Background Cardiovascular (CV) risk factors have been associated with changes in clinical outcomes in patients with multiple sclerosis (MS).
Objectives To investigate the frequency of CV risks in patients with MS and their association with MRI outcomes.
Methods In a prospective study, 326 patients with relapsing–remitting MS and 163 patients with progressive MS, 61 patients with clinically isolated syndrome (CIS) and 175 healthy controls (HCs) were screened for CV risks and scanned on a 3T MRI scanner. Examined CV risks included hypertension, heart disease, smoking, overweight/obesity and type 1 diabetes. MRI measures assessed lesion volumes (LVs) and brain atrophy. Association between individual or multiple CV risks and MRI outcomes was examined adjusting for age, sex, race, disease duration and treatment status.
Results Patients with MS showed increased frequency of smoking (51.7% vs 36.5%, p=0.001) and hypertension (33.9% vs 24.7%, p=0.035) compared with HCs. In total, 49.9% of patients with MS and 36% of HCs showed ≥2 CV risks (p=0.003), while the frequency of ≥3 CV risks was 18.8% in the MS group and 8.6% in the HCs group (p=0.002). In patients with MS, hypertension and heart disease were associated with decreased grey matter (GM) and cortical volumes (p<0.05), while overweight/obesity was associated with increased T1-LV (p<0.39) and smoking with decreased whole brain volume (p=0.049). Increased lateral ventricle volume was associated with heart disease (p=0.029) in CIS.
Conclusions Patients with MS with one or more CV risks showed increased lesion burden and more advanced brain atrophy.
- MULTIPLE SCLEROSIS
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Multiple sclerosis (MS) is an autoimmune demyelinating, inflammatory and neurodegenerative disease of the central nervous system (CNS).1 A complex environmental and genetic multifactorial interplay is associated with the risk of developing MS.2 Evidence is mounting that environmental risk factors like exposure to the Epstein-Barr virus, decreased vitamin D levels, smoking and altered lipid metabolism are associated with MS progression.3–11
The progression of MS may be related to other risk factors, including underlying comorbidities.12 Patients who reported more than one cardiovascular (CV) risk factors at the time of diagnosis had an increased chance of ambulatory disability, and the risk increased with the number of CV risk factors reported.13 Two nationwide Danish mortality studies reported that patients with MS had more than a 30% higher risk of death due to CV disease, including cerebrovascular disease, compared with the age-matched general population.14 ,15 Another Danish study showed that the risk of CV disease among patients with incident MS is relatively low, but higher than that in the general population.16 A higher risk of death due to CV disease, excluding stroke (6%), was also reported in a study from South Wales.17
CV risk factors like hypertension, hyperlipidaemia and heart disease are associated with increased number of brain white matter (WM) signal abnormalities18 and decreased grey matter (GM) volume19–21 in the general population. A number of recent studies have investigated the relationship between individual CV risk factors and MRI measures of MS disease progression. Smoking and altered lipid profiles are positively associated with more severe MRI outcomes.5 ,8 ,11 ,22 ,23 African-Americans, who have an increased rate of CV risk factors compared with Caucasians,24 have been shown to have greater lesion burden and more brain atrophy in patients with MS.25
The primary goal of this study was to investigate the frequency of CV risk factors in a large cohort of patients with MS, compared with that of healthy controls (HCs) and patients with clinically isolated syndrome (CIS), and assess their association with MRI outcomes of disease severity.
This study utilised baseline data from an ongoing prospective study of genetic and environmental risk factors in MS that enrolled over 1000 participants with CIS, MS, HCs and other neurological diseases.26 ,27 The inclusion criteria for this substudy of CV risk factors were: (A) age 18–75 years, (B) being CIS, MS or HC and (C) having an MRI examination performed within 30 days of physical/neurological examination with the standardised study protocol. Exclusion criteria were: presence of relapse and steroid treatment in the 30 days preceding study entry for patients with CIS and MS, pre-existing medical conditions known to be associated with brain pathology (cerebrovascular disease, positive history of alcohol abuse) and pregnancy. Seven hundred and twenty-five consecutive participants who fulfilled inclusion and exclusion criteria entered this substudy of CV risk factors in MS. These included 489 patients with MS, of whom 326 (66.7%) had relapsing–remitting (RR) MS, 127 (26%) had secondary-progressive (SP) MS and 36 (7.4%) had primary-progressive (PP) MS, as well as 61 patients with CIS and 175 HCs.
