
==== Front
Neurol Neuroimmunol Neuroinflamm
Neurol Neuroimmunol Neuroinflamm
nnn
NEURIMMINFL
Neurology® Neuroimmunology & Neuroinflammation
2332-7812
Lippincott Williams & Wilkins Hagerstown, MD

39088840
NXI-2023-000759
10.1212/NXI.0000000000200289
3
41
Research Article
Association Between Alcohol Consumption and Disability Accumulation in Multiple Sclerosis
https://orcid.org/0000-0002-6033-3734
Wu Jing PhD
https://orcid.org/0000-0002-2938-1877
Olsson Tomas MD, PhD
https://orcid.org/0000-0002-7386-6732
Hillert Jan A. MD, PhD
https://orcid.org/0000-0003-1688-6697
Alfredsson Lars PhD
https://orcid.org/0000-0002-6612-4749
Hedström Anna Karin MD, PhD
From the Institute of Environmental Medicine (J.W., L.A.); Department of Clinical Neuroscience (T.O., J.A.H., L.A., A.K.H.), Karolinska Institutet; and Centre for Occupational and Environmental Medicine (L.A.), Region Stockholm, Stockholm, Sweden.
Correspondence Dr. Wu jing.wu@ki.se
Go to Neurology.org/NN for full disclosures. Funding information is provided at the end of the article.

The Article Processing Charge was funded by the authors.

Submitted and externally peer reviewed. The handling editor was Associate Editor Friedemann Paul, MD.

9 2024
31 7 2024
31 7 2024
11 5 e20028902 1 2024
06 6 2024
Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.
2024
American Academy of Neurology
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Background and Objectives

Previous studies have indicated that alcohol consumption is associated with multiple sclerosis (MS) disease progression. We aimed to study the influence of alcohol consumption habits on disease progression and health-related quality of life in MS.

Methods

We categorized patients from 2 population-based case-control studies by alcohol consumption habits at diagnosis and followed them up to 15 years after diagnosis through the Swedish MS registry regarding changes in the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Impact Scale 29 (MSIS-29). We used Cox regression models with 95% confidence intervals (CIs) using 24-week confirmed disability worsening, EDSS 3, EDSS 4, and physical and psychological worsening from the patient's perspective as end points.

Results

Our study comprised 9,051 patients with MS, with a mean age of 37.5 years at baseline/diagnosis. Compared with nondrinking, low and moderate alcohol consumption was associated with reduced risk of EDSS-related unfavorable outcomes (hazard ratios between 0.81 and 0.90) and with reduced risk of physical worsening. The inverse association was confined to relapsing-remitting MS and was more pronounced among women. High alcohol consumption did not significantly affect disease progression. The inverse relationship between low-moderate alcohol consumption and disability progression became stronger when we only included those who had not changed their alcohol consumption during follow-up (hazard ratios between 0.63 and 0.71). There were no differences in measures of disability at baseline between drinkers who continued drinking alcohol after diagnosis and those who later discontinued. Our findings speak against bias due to reverse causation.

Discussion

Low and moderate alcohol consumption was associated with more favorable outcomes in relapsing-remitting MS, compared with nondrinking, while there was no significant influence of high alcohol consumption on disease outcomes.

OPEN-ACCESSTRUE
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pmcIntroduction

Alcohol consumption dose-dependently affects the innate and adaptive immune system.1 An inverse association has been observed between alcohol consumption and risk of autoimmune disorders such as systemic lupus erythematosus,2 autoimmune diabetes,3 rheumatoid arthritis,4 autoimmune thyroid diseases,5 and multiple sclerosis (MS).6-8

Cross-sectional studies have observed that patients with MS who consume alcohol have a lower disability and higher health-related quality of life, compared with nondrinkers.9-12 One prospective study, comprising 181 patients with MS, indicated that alcohol consumption is associated with slower disability progression.13 However, there is a possibility that patients with faster disability progression reduce their alcohol intake and, consequently, that the inverse relationship between alcohol consumption and disease progression may be explained by reverse causation.

Considering the immunomodulatory properties of alcohol, our hypothesis posited that alcohol consumption may affect both inflammation and neurodegeneration in MS. We followed up 9,051 patients with MS from 2 case-control studies through the Swedish MS registry to investigate the influence of alcohol consumption habits on MS disease progression while also exploring potential signs of reverse causation.

