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The impact of modifiable risk factors on lesion burden in patients with early multiple sclerosis
Multiple Sclerosis and Related Disorders 39 (2020) 101886
Contents lists available at ScienceDirect
Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard
The impact of modifiable risk factors on lesion burden in patients with early multiple sclerosis
T
Lorefice La,1, , Destro Fb,1, Fenu Ga, Mallus Mc, Gessa Ia, Sechi Vd, Barracciu MAd, Frau Ja, Coghe Ga, Carmagnini Dc, Marrosu MGc, Saba Lb, Cocco Ec ⁎
a
MS Centre, Binaghi Hospital, ATS Sardegna, Cagliari, Italy Department of Radiology, University of Cagliari, Italy c MS Centre, Department of Medical Sciences and Public Health, University of Cagliari, Italy d Radiology Unit, Binaghi Hospital, ATS Sardegna, Cagliari, Italy b
ABSTRACT
Introduction: Some studies have indicated the importance of considering smoking, vitamin D deficiency and obesity as negative prognostic factors for clinical and MRI outcomes in multiple sclerosis (MS). This study aimed to evaluate the possible effects of these modifiable risk factors on brain MRI lesion burden of patients with early MS, also exploring the influence on initial clinical features. Methods: MS patients were enrolled at diagnosis time and examined for smoking, body mass index (BMI), serum level of lipids and 25(OH) vitamin D. Brain MRIs’ were acquired and lesion volume assessed by Jim software. Clinical data (disease course, disease duration, and EDSS score) were also collected. Results: 64 patients were enrolled, of these 4 (6.2%) had a primary progressive course. Mean age was 39.8 ± 11.1 years and mean EDSS 1.5 ± 1.1. Forty (62.5%) patients were smokers and 40 (62.5%) were overweight (BMI>25). Insufficient levels of vitamin D (<20 ng/mL) were reported in 36 (56.2%) patients, while 24 (37.5%) patients had an altered lipid profile with total cholesterol >200 mg/dl and LDL >100 mg/dl. No association between early clinical features and modifiable risk factors were reported. Multiple regression analysis showed an association between lesion burden and smoking status (p 0.003), while no association was reported with BMI, altered lipid profile and vitamin D insufficiency. Conclusions: Several risk factors may play a role in evolution of MS. Our results show that smoking status, probably due to chronic vascular and neurotoxic effects of the cigarette components, can affect the brain damage from the early stages of MS. No association was observed with the other explored modifiable risk factors, although an effect due to the small sample size cannot be excluded.
1. Introduction Multiple sclerosis (MS) is a lifelong inflammatory and neurodegenerative disease characterized by great heterogeneity in clinical and radiologic features with different prognosis and long-term outcomes (Thompson et al., 2018). As epidemiologic studies have previously shown, MS rates vary with several environmental factors, suggesting a putative role of numerous potentially modifiable risk factors (Olsson et al., 2017; Marrie, 2004). In addition to their possible etiological role in MS, many of these factors may explain and influence the phenotypic and neuroradiological heterogeneity as well as the different trajectories of MS evolution (Hempel et al., 2017). A substantial amount of research has been dedicated to the role of lifestyle-related factors as smoking, obesity, altered lipid profiles, and serum vitamin D levels on MS course (Jakimovski et al.,2019 ). Smoking increases twice the risk of MS and can also aggravate its course both acutely and chronically (Alrouji et al., 2019). In particular, smoking intensity is associated with an increased
relapse rate of over 30%, with a reduced response to disease modifying treatments (DMDs) (Petersen et al., 2018a,b), and with worse disease progression and disability (Sundström and Nyström, 2008). Analogously, several studies indicated that obesity and vitamin D insufficiency, acting by different mechanisms (Novo and Batista, 2017; Guerrero-García et al., 2016; Colotta et al., 2017), seem to be associated with poorer MS clinical outcomes (Ascherio et al., 2014; Stampanoni Bassi et al., 2019). However, the impact of these factors on the neuroradiological characteristics of MS patients, in particular on lesion burden and brain volume, is instead still relatively unexplored, although growing evidence indicate these MRI parameters as gold predictive markers of long-term MS-related disability (Popescu et al., 2013). Based on these considerations, this study aimed to evaluate the possible effects of cigarette smoking, overweight, altered serum lipid profile and vitamin D levels on brain MRI lesion volume of patients with MS at the time of diagnosis, also exploring the influence on early clinical features.
Correspondence to: Multiple Sclerosis Centre, Binaghi Hospital, ATS Sardegna, Via Is Guadazzonis 2, 09126 Cagliari, Italy. E-mail address: [email protected] (L. L). 1 These authors equally contributed. ⁎
https://doi.org/10.1016/j.msard.2019.101886 Received 10 September 2019; Received in revised form 4 December 2019; Accepted 7 December 2019 2211-0348/ © 2019 Elsevier B.V. All rights reserved.
Multiple Sclerosis and Related Disorders 39 (2020) 101886
L. L, et al.
2. Methods
Table 1 Demographic and clinical features of MS patients included in the study.
2.1. Patients
64 MS patients
The study included a cohort of MS patients (according to 2017 revisions of the McDonald criteria) (Thompson et al., 2018) recruited at the time of diagnosis at the Regional MS centre of Cagliari. The patient's demographic characteristics (sex and age) and clinical data [disease course, disease duration, and disability level, evaluated using the Expanded Disability Status Scale (EDSS)] (Kurtzke, 1983), were collected. For each patient, height and weight were measured at diagnosis time and, after the body mass index (BMI) as weight (kg)/height (m2) was obtained, participants were divided in overweight (BMI ≥ 25) and non overweight (BMI<25). Information was collected regarding smoking habits and subjects were classified as “never-smokers” or “active-smokers”, including subjects who smoked more than 10 cigarettes per day for at least 6 months in the 2 years prior to diagnosis. All brain MRI acquisitions performed at the time of diagnosis at the MS centre have been examined, thus radiological activity and brain white matter lesion volume was evaluated for each patient. Finally, serum samples were collected to evaluate lipid profile and vitamin D level. The local ethics committee approved the study and informed consent was obtained from all patients prior to participation.
