Association of body mass index with progression and prediction of multiple sclerosis
Abstract
Background: Multiple sclerosis is a disease whose etiology involves multifactorial interactions among genetic and environmental factors. Obesity is one of the most important environmental factors conducive to the onset and progression of the disease. The aim of the study was to determine the value of body mass index (BMI) in a population of patients with multiple sclerosis compared to the general population, to assess the relation between the BMI and physical disability in patients with multiple sclerosis and the influence of the BMI on the course and progression of the disease.
Material and Methods: A cross-sectional study was done on 100 patients suffering from multiple sclerosis (experimental group) and 50 healthy people (control group). In order to determine the degree of physical disability the Expanded disability status scale (EDSS) was used. Clinical and demographic data and values of the BMI in both studied groups were collected. BMI was defined as the weight in kilograms divided by the surface area measured in square meters. Statistical analysis included the descriptive statistics, t-test, chi- square test, analysis of variance, correlation, and regression analysis.
Results: Total body weight and BMI were significantly higher in the control group (p< 0.05). There was no statistically significant correlation between EDSS and BMI (p = 0.574). There was a correlation between the course of MS and whether BMI has an abnormal or normal level (p = 0.031). Normal BMI proved to be a predictive factor (p = 0.086).
Conclusion: BMI is an environmental factor that significantly affects the progression and prediction of multiple sclerosis, but not to the degree of physical disability.
Keywords: multiple sclerosis, BMI, progression, prediction, physical disability.
References
Compston A, Ebers G, Lassmann H, McDonald I, Matthews B, Wekerle H. McAlpine’s multiple sclerosis. 3rd ed. London: Churchill Livingstone, 1998.
Wingerchuk DM, Carter JL. Multiple sclerosis: current and emerging disease-modifying therapies and treatment strategies. Mayo Clin Proc 2014;89(2):225–240.
Waubant E, Lucas R, Mowry E, et al. Environmental and genetic risk factors for MS an integrated review. Ann Clin Transl Neurol 2019. doi: 101002/ acn3.50862.
Olsson T, Barcellos LF, Alfredsson L. Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nat Rev Neurol 2017; 13(1):25-36.
Hedström AK. Smoking and its interaction with genetics in MS etiology. Mult Scler 2019; 1352458518801727. doi: 10.1177/1352458518801727.
Marrie RA, Beck CA. Obesity and HLA in multiple sclerosis: Weighty matters. Neurology 2014; 82(10):826-7.
Marrie R, Horwitz R, Cutter G, et al. High frequency of adverse health behaviors in multiple sclerosis. Mult Scler 2009; 15 (1): 105-13.
Overs S, Hughes CM, Haselkorn JK, et al. Modifiable comorbidities and disability in multiple sclerosis. Curr Neurol Neurosci Rep 2012; 12 (5): 610-7.
Materese G, Carrieri PB, La Cava A, et al. Leptin increase in multiple sclerosis associates with reduced number of CD4+CD25+ regulatory T cells. Proc Natl Acad Sci USA 2005; 102: 5150-5.
Lukens JR, Dixit VD, Kanneganti TD. Inflammasome activation in obesity-related inflammatory diseases and autoimmunity. Discov Med 2011; 12 (62): 65-74.
Maffei M, Halaas J, Ravussin E, et al. Leptin levels in human and rodent: measurement of plasma leptin and ob RNA in obese and weight-reduced subjects. Nat Med 1995;1:1155–1161.
Birnbaum G, Cree B, Altafullah I, et al. Combining beta interferon and atorvastatin may increase disease activity in multiple sclerosis. Neurology 2008; 71: 1390–1395.
Lambert CP, Lee AR, Evans WJ. Body composition in ambulatory women with multiple sclerosis. Arch Phys Med Rehabil 2002; 83: 1559–1561.
Hedström AK, Olsson T, Alfredsson L. High body mass index before age 20 is associated with increased risk for multiple sclerosis in both men and women. Mult Scler 2012; 18 (9): 1334-6.
Mohamed-Ali V, Goodrick S, Rawesh A, et al. Subcutaneous adipose tissue releases interleukin-6, but not tumor necrosis factor-alpha, in vivo. J Clin Endocrinol Metab 1997; 82:4196–4200.