Methods

EIMS (Epidemiologic Investigation of Multiple Sclerosis) and GEMS (Genes and Environment in Multiple Sclerosis) are Swedish population-based case-control studies. EIMS enrolled incidence cases of MS from hospital-based and privately run neurology units from April 2005 to December 2019 (n = 3,567) while GEMS identified prevalent cases, which were different from those in EIMS, from the Swedish MS registry between November 2009 and November 2011 (n = 6,148). The response rate among cases was 93% in EIMS and 82% in GEMS. All cases met the McDonald criteria.14,15 Further information on the study design and methods can be found elsewhere.16

Patients from EIMS and GEMS were followed up through the Swedish MS registry.17 Of the 9,715 patients, 9,089 (94%) were followed up with EDSS scores in the Swedish MS registry. Those with missing data on alcohol consumption habits were excluded (38 cases). Our study thus comprised 9,051 patients with MS.

With the purpose of investigating changes in lifestyle habits after diagnosis, patients enrolled in EIMS from April 2005 to December 2019 were requested to complete a digitalized follow-up questionnaire regarding lifestyle habits, spanning from diagnosis to 2021. A total of 1,823 patients (66%) submitted completed questionnaires, of whom 1,733 (95%) had follow-up data available in the Swedish MS registry.

Standard Protocol Approvals, Registrations, and Patient Consents

The studies were approved by the Regional Ethical Review Board at Karolinska Institute (DNR 04-252/1, 2012/359-32, 2008/1617-31/2, 2016/1167-32, and 2018/2689-32) and have been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Definition of Exposures

Information on environmental exposures and lifestyle habits was collected at study inclusion using a standardized questionnaire. Questions regarding alcohol consumption are provided in eAppendix 1. Alcohol consumption at the time of diagnosis was categorized into nondrinking, low alcohol consumption (<50 g/wk for women and <100 g/wk for men), moderate alcohol consumption (50–108 g/wk for women and 100–168 g/wk for men), and high alcohol consumption (>108 g/wk for women and >168 g/wk for men). The cutoffs were the same as those used by Statistics Sweden, a governmental agency responsible for official statistics. In the follow-up questionnaire, patients were asked to report their alcohol consumption both at the time of diagnosis and at five-year intervals thereafter, as well as their current alcohol consumption.

Outcome Measures

The Swedish MS registry is used in all neurology units across the country. Information is continuously registered regarding medical treatment, disease activity, physical functioning, and health-related quality of life. The baseline was determined as the date of the initial recorded EDSS assessment. Confirmed disability worsening (CDW) was characterized by an EDSS score increase of at least 1 point from baseline, sustained between 2 follow-up visits separated by no less than 6 months (1.5 points if the EDSS score at baseline was 0, 0.5 points if the baseline EDSS score was ≥5.5). Secondary outcomes included time to reaching EDSS milestones of 3 and 4, which were analyzed in subgroups of patients with baseline EDSS scores of less than 3 and less than 4, respectively. Another secondary outcome was a change in health-related quality of life, assessed by the Multiple Sclerosis Impact Scale 29 (MSIS-29).18 Physical and psychological deterioration from the patient's perspective was defined as an increase of 7.5 points or more in the physical or mental component of MSIS-29, respectively.19

Statistical Analysis

Categorical variables were summarized using frequency and percentage. Continuous variables were summarized using mean and SD or median and interquartile range as appropriate.

Time to 24-week CDW and the attainment of EDSS 3 and 4 milestones, along with physical and psychological deterioration from the patient's viewpoint, were analyzed using multivariable Cox proportional hazard regression. Follow-up duration was computed from baseline to the occurrence of the specified events of interest, dropout, death, or end of follow-up, whichever occurred first. The proportional hazard assumption was assessed using the Schoenfeld residuals, with no observed violations of proportionality. p values for trend were calculated using a categorical variable for alcohol consumption and each outcome variable.