Male Gender Age (mean ± sd) years MS Disease Duration (mean ± sd) years Progressive course EDSS score Lesion volumes (mean ± sd) ml Gd enhancing lesions
28 (43.8%) 39.8 ± 11.1 2.1 ± 0.5 4 (6.2%) 1.5 ± 1.1 2772 ± 3098 8 (12.5%)
variables (disease duration, EDSS score, radiological activity). For all assays, statistical significance was set at p < 0.05. 3. Results The sample included 64 patients with early diagnosis of MS (male 28; 43.8%). Of these, 4 (6.2%) had a primary progressive course. Mean values for age and disease duration were 39.8 (SD ± 11.1) and 1.1 (SD ± 0.5) years respectively, while mean EDSS was 1.5 (SD ± 1.1). Table 1 shows the demographic and clinical features of MS patients examined in the study, with information of mean lesion volume (2772 ± 3098 mm3) and percentage of patients with radiological activity (8; 12.5%) at diagnostic MRI acquisition. Of all patients, 40 (66.6%) were active smokers and 40 (66.6%) were overweight (BMI ≥ 25); the presence of both risk factors was reported in 14 (21.8%) patients. Biochemical analyses showed that 36 (56.2%) patients had insufficient levels of vitamin D (<20 ng/mL) and 24 (37.5%) had an altered lipid profile with increased total cholesterol (>200 mg/dl) and LDL (>100 mg/dl) (Tables 2). Using independentsamples t-tests, significant difference in lesion volume at diagnosis time was observed between active and never smokers (3410 ± 3694 vs 1710 ± 1122 mm3; p < 0.005), as well as between overweight and non-overweight patients (4310 ± 4478 vs 2341 ± 2481 mm3; p < 0.005). The smokers’ group mainly included young and male subjects, while an older age and a female predominance was observed in the group of overweight patients (p < 0.05). Tables 3 and 4 show a characterization of these groups, including information regarding BMI, vitamin D and lipid levels. The possible relationships between each modifiable risk factor and lesion load were explored by linear regression analyses, showing a significant association after unadjusted analysis only with smoking habit (p < 0.005). On the contrary, no association was observed with BMI, vitamin D insufficiency and altered lipid profile. As shown in table 5, a multiple regression analysis was performed, confirming that in smoker patients a higher lesion burden was observed (p = =0.003), independently from disease duration (p = =0.004), EDSS score (p = =0.005) and radiological activity (p = =0.031).
2.2. MRI assessments Brain MRIs were performed using a 1.5 T scanner (Siemens Medical Solutions, Erlangen, Germany). For each patient, sequences of dualecho proton density, fluid-attenuated inversion recovery, T1-weighted spin-echo (SE), T2-weighted fast SE, and contrast-enhanced T1weighted SE after intravenous gadolinium (Gd) infusion were obtained to define MS diagnosis. Radiological activity was defined as the presence of Gd+ lesions. Segmentation of brain white matter lesions, hyperintense on FLAIR acquisitions, and lesion volume measurements were performed by a single observer using Jim 7, a previously described semi-automated segmentation technique (Jim 7, Xinapse System, Leicester, UK, http://www.xinapse.com). 2.3. Biochemical serum analyses Non-fasting serum samples were collected at diagnosis time and, after centrifugation, total cholesterol and low-density lipoprotein cholesterol (LDL) were estimated using recommended procedures. Furthermore, the 25-hydroxyvitamin D concentration (vitamin D level) was measured with a commercially available radioimmunoassay. All biochemical serum analyses were centralized and performed at the regional MS centre of Cagliari. 2.4. Statistical analysis Statistical analyses were performed using SPSS for Mac version 22.0 (SPSS Inc., Chicago, IL, USA). Firstly, a descriptive analysis was done summarising patients’ demographic and clinical data as a mean for quantitative variables and percentages for qualitative variables. Demographic and clinical differences of “never-smokers” versus “active-smokers” and of overweight versus not overweight patients were evaluated using t-tests and chi-squared tests. After checking of the linearity assumption and normality testing of lesion load, linear regression analyses were performed to explore the relationships between brain lesion volume, which was entered into the model as a quantitative dependent variable, and the presence of each modifiable risk factor (smoking status, BMI, altered lipid profile and Vitamin D insufficiency). Thus, for the modifiable risk factors that are significantly associated in the unadjusted analysis, a multivariate analysis was performed while controlling for demographic and clinical
Table 2 Body mass index, cholesterol values, vitamin D level and smoking status at diagnostic brain MRI time. 64 MS patients Smokers Body mass index (mean ± sd) Overweight (BMI≥ 25) Total cholesterol (mean ± sd mg/dl) LDL (mean ± sd md/dl) *Altered lipid profile Vitamin D (mean ± sd ng/ml) Vitamin D insufficiency (<20 ng/mL)
40 (62.5%) 23.6 ± 3.5 40 (62.5%) 208.5 ± 50.1 114.1 ± 31.9 24 (37.5%) 31.2 ± 21.8 40 (62.5%)
⁎ The group with altered lipid profile included subjects with increased total cholesterol (>200 mg/dl) and LDL levels (> 100 mg/dl).