Munger KL, Bentzen J, Laursen B, et al. Childhood body mass index and multiple sclerosis risk: a long-term cohort study. Mult Scler 2013; 19 (10): 1323-9.
Wesnws K, Riise T, Bjornevik T, et al. The relationship between body size and the risk of multiple sclerosis. Mult Scler 2012; 18: 55-277.
Bell NH, Epstein S, Greene A, et al. Evidence for alteration of the vitamin D-endocrine system in obese subjects. J Clin Invest 1985; 76: 370–373.
Liel Y, Ulmer E, Shary J, et al. Low circulating vitamin D in obesity. Calcif Tissue Int 1988; 43: 199–201.
Wortsman J, Matsuoka LY, Chen TC, et al. Decreased bioavailability of vitamin D in obesity. Am J Clin Nutr 2000; 72: 690–693.
Hernan MA, Olek MJ, Ascherio A. Geographic variation of MS incidence in two prospective studies of US women. Neurology 1999; 53: 1711–1718.
Huppke B, Ellenberger D, Hummel H, et al. Association of Obesity With multiple sclerosis risk and response to first-line disease modifying drugs in children. JAMA Neurol 2019: PMID: 31305922.
Gianfrancesco MA, Glymour MM, Walter S, et al. Causal effect of genetic variants associated with body mass index on multiple sclerosis susceptibility. Am J Epidemiol 2017; 185(3): 162-171.
Hedström AK, Lima Bomfim I, Barcellos L, et al. Interaction between adolescent obesity and HLA risk genes in the etiology of multiple sclerosis. Neurology 2014; 82: 865–872.
Kurtzke JF. Rating neurologic instrument in multiple sclerosis: An expandede disability status scale (EDSS). Neurology 1983; 33: 1444-52.
NHLBI Obesity Task Force. Clinical guidelines on the identification, evaluation and treatment of overweight and obesity in adults – the evidence report. National Institutes of Health. Obes Res 1998; 2: 51–209.
Markianos M, Evangelopoulos ME, Koutsis G et al. Body mass index in multiple sclerosis: Associations with CSF neurotransmitter metabolite level. Neurology 2013; 5: 27-33.
Nortvedt MW, Riise T, Maeland JG. Multip sclerosis and lifestyle factors: the Hordaland Health Study. Neurol Sci 2005; 26: 334–9.
Alschuler KN, Gibbons LE, Rosenberg DE, et al. Body mass index and waist circumference in persons aging with muscular dystrophy, multiple sclerosis, post-polio syndrome, and spinal cord injury. Disab Health Journal 2012; 5: 177–184.
Ghadirian P, Jain M, Ducic S, et al. Nutritional factors in the etiology of multiple Int J Epidemiol 1998; 27: 845-852.
Snook EM, Mojtahedi MC, Evans EM, et al. Physical activity and body composition among ambulatory individuals with multiple sclerosis. Int J MS Care 2005; 7: 137–142.
Allen NB, Lichtman JH, Cohen HW, et al.Vascular disease among hospitalized multiple sclerosis patients. Neuroepidemiology 2008; 30: 234–238.
Formica CA, Cosman F, Nieves J, et al. Reduced bone mass and fat-free mass in women with multiple sclerosis: effects of ambulatory status and glucocorticoid use. Calc Tiss Int 1997; 61: 129–133.
Sioka C, Fotopoulos A, Georgiou A, et al. Body composition in ambulatory patients with multiple sclerosis. J Clin Densitom 2011; 14: 465–470.
Pike J, Jones E, Rajagopalan K, et al. Social and economic burden of walking and mobility problems in multiple sclerosis. BMC Neurology 2012; 12: 94.
Mahler A, Steiniger J, Bock M, et al. Is metabolic flexibility altered in multiple sclerosis patients? PLoS One 2012; 7: e43675.
Comoglu S, Yardimici S, Okcu Z. Body fat distribution and plasma lipid profiles of patients with multiple sclerosis. Turk J Med Sci 2004; 34: 43-48.
Dardiotis E, Tsouris Z, Aslanidou P, et al. Body mass index in patients with multiple sclerosis: a meta– analysis. Neurolol Res 2019: 41(9): 836-846.
Marrie RA, Horwitz RI, Cutter G, et al. Association between comorbidity and clinical characteristics of MS. Acta Neurol Scand 2011; 124: 135-41.
