Research Article - (2025) Volume 20, Issue 4
Lipid Profiles, Cognitive Function, and the role of Physical Activity in Multiple Sclerosis
Esraa Fahmy1*, Ehab S. Ramadan1, Nahla A. Nosair2 and Salma Ragab1*Correspondence: Esraa Fahmy, Department of Neuropsychiatry, Faculty of Medicine, Kafrelsheikh University, Kafrelsheikh, Egypt, Email:
Abstract
Background: Delayed cognition is common among patients with Multiple Sclerosis (MS) affecting their quality of life. In MS, lipid biomarkers are associated with neurodegeneration, and the blood-brain barrier disruption. This study aimed to investigate the role of lipid components in MS and their association with cognition.
Methods: This case-control study included 71 patients with MS and 71 healthy control participants. The definitive diagnosis of MS was determined according to the revised McDonald criteria. Demographic and clinical data of patients were obtained. In addition, blood samples were collected from all participants. The lipid biomarkers panel included total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C). The physical disabilities were assessed using EDSS, progression index (PI), whereas the cognitive function was assessed utilizing BICAMS.
Results: The Symbol Digit Modalities Test (SDMT) was demonstrating negative correlation with TC, LDL-C, and TC/HDL-C in MS patients. Higher TG levels were associated with increased impairment and disease progression in MS patients, as TG exhibited a positive correlation with disease severity and progression.
Conclusions: Lipid biomarkers are associated with cognitive impairment in MS. The results suggest a potential association between lipid biomarkers and cognitive impairment.
Keywords
Multiple Sclerosis, triglycerides, low-density lipoprotein cholesterol
Introduction
Multiple Sclerosis (MS) is an immune-mediated inflammatory neurodegenerative disorder that affects the central nervous system (CNS) (Mohamed Elshaer et al., 2018). Research has shown that MS frequently leads to cognitive impairment (Messinis et al., 2017), Cognitive impairment has been reported in up to 40–70% of MS. Therefore, early detection of cognitive impairment is crucial as the timely intervention may contribute to ameliorating, stabilizing, or compensating for cognitive impairment while addressing its emotional effects and improving the overall quality of life (Jackson et al., 2020). Lipids play an essential role in the formation of the myelin sheath, as well as supporting communication within the CNS (Pousinis et al., 2020). Moreover, lipids are potential targets for novel, efficient, and stage-specific therapeutic interventions. The derangements of lipid metabolism in MS remain inadequately investigated (Zahoor et al., 2021).
Previous studies indicate that approximately 30% of multiple sclerosis patients exhibit altered lipid profiles (Nori et al., 2019). However, it remains unclear whether there is a relationship between the lipid profile of MS patients and disability and cognitive function.
A Previous study suggested that atherosclerosis and abnormal systolic blood pressure may play a role in the progression and deterioration of cognitive function (Reia et al., 2021). Additionally, lipid biomarkers have been associated with cognitive outcomes in other neurodegenerative diseases, including Alzheimer’s disease (Martin et al., 2014). These studies enhance our understanding that lipids may play a role in MS and could serve as potential biomarkers for disease progression.
This study aims to investigate the role of lipid in MS and their correlation with various disease characteristics.
Material and methods
Study population
Study Setting and Design: This case-control study was conducted at Neuropsychiatry Department in Kafrelsheikh University Hospital, With the IRB approval number (487)
This study was composed of two groups
- Study group: it consists of 71 patients diagnosed with MS according to revised McDonald criteria (Thompson et al., 2018).
- Control group: it includes 71 participants with no history of neurologic or psychiatric illnesses and did not receive any therapy. Participants in both groups were matched in terms of education, gender, and age.
MS patients were included in the study based on the following
Inclusion criteria
- MS diagnosis according to revised McDonald 2017 criteria
- Age >18 years
Exclusion criteria
- Presence of severe medical and psychiatric illness.
- MS clinical and/or neuroradiological relapse in the sex months prior to enrollment
- Treatment with steroids, psychoactive drugs
- Adherence to a special diet, such as vegetarian or weight loss regimen
- History of alcohol or drug abuse
Demographic and clinical features of the study population
Data regarding sex, age, BMI, marital status, years of education, and history of other medical conditions were collected through in-person interview.
History taking included age of onset, clinical type of first attack, disease duration, number of relapses, disease activity (Ontaneda, D et al., 2024), and disease progression (Comi, G et al., 2024) were retrieved from patients’ clinical records.