2
Multiple Sclerosis and Related Disorders 39 (2020) 101886
L. L, et al.
observed in these patients that were predominantly young and therefore with relatively short duration of smoking exposure. No association was observed with particular early clinical features as higher neurological disability or with the presence of radiological activity at brain MRI, as some studies reported (Zivadinov et al., 2009; Kappus et al., 2016). Nevertheless, it is not excluded that the small sample size and the low EDSS observed in most patients may have affected this result. In addition, although a high level of structural brain damage may be present at MS onset, it is common not to observe a concomitant neurological disability, which can occur over time in relation to the progressive reduction of brain plasticity due to both aging and the accumulation of chronic brain damage during the disease (Tomassini et al., 2012), both aspects that could be affected by smoking exposure resulting in worse long-term MS outcomes (Mora, 2013). There are many mechanisms by which cigarette smoke can impact on brain damage. Firstly nicotine, the major component of cigarettes, shows to augment the generation of auto reactive pro-inflammatory T cells and of numerous pro-inflammatory cytokines, triggering the autoimmune cascade (Arnson et al., 2010). In addition, smoking exposure can induce the production of free radicals, resulting in microvascular endothelial alterations and impairment of the blood-brain barrier that, being the entry site of immune cells into the brain, is crucial in pathogenesis and progression of several neurological disorders including MS (Naik et al., 2014). Lastly, smoking habits are related to cerebral small vessels disease characterized by white matter alterations and leukoaraiosis (Gouw et al.,2011; Power et al., 2015) that could complicate the identification of demyelinating white matter lesions. Analogously to smoke, some studies indicated that obesity and altered lipid profile might induce vascular endothelium alterations with breakdown of the blood-brain-barrier leading to central inflammation (Stampanoni Bassi et al., 2019). Recent studies have shown that the presence of vascular risk factors in subjects affected by MS could have an important influence on brain chronic injury and MRI outcomes (Kappus et al., 2016; Lorefice et al., 2019). Although with some differences among studies, an association between high BMI and an adverse lipid profile with worse clinical and MRI parameters of MS was reported in some series (Kappus et al., 2016; Weinstock-Guttman et al., 2011; Mowry et al., 2018). Conversely, our study showed that the lesion burden, the radiological activity and the neurological impairment at the time of MS diagnosis do not appear to be affected by overweight and hyperlipidemia. However, this result may have been influenced by the small number of patients in the highest BMI categories as well as from the relatively low number of patients with altered lipid profile as a total cholesterol >200 mg/dl and LDL levels > 100 mg/dl. Finally, notoriously vitamin D status is meaningful with respect to MS course principally via anti-inflammatory action (Smolders et al., 2008). Although over half of the patients had insufficient serum vitamin D levels at the time of diagnosis, no association was observed with clinical and MRI features (lesion burden and radiological activity). However, vitamin D levels were determined at the time of MS diagnosis, therefore an influence in relation to the season in which the determination was made is not excluded. Our study has several limitations that need to be mentioned. Firstly, lesion load was evaluated as unique surrogate of MRI severity, while brain atrophy measurements were not assessed. In addition, a differential diagnosis of white matter demyelinating lesions from micro vascular ones by using specific MRI sequences or lesion characterization (mapping and lesion morphology) was not performed (Hosseini et al., 2018; Geraldes et al., 2018). In fact, to obtain a complete picture of brain damage and to explore the impact of smoking and other lifestyle risk factors on brain injury, all the identified white matter alterations were estimated. In addition, as mentioned above, lipid and vitamin D levels were determined at the time of MS diagnosis and therefore potentially influenced by the period. No information on diet habits has been collected, while data regarding the use of specific medications/integrators were recorded.
Table 3 Characterization of MS smoker patients vs non smokers at diagnosis time.
Age (mean ± sd) Male EDSS score Lesion volumes (mean ± sd) ml Body mass index Altered lipid profile Vitamin D (ng/dl)
Smokers (40)
Non Smokers (24)
37.6 ± 11.4* 24 (60%)* 1.4 ± 1.0 3410 ± 3694* 23.9 ± 3.5 10 (25%) 26.5 ± 12.2
43.3 ± 9.8* 4 (16.6%)* 1.5 ± 1.2 1710 ± 1122* 23.2 ± 3.3 14 (58.3%)* 39.3 ± 30.9
T-test was used to compare lesion MRI burden, vitamin D levels and MS clinical variables between MS smokers and non-smokers. Chi 2 was used to other comparations. ⁎ P value: <0.05. Table 4 Characterization of MS overweight (BMI>25) patients vs non overweight at diagnosis time.
Age (mean ± sd) Male EDSS score Lesion volumes (mean ± sd) ml Altered lipid profile Vitamin D (ng/dl)
Overweight (40)
Non overweight (24)
47.3 ± 11.2* 8 (20%)* 1.5 ± 1.1
37.6 ± 10.2* 20 (83%)* 1.4 ± 1.1
4310 ± 4478* 20 (50%)* 26.5 ± 12.2
2341 ± 2481 5 (20.8%) 39.3 ± 30.9
T-test was used to compare lesion MRI burden, vitamin D level and MS clinical variables between overweight and non-overweight patients. Chi 2 was used to other comparations. Table 5 Multiple regression analysis. Relationships of lesion load with demographic, MS clinical features and smoking status. Lesion Load
Age Disease duration EDSS score Gd+ enhancing lesions Smoking status
B
95% C.I. for EXP (B) Lower Upper
p
55.75 1934.73 939.34 2378.15 2340.88
−9.47 660.90 288.26 228.58 850.60
0.092 0.004 0.005 0.031 0.003
120.98 3208.55 1590.41 4527.72 3831.16
Multiple linear regression analysis was used to examine the relationship between lesion load, which was included in the model as a dependent variable, and the presence of smoking habits, while controlling for demographic and clinical variables (disease duration and EDSS score).