All analyses controlled for age at diagnosis, sex, disease phenotype, disease duration, baseline EDSS, disease-modifying therapy (the proportion of follow-up time on treatment), and current smoking at baseline. The following potential confounding variables were not kept in the final model because their inclusion resulted in negligible changes in the estimated hazard ratios: ancestry (Nordic or non-Nordic), educational level (postsecondary education or not), body mass index at diagnosis (underweight, normal weight, overweight, or obese, as defined by the World Health Organization), physical activity at diagnosis (sedentary leisure time, moderate exercise, regular exercise 1–2 times/week, and regular exercise 3 or more times/week), fish consumption, and sun exposure at diagnosis. Overall fish consumption was divided into 6 groups based on 2 questions regarding how often the participants consumed lean and oily fish, respectively. We then dichotomized overall fish consumption into low (groups 1 and 2) or high (groups 3–6). The participants assessed their sun exposure by answering 3 questions with answer alternatives on a four-point scale, and we constructed an index ranging between 3 and 12 by adding the numbers together. An index value equal to or more than the median (6) was considered the reference. The analyses were mainly performed based on the overall sample, with EDSS-related outcomes further stratified by both sex and disease phenotype. Interaction tests were conducted to evaluate the effect modification by sex and disease phenotype. Statistical significance was set at p < 0.05. We used the EIMS follow-up questionnaire to investigate potential effects of reverse causation and performed the analysis restricted to those who had not changed their alcohol consumption between the clinical onset of MS and the time of completing the follow-up questionnaire in 2021. Several complementary analyses were conducted. We used mixed models to analyze long-term changes. We used linear mixed-effect models to estimate the baseline differences and the rate of change in EDSS scores over the follow-up by alcohol consumption levels with nondrinkers as the reference group. We included a quadratic term of follow-up time in the models to consider the nonlinear change of EDSS over time. We used the Wald test to test the departure from linearity. Random intercept and slope were estimated as the random part in the mixed model. The unstructured covariance matrices were used for all models.

In addition to traditional covariate adjustment, propensity score analysis was performed to account for potential confounding by indication. Logistic regression was used to estimate the propensity scores, which represent the likelihood of being in the alcohol-consuming groups based on baseline characteristics. The propensity scores were then included as an additional covariate in Cox regression models, enabling a more comprehensive control for baseline differences between alcohol consumption groups. We also assessed the impact of covariate selection on study outcomes. Specifically, we examined the stability of effect estimates and model fit when adjusting for alternative sets of covariates, including those specifically relevant to EDSS or MSIS-29 outcomes. Because most of the patients receive disease-modifying treatment that has a profound influence on disease outcomes, we performed subanalyses in which we excluded patients who were untreated. We also separately studied the impact of alcohol consumption on disease outcomes in those who were untreated. We further performed the EDSS-related analyses by study and dichotomized by smoking status (never, past, or current smoking at baseline). To further address the issue of reverse causation, we conducted a subanalysis limited to patients with disease onset within 1 year before diagnosis. Finally, taking into account the possibility of secular trends that might affect drinking habits over the recruitment period, we performed sensitivity analyses specifically focusing on the subset of participants enrolled during the periods 2000–2005, 2006–2010, and 2011–2015, respectively. All analyses were conducted in Statistical Analysis System (SAS) version 9.4.

Data Availability

Anonymized data underlying this article will be shared on reasonable request from any qualified investigator who wants to analyze questions that are related to the published article.

Results

We followed 9,051 patients with MS with different alcohol consumption habits through the Swedish MS registry. At diagnosis, 44% were nondrinkers, 38% low consumers, 12% moderate consumers, and 6% high consumers of alcohol. Baseline characteristics of cases, overall and by alcohol consumption, are presented in Table 1.

Table 1 Baseline Characteristics of the Overall Sample and by Alcohol Consumption at Diagnosis