Participants underwent a clinical and MRI examination. All participants were assessed with a structured environmental questionnaire, and had a physical and neurological examination. CV risk factors were collected from all participants in person by a trained interviewer with cross-examination of medical records.28 The details of the structured questionnaire were reported previously.28
HCs needed to meet the health screen MRI requirements and had to have a normal neurological examination. They were recruited from hospital personnel, respondents to a local advertisement or were spouses of patients with MS. Vascular risks or heart disease (see below for a more detailed definition) did not represent an exclusion criterion.
Race/ethnicity was determined according to the US Census Bureau definitions. Body mass index (BMI) was obtained during the examination and participants were divided into four categories: underweight <18.5, normal weight 18.5–24.9, overweight 25–29.9 and obesity BMI >30 kg/m2 or greater.
The CV risk factors included evaluation of hypertension, heart disease, smoking and overweight/obesity (defined as BMI >25 kg/m2) and type 1 diabetes. The heart disease classification feature included any of the following: history of heart attack, status post stenting or coronary artery bypass graft, arrhythmia, valvular disease, heart murmurs, enlarged heart or congestive heart failure.
Information was collected regarding the active and former smoking habits. Active smokers were classified as individuals who smoked more than 10 cigarettes per day in the 3 months prior to the start of the study, while former smokers were those who had smoked consecutively for a minimum of 6 months at some point in the past.8 For the purpose of this study, participants were divided into ever/never smokers.
The study protocol was approved by the local Institutional Review Board and all participants gave their written informed consent.
MRI acquisition and analysis
All participants were examined on a 3T GE Signa Excite HD 12.0 Twin Speed 8-channel scanner (General Electric, Milwaukee, Wisconsin, USA), using an 8-channel head and neck (HDNV) coil. MRI sequences included the axial dual fast spin-echo (FSE) T2/PD-weighted image (WI), 3D-spoiled-gradient recalled (SPGR) T1-WI, spin-echo (SE) T1-WI precontrast and fluid attenuated inversion recovery (FLAIR) scans, as previously reported.29
MRI analysts were blinded to the participant's physical and neurological condition. The MRI measures included in the analysis were T1 and T2 lesion number and lesion volumes (LVs), assessed by a semiautomated edge detection contouring/thresholding technique,29 and measures of brain atrophy, including normalised brain parenchymal (NBPV), GM (NGMV), WM (NWMV) and lateral ventricle volume (NLVV),29 assessed by the SIENAX 2.6 cross-sectional software tool.30
Analyses were conducted using Statistical Package for Social Science, V.20.0 (IBM, Armonk, New York, USA). Differences in the categorical variables between the groups were analysed using the χ2 test. An analysis of variance and covariance (ANCOVA), adjusted for age and sex, were used to analyse the differences in continuous variables between the groups. The differences in ordinal variables between the groups were assessed using non-parametric statistics.
The CV risk factors were categorised based on their presence/absence of individual CV risks or based on the number of combined CV risks. OR and 95% CI were calculated. In order to decrease the number of disease subgroups, patients with SP and PP MS were merged into the progressive MS (PMS, n=163) disease subgroup. The data were separately investigated by disease group (HC, CIS, MS) and by the disease subgroup status (RRMS and PMS). In order to decrease the number of comparisons, the SPMS and PPMS patient groups were merged into the PMS group because no CV risk factors frequency differences were found.
We used ANCOVA, adjusted for age, sex, race, disease duration and treatment status, to investigate associations between CV risk factors and MRI outcomes. In the ANCOVA analysis, CV risk factors were entered into the model as dependent, and the MRI variables as independent. The treatment status included duration in months and type of MS disease-modifying therapies.
The association analyses between individual and combined CV risk factors and MRI outcomes were corrected for multiple comparisons using the Benjamini-Hochberg correction. Nominal p values <0.05 were regarded as significant, using two-tailed testing.