4. Discussion Notoriously, the course of MS shows a great inter-individual variability (Cree et al., 2016). Although several clinical and MRI features are considered as prognostic indicators from the early stage of the disease (Tomassini et al., 2019), numerous other factors, including those unrelated to MS, could unpredictably modify its trajectory of evolution. Our study hypothesis was that the presence of some lifestyle risk factors, including smoking, overweight, hyperlipidemia and hypovitaminosis D, would increase the lesion load in MS, resulting in an additional effect on brain MRI damage visible already in the early phase of the disease. Previously, Zivadinov et al. reported in a large cohort of patients with MS that quantitative brain MRI markers, as lesion load and brain atrophy measurements, are affected by smoking, also indicating an increased risk for disease progression as suggested by higher EDSS score observed in smoker patients (Zivadinov et al., 2009). Our study, that included patients with recent MS diagnosis, showed that cigarette smoking seems to play a negative effect on the lesion burden already in early phase of the disease. No specific subtle tissue damage was 3
Multiple Sclerosis and Related Disorders 39 (2020) 101886
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5. Conclusions
213. Gouw, A.A., Seewann, A., van der Flier, W.M., et al., 2011. Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations. J. Neurol. Neurosurg. Psychiatry 82 (Feb (2)), 126–135. Guerrero-García, J.J., Carrera-Quintanar, L., López-Roa, R.I., et al., 2016. Multiple sclerosis and obesity: possible roles of adipokines. Mediators Inflamm. 2016, 4036232. Hempel, S., Graham, G.D., Fu, N., et al., 2017. A systematic review of modifiable risk factors in the progression of multiple sclerosis. Mult. Scler. 23 (Apr (4)), 525–533. Hosseini, Z., Matusinec, J., Rudko, D.A., et al., 2018. Morphology-Specific discrimination between MS white matter lesions and benign white matter hyperintensities using ultra-high-field MRI. AJNR Am. J. Neuroradiol. 39 (Aug (8)), 1473–1479. Jakimovski, D., Guan, Y., Ramanathan, M., et al., 2019. Lifestyle-based modifiable risk factors in multiple sclerosis: review of experimental and clinical findings. Neurodegener. Dis. Manag. 9 (Jun (3)), 149–172. Kappus, N., Weinstock-Guttman, B., Hagemeier, J., et al., 2016. Cardiovascular risk factors are associated with increased lesion burden and brain atrophy in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 87 (Feb (2)), 181–187. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33 (11), 1444–1452. Lorefice, L., Frau, J., Coghe, G., et al., 2019. Assessing the burden of vascular risk factors on brain atrophy in multiple sclerosis: a case- control MRI study. Mult. Scler. Relat. Disord. 27 (Jan), 74–78. Marrie, R.A., 2004. Environmental risk factors in multiple sclerosis aetiology. Lancet Neurol. 3 (Dec (12)), 709–718. Mora, F., 2013. Successful brain aging: plasticity, environmental enrichment, and lifestyle. Dialogues Clin. Neurosci. 15 (Mar (1)), 45–52. Mowry, E.M., Azevedo, C.J., McCulloch, C.E., et al., 2018. Body mass index, but not vitamin D status, is associated with brain volume change in MS. Neurology 91 (Dec (24)), e2256–e2264. Naik, P., Fofaria, N., Prasad, S., et al., 2014. Oxidative and pro-inflammatory impact of regular and denicotinized cigarettes on blood brain barrier endothelial cells: is smoking reduced or nicotine-free products really safe? BMC Neurosci. 15 (Apr (23)), 51. Novo, A.M., Batista, S., 2017. Multiple sclerosis: implications of obesity in neuroinflammation. Adv. Neurobiol. 19, 191–210. Olsson, T., Barcellos, L.F., Alfredsson, L., 2017. Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nat. Rev. Neurol. 13 (Jan (1)), 25–36. Petersen, E.R., Oturai, A.B., Koch-Henriksen, N., et al., 2018a. Smoking affects the interferon beta treatment response in multiple sclerosis. Neurology 90, e593–e600. Petersen, E.R., Søndergaard, H.B., Laursen, J.H., et al., 2018b. Smoking is associated with increased disease activity during natalizumab treatment in multiple sclerosis. Mult. Scler Aug 2:1352458518791753. Popescu, V., Agosta, F., Hulst, H.E., et al., 2013. Brain atrophy and lesion load predict long term disability in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 84 (Oct (10)), 1082–1091. Power, M.C., Deal, J.A., Sharrett, A.R., et al., 2015. Smoking and white matter hyperintensity progression: the ARIC-MRI study. Neurology 84 (Feb (8)), 841–848. Smolders, J., Damoiseaux, J., Menheere, P., et al., 2008. Vitamin D as an immune modulator in multiple sclerosis, a review. J. Neuroimmunol. 194 (Feb (1–2)), 7–17. Stampanoni Bassi, M., Iezzi, E., Buttari, F., et al., 2019. Obesity worsens central inflammation and disability in multiple sclerosis. Mult. Scler Jun 4:1352458519853473. Sundström, P., Nyström, L., 2008. Smoking worsens the prognosis in multiple sclerosis. Mult. Scler. 14 (Sep (8)), 1031–1035. Thompson, A.J., Banwell, B.L., Barkhof, F., et al., 2018. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 17 (Feb (2)), 162–173. Thompson, A.J., Baranzini, S.E., Geurts, J., et al., 2018. Multiple sclerosis. Lancet 391 (Apr (10130)), 1622–1636. Tomassini, V., Fanelli, F., Prosperini, L., et al., 2019. Predicting the profile of increasing disability in multiple sclerosis. Mult. Scler. 25 (Aug (9)), 1306–1315. Tomassini, V., Johansen-Berg, H., Jbabdi, S., et al., 2012. Relating brain damage to brain plasticity in patients with multiple sclerosis. Neurorehabil. Neural Repair 26 (Jul-Aug (6)), 581–593. Weinstock-Guttman, B., Zivadinov, R., Mahfooz, N., et al., 2011. Serum lipid profiles are associated with disability and MRI outcomes in multiple sclerosis. J. Neuroinflamm. 8 (Oct (4)), 127. Zivadinov, R., Weinstock-Guttman, B., Hashmi, K., et al., 2009. Smoking is associated with increased lesion volumes and brain atrophy in multiple sclerosis. Neurology 73 (Aug (7)), 504–510.