Characteristics	Total	Alcohol consumption	p Value	
None	Low	Moderate	High	
N	9,051	3,956	3,487	1,098	510		
Age (SD)	37.5 (11.2)	37.1 (11.7)	37.9 (10.6)	37.9 (11.3)	37.2 (11.7)	0.01	
Female, n (%)	6,514 (72)	2,907 (73)	2,432 (70)	840 (77)	335 (66)	<0.0001	
Nordic origin, n (%)	7,796 (86)	3,940 (85)	3,476 (88)	1,093 (89)	508 (87)	0.0001	
Treatment, n (%)	7,460 (82)	3,116 (79)	2,980 (85)	923 (84)	441 (86)	<0.0001	
Proportion of follow-up time on treatmenta							
 Only first-line treatment, n (%)a	6,261 (85)	2,595 (85)	2,524 (86)	779 (86)	363 (83)		
 Second-line treatment, n (%)a	937 (13)	388 (13)	381 (13)	109 (12)	59 (14)		
 MS phenotype						0.0008	
 Relapsing onset, n (%)	8,241 (91.0)	3,562 (90.0)	3,206 (92)	997 (90.8)	476 (93.3)		
 Progressive onset, n (%)	724 (8.0)	360 (9.1)	246 (7.0)	91 (8.3)	27 (5.3)		
 Unknown, n (%)	86 (1.0)	34 (0.9)	35 (1.0)	10 (0.9)	7 (1.4)		
Disease duration, y (SD)	6.0 (6.5)	6.3 (6.6)	5.8 (6.4)	5.9 (6.2)	5.9 (6.2)	0.89	
Mean baseline EDSS (SD)	2.8 (2.2)	3.2 (2.4)	2.6 (2.1)	2.5 (2.1)	2.5 (2.0)	<0.0001	
Median baseline EDSS (range)	2.0 (0–7)	2.5 (0–7)	2.0 (0–7)	2.0 (0–7)	2.0 (0–7)	<0.0001	
Baseline MSIS-PHYS (SD)	25 (23)	28 (24)	23 (22)	22 (22)	26 (24)	<0.0001	
Baseline MSIS-PSYC (SD)	31 (24)	33 (24)	32 (24)	31 (24)	31 (24)	<0.0001	
Postsecondary education, n (%)	3,477 (37)	1,286 (33)	1,440 (41)	458 (42)	197 (39)	<0.0001	
Never smoking, n (%)	3,680 (41)	1,669 (42)	1,557 (45)	341 (31)	113 (22)	<0.0001	
Past smoking, n (%)	2,479 (27)	976 (25)	997 (27)	352 (32)	154 (30)	<0.0001	
Current smoking, n (%)	2,892 (32)	1,311 (33)	933 (28)	405 (37)	243 (48)	<0.0001	
Pack y of smoking (SD)	4.6 (8.1)	4.8 (8.5)	3.9 (7.2)	5.4 (8.1)	6.6 (9.1)	<0.0001	
Physical activity (SD)	2.4 (0.9)	2.3 (0.9)	2.4 (0.9)	2.4 (0.9)	2.3 (0.9)	0.0002	
Low fish consumption (SD)	3,300 (36)	1,232 (31)	1,358 (39)	496 (45)	214 (42)	<0.0001	
Sun exposure index (SD)	6.2 (1.8)	6.0 (1.8)	6.2 (1.7)	6.6 (1.8)	6.6 (1.9)	<0.0001	
a Patients on disease-modifying treatment.

Compared with nondrinking, low and moderate alcohol consumption was associated with a reduced risk of EDSS-related unfavorable outcomes and with a reduced risk of physical worsening as measured by MSIS-29 while there was no significant influence of alcohol consumption on psychological worsening (Figure 1, Table 2). Trend tests revealed a lower risk of physical worsening and unfavorable EDSS-related outcomes with increasing alcohol consumption among low and moderate alcohol consumers while high alcohol consumption had no significant influence on the disease outcomes (Figure 1, Table 2).

Figure 1 HR With 95% CI of Having Unfavorable Outcomes After Diagnosis, by Alcohol Consumption at Diagnosis

The analysis was adjusted for age at diagnosis, sex, disease phenotype, disease duration, baseline EDSS, disease-modifying therapy, physical activity, and smoking.

Table 2 HR With 95% CI of Having Unfavorable Outcomes After Diagnosis, by Alcohol Consumption at Diagnosis

