An Exploratory Cross-Sectional Study of the Association Between Regular Cigarette Smoking and Level of Disability, Hand Dexterity, Cognitive Impairment, Fatigue, and Markers of Oxidative Stress in Male Patients With Relapsing-Remitting Multiple Sclerosis.

An Exploratory Cross-Sectional Study of the Association Between Regular Cigarette Smoking and Level of Disability, Hand Dexterity, Cognitive Impairment, Fatigue, and Markers of Oxidative Stress in Male Patients With Relapsing-Remitting Multiple Sclerosis - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Am J Mens Health . 2026 May 30;20(3):15579883261453962. doi: 10.1177/15579883261453962 An Exploratory Cross-Sectional Study of the Association Between Regular Cigarette Smoking and Level of Disability, Hand Dexterity, Cognitive Impairment, Fatigue, and Markers of Oxidative Stress in Male Patients With Relapsing-Remitting Multiple Sclerosis Melika Ahmadi Bonabi 1, * , Reza Mosaddeghi-Heris 2, * , Niloofar Taheri 3 , Mahnaz Talebi 4, ✉ , Amirreza Naseri 1, 2, 5, 6, ✉ Author information Article notes Copyright and License information 1 Student Research Committee, Tabriz University of Medical Sciences, Iran 2 Research Center for Integrative Medicine in Aging, Aging Research Institute, Tabriz University of Medical Sciences, Iran 3 Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA 4 Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Iran 5 Research Center for Evidence-Based Medicine, Iranian EBM Centre: A Joanna Briggs Institute (JBI) Center of Excellence, Tabriz University of Medical Sciences, Iran 6 Tabriz USERN Office, Universal Scientific Education and Research Network (USERN), Iran ✉ Mahnaz Talebi, Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz 5166614756, Iran. Email: Talebi511@yahoo.com ✉ Amirreza Naseri, Student Research Committee, Tabriz University of Medical Sciences, Tabriz 5166614756, Iran. Emails: Amirx2eza@gmail.com ; naseria@tbzmed.ac.ir * Melika Ahmadi Bonabi and Reza Mosaddeghi-Heris contribute equally as co-first authors. Received 2026 Feb 12; Revised 2026 May 1; Accepted 2026 May 7; Collection date 2026 May-Jun. © The Author(s) 2026 This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/ ) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage ). PMC Copyright notice PMCID: PMC13222399  PMID: 42218574 Abstract Cigarette smoking is a recognized risk factor for multiple sclerosis (MS) development and progression; however, the association between smoking and features of MS in male patients remains insufficiently explored. A cross-sectional exploratory study was conducted involving 31 male patients with approved relapsing–remitting MS (RRMS), divided into smokers ( n = 9) and non-smokers ( n = 22). The Symbol Digit Modalities Test (SDMT) and Paced Auditory Serial Addition Test (PASAT) were used to assess cognitive performance. Hand dexterity was evaluated using the 9-Hole Peg Test (9HPT). Depressive symptoms and disability were assessed via the Beck Depression Inventory (BDI) and the Expanded Disability Status Scale (EDSS), respectively. Fatigue and related factors were assessed using the Comprehensive Fatigue Assessment Battery for Multiple Sclerosis (CFAB-MS). Serum markers of oxidative stress and antioxidant status, including superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT), total antioxidant capacity (TAC), malondialdehyde (MDA), and glutathione (GSH), were also measured. Smokers demonstrated significantly lower SDMT scores compared with non-smokers (36.86 ± 11.16 vs. 52.47 ± 18.54; p = .04), which was no longer significant after adjusting for EDSS and age. No significant differences were observed between groups in PASAT, 9HPT, EDSS, or BDI. Smokers reported higher anxiety and worry scores on the CFAB-MS ( p < .05), while other fatigue-related domains were comparable between groups. Regarding the oxidative stress markers, a statistically significant difference was only detected in SOD activity. Regular cigarette smoking may be associated with decreased cognitive processing speed and increased anxiety in male patients with RRMS, which warrants further investigation. Keywords: cognitive processing, cognitive impairment, disability, smoking, cigarette, multiple sclerosis, MS Introduction Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system, attacking the myelin sheath around nerves in the brain and spinal cord due to inflammation ( Marcus, 2022 ). MS affects approximately 900,000 people in the United States, especially young adults. It leads to physical disability and cognitive impairment, which leads to social withdrawal and avoidance from work and social activities and reduced quality of life ( Amato et al., 2019 ; Arneth, 2020 ; McGinley et al., 2021 ). Upper