Our data indicated that the lesion burden, principal surrogate of MRI severity and worse long-term clinical outcomes, is affected by smoking already at the time of MS diagnosis. Instead, it is conceivable that the low number of patients included in the study may have prevented to observe possible significant associations with the other explored modifiable risk factors. Further investigations in larger and multi-centre cohorts are necessary to confirm the effects of smoking on clinical and MRI outcomes in early MS, also exploring how lesion burden changes in smokers and the possible relationships with brain volume loss. Exploring modifiable risk factors may highlight the complex underlying mechanisms of MS heterogeneity as well as the different trajectories of MS evolution. Therefore, it is crucial to identify the modifiable lifestyle and health risk factors that could be targeted in interventions as well as to improve health outcomes for people with MS. CRediT authorship contribution statement Lorefice L: Conceptualization, Formal analysis, Writing - original draft. Destro F: Conceptualization, Formal analysis, Writing - original draft. Fenu G: Conceptualization, Formal analysis, Writing - original draft. Mallus M: Writing - review & editing. Gessa I: Writing - review & editing. Sechi V: . Barracciu MA: Writing - review & editing. Frau J: Writing - review & editing. Coghe G: Writing - review & editing. Carmagnini D: Writing - review & editing. Marrosu MG: Supervision, Writing - review & editing. Saba L: Writing - review & editing, Conceptualization, Supervision. Cocco E: Writing - review & editing, Conceptualization, Supervision. Declaration of Competing Interest Dr. L. Lorefice, G. Fenu, J.Frau, G. Coghe, MG Marrosu, E. Cocco received travel grant, speaker fee and consultancy from Biogen Idec, Sanofi, Teva, Admirall, Genzyme, Merck Serono, and Novartis; Dr D. Carmagnini received travel grant from Teva; Dr. Barracciu, Dr Sechi received travel grant from Biogen Idec; Professor L. Saba, Dr. F. Destro, Mrs I. Gessa and Mrs M. Mallus have nothing to disclose. Acknowledgment None. References Alrouji, M., Manouchehrinia, A., Gran, B., et al., 2019. Effects of cigarette smoke on immunity, neuroinflammation and multiple sclerosis. J. Neuroimmunol. 329 (Apr), 24–34. Arnson, Y., Shoenfeld, Y., Amital, H., 2010. Effects of tobacco smoke on immunity, inflammation and autoimmunity. J. Autoimmun. 34 (May (3)), J258–J265. Ascherio, A., Munger, K.L., White, R., et al., 2014. Vitamin D as an early predictor of multiple sclerosis activity and progression. JAMA Neurol. 71 (Mar (3)), 306–314. Colotta, F., Jansson, B., Bonelli, F., 2017. Modulation of inflammatory and immune responses by vitamin D. J. Autoimmun. 85 (Dec), 78–97. Cree, B.A., Gourraud, P.A., Oksenberg, J.R., et al., 2016. Long-term evolution of multiple sclerosis disability in the treatment era. Ann. Neurol. 80 (Oct (4)), 499–510. Geraldes, R., Ciccarelli, O., Barkhof, F., et al., 2018. The current role of MRI in differentiating multiple sclerosis from its imaging mimics. Nat. Rev. Neurol. 14 (Mar (4)),
4
Contents lists available at ScienceDirect
Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard
The impact of modifiable risk factors on lesion burden in patients with early multiple sclerosis
T
Lorefice La,1, , Destro Fb,1, Fenu Ga, Mallus Mc, Gessa Ia, Sechi Vd, Barracciu MAd, Frau Ja, Coghe Ga, Carmagnini Dc, Marrosu MGc, Saba Lb, Cocco Ec ⁎
a
MS Centre, Binaghi Hospital, ATS Sardegna, Cagliari, Italy Department of Radiology, University of Cagliari, Italy c MS Centre, Department of Medical Sciences and Public Health, University of Cagliari, Italy d Radiology Unit, Binaghi Hospital, ATS Sardegna, Cagliari, Italy b
ABSTRACT
Introduction: Some studies have indicated the importance of considering smoking, vitamin D deficiency and obesity as negative prognostic factors for clinical and MRI outcomes in multiple sclerosis (MS). This study aimed to evaluate the possible effects of these modifiable risk factors on brain MRI lesion burden of patients with early MS, also exploring the influence on initial clinical features. Methods: MS patients were enrolled at diagnosis time and examined for smoking, body mass index (BMI), serum level of lipids and 25(OH) vitamin D. Brain MRIs’ were acquired and lesion volume assessed by Jim software. Clinical data (disease course, disease duration, and EDSS score) were also collected. Results: 64 patients were enrolled, of these 4 (6.2%) had a primary progressive course. Mean age was 39.8 ± 11.1 years and mean EDSS 1.5 ± 1.1. Forty (62.5%) patients were smokers and 40 (62.5%) were overweight (BMI>25). Insufficient levels of vitamin D (<20 ng/mL) were reported in 36 (56.2%) patients, while 24 (37.5%) patients had an altered lipid profile with total cholesterol >200 mg/dl and LDL >100 mg/dl. No association between early clinical features and modifiable risk factors were reported. Multiple regression analysis showed an association between lesion burden and smoking status (p 0.003), while no association was reported with BMI, altered lipid profile and vitamin D insufficiency. Conclusions: Several risk factors may play a role in evolution of MS. Our results show that smoking status, probably due to chronic vascular and neurotoxic effects of the cigarette components, can affect the brain damage from the early stages of MS. No association was observed with the other explored modifiable risk factors, although an effect due to the small sample size cannot be excluded.