Slawta JN, Wilcox AR, MeCubbin JA, Health behaviors. body composition, coronary heart disease risk in women with multiple sclerosis. Arch phys Med Rehabil 2003; 84: 1823-1830.
Pilutti LA, Dlugonski D, Pula JH, et al. Weight status in persons with multiple sclerosis: implications for mobility outcomes.J Obes 2012;2012:868256. doi:10.1155/2012/868256 868256
White LJ, McCoy SC, Castellano V, et al. Effect of resistance training on risk of coronary artery disease in women with multiple sclerosis. Scand J Clin Lab Invest 2006; 66: 351-355.
Mojtahedi MC, Snook EM, Motl RW, et al. Bone health in ambulatory individuals with multiple sclerosis: Impact of physical activity, glucocorticoid use, and body composition. J Rehabil Res Dev 2008; 45: 851–861.
Lalmohamed A, Bazelier MT, Van Staa TP, et al. Causes of death in patients with multiple sclerosis and matched referent subjects: A population-based cohort study. Eur J Neurol 2012; 19: 1007–1014.
Khurana SR, Bamer AM, Turner AP, et al. The prevalence of overweight and obesity in veterans with multiple sclerosis. Am J Phys Med Rehabil 2009; 88(2): 83-91.
Muñoz D, Escartín A, Dapena D, et al. Adverse events during the titration phase of interferon-beta in remitting-relapsing multiple sclerosis are not predicted by body mass index nor by pharmacodynamic biomarkers. BMC Neurol 2013; 11: 13:82.
Zamzam D, Foad M, Svelam M, et al. Vitamin D and body mass index in Egyptiam multiple sclerosis patients. Mult Scler Relat Disord 2019; 28: 313-316.
Stampanoni M, Lezzi E, Buttrai F, et al. Obesity worsens central inflammation and disability in multiple sclerosis. Mult Scler 2019; doi: 10.177/1352458519853473
Piluti LA, Molti RW. Body composition and disability in people with multiple sclerosis. A dual energy x-ray absorptiometry study. Mult Scler Relat Disord 2019; 29: 41-47.
Flauzino T, Simao ANC, de Carvahlo Jennings Pereira WL, et al. Disability in multiple sclerosis is associated with age and inflammatory, metabolic and oxidative/nitrosative stress biomarkers: results of multivariate and machine learning procedures. Metab Brain Dis 2019; doi: 10.1007/s11011-019-00456-7.
Briggs FBS, Yu JC, Davis MF, et al. Multiple sclerosis risc factors contribute to onset heterogeneity. Mult Scler Relat Disord 2019; 28: 11-1.
Jakimovski D, Guan Y, Ramanathan M, et al. Lifestyle-based modifiable risk factors in multiple sclerosis: review of experimental and clinical findings. Neurodegener Dis Manag 2019; 9(3): 149-172.
Castro K, Nitranos A, Amatruda M. Body mass index in multiple sclerosis modulates ceramide induced DNA methylation and disease course. EbioMedicine 2019;43:392-410.
Jakimovski D, Weinstock-Guttman B, Gandhi S, et al. Dietary and lifestyle factors in multiple sclerosis progression: results from 5-year longitudinal MRI study. J Neurol 2019; 266(4):866-875.
Tettey P, Simpson S, Taylor B, et al. An adverse lipid profile and increased levels of adiposity significantly predict clinical course after first demyelinating event. J Neurol Neurosurg Psychiatry; 88(5)395-401.
Pilutti LA, McAuley E, Motl RW. Weigth status and disability in multiple sclerosis: An examination of bi-directional associations over a 24-month period. Mult scler Relat Disord 2012; 1(3):139-44.
Ro LS, Yang CC, Lyu RK. A prospective, observational study on conversion of clinically isolated syndrome to multiple sclerosis during 4-year period (MS NEO study) in Taiwan. PLoS One 2019 15;14(7):e0202453
Owji M, Ashraf-Ganjouei A, Sahraian MA, et al.The relationship between cognitive function and body mass index in multiple sclerosis patients. Mult Scler Relat Disord 2019;32:37-40.
Esposito S, Bonavita S, Sparaco M, et al. The role of diet in multiple sclerosis: A review. Nutr Neurosci 2018;21(6):377-39.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).