limb dysfunction also affects about 75% of MS patients and may present with tremor, ataxia, spasticity, restricted range of motion in limbs, and a reduction in their fine motor skills or dexterity, resulting in their inability to perform daily tasks ( Ghandi Dezfuli et al., 2015 ). Although the exact pathophysiology of neurodegeneration in MS remains unclear, research suggests a role for oxidative stress ( Jiménez-Jiménez et al., 2024 ; Piñar-Morales et al., 2025 ). Brain tissue is particularly vulnerable to radical damage due to high oxygen demand and limited antioxidant availability. Elevated levels of advanced oxidation products in the cerebrospinal fluid of MS patients further support this link ( Irani, 2017 ; Ramos-González et al., 2024 ). Smoking habits are considered a significant factor in disease development and progression, affecting complex gene–environment interactions ( Dobson & Giovannoni, 2019 ; Vitturi et al., 2025 ). Smoking triggers a proinflammatory cascade in the lungs driven by free radicals, cyanates, and carbon monoxide. This can lead to chronic inflammation, immune system modulation (including immunosuppression, inflammatory responses, apoptosis, and altered cytokine balance), and potentially increase the risk of autoimmune diseases ( Arneth, 2020 ; Bazmi et al., 2024 ; Lie et al., 2022 ). Smoking is also recognized as a risk factor for Alzheimer’s disease, and it is associated with a higher risk of cognitive decline and increased risk of dementia ( Amato et al., 2019 ); however, the effects of smoking on cognition remain controversial, with conflicting reports on its role, possibly due to its influence on nicotinic acetylcholine receptors ( Özcan et al., 2014 ). MS patients who smoke are suggested to experience greater disease activity, higher relapse rates, increased lesion loads that accelerate brain atrophy, and increased disability ( Arneth, 2020 ; Bazmi et al., 2024 ; Lie et al., 2022 ). Despite accumulating evidence linking cigarette smoking to increased disease susceptibility and progression in MS, limited data are available regarding its association with oxidative stress biomarkers and clinical characteristics specifically in male patients with relapsing-remitting MS (RRMS), which aimed to be evaluated in the current research. Method This exploratory cross-sectional study included adult male patients diagnosed with RRMS based on 2017 McDonald criteria. Participants were selected from a larger dataset, then categorized into two groups based on self-reported smoking status: regular smokers (at least one pack per week, n = 9) and non-smokers ( n = 22). Individuals with comorbid neurological, inflammatory, or rheumatologic diseases in addition to MS, acute or chronic infectious diseases, diabetes mellitus, anemia, recent relapse (within the past 4 months), receiving corticosteroid therapy, and/or diagnosed psychiatric conditions (such as depression) were excluded. Ethical approval was obtained from the Ethics Committee of Tabriz University of Medical Sciences, and all procedures adhered to the Declaration of Helsinki. Written informed consent was obtained from all participants. Neurological disability was assessed using the Expanded Disability Status Scale (EDSS). Depressive symptoms were evaluated with the Persian-validated version of the Beck Depression Inventory (BDI) ( Ghassemzadeh et al., 2005 ). Hand dexterity was assessed using the 9-Hole Peg Test (9HPT) for both dominant and non-dominant hands. Cognitive performance was assessed using two validated tools: the Symbol Digit Modalities Test (SDMT) for processing speed and the Paced Auditory Serial Addition Test (PASAT) for working memory and attention. Fatigue and its contributing factors were assessed using the Persian-validated version of the Comprehensive Fatigue Assessment Battery for Multiple Sclerosis (CFAB-MS; Motaharinezhad et al., 2015 ). It comprises general health status (reported using the Visual Analog Scale [VAS]) and fatigue and its related factors ( Forwell & Ghahari, 2013 ). Five cc samples of venous blood were also drawn to assess serum levels of oxidative stress markers and endogenous antioxidants in 19 patients (4 smokers and 15 non-smokers) including serum levels of GPx activity (U/mL), superoxide dismutase (SOD; U/mL), catalase (CAT; U/mL), total antioxidant capacity (TAC; mmol/L Trolox equivalents), glutathione (GSH; µmol/L), and malondialdehyde (MDA; µmol/L). Serum markers were quantified using commercially available kits from MyBioSource according to the manufacturer’s instructions (ELISA for SOD, GPx, CAT, GSH, and MDA; ABTS method for TAC). All data analysis was performed using SPSS version 23. The distribution of quantitative variables was assessed