1. Introduction Multiple sclerosis (MS) is a lifelong inflammatory and neurodegenerative disease characterized by great heterogeneity in clinical and radiologic features with different prognosis and long-term outcomes (Thompson et al., 2018). As epidemiologic studies have previously shown, MS rates vary with several environmental factors, suggesting a putative role of numerous potentially modifiable risk factors (Olsson et al., 2017; Marrie, 2004). In addition to their possible etiological role in MS, many of these factors may explain and influence the phenotypic and neuroradiological heterogeneity as well as the different trajectories of MS evolution (Hempel et al., 2017). A substantial amount of research has been dedicated to the role of lifestyle-related factors as smoking, obesity, altered lipid profiles, and serum vitamin D levels on MS course (Jakimovski et al.,2019 ). Smoking increases twice the risk of MS and can also aggravate its course both acutely and chronically (Alrouji et al., 2019). In particular, smoking intensity is associated with an increased
relapse rate of over 30%, with a reduced response to disease modifying treatments (DMDs) (Petersen et al., 2018a,b), and with worse disease progression and disability (Sundström and Nyström, 2008). Analogously, several studies indicated that obesity and vitamin D insufficiency, acting by different mechanisms (Novo and Batista, 2017; Guerrero-García et al., 2016; Colotta et al., 2017), seem to be associated with poorer MS clinical outcomes (Ascherio et al., 2014; Stampanoni Bassi et al., 2019). However, the impact of these factors on the neuroradiological characteristics of MS patients, in particular on lesion burden and brain volume, is instead still relatively unexplored, although growing evidence indicate these MRI parameters as gold predictive markers of long-term MS-related disability (Popescu et al., 2013). Based on these considerations, this study aimed to evaluate the possible effects of cigarette smoking, overweight, altered serum lipid profile and vitamin D levels on brain MRI lesion volume of patients with MS at the time of diagnosis, also exploring the influence on early clinical features.
Correspondence to: Multiple Sclerosis Centre, Binaghi Hospital, ATS Sardegna, Via Is Guadazzonis 2, 09126 Cagliari, Italy. E-mail address: [email protected] (L. L). 1 These authors equally contributed. ⁎
https://doi.org/10.1016/j.msard.2019.101886 Received 10 September 2019; Received in revised form 4 December 2019; Accepted 7 December 2019 2211-0348/ © 2019 Elsevier B.V. All rights reserved.
Multiple Sclerosis and Related Disorders 39 (2020) 101886
L. L, et al.
2. Methods
Table 1 Demographic and clinical features of MS patients included in the study.
2.1. Patients
64 MS patients
The study included a cohort of MS patients (according to 2017 revisions of the McDonald criteria) (Thompson et al., 2018) recruited at the time of diagnosis at the Regional MS centre of Cagliari. The patient's demographic characteristics (sex and age) and clinical data [disease course, disease duration, and disability level, evaluated using the Expanded Disability Status Scale (EDSS)] (Kurtzke, 1983), were collected. For each patient, height and weight were measured at diagnosis time and, after the body mass index (BMI) as weight (kg)/height (m2) was obtained, participants were divided in overweight (BMI ≥ 25) and non overweight (BMI<25). Information was collected regarding smoking habits and subjects were classified as “never-smokers” or “active-smokers”, including subjects who smoked more than 10 cigarettes per day for at least 6 months in the 2 years prior to diagnosis. All brain MRI acquisitions performed at the time of diagnosis at the MS centre have been examined, thus radiological activity and brain white matter lesion volume was evaluated for each patient. Finally, serum samples were collected to evaluate lipid profile and vitamin D level. The local ethics committee approved the study and informed consent was obtained from all patients prior to participation.
Male Gender Age (mean ± sd) years MS Disease Duration (mean ± sd) years Progressive course EDSS score Lesion volumes (mean ± sd) ml Gd enhancing lesions
28 (43.8%) 39.8 ± 11.1 2.1 ± 0.5 4 (6.2%) 1.5 ± 1.1 2772 ± 3098 8 (12.5%)
variables (disease duration, EDSS score, radiological activity). For all assays, statistical significance was set at p < 0.05. 3. Results The sample included 64 patients with early diagnosis of MS (male 28; 43.8%). Of these, 4 (6.2%) had a primary progressive course. Mean values for age and disease duration were 39.8 (SD ± 11.1) and 1.1 (SD ± 0.5) years respectively, while mean EDSS was 1.5 (SD ± 1.1). Table 1 shows the demographic and clinical features of MS patients examined in the study, with information of mean lesion volume (2772 ± 3098 mm3) and percentage of patients with radiological activity (8; 12.5%) at diagnostic MRI acquisition. Of all patients, 40 (66.6%) were active smokers and 40 (66.6%) were overweight (BMI ≥ 25); the presence of both risk factors was reported in 14 (21.8%) patients. Biochemical analyses showed that 36 (56.2%) patients had insufficient levels of vitamin D (<20 ng/mL) and 24 (37.5%) had an altered lipid profile with increased total cholesterol (>200 mg/dl) and LDL (>100 mg/dl) (Tables 2). Using independentsamples t-tests, significant difference in lesion volume at diagnosis time was observed between active and never smokers (3410 ± 3694 vs 1710 ± 1122 mm3; p < 0.005), as well as between overweight and non-overweight patients (4310 ± 4478 vs 2341 ± 2481 mm3; p < 0.005). The smokers’ group mainly included young and male subjects, while an older age and a female predominance was observed in the group of overweight patients (p < 0.05). Tables 3 and 4 show a characterization of these groups, including information regarding BMI, vitamin D and lipid levels. The possible relationships between each modifiable risk factor and lesion load were explored by linear regression analyses, showing a significant association after unadjusted analysis only with smoking habit (p < 0.005). On the contrary, no association was observed with BMI, vitamin D insufficiency and altered lipid profile. As shown in table 5, a multiple regression analysis was performed, confirming that in smoker patients a higher lesion burden was observed (p = =0.003), independently from disease duration (p = =0.004), EDSS score (p = =0.005) and radiological activity (p = =0.031).