First clinical disease worsening (CDW)		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b	Trend estimate (95% CI), p value	
None	3,956	6.2 (5.0)	2,346 (59)	1.0 (reference)	1.0 (reference)	0.95 (0.92–0.98)
0.002	
Low	3,487	6.6 (5.0)	1963 (56)	0.89 (0.84–0.94)	0.90 (0.85–0.95)	
Moderate	1,098	6.8 (5.1)	614 (56)	0.84 (0.77–0.92)	0.85 (0.78–0.93)	
High	510	6.3 (5.1)	298 (58)	0.94 (0.84–1.06)	0.96 (0.85–1.08)	
EDSS 3		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b	Trend estimate (95% CI), p value	
None	2010	7.6 (5.4)	901 (45)	1.0 (reference)	1.0 (reference)	0.93 (0.89–0.98)
0.005	
Low	2,181	8.1 (5.4)	848 (39)	0.81 (0.74–0.89)	0.83 (0.76–0.92)	
Moderate	697	8.3 (5.3)	265 (38)	0.77 (0.67–0.88)	0.78 (0.69–0.91)	
High	320	7.4 (5.5)	139 (43)	0.98 (0.82–1.18)	0.97 (0.81–1.16)	
EDSS 4		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b	Trend estimate (95% CI), p value	
None	2,634	8.7 (5.6)	898 (34)	1.0 (reference)	1.0 (reference)	0.93 (0.88–0.98)
0.006	
Low	2,688	9.3 (5.6)	740 (28)	0.75 (0.68–0.83)	0.82 (0.76–0.92)	
Moderate	862	9.5 (5.7)	229 (27)	0.71 (0.61–0.82)	0.79 (0.69–0.91)	
High	402	8.8 (5.6)	135 (34)	0.96 (0.80–1.15)	0.97 (0.81–1.16)	
Physical worsening (increased MSIS-29 physical score by 7.5 or more)		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b,c	Trend estimate (95% CI), p value	
None	1804	4.9 (4.7)	826 (46)	1.0 (reference)	1.0 (reference)	0.96 (0.91–1.01)
0.06	
Low	1994	5.1 (4.6)	843 (42)	0.89 (0.81–0.98)	0.88 (0.80–0.97)	
Moderate	609	5.2 (4.0)	265 (44)	0.90 (0.79–1.04)	0.87 (0.76–0.99)	
High	297	4.9 (4.4)	138 (46)	1.01 (0.84–1.21)	0.99 (0.82–1.19)	
Psychological worsening (increased MSIS-29 psychological score by 7.5 or more)		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b,d	Trend estimate (95% CI), p value	
None	1804	4.6 (4.7)	891 (49)	1.0 (reference)	1.0 (reference)	0.96 (0.91–1.01)
0.11	
Low	1979	4.8 (4.7)	1,009 (51)	1.00 (0.91–1.09)	0.96 (0.88–1.06)	
Moderate	606	4.5 (4.0)	345 (57)	1.16 (1.02–1.31)	1.12 (0.98–1.25)	
High	296	4.3 (4.2)	164 (55)	1.16 (0.98–1.37)	1.13 (0.95–1.33)	
a Crude.

b Adjusted for age at diagnosis, sex, disease phenotype, disease duration, baseline EDSS, disease-modifying therapy, physical activity, and smoking.

c Adjusted for baseline MSIS-PHYS.

d Adjusted for baseline MSIS-PSYC.

The inverse relationship between low and moderate alcohol consumption and adverse outcomes seemed stronger among women than among men (eTable 1) and was confined to relapsing-remitting MS onset (eTable 2). Significant interaction effects between alcohol consumption and both sex and disease phenotype were revealed (Wald tests p < 0.0001).

Among EIMS participants who answered the follow-up questionnaire in 2021, 21% had reduced their alcohol consumption after diagnosis while 12% consumed more alcohol. There were no differences in measures of disability at baseline between drinkers who continued drinking alcohol after diagnosis and those who later discontinued (Table 3). The inverse association between low and moderate alcohol consumption and the risk of unfavorable outcomes became stronger when the analyses were restricted to those who had not changed their alcohol consumption between disease onset and 2021 (Table 4).

Table 3 Baseline Characteristics, by Alcohol Consumption Habits at Diagnosis and in 2021

	Alcohol consumption at disease onset	
	All participants	No	Yes	
Alcohol consumption during follow-up	All participants	No	Unchanged since diagnosis	Reduced since diagnosis	Increased since diagnosis	
N	1,517	150	1,005	362	216	
Age at disease onset	35.3 (10.4)	35.5 (10.8)	35.7 (10.2)	34.1 (10.5)	32.6 (9.8)	
Age at diagnosis	38.8 (10.8)	38.4 (11.0)	39.4 (10.6)	37.2 (11.0)	35.3 (9.9)	
Baseline mean EDSS (SD)	1.8 (1.4)	2.2 (1.6)	1.7 (1.4)	1.8 (1.4)	1.7 (1.4)	
Baseline mean MSIS-29 PHYS (SD)	19 (21)	30 (24)	17 (18)	23 (22)	19 (21)	