using the Shapiro–Wilk test. Numeric variables were expressed as mean ± standard deviation ( SD ) or median with interquartile range (IQR), depending on distribution. Between-group comparisons were performed using independent sample t -tests for normally distributed data and Mann–Whitney U as non-parametric alternative. A p -value of <.05 was considered statistically significant. In addition, regression analyses were performed to examine the association between smoking status and outcomes. Despite the exploratory nature of the study, the Benjamini–Hochberg false discovery rate correction was applied to account for multiple testing. Results A total of 31 eligible patients were included. As presented in Table 1 , there was no significant difference between the groups regarding age ( p = .53), disability levels based on EDSS ( p = .35), depressive symptoms measured by the BDI ( p = .14), and hand dexterity measured by 9HPT ( p = .61 and p = .53), indicating no significant association with smoking status. Cognitive assessment showed a significant reduction in SDMT performance, with smokers scoring markedly lower than non-smokers ( p = .04). However, this difference was no longer statistically significant after adjusting for EDSS and age in the regression analysis ( p = .07). In addition, performance on the PASAT did not differ significantly between groups ( p = .23). Of the 31 patients, 19 provided venous blood samples, yielding oxidative stress marker data for 4 smokers and 15 non-smokers. No statistically significant differences were found between the groups in GPx, TAC, CAT, MDA, or GSH (all p > .05). SOD was numerically higher in smokers (median 224.55 vs. 125.30 U/mL), but this trend did reach statistical significance only in regression analysis (adjusted for EDSS and age; p = .003). Table 1. Association Between Smoking Status and Clinical Characteristics as Well as Markers of Oxidative Stress in Men With RRMS. Characteristics ( n = 31) Smoking + ( n = 9) Smoking − ( n = 22) p -value p -value a Age (years old, mean ± SD ) 36.00 ± 10.05 33.41 ± 10.26 .53 - EDSS (median [IQR]) 2 [2.8] 1 [2.5] .35 - BDI (median [IQR]) 19 [14] 12 [10] .14 .47 9HPT-Right hand (median [IQR]) 22.14 [11.09] 23.77 [4.23] .61 .72 9HPT-Left hand (median [IQR]) 26.26 [11.07] 23.43 [3.10] .53 .29 SDMT (mean ± SD ) 36.86 ± 11.16 52.47 ± 18.54 .049 * .07 PASAT (mean ± SD ) 47.00 ± 9.14 51.65 ± 7.44 .23 .26 Markers of oxidative stress ( n = 19) Smoking + ( n = 4) Smoking − ( n = 15) p -value p -value a GPx (U/mL, median [IQR]) 191.95 [203.20] 231.50 [71.20] .66 .59 TAC (mmol/L, median [IQR]) 316.00 [120.35] 365.10 [117.10] .81 .50 CAT (U/mL, median [IQR]) 36.5 [10.93] 34.8 [5] .88 .47 SOD (U/mL, median [IQR]) 224.55 [158.10] 125.30 [40.70] .10 .003 * MDA (µmol/L, median [IQR]) 2.12 [2.46] 1.58 [1.30] .74 .98 GSH (µmol/L, median [IQR]) 1.80 [0.63] 2.34 [1.00] .31 .34 Open in a new tab Note. SD = Standard Deviation; IQR = Interquartile Range; EDSS = Expanded Disability Status Scale; BDI = Beck Depression Inventory; 9HPT = 9-Hole Peg Test; SDMT = Symbol Digit Modalities Test; PASAT = Paced Auditory Serial Addition Test; GPx = Glutathione Peroxidase; TAC = Total Antioxidant Capacity; CAT = Catalase; SOD = Superoxide Dismutase; MDA = Malondialdehyde; GSH = Glutathione. a Based on binary regression with age and EDSS considered as confounders. In this analysis, smoking status was coded as a binary variable (0 = non-smoker , 1 = smoker ). * Statistically significant. Table 2 compares self-reported health and fatigue-related measures between smokers and non-smokers. There was no significant difference in general health domains, including fatigue, pain, depression, stress, anxiety and worry, sleep problems, poor nutrition, or walking disability (all p > .05). According to the CFAB-MS, smokers tended to have higher scores in several fatigue-related indices, but most of these differences were not significant. The Physical, Psychological, and Social Fatigue Index was higher in smokers (41.00 ± 19.29) than in non-smokers (31.50 ± 23.47), although this difference did not reach significance ( p = .29). The pain index, stress index, mood index, sleep problems index, nutrition index, mobility index, environment, and fatigue management index were also similar between the two groups. The only domain with a significant difference was the anxiety and worry index, where smokers reported higher scores than non-smokers (12.33 ± 5.58 vs. 7.54 ± 5.58, p < .05). In Benjamini–Hochberg false discovery rate correction, none of the observed differences remained statistically significant. Table 2. Association Between Smoking Status and General Summary of Health, Fatigue and its Related Factors in Men With RRMS, Based on