2.2. MRI assessments Brain MRIs were performed using a 1.5 T scanner (Siemens Medical Solutions, Erlangen, Germany). For each patient, sequences of dualecho proton density, fluid-attenuated inversion recovery, T1-weighted spin-echo (SE), T2-weighted fast SE, and contrast-enhanced T1weighted SE after intravenous gadolinium (Gd) infusion were obtained to define MS diagnosis. Radiological activity was defined as the presence of Gd+ lesions. Segmentation of brain white matter lesions, hyperintense on FLAIR acquisitions, and lesion volume measurements were performed by a single observer using Jim 7, a previously described semi-automated segmentation technique (Jim 7, Xinapse System, Leicester, UK, http://www.xinapse.com). 2.3. Biochemical serum analyses Non-fasting serum samples were collected at diagnosis time and, after centrifugation, total cholesterol and low-density lipoprotein cholesterol (LDL) were estimated using recommended procedures. Furthermore, the 25-hydroxyvitamin D concentration (vitamin D level) was measured with a commercially available radioimmunoassay. All biochemical serum analyses were centralized and performed at the regional MS centre of Cagliari. 2.4. Statistical analysis Statistical analyses were performed using SPSS for Mac version 22.0 (SPSS Inc., Chicago, IL, USA). Firstly, a descriptive analysis was done summarising patients’ demographic and clinical data as a mean for quantitative variables and percentages for qualitative variables. Demographic and clinical differences of “never-smokers” versus “active-smokers” and of overweight versus not overweight patients were evaluated using t-tests and chi-squared tests. After checking of the linearity assumption and normality testing of lesion load, linear regression analyses were performed to explore the relationships between brain lesion volume, which was entered into the model as a quantitative dependent variable, and the presence of each modifiable risk factor (smoking status, BMI, altered lipid profile and Vitamin D insufficiency). Thus, for the modifiable risk factors that are significantly associated in the unadjusted analysis, a multivariate analysis was performed while controlling for demographic and clinical
Table 2 Body mass index, cholesterol values, vitamin D level and smoking status at diagnostic brain MRI time. 64 MS patients Smokers Body mass index (mean ± sd) Overweight (BMI≥ 25) Total cholesterol (mean ± sd mg/dl) LDL (mean ± sd md/dl) *Altered lipid profile Vitamin D (mean ± sd ng/ml) Vitamin D insufficiency (<20 ng/mL)
40 (62.5%) 23.6 ± 3.5 40 (62.5%) 208.5 ± 50.1 114.1 ± 31.9 24 (37.5%) 31.2 ± 21.8 40 (62.5%)
⁎ The group with altered lipid profile included subjects with increased total cholesterol (>200 mg/dl) and LDL levels (> 100 mg/dl).
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observed in these patients that were predominantly young and therefore with relatively short duration of smoking exposure. No association was observed with particular early clinical features as higher neurological disability or with the presence of radiological activity at brain MRI, as some studies reported (Zivadinov et al., 2009; Kappus et al., 2016). Nevertheless, it is not excluded that the small sample size and the low EDSS observed in most patients may have affected this result. In addition, although a high level of structural brain damage may be present at MS onset, it is common not to observe a concomitant neurological disability, which can occur over time in relation to the progressive reduction of brain plasticity due to both aging and the accumulation of chronic brain damage during the disease (Tomassini et al., 2012), both aspects that could be affected by smoking exposure resulting in worse long-term MS outcomes (Mora, 2013). There are many mechanisms by which cigarette smoke can impact on brain damage. Firstly nicotine, the major component of cigarettes, shows to augment the generation of auto reactive pro-inflammatory T cells and of numerous pro-inflammatory cytokines, triggering the autoimmune cascade (Arnson et al., 2010). In addition, smoking exposure can induce the production of free radicals, resulting in microvascular endothelial alterations and impairment of the blood-brain barrier that, being the entry site of immune cells into the brain, is crucial in pathogenesis and progression of several neurological disorders including MS (Naik et al., 2014). Lastly, smoking habits are related to cerebral small vessels disease characterized by white matter alterations and leukoaraiosis (Gouw et al.,2011; Power et al., 2015) that could complicate the identification of demyelinating white matter lesions. Analogously to smoke, some studies indicated that obesity and altered lipid profile might induce vascular endothelium alterations with breakdown of the blood-brain-barrier leading to central inflammation (Stampanoni Bassi et al., 2019). Recent studies have shown that the presence of vascular risk factors in subjects affected by MS could have an important influence on brain chronic injury and MRI outcomes (Kappus et al., 2016; Lorefice et al., 2019). Although with some differences among studies, an association between high BMI and an adverse lipid profile with worse clinical and MRI parameters of MS was reported in some series (Kappus et al., 2016; Weinstock-Guttman et al., 2011; Mowry et al., 2018). Conversely, our study showed that the lesion burden, the radiological activity and the neurological impairment at the time of MS diagnosis do not appear to be affected by overweight and hyperlipidemia. However, this result may have been influenced by the small number of patients in the highest BMI categories as well as from the relatively low number of patients with altered lipid profile as a total cholesterol >200 mg/dl and LDL levels > 100 mg/dl. Finally, notoriously vitamin D status is meaningful with respect to MS course principally via anti-inflammatory action (Smolders et al., 2008). Although over half of the patients had insufficient serum vitamin D levels at the time of diagnosis, no association was observed with clinical and MRI features (lesion burden and radiological activity). However, vitamin D levels were determined at the time of MS diagnosis, therefore an influence in relation to the season in which the determination was made is not excluded. Our study has several limitations that need to be mentioned. Firstly, lesion load was evaluated as unique surrogate of MRI severity, while brain atrophy measurements were not assessed. In addition, a differential diagnosis of white matter demyelinating lesions from micro vascular ones by using specific MRI sequences or lesion characterization (mapping and lesion morphology) was not performed (Hosseini et al., 2018; Geraldes et al., 2018). In fact, to obtain a complete picture of brain damage and to explore the impact of smoking and other lifestyle risk factors on brain injury, all the identified white matter alterations were estimated. In addition, as mentioned above, lipid and vitamin D levels were determined at the time of MS diagnosis and therefore potentially influenced by the period. No information on diet habits has been collected, while data regarding the use of specific medications/integrators were recorded.
Table 3 Characterization of MS smoker patients vs non smokers at diagnosis time.