Table 4 HR With 95% CI of Having Unfavorable Outcomes After Diagnosis, by Alcohol Consumption at Diagnosis

First clinical disease worsening (CDW)		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b	Trend estimate (95% CI), p value	
None	150	6.1 (4.2)	76 (51)	1.0 (reference)	1.0 (reference)	0.94 (0.85–1.06)
0.35	
Low	632	6.8 (4.5)	307 (49)	0.78 (0.60–1.00)	0.71 (0.55–0.92)	
Moderate	273	7.6 (4.9)	128 (47)	0.69 (0.52–0.92)	0.63 (0.48–0.85)	
High	100	6.3 (4.7)	58 (58)	0.99 (0.71–1.41)	0.95 (0.67–1.35)	
EDSS 3		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b	Trend estimate (95% CI), p value	
None	105	6.8 (4.4)	45 (43)	1.0 (reference)	1.0 (reference)	0.86 (0.74–1.00)
0.05	
Low	500	8.3 (4.6)	171 (34)	0.73 (0.52–1.01)	0.64 (0.46–0.90)	
Moderate	224	8.8 (4.8)	68 (30)	0.61 (0.42–0.89)	0.52 (0.36–0.77)	
High	78	7.9 (5.2)	30 (38)	0.86 (0.54–1.36)	0.71 (0.44–1.15)	
EDSS 4		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b	Trend estimate (95% CI), p value	
None	131	7.7 (4.3)	39 (30)	1.0 (reference)	1.0 (reference)	0.87 (0.73–1.04)
0.12	
Low	585	9.3 (4.6)	118 (20)	0.74 (0.51–1.06)	0.69 (0.48–0.99)	
Moderate	256	9.7 (4.8)	45 (18)	0.64 (0.42–0.98)	0.55 (0.36–0.85)	
High	94	9.5 (5.1)	22 (23)	0.82 (0.48–1.39)	0.80 (0.46–1.37)	
Physical worsening (increased MSIS-29 physical score by 7.5 or more)		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b,c	Trend estimate (95% CI), p value	
None	117	5.0 (3.6)	59 (50)	1.0 (reference)	1.0 (reference)	0.97 (0.84–1.11)
0.66	
Low	480	5.7 (4.7)	187 (39)	0.70 (0.52–0.95)	0.62 (0.46–0.85)	
Moderate	205	5.9 (3.9)	73 (36)	0.62 (0.44–0.89)	0.57 (0.40–0.81)	
High	76	5.0 (3.4)	41 (54)	1.07 (0.71–1.61)	1.04 (0.68–1.58)	
Psychological worsening (increased MSIS-29 psychological score by 7.5 or more)		
Alcohol consumption	N	Years (SD)	Outcome (%)	HR (95% CI)a	HR (95% CI)b,d	Trend estimate (95% CI), p value	
None	117	4.8 (3.8)	58 (50)	1.0 (reference)	1.0 (reference)	1.04 (0.92–1.18)
0.50	
Low	478	5.3 (4.8)	234 (49)	0.90 (0.68–1.20)	0.70 (0.52–0.95)	
Moderate	204	5.2 (4.0)	106 (52)	0.96 (0.70–1.32)	0.73 (0.53–1.02)	
High	76	4.7 (3.8)	52 (68)	1.36 (0.94–1.98)	1.10 (0.74–1.62)	
Restricted to patients who have not changed their alcohol consumption habits between diagnosis and 2021.

a Crude.

b Adjusted for age at diagnosis, sex, disease phenotype, disease duration, baseline EDSS, disease-modifying therapy, physical activity, and smoking.

c Adjusted for baseline MSIS-PHYS.

d Adjusted for baseline MSIS-PSYC.

Supplementary Analyses

All drinking groups had lower baseline EDSS scores compared with nondrinkers (Table 1, Figure 2). Compared with nondrinkers, the annual rate of increase in the EDSS score during follow-up was slower in low and moderate alcohol consumers (−0.03, 95% CI −0.04 to −0.02 among low consumers and −0.02, 95% CI −0.04 to −0.01 among moderate consumers), but not in high consumers (−0.00, 95% CI −0.02 to 0.02) (Figure 1).