Subject demographic, clinical and MRI characteristics
The mean age of patients with MS was 47.3 years (SD=10.9) and 70.6% of the patients with MS were females (table 1). As expected, the MS group had a greater number and volume of T2 lesions compared with HCs. The MS group also had lower NBPV, NGMV, increased NLVV (all p<0.0001) and significantly decreased NWMV (p=0.0001).
Table 2 provides demographic, clinical and MRI characteristics of patients with CIS, RRMS and PMS. As expected, there was a significantly different mean age, disease duration (both p<0.0001), age at onset (p=0.007), median Expanded Disability Status Score (p<0.0001) and treatment status (p=0.018) among the three disease subgroups. There were also significant differences for all MRI outcomes among the three disease subgroups (p≤0.001).
Frequency of CV risk factors
Tables 3 and 4 show the frequency of individual CV risk factors among the study groups. Relatively small amounts of CV risks were not collected (range 2.3–5.9%). Patients with MS showed significantly increased frequency of smoking compared with HCs (50.7% vs 34.3%, p=0.001, table 3). No significant differences in smoking were found between the disease subgroups (table 4). The frequency of hypertension in patients with MS was higher compared with HCs (30.3% vs 21.7%, p=0.035, table 3). There was no evidence for differences in the frequency of hypertension between the disease subgroups (table 4). No significant differences in the presence of heart disease were found between patients with MS (21.1%) and HCs (18.3%). The number of patients with MS who were classified as overweight/obese (55.8%) according to their BMI status did not differ from the number of HCs (54.3%). No significant differences in overweight/obesity were found between the disease subgroups (table 4). Only three participants (0.4%) had type 1 diabetes, with one in HC and two in the RRMS group. Owing to the low frequency of type 1 diabetes, this CV variable was excluded from further analyses.
Tables 3 and 4 show the frequency of the combinations of two or more CV risk factors among the HC and MS groups. Among the participants who had two or more CV risk factors, 244 (49.9%) were in the MS group and 63 (36%) in the HC group (p=0.003, table 3). The frequency of the combination of three or more CV risk factors was also significantly increased in patients with MS compared with HCs (18.8% vs 8.6%, p=0.002, table 3). Patients with MS also showed an increased frequency of several combinations of two or more CV risk factors compared with HCs (p<0.01, table 3). No significant differences were found in any of the combinations of two or more CV risk factors between the three disease subgroups.
Association between MRI outcomes and CV risk factors
Table 5 summarises the ANCOVA analyses regarding associations between the CV risk factors and MRI outcomes in the study groups. There was an association between hypertension and decreased NGMV (p=0.042) and NCV (p=0.046) in the overall MS group. There was also an association between heart disease and decreased NGMV (p=0.029) and NCV (p=0.033) in the overall MS group, decreased NGMV (p=0.046) in RRMS and increased NLVV (p=0.029) in patients with CIS. The presence of overweight/obesity was associated with increased T1-LV in patients with MS (p=0.039) and RRMS (p=0.048). There were also a significant association between smoking and decreased NBPV (p=0.049) in the overall MS group. There were no significant associations between MRI outcomes and individual CV risk factors among the participants in the HC group.
Table 5 also summarises the associations between combinations of two or more CV risk factors and MRI outcomes. Overall, patients with MS who presented with two or more CV risk factors had decreased NGMV (p<0.001) and normalised cortical volume (NCV; p=0.003). This was confirmed in the RRMS disease subgroup. Among combinations of two or more CV risk factors, those patients who had hypertension and were smoking showed decreased NGMV (p=0.034) in the overall MS group and increased T2-LV (p=0.035) in the RRMS group. Hypertension and overweight/obesity were associated with decreased NGMV in the RRMS group (p=0.048), whereas heart disease and smoking were associated with increased NLVV (p=0.048) in patients with CIS.
A combination of three or more CV risk factors was associated with decreased NGMV (p=0.04) and NCV (p=0.048) in the overall MS group. A combination of hypertension, heart disease and overweight/obesity was associated with increased T2-LV in the overall MS group (p=0.009) and with increased NLVV (p=0.045) in the PMS group. In the overall MS group with patients with RRMS and PMS, a combination of smoking, heart disease and hypertension was associated with significantly increased T2-LV (p<0.05). Finally, a combination of hypertension, smoking and overweight/obesity was associated with decreased NBPV and NGMV (p<0.005) in the RRMS group and increased NLVV (p=0.045) in the PMS group.