Age (mean ± sd) Male EDSS score Lesion volumes (mean ± sd) ml Body mass index Altered lipid profile Vitamin D (ng/dl)
Smokers (40)
Non Smokers (24)
37.6 ± 11.4* 24 (60%)* 1.4 ± 1.0 3410 ± 3694* 23.9 ± 3.5 10 (25%) 26.5 ± 12.2
43.3 ± 9.8* 4 (16.6%)* 1.5 ± 1.2 1710 ± 1122* 23.2 ± 3.3 14 (58.3%)* 39.3 ± 30.9
T-test was used to compare lesion MRI burden, vitamin D levels and MS clinical variables between MS smokers and non-smokers. Chi 2 was used to other comparations. ⁎ P value: <0.05. Table 4 Characterization of MS overweight (BMI>25) patients vs non overweight at diagnosis time.
Age (mean ± sd) Male EDSS score Lesion volumes (mean ± sd) ml Altered lipid profile Vitamin D (ng/dl)
Overweight (40)
Non overweight (24)
47.3 ± 11.2* 8 (20%)* 1.5 ± 1.1
37.6 ± 10.2* 20 (83%)* 1.4 ± 1.1
4310 ± 4478* 20 (50%)* 26.5 ± 12.2
2341 ± 2481 5 (20.8%) 39.3 ± 30.9
T-test was used to compare lesion MRI burden, vitamin D level and MS clinical variables between overweight and non-overweight patients. Chi 2 was used to other comparations. Table 5 Multiple regression analysis. Relationships of lesion load with demographic, MS clinical features and smoking status. Lesion Load
Age Disease duration EDSS score Gd+ enhancing lesions Smoking status
B
95% C.I. for EXP (B) Lower Upper
p
55.75 1934.73 939.34 2378.15 2340.88
−9.47 660.90 288.26 228.58 850.60
0.092 0.004 0.005 0.031 0.003
120.98 3208.55 1590.41 4527.72 3831.16
Multiple linear regression analysis was used to examine the relationship between lesion load, which was included in the model as a dependent variable, and the presence of smoking habits, while controlling for demographic and clinical variables (disease duration and EDSS score).
4. Discussion Notoriously, the course of MS shows a great inter-individual variability (Cree et al., 2016). Although several clinical and MRI features are considered as prognostic indicators from the early stage of the disease (Tomassini et al., 2019), numerous other factors, including those unrelated to MS, could unpredictably modify its trajectory of evolution. Our study hypothesis was that the presence of some lifestyle risk factors, including smoking, overweight, hyperlipidemia and hypovitaminosis D, would increase the lesion load in MS, resulting in an additional effect on brain MRI damage visible already in the early phase of the disease. Previously, Zivadinov et al. reported in a large cohort of patients with MS that quantitative brain MRI markers, as lesion load and brain atrophy measurements, are affected by smoking, also indicating an increased risk for disease progression as suggested by higher EDSS score observed in smoker patients (Zivadinov et al., 2009). Our study, that included patients with recent MS diagnosis, showed that cigarette smoking seems to play a negative effect on the lesion burden already in early phase of the disease. No specific subtle tissue damage was 3
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5. Conclusions
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Our data indicated that the lesion burden, principal surrogate of MRI severity and worse long-term clinical outcomes, is affected by smoking already at the time of MS diagnosis. Instead, it is conceivable that the low number of patients included in the study may have prevented to observe possible significant associations with the other explored modifiable risk factors. Further investigations in larger and multi-centre cohorts are necessary to confirm the effects of smoking on clinical and MRI outcomes in early MS, also exploring how lesion burden changes in smokers and the possible relationships with brain volume loss. Exploring modifiable risk factors may highlight the complex underlying mechanisms of MS heterogeneity as well as the different trajectories of MS evolution. Therefore, it is crucial to identify the modifiable lifestyle and health risk factors that could be targeted in interventions as well as to improve health outcomes for people with MS. CRediT authorship contribution statement Lorefice L: Conceptualization, Formal analysis, Writing - original draft. Destro F: Conceptualization, Formal analysis, Writing - original draft. Fenu G: Conceptualization, Formal analysis, Writing - original draft. Mallus M: Writing - review & editing. Gessa I: Writing - review & editing. Sechi V: . Barracciu MA: Writing - review & editing. Frau J: Writing - review & editing. Coghe G: Writing - review & editing. Carmagnini D: Writing - review & editing. Marrosu MG: Supervision, Writing - review & editing. Saba L: Writing - review & editing, Conceptualization, Supervision. Cocco E: Writing - review & editing, Conceptualization, Supervision. Declaration of Competing Interest Dr. L. Lorefice, G. Fenu, J.Frau, G. Coghe, MG Marrosu, E. Cocco received travel grant, speaker fee and consultancy from Biogen Idec, Sanofi, Teva, Admirall, Genzyme, Merck Serono, and Novartis; Dr D. Carmagnini received travel grant from Teva; Dr. Barracciu, Dr Sechi received travel grant from Biogen Idec; Professor L. Saba, Dr. F. Destro, Mrs I. Gessa and Mrs M. Mallus have nothing to disclose. Acknowledgment None. References Alrouji, M., Manouchehrinia, A., Gran, B., et al., 2019. Effects of cigarette smoke on immunity, neuroinflammation and multiple sclerosis. J. Neuroimmunol. 329 (Apr), 24–34. Arnson, Y., Shoenfeld, Y., Amital, H., 2010. Effects of tobacco smoke on immunity, inflammation and autoimmunity. J. Autoimmun. 34 (May (3)), J258–J265. Ascherio, A., Munger, K.L., White, R., et al., 2014. Vitamin D as an early predictor of multiple sclerosis activity and progression. JAMA Neurol. 71 (Mar (3)), 306–314. Colotta, F., Jansson, B., Bonelli, F., 2017. Modulation of inflammatory and immune responses by vitamin D. J. Autoimmun. 85 (Dec), 78–97. Cree, B.A., Gourraud, P.A., Oksenberg, J.R., et al., 2016. Long-term evolution of multiple sclerosis disability in the treatment era. Ann. Neurol. 80 (Oct (4)), 499–510. Geraldes, R., Ciccarelli, O., Barkhof, F., et al., 2018. The current role of MRI in differentiating multiple sclerosis from its imaging mimics. Nat. Rev. Neurol. 14 (Mar (4)),
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