The disability status of MS cases was evaluated as follows
The Expanded Disability Status Scale (EDSS): The EDSS assesses disability in eight Functional Systems (FS) by assigning a Functional System Score (FSS) in each of these functional systems (pyramidal, cerebellar, brain stem, sensory, visual, bowel /bladder, mental and ambulation).
The EDSS follows an ordinal rating system ranging from 0 (normal neurological status) to 10 (death due to MS) in 0.5-increments interval (Kurtzke JF., 1983).
Progression index (PI): The PI serves as an indicator of disease progression and is calculated by dividing an individual’s EDSS score by their disease duration (Cendrowski WS et al., 1985). PI scores lower than 2 have good prognostic value (Pinto et al., 2020).
Cognitive assessment
The cognitive function was evaluated using the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) (Artemiadis et al., 2021) , utilizing the Arabic version ( Abualhasan A et al., 2023)(. The BICAMS includes the following subtests:
- Symbol Digit Modalities Test (SDMT): The score is determined by counting the number of correct responses in matching an abstract symbol with its designated number.
- California Verbal Learning Test (CVLT): This test involves the oral presentation of a list of 16 words over five immediate-recall trials.
- Brief Visuospatial Memory Test-Revised (BVMT-R): This test consists of a visual display of six simple figures arranged in a 2 × 3 matrix over three consecutive 10-second trials.
- Higher scores in each subtest indicate better cognitive function (Benedict et al., 2002). For this study, cutoff scores were set at 34 for SDMT, 46 for CVLT, and 12 for BVMT-R (Arghaly, M et al., 2021).
Blood sampling
Lipids and apolipoproteins were analyzed on plasma samples obtained in the fasted state.
Plasma samples were stored at -80 ◦C until use. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) were measured using an automated chemistry analyzer with diagnostic reagent kits. Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald equation (Friedewald et al., 1972)
Data analysis
Descriptive statistics were performed and Spearman rank correlation coefficients were calculated. Independent sample t-test and Mann-Whitney U tests were performed to determine differences between groups. Statistical analysis was done using the Statistical Package for Social Science (SPSS v.22).
A categorical variable was created to classify participants into healthy controls (HC), relapsing-remitting multiple sclerosis (RR-MS), and progressive multiple sclerosis (P-MS).
Results
The demographic data indicated that approximately 76.1% of participants were females and 23.9% were males, with a mean age of 30.72 + 9.19. The age of onset ranged from 15 to 46 years, with a median of 25 years. The disease duration ranged from 1 to 33, with a median of 4. In terms of clinical data, approximately 85%, 75%, and 51% of patients exhibited sensory, motor, and sphincteric dysfunction, respectively. Visual acuity was impaired in 73.2% of patients, while the brainstem and cerebellum were affected in 63.4% and 43.7%, respectively. Neurophysiological function, Uthoff phenomenon and tonic spasm occurred in 46.5%, 18.3% and 9.9%, respectively. Among patients, 31% exhibited active disease and 22.5% experienced disease progression. Approximately 77.46% were diagnosed with RRMS, 12.7% with SPMS, and 9.86 % with PPMS. The EDSS varied from 1 to 8.5, with a median of 2. The PI ranged from 0.12 to 3, with a median of 0.57. (Table 1).
| N=71 | % | |
|---|---|---|
| Sex | ||
| female | 54 | 76.10% |
| male | 17 | 23.90% |
| Age | 30.72 + 9.19 | |
| Median (IQR) | Range | |
| Age of onset (year) | 25(18 – 32) | 15 – 46 |
| Disease duration (year) | 4(2.5 – 7) | 1 – 33 |
| Total number of relapses | 3(2 – 5) | 1 – 9 |
| Number of relapses in the past 2 years | 1(1 – 2) | 0 – 5 |
| N= 71 | % | |
| System affection | ||
| Sensory | 84.50% | |
| Motor | 74.60% | |
| Visual acuity | 73.20% | |
| Brainstem | 63.40% | |
| Sphincteric function | 50.70% | |
| Neurophysiological function | 46.50% | |
| Cerebellum | 43.70% | |
| Uthoff phenomenon | 18.30% | |
| Tonic spasm | 9.90% | |
| disease activity | ||
| Inactive | 49 | 69% |
| Active | 22 | 31% |
| Progression | ||
| Absent | 55 | 77.50% |
| Present | 16 | 22.50% |
| Type of MS | ||
| RRMS | 55 | 77.46% |
| SPMS | 9 | 12.70% |
| PPMS | 7 | 9.86% |
| Median (IQR) | Range | |
| EDSS | 2(1.5 – 3.5) | 1 – 8.5 |
| PI | 0.57(0.38 – 1.03) | 0.12 – 3 |
Abbreviation: RRMS: relapsing-remitting multiple sclerosis, SPMS: secondary progressive multiple sclerosis, PPMS: primary progressive multiple sclerosis, EDSS: Expanded Disability Status Scale, PI: progressive index.