This is the first large cohort study to investigate the relationship between multiple CV risk factors and MRI outcomes in patients with MS. The findings showed that patients with MS with one or more CV risks present with increased lesion burden and more advanced brain atrophy. These findings were not observed in age-matched and sex-matched HCs. The study confirmed previous observations showing increased frequency of CV risk factors in MS.13–17 Increased frequency of smoking and hypertension, and of two or three combined CV risks was detected in patients with MS compared with HCs. However, no CV risk differences among MS disease subgroups were detected. This finding is of particular interest when considering that patients with RRMS and CIS were approximately 10–15 years younger in age than patients with PMS, suggesting that CV comorbidities occur earlier in patients with MS than was previously thought.13–17 In fact, patients with CIS who presented with the heart disease had more advanced central atrophy, as measured by increased NLVV. However, it has to be noted that the patients with CIS recruited in the study were somewhat older and had a longer disease duration then is usually reported,31 ,32 which could explain the somewhat higher frequency of CV risk factors in this disease subgroup.
It has been established that CV comorbidities, including smoking, hypertension, hyperlipidaemia, overweight/obesity, diabetes and heart disease can lead to inflammatory neurological disease.33 A number of studies investigated the relationship between CV risk factors and type of neurological injury in ageing and different neurological disease states. Some of these studies showed that the presence and severity of CV comorbidities may lead to increased accumulation of WM hyperintense lesions and development of brain atrophy in the general ageing population.18–21 Other studies showed that the CV comorbidities may accelerate cognitive decline and progression of neurological diseases, especially Alzheimer's.34 ,35 It is presumed that CV comorbidities, by causing decreased arterial supply to the brain parenchyma, contribute to hypoperfusion, which in turn leads to increased inflammation and risk for stroke.36 ,37 It has been shown that CV comorbidities can accelerate neurodegeneration, as evidenced by the faster rate of brain atrophy development in normal ageing.19 ,20 While the pathogenetic mechanisms of these processes are not completely elucidated,38 ,39 it has been shown that obesity decreases cerebral blood flow which is associated with decreased synthesis and actions of nitric oxide leading to oxidative stress.38 Endothelial dysfunction and cerebral hypoperfusion enhance the production of β-amyloid, which in turn impairs endothelial function; this vicious cycle promotes the pathogenic changes leading to Alzheimer's disease. However, no mechanistic studies examined the effect of CV comorbidities on the pathogenesis of CNS damage in patients with MS. Our study hypothesis was that the presence of CV risk factors would exert an additional damaging effect on brain MRI outcomes in patients with MS presenting with these CV comorbidities. Use of MRI techniques, such as diffusion-weighted and perfusion-weighted imaging, may help characterise the demyelinating versus ischaemic nature of WM and GM lesions in patients with MS and could be an important direction for future research.
A number of previous cross-sectional and longitudinal studies showed that individual CV risk factors may lead to increased clinical and MRI disease progression in patients with MS.5 ,8 ,11 ,22 ,23 ,40 ,41 Smoking was associated with increased disability, lesion burden and more advanced brain atrophy,8 ,40 ,41 while altered lipid metabolism was linked to increased disability, more frequent occurrence of inflammatory lesions and progression of brain atrophy.5 ,11 ,22 ,23 This study confirms some of these reports by showing more advanced whole brain atrophy in patients with MS who smoked and increased T1 lesion burden in patients with MS who are overweight/obese. In addition, patients with MS who had hypertension also showed more advanced GM and cortical atrophy. To the best of our knowledge, this is one of the first studies to report the relationship between overweight/obesity and increased lesion burden in patients with MS, and our initial results warrant a more careful investigation on this topic. Most interestingly, having two or more CV risk factors, and in particular combinations of hypertension with smoking and overweight/obesity with hypertension were related to increased lesion burden and more advanced brain atrophy in patients with MS. A combination of smoking and heart disease was associated with more advanced central atrophy in patients with CIS. These findings suggest that CV comorbidities may play an important role in MS disease progression. In fact, the patients with PMS showed association with MRI outcomes only when they presented three or more CV risk factors. This suggests that in more advanced diseases stages, the effect of CV risk factors on MRI outcomes may be cumulative.