Figure 2 Predicted Trajectories of EDSS Scores After Diagnosis, by Alcohol Consumption Habits at Diagnosis

The lines represent coefficients from the linear mixed-effects model adjusted for age at diagnosis, sex, disease phenotype, disease duration, baseline EDSS, physical activity, and smoking. Models considered a nonlinear trajectory with quadratic time (with corresponding random effects).

After adjusting for propensity scores in Cox regression models, estimates of the association between alcohol consumption and MS disease progression remained consistent. The inclusion of propensity scores resulted in narrower confidence intervals for the estimates, indicating increased precision in the assessment of the relationship between alcohol consumption and MS disease progression. After adjustment for alternative sets of covariates, including those specifically relevant to EDSS or MSIS-29 outcomes, the estimates changed very little, suggesting that our results are stable and that specific covariates have minimal influence on the observed associations.

Our findings remained significant when we stratified the analyses by study, stratified by smoking habits (never, past, or current smoking at baseline), and separately performed the analyses among patients on disease-modifying treatment (eTable 3). In the group of untreated patients, the HR of CDW was 0.75 (95% CI 0.60–0.95) among those with moderate alcohol consumption, compared with nondrinkers (the inverse trend, revealing a lower risk of CDW with increasing alcohol exposure, was 0.92 (95% CI 0.84–0.99)) (not in table).

Our subanalysis, limited to patients with disease onset within 1 year before diagnosis, revealed a HR of CDW of 0.83 (95% CI 0.73–0.94) among moderate alcohol consumers, compared with nondrinkers, and the trend showing lower risk of CDW with increasing alcohol exposure was 0.95 (95% CI 0.91–0.99) (not in table). When we performed the analysis based on those recruited during the periods 2000–2005, 2006–2010, and 2011–2015, respectively, the association between alcohol consumption and risk of CDW remained significant, as did the trends showing lower risk of CDW with increasing alcohol exposure (not in table).

Discussion

Low and moderate alcohol consumption was associated with more favorable EDSS-related outcomes and lower risk of physical worsening, compared with nondrinking while there was no significant influence of high alcohol consumption on disease outcomes. The inverse relationship between alcohol consumption and disease progression was confined to relapsing-remitting MS.

Experimental and clinical data have demonstrated that alcohol dose-dependently affects both the innate and adaptive immune system.1 Low and moderate alcohol consumption has been shown to reduce the level of systemic inflammation while nondrinking and high alcohol consumption were associated with elevated levels of inflammatory markers.20,21

Alcohol exposure has been shown to attenuate B-cell and T-cell immune responses and suppress the production of interleukin-21, which has been correlated with both MS severity and progression.22,23 Consumption of alcohol may also affect MS progression by altering the composition of the gut microbiome. Low to moderate alcohol consumption may promote the generation of gut-derived anti-inflammatory fatty acids, such as short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs).24 The anti-inflammatory properties of these fatty acids have been shown to reduce inflammation in autoimmune diseases.25-27

Conversely, high doses of alcohol consumption have been associated with increased fatty acid catabolism and decreased PUFA concentrations.28 The effects of alcohol in MS may share common pathways with other autoimmune conditions, reflecting broader immunomodulatory properties. Further exploration of these shared mechanisms may provide valuable insights into potential interventions aimed at mitigating disease progression in MS and other autoimmune diseases.

Our finding of an inverse relationship between alcohol consumption and disease progression confined to relapsing-remitting MS is in agreement with a Belgian cross-sectional survey.12 While the relapsing-remitting phase of the disease is associated with focal inflammatory activity, the progressive phase is dominated by diffuse gray and white matter atrophy and cortical demyelination.29 At least to some extent, the inflammation and the degeneration seem to be dissociated.30 Disability progression in the relapsing onset and progressive phase of MS may thus be differentially affected by lifestyle factors, such as alcohol consumption.

Despite the possibility that alcohol primarily affects relapse-associated worsening, the slower rate of EDSS progression among moderate alcohol consumers reflects a favorable outcome regarding disability accumulation. Future studies using longitudinal designs and multimodal assessments will be essential for elucidating the specific mechanisms underlying the observed differences in disability progression among patients with varying alcohol consumption habits.

