our knowledge of the effects of social determinants -that is, the 'risks of risks' -on health has not yet changed our approach to MS. Assessing and addressing social determinants of health could fundamentally improve health and health care in MS; this approach has already been successful in improving outcomes in other chronic diseases. In this narrative Review, we identify and discuss the body of evidence supporting an effect of many social determinants of health, including racial background, employment and social support, on MS outcomes. It must be noted that many of the published studies were subject to bias, and screening tools and/or practical interventions that address these social determinants are, for the most part, lacking. The existing work does not fully explore the potential bidirectional and complex relationships between social determinants of health and MS, and the interpretation of findings is complicated by the interactions and intersections among many of the identified determinants. On the basis of the reviewed literature, we consider that, if effective interventions targeting social determinants of health were available, they could have substantial effects on MS outcomes. Therefore, funding for and focused design of studies to evaluate and address social determinants of health are urgently needed. Sections Key points• Addressing an individual's social determinants of health -that is, the conditions under which they are born, grow, live, work and age -could provide opportunities to reduce the burden of living with multiple sclerosis (MS).• Individual factors that may influence MS-related outcomes include sex, gender and sexuality, race and ethnicity, education and employment, socioeconomic status, and domestic abuse.• Societal infrastructures, including access to food, health care and social support, can also affect MS-related outcomes.• Awareness of the specific circumstances of a patient with MS might help neurologists deliver better care.• Social determinants of health are not static and can change according to wider sociopolitical contexts, as highlighted by the COVID-19 pandemic.• Rigorous studies of interventions to ameliorate the effects of poor social determinants on people with MS are urgently needed.Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author selfarchiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Review criteriaTo ensure an inclusive overview, we searched PubMed, Scopus, CINAHL through EBSCOhost, MEDLINE through OVID, all other Web of ...

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Socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis

Cited by 23 publications

References 44 publications

Premorbid Sociodemographic Status and Multiple Sclerosis Outcomes in a Universal Health Care Context

Premorbid Sociodemographic Status and Multiple Sclerosis Outcomes in a Universal Health Care Context

Differences in Age-related Retinal and Cortical Atrophy Rates in Multiple Sclerosis

Social determinants of health in multiple sclerosis

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