There was a statistically significant difference between the studied groups for all BICAMS items (SDMT, CVLT, and BVST-R), with higher scores observed in the control group. (Table 2)
| HC group | All-MS group | Z | P | |
|---|---|---|---|---|
| Median (IQR) | Median (IQR) | |||
| SDMT | 27(19 – 36) | 43(39 – 50) | -7.874 | <0.001 |
| CVLT | 63(49 – 71) | 78(76 – 80) | -8.076 | <0.001 |
| BVST-R | 28(20 – 32) | 27(19.5 – 36) | -4.864 | <0.001 |
The p-values for the differences between the HC and all-MS groups were based on the Mann-Whitney test for all items of BICAMS (SDMT, CVLT, and BVST-R).
Abbreviations: SDMT: Symbol Digit Modalities Test, CVLT: California Verbal Learning Test, BVST-R: Brief Visuospatial Memory Test-Revised.
A statistically significant difference was observed between the studied groups regarding TG, LDL-C, HDL-C, and TC/HDL ratio. Specifically, LDL-C, TG, and TC/HDL ratio were significantly higher in the case group, while HDL-C levels were significantly lower. (Table 3).
| All-MS group | HC group | T | P | |
|---|---|---|---|---|
| Mean ± SD | Mean ± SD | |||
| TC (mg/dl) | 190.82 ± 36.96 | 181.63 ± 23.83 | 1.76 | 0.081 |
| LDL-C (mg/dl) | 122.56 ± 35.7 | 106.47 ± 16.7 | 3.44 | 0.001** |
| HDL-C (mg/dl) | 49.38 ± 13.37 | 59.25 ± 22.45 | -3.186 | 0.002* |
| Median (IQR) | Median (IQR) | Z | P | |
| Triglycerides (mg/dl) | 92(62 – 111) | 70(61 – 90) | -2.801 | 0.005* |
| TC/HDL ratio | 3.89(3.21 – 4.61) | 2.98(2.59 – 3.77) | -3.407 | 0.001** |
The p-values for the differences between the HC and all-MS groups were based on independent samples t-test and Mann-hitney test for lipid pathway biomarkers.
Abbreviations: TC: Total cholesterol, LDL-C: Low-density lipoprotein cholesterol, HDL-C: High-density lipoprotein cholesterol.
There was a statistically significant positive correlation between total cholesterol and age, age of onset, and number of relapses in the past two years. Conversely, a statistically significant negative correlation was observed between total cholesterol and SDMT. (Table 4)
| R | P | R | P | R | P | R | P | R | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total cholesterol | LDL cholesterol | HDL cholesterol | Triglycerides | TC/ HDL-C | |||||||||
| Age (year) | 0.242 | 0.042 | 0.326 | 0.003 | -0.267 | 0.024 | 0.347 | 0.001 | 0.323 | ||||
| BMI | 0.215 | 0.072 | 0.133 | 0.268 | -0.236 | 0.048 | 0.46 | <0.001 | 0.341 | ||||
| Disease-specific data | |||||||||||||
| Age of onset (year) | 0.338 | 0.004 | 0.266 | 0.025 | -0.162 | 0.177 | 0.433 | <0.001 | 0.226 | 0.058 | |||
| Disease duration (year) | -0.106 | 0.385 | -0.035 | 0.775 | -0.218 | 0.071 | -0.179 | 0.141 | 0.064 | 0.603 | |||
| Total number of relapses | 0.048 | 0.688 | -0.035 | 0.774 | -0.043 | 0.0723 | -0.061 | 0.613 | 0.026 | 0.832 | |||
| Number of relapses in the past 2 years | 0.246 | 0.039 | 0.029 | 0.808 | 0.213 | 0.074 | 0.226 | 0.058 | -0.038 | 0.751 | |||
| EDSS | 0.205 | 0.086 | 0.164 | 0.173 | -0.149 | 0.215 | 0.204 | 0.088 | 0.147 | 0.223 | |||
| PI | 0.228 | 0.058 | 0.125 | 0.304 | 0.18 | 0.136 | 0.248 | 0.038 | 0.248 | 0.038 | |||
| Vital data | |||||||||||||
| Systolic blood pressure (mmHg) | -0.055 | 0.651 | -0.132 | 0.273 | 0.108 | 0.369 | 0.055 | 0.65 | 0.055 | 0.65 | |||
