Associations of Alcohol Consumption and Smoking With Disease Risk and Neurodegeneration in Individuals With Multiple Sclerosis in the United Kingdom

Abstract

IMPORTANCEUnderstanding the effects of modifiable risk factors on risk for multiple sclerosis (MS) and associated neurodegeneration is important to guide clinical counseling. OBJECTIVE To investigate associations of alcohol use, smoking, and obesity with odds of MS diagnosis and macular ganglion cell layer and inner plexiform layer (mGCIPL) thickness. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study analyzed data from the community-based UK Biobank study on health behaviors and retinal thickness (measured by optical coherence tomography in both eyes) in individuals aged 40 to 69 years examined from December 1, 2009, to December 31, 2010. Risk factors were identified with multivariable logistic regression analyses. To adjust for intereye correlations, multivariable generalized estimating equations were used to explore associations of alcohol use and smoking with mGCIPL thickness. Finally, interaction models explored whether the correlations of alcohol and smoking with mGCIPL thickness differed for individuals with MS. Data were analyzed from February 1 to July 1, 2021. EXPOSURES Smoking status (never, previous, or current), alcohol intake (never or special occasions only [low], once per month to Յ4 times per week [moderate], or daily/almost daily [high]), and body mass index. MAIN OUTCOMES AND MEASURES Multiple sclerosis case status and mGCIPL thickness. RESULTS A total of 71 981 individuals (38 685 women [53.7%] and 33 296 men [46.3%]; mean [SD] age, 56.7 [8.0] years) were included in the analysis (20 065 healthy control individuals, 51 737 control individuals with comorbidities, and 179 individuals with MS). Modifiable risk factors significantly associated with MS case status were current smoking (odds ratio [OR], 3.05 [95% CI, 1.95-4.64]), moderate alcohol intake (OR, 0.62 [95% CI, 0.43-0.91]), and obesity (OR, 1.72 [95% CI, 1.15-2.56])compared with healthy control individuals. Compared with the control individuals with comorbidities, only smoking was associated with case status (OR, 2.30 [95% CI,). High alcohol intake was associated with a thinner mGCIPL in individuals with MS (adjusted β = −3.09 [95% CI, −5.70 to −0.48] μm; P = .02). In the alcohol interaction model, high alcohol intake was associated with thinner mGCIPL in control individuals (β = −0.93 [95% CI, −1.07 to −0.79] μm; P < .001), but there was no statistically significant association in individuals with MS (β = −2.27 [95% CI, −4.76 to 0.22] μm; P = .07). Smoking was not associated with mGCIPL thickness in MS. However, smoking was associated with greater mGCIPL thickness in control individuals (β = 0.89 [95% CI, 0.74-1.05 μm]; P < .001).

Blocking of P2X7r Reduces Mitochondrial Stress Induced by Alcohol and Electronic Cigarette Exposure in Brain Microvascular Endothelial Cells

“…It is known that exposure to alcohol and cigarettes (tobacco smoke) results in tissue injury associated with oxidative stress [ 35 ]. It has been suggested that e-Cig could also produce similar effects [ 4 ].…”

Applying a genetic risk score model to enhance prediction of future Multiple Sclerosis diagnosis at first presentation with optic neuritis: a cohort study in the UK Biobank

“…15 Continuous variables included MS-GRS (standardised for 545 individuals with undifferentiated ON), and Body Mass Index (kg/m 2 , UK Biobank Data-Field 21001). 15,[17][18][19] Categorical variables included smoking status (ever vs never vs missing, Data-Field 20160), [21][22][23] country of birth (England, Scotland, Northern Ireland, Republic of Ireland, Wales and Other/Unknown, Data-Field 1647), Townsend deprivation index quintiles (1 to 5 or missing, Data-Field 189), 37 and serum 25-OH vitamin D level at UKBB baseline assessment (su cient [>50nmol/L],…”

“…46 We did not nd signi cant association with additional clinical risk factors including BMI, smoking status, or vitamin D insu ciency at UKBB study entry, which have been highlighted in other studies. [15][16][17][18][19][21][22][23] It is possible that this is because our study only measures these variables at a single time point (UK biobank study entry) unrelated to diagnosis of ON and/or MS . Additionally, risk factors that are signi cant associated with disease in large observational epidemiology studies, sometimes do not explain enough variation in disease development to be useful for clinical prediction.…”

“…Additional risk factors for MS include female sex, age, latitude of country of residence, low serum 25-hydroxyvitamin, [15][16][17] increased body mass index, 15,[17][18][19] and Epstein-Barr virus seropositivity, 20 with a possible association with smoking still unclear. [21][22][23] Integrating GRS with other known risk factors into a combined model has previously been shown to improve prediction and classi cation in a range of autoimmune diseases. 24,25 To our knowledge, genetic data has not previously been used in combination with other risk factors to aid MS risk strati cation in undifferentiated ON.…”

A systematic review of Mendelian randomization studies on multiple sclerosis

“…The same null causal effect was found for alcohol consumption despite observational studies revealing an involvement of it in MS risk, although with controversial findings. An association between moderate alcohol consumption and a lower odds of having MS was indeed found in some studies (Andersen et al, 2019;Hedström et al, 2014;Kleerekooper et al, 2022;Weiland et al, 2014), but an increased risk has been reported as well (Abdollahpour et al, 2018;Pakpoor et al, 2014). No evidence of association between alcohol consumption and MS risk has instead been found in a recent study (Dreyer-Alster et al, 2022).…”