Although our findings indicate that alcohol consumption ameliorates disease progression in both sexes, the association was less pronounced and nonsignificant in men. Alcohol consumption increases glucocorticoid hormone levels and decreases estrogen level in women that may mediate immune-suppressive effects,31 which could contribute to explain the observed sex difference. However, given the complexity of interaction effects, careful consideration should be given to subgroup analyses across diverse patient populations.

The main strengths of our study lie in its population-based design, high response rate, and comprehensive data on exposures, allowing for the consideration of numerous potential confounding factors. Although the response rate was lower in the EIMS follow-up study, there were no significant differences in age, sex, smoking habits, alcohol consumption, or baseline EDSS scores between participants and nonparticipants.

Information on alcohol consumption among newly diagnosed cases in EIMS was collected at baseline, minimizing recall bias. By contrast, lifestyle habit data for GEMS participants were gathered retrospectively. Despite the potential for recall bias in GEMS, our analyses yielded similar results when EIMS and GEMS participants were examined separately.

Reverse causation may raise concerns if reduced general well-being before diagnosis led some patients to be less inclined to consume alcohol. However, our discovery of a negative correlation between alcohol intake and MS-specific outcomes persisted even when we restricted our analyses to patients with disease onset within 1 year before diagnosis and when we only included those who did not alter their alcohol consumption during follow-up. In addition, there were no disparities in baseline disability between drinkers who continued vs those who ceased alcohol consumption after baseline. Therefore, our findings argue against reverse causality as an explanation for the association between alcohol consumption and MS disease progression.

Communicating and implementing data on the potential beneficial effects of alcohol in MS is challenging, given the well-documented adverse effects of alcohol consumption on human health. However, we believe that this knowledge should be disseminated because further research into underlying mechanisms may offer insights into how to mitigate disease progression through the development of alternative treatments or dietary interventions that do not involve alcohol. Clinical implementation should be individualized, considering both the potential benefits and risks of alcohol consumption for each patient.

In conclusion, low and moderate alcohol consumption was associated with more favorable outcomes in relapsing-remitting MS, compared with nondrinking, while there was no significant influence of high alcohol consumption on disease outcomes.

Study Funding

The study was supported by grants from the Swedish Research Council (2016–02349 and 2020-01998), the Swedish Research Council for Health, Working Life and Welfare (2015-00195 and 2019-00697), the Swedish Brain Foundation (FO2020-0077 and FO2022-0123), the Swedish Medical Research Council, Margaretha af Ugglas Foundation, the Swedish Foundation for MS Research, and NEURO Sweden.

Disclosure

J. Wu has nothing to disclose; L. Alfredsson reports grants from Swedish Research Council, Swedish Research Council for Health Working Life and Welfare, and Swedish Brain Foundation, during the conduct of the study, and personal fees from Teva and Biogene Idec, outside the submitted work. T. Olsson has received lecture/advisory board honoraria and unrestricted MS research grants from Biogen, Novartis, Sanofi, and Merck. J.A. Hillert has received honoraria for serving on advisory boards for Biogen, Celgene, Sanofi-Genzyme, Merck KGaA, Novartis, and Sandoz and speaker's fees from Biogen, Novartis, Merck KGaA, Teva, and Sanofi-Genzyme. He has served as P.I. for projects or received unrestricted research support from, Biogen, Bristol-Myers-Squibb, Merck KGaA, Novartis, Roche, and Sanofi-Genzyme; A.K. Hedström has nothing to disclose. Go to Neurology.org/NN for full disclosures.

Appendix Authors

Name	Location	Contribution	
Jing Wu, PhD	Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden	Drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data	
Tomas Olsson, MD, PhD	Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden	Drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data	
Jan A. Hillert, MD, PhD	Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden	Drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data	
Lars Alfredsson, PhD	Institute of Environmental Medicine; Department of Clinical Neuroscience, Karolinska Institutet; Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden	Drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data	
Anna Karin Hedström, MD, PhD	Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden	Drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data	

Glossary

CDW confirmed disability worsening

EDSS Expanded Disability Status Scale

EIMS Epidemiologic Investigation of MS

GEMS Genes and Environment in MS

MS multiple sclerosis

PUFA polyunsaturated fatty acid
==== Refs
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