| Diastolic blood pressure (mmHg) | -0.013 | 0.915 | 0.006 | 0.959 | -0.026 | 0.833 | 0.046 | 0.705 | 0.046 | 0.705 | |||
| Pulse (beat/minute) | 0.005 | 0.966 | -0.042 | 0.731 | -0.043 | 0.721 | 0.046 | 0.663 | 0.063 | 0.663 | |||
| BICAMS | |||||||||||||
| SDMT | -0.388 | 0.001 | -0.358 | 0.002 | 0.175 | 0.144 | -0.14 | 0.245 | -0.322 | 0.006 | |||
| CVLT | -0.201 | 0.092 | -0.115 | 0.304 | 0.09 | 0.442 | -0.182 | 0.128 | -0.202 | 0.092 | |||
| BVST-R | -0.231 | 0.053 | -0.154 | 0.2 | -0.047 | 0.694 | -0.034 | 0.775 | -0.079 | 0.514 |
A statistically significant positive correlation was found between LDL-C and both age and age of onset, while a statistically significant negative correlation was observed between LDL-C and SDMT (Table 4).
HDL-C showed a statistically significant negative correlation with age and BMI. (Table 4)
TG demonstrated a statistically significant positive correlation with age, BMI, age of onset, and PI. (Table 4)
The TC/HDL-C ratio exhibited a statistically significant positive correlation with age, BMI, and PI, and a statistically significant negative correlation with SDMT. (Table 4)
(Table 5) summarizes the linear stepwise regression analysis of factors associated with SDMT. Factors independently and significantly associated with SDMT included LDL cholesterol (unstandardized β = -0.114, p = 0.005).
| Model | Unstandardized Coefficients | Standardized Coefficients | t | p | 95.0% Confidence Interval | |||
|---|---|---|---|---|---|---|---|---|
| B | Std. Error | Beta | Lower | Upper | ||||
| SDMT | (Constant) | 70.864 | 5.366 | 13.206 | <0.001** | 60.253 | 81.474 | |
| LDL Cholesterol | -0.114 | 0.04 | -0.224 | -2.876 | 0.005* | -0.193 | -0.036 | |
| Total cholesterol | -0.0015 | 0.036 | -0.042 | -0.042 | 0.967 | -0.074 | 0.071 | |
| TC/HDL-C ratio | -0.593 | 1.506 | -0.394 | -0.394 | 0.695 | -3.599 | 2.413 | |
Discussion
Multiple Sclerosis (MS) is an immune-mediated inflammatory neurodegenerative disorder of the central nervous system that destroys myelinated axons. Cognitive impairment is a common consequence of multiple sclerosis and is defined as a reduction in intellectual abilities, such as memory, processing speed, and executive functioning issues (Eshandarieh et al., 2018).
This work was designed to investigate the correlation between the lipid profile and cognitive impairment in MS patients.
In this work, 142 participants were enrolled divided into 71 individuals as a control group and 71 MS patients as a study group. This work showed that about 76.1% were females and 23.9% were males this finding agreed with Harbo HF et al, 2013 who found that the prevalence of MS was higher in Females than males where the ratio was 2.3– 3.5:1. This indicated a true increase in MS among females. Contradictory result was reported by Deleu et al., 2013 who reported lower female to male ratio by 1.33:1 in the Middle East region. Moreover, Elshebawy et al., 2021 reported no difference in female to male ratio in their Egyptian study. This suggested that epidemiological factors might play a role in MS susceptibility.
The mean of age is 30.72 + 9.91 and the age of onset of MS ranged from 15 to 46 years with median 25 (18 – 32). Similar results were found by Donald W. Paty 2003 who reported a mean age of onset of 25.36±8.6 years.