Despite new and more potent immunomodulatory therapies which appear to control the inflammatory aspect of the disease, a significant number of patients continue to deteriorate, particularly in the later stages of the disease. Therefore, it is important to explore whether environmental and, in particular, CV comorbidities may contribute independently to MS disease progression. It has been shown that the median time between diagnosis and need for ambulatory assistance was shorter for patients with CV comorbidities (12.8 years) as compared to those without (18.8 years), suggesting that the clinical outcomes in MS might be influenced by CV comorbidities developed at the time of MS symptom onset, or later during the disease course.13 Although in the present study we did not investigate the association between clinical outcomes and CV comorbidities, our MRI findings indicate that careful management of CV risk factors should become the standard of care in patients with MS.
The methodological strength of this study is that physical and clinical examinations were carried out on a large cohort in the setting of a specialised MS centre by expert physicians, and that CV risk factors were collected by a trained interviewer. However, there are also important limitations to this study. The number of patients with type 1 diabetes was too small to be included in the analyses, and no data were collected on type 2 diabetes and hyperlipidaemia, because our original questionnaire did not include these CV risk factors. In addition, medications related to CV comorbidities were not collected in a standardised fashion and were therefore not included in the analyses. These limits could have potentially affected some of the analyses results. For example, a recent study showed that statins can reduce progression of brain atrophy in SPMS.42 The cross-sectional nature of this study cannot establish a causal relationship between CV risk factors and more advanced disease severity in patients with MS. Therefore, a longitudinal 5-year examination of the present cohort is under way in our centre to determine the cause–effect relationship, and the original questionnaire was adapted to assess CV comorbidities as well as specific therapies more reliably.
In conclusion, patients with MS with one or more CV risks showed increased lesion burden and more advanced brain atrophy. The inflammatory nature of MS disease and CV comorbidities may contribute to more advanced brain damage and longitudinal studies should further explore these associations.
Contributors NK, BW-G, JH, MR and RZ contributed substantially to the concept and design of the study. NK and RZ drafted the article, while all authors revised it critically for important intellectual content. NK and JH performed statistical analysis. All authors had access to the data.
Competing interests BW-G received honoraria as a speaker and as a consultant for Biogen Idec, Teva Pharmaceuticals, EMD Serono, Genzyme & Sanofi, Novartis and Acorda. BW-G received research funds from Biogen Idec, Teva Pharmaceuticals, EMD Serono, Genzyme & Sanofi, Novartis and Acorda. MGD received consultant fees from Claret Medical and EMD Serono. Channa Kolb received speaker honoraria from Novartis, Genzyme and Biogen-Idec. DH received speaker honoraria and consultant fees from Biogen Idec, Teva Pharmaceutical Industries Ltd., EMD Serono, Pfizer Inc and Novartis. MR received research funding or consulting fees from EMD Serono, Biogen Idec, Pfizer, the National Multiple Sclerosis Society, the Department of Defense, Jog for the Jake Foundation, the National Institutes of Health and the National Science Foundation. He received compensation for serving as an Editor from the American Association of Pharmaceutical Scientists. These are unrelated to the research presented in this report. RZ received personal compensation from Biogen Idec, EMD Serono, Novartis, Claret Medical and Genzyme for speaking and consultant fees. RZ received financial support for research activities from Biogen Idec, Teva Pharmacuticals, EMD Serono, Novartis, Claret Medical and Genzyme. RZ serves on the editorial board of J Alzh Dis, BMC Med, BMC Neurol, BioMed Res Int, Vein and Lymphatics, Clinical CNS Drugs, Conf Pap Neurosci and Word J Surg Proc. He is the Treasurer of the International Society for Neurovascular Disease.
Ethics approval The study protocol was approved by the local Institutional Review Board.
Provenance and peer review Not commissioned; externally peer reviewed.
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