Analysis of the clinical data of MS patients showed that the most common type of MS in this work was RRMS (77.46%) followed by SPMS (12.7 %) then PPMS (9.86%). This is similar to the findings of Siger, M. 2022 who reported that the percentage of RRMS was 80 % while that of SPMS was 10% and that of PPMS is 10% .IN CONTRAST, Asadollahi et al., 2013 who reported that the percentage of RRMS was 56.7 % while that of SPMS was 23.3 % and that of PPMS is 20%
To assess the clinical severity of MS, two tests were chosen that have reliable, validated and well accepted clinical scores. First, the Expanded Disability Status Scale (EDSS) which is the most used rating scale to evaluate the clinical status of patients with MS. It has the advantage of being the most widely accepted and familiar measure of disability in MS, easy and not time consuming to perform (Kurtzke JF., 1983). MS patients with lower scores in scales measuring disease severity have lower disability and better performance in daily activities. EDSS scores below 4.5 refer to MS patients who are able to walk without any aid while scores of 5 or more are reflecting impairment in walking. Second, the Progression index (PI) which is used as an indicator of disease progression. It was done after dividing the individual’s EDSS by disease duration. Progression index (PI) scores lower than 2 have good prognostic value (Pinto et al., 2020).
In this work, MS patients had the range of EDSS scores from 1 to 8.5 with median 2, the range of Progression index from 0.12 to 3 with median 0.57.
The Brief International Cognitive Assessment for MS (BICAMS) includes tests of mental processing speed and memory that are assessed by the Symbol Digit Modalities Test (SDMT) , tests of learning and memory that are assessed by the California Verbal Learning Test (CVLT) and test of visual/spatial memory that is assessed by the revised Brief Visuospatial Memory Test (BVMT-R) (Benedict, R.H. et al., 2012). Greater score in each subtest means better cognitive function, the cutoff scores were 34 in SDMT, 46 in CVLT, and 12 in BVMT-R .in this work, we found that all items of BICAMs were higher among control groups than among MS groups.
The primary lipid component of neurons and myelin, cholesterol makes up around 25–30% of the brain's total content. It is essential for axonal growth and synaptic connection, and abnormalities in its metabolism may be the cause of neuroinflammation, ischemia, and brain atrophy (Hernández-Ledesma et al., 2020). In this work, we discovered that lipid components (TG, LDL-C, and TC/HDL-C) were higher among MS groups than among control groups while HDL-C was lower this finding agreed with Meyers L et al., 2014 .
We discovered that PI and TG levels were correlated, with higher TG levels being linked to more impairment in MS patients; the age of patients and the age of onset were positively correlated with TC, TG and LDL-C. This result is in line with the previous study, which hypothesizes a link between elevated lesion load and hypercholesterolemia, therefore raising the likelihood of disability progression (Gafson et al., 2018). In contrast, Hesham B.M et al, 2023, who reported that no significant correlation was found between serum lipids and disease duration or disability.
We discovered that SDMT was negatively correlated with TC, LDL, and TC/HDL-C. These findings are largely consistent with earlier studies on lipid pathway biomarkers and cognitive tests in MS (Andaloro et al., 2020), so underlining how this aspect is useful to consider for preventive patient monitoring. It has been discovered that elevated cholesterol levels in MS patients are linked to cognitive impairment. This discovery holds significance because it is a controllable factor, indicating that lowering cholesterol levels can avert future difficulties.
We discovered that disease duration and total number of relapses were not correlated with TC, TG, LDL-C, and HDL-C in similar to Hesham B.M et al, 2023.
Limitations of the study
The primary limitation of this study is the small sample. Further investigation is required to fully elucidate the relationships between cognitive functions and lipid distribution.
The lack of longitudinal data limits understanding of temporal relationship between lipid dysregulation and cognitive decline.
Future directions
Further studies with larger sample size and longitudinal designs are required to validate these findings. Investigating the effects of lipid-lowering interventions on cognitive outcomes in MS may yield valuable insights into potential therapeutic strategies.
Conclusion
Symbol Digit Modalities Test (SDMT) was used to assess mental processing speed and memory, demonstrating a negative correlation with TC, LDL-C, and TC/HDL-C ratio in MS patients. Higher TG levels were linked to increased impairment and disease progression in MS patients, as TG was positively correlated with disease severity and progression. Therefore, lipid pathway biomarkers are associated with cognitive function in MS patients. These findings highlight the association between lipid pathway biomarkers and cognitive function in MS patients. Hyperlipidaemia, as a modifiable risk factor, can be managed to improve lipid profiles in patients with MS, potentially mitigating cognitive impairment and enhancing overall disease outcomes.
Funding information
None
CRediT authorship contribution statement
Esraa fahmy: Conceptualization, Methodology, Formal analysis, Software, Writing-original draft, writing -review & editing. Ehab S.Ramadan: supervision, writing-review & editing. Nahla A.Nosair: supervision, writing – review & editing. Salma Ragab: methodology, formal analysis, supervision, writing-review & editing.
Declaration of Competing Interest
None
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