Comprehensive Fatigue Assessment Battery for Multiple Sclerosis (CFAB-MS). A general summary of health Smoking + ( n = 9) Smoking − ( n = 22) p -value p -value a Fatigue (median [IQR]) 80 [60] 50 [54] .34 .41 Pain (median [IQR]) 10 [48] 15 [36] .37 .64 Depression (median [IQR]) 10 [43] 30 [65] .17 .21 Stress (median [IQR]) 45 [73] 57.5 [58] .26 .36 Anxiety and worry (median [IQR]) 35 [70] 52.5 [58] .41 .38 Sleep problems (median [IQR]) 30 [70] 22.5 [53] .91 .91 Poor nutrition (median [IQR]) 10 [75] 25 [70] .68 .89 Waking disability (median [IQR]) 15 [90] 12.5 [50] .34 .48 Fatigue and its related factors Smoking + ( n = 9) Smoking − ( n = 22) p -value - Physical, Psychological, and Social Fatigue Index (mean ± SD ) 41.00 ± 1 9.29 31.50 ± 23.47 .29 .50 Pain index (median [IQR]) 14 [17] 7.5 [15] .39 .53 Stress index (mean ± SD ) 20.89 ± 11.79 15.11 ± 5.25 .13 .18 Mood index (mean ± SD ) 14.11 ± 4.91 11.95 ± 6.57 .38 .37 Anxiety and worry index (mean ± SD ) 12.33 ± 5.58 7.54 ± 5.58 .044 * .047 * Sleep problems index (mean ± SD ) 13.56 ± 5.34 11.36 ± 4.68 .26 .38 Nutrition index (mean ± SD ) 6.00 ± 2.95 5.68 ± 3.24 .80 .91 Mobility index (median [IQR]) 1 [9] 1 [8] .51 .96 Environment (median [IQR]) 0.8 [1.35] 0.57 [1.15] .62 .94 Fatigue management index (median [IQR]) 2 [7] 2.5 [5] .65 .61 Open in a new tab Note. SD = Standard Deviation; IQR = Interquartile Range. a Based on binary regression with age and EDSS considered as confounders. In this analysis, smoking status was coded as a binary variable (0 = non-smoker , 1 = smoker ). * Statistically significant. Discussion Epidemiological data consistently demonstrate a predominance of females among individuals with MS ( Hauser & Cree, 2020 ). This leads to less specific evaluations for male MS cases in clinical studies ( Luetic et al., 2022 ). Also given the findings from previous studies, it has been suggested that male sex is correlated with accelerated disability and more aggressive disease course in MS patients ( Dörtkol et al., 2026 ; Magyari & Koch-Henriksen, 2019 ; Vukusic & Confavreux, 2003 ); therefore, in this study, we aimed to investigate the association between regular smoking habit and clinical and laboratory findings specifically in male patients with RRMS. Our findings provide preliminary evidence that regular cigarette smoking may be associated with higher anxiety in male patients with RRMS. We also observed a possible association between smoking and reduced cognitive processing speed; however, these differences were no longer significant after adjustment for age and EDSS, likely reflecting limited statistical power due to the small sample size. Although most between-group comparisons did not reach statistical significance, smokers tended to show poorer performance on cognitive testing and higher scores on anxiety and worry-related indices and serum SOD levels. Taken together, these findings may suggest that smoking could be linked to a less favorable neuropsychological and symptom profile in male RRMS patients; however, the results should be interpreted with caution due to the limited small sample size and potential reporting bias from self-reported smoking data. Nonetheless, the findings support the inclusion of smoking-cessation counseling as an important component of MS management. Our exploratory findings are consistent with Özcan et al. (2014) , who reported that heavy smoking was significantly associated with cognitive impairment in MS patients ( Özcan et al., 2014 ). More recently, Alshehri et al. (2023) conducted a retrospective analysis of 5,536 patients with MS and reported that current smokers had significantly lower processing speed test scores and this difference persisted longitudinally ( Alshehri et al., 2023 ). Lie et al. (2022) also conducted a 10-year follow-up study involving 85 individuals with RRMS, and the findings suggested that after 10 years, smokers showed a larger decline in attention scores ( Lie et al., 2022 ). Similarly, a large Swedish cohort study by Eva et al. (2025) found that smoking and obesity synergistically interact to worsen both disability and cognitive function, with obese smokers experiencing the greatest impairment, suggesting convergent inflammatory mechanisms ( Eva et al., 2025 ). The evidence presented by these longitudinal studies strengthens the idea that cigarette smoking is correlated with slower cognitive processing. Our observation of lower SDMT scores in smokers, in the absence of group differences in PASAT, also fits well with the idea that visual processing speed is a particularly sensitive domain, which may often be affected earlier and more robustly. While our results found no significant EDSS differences between smokers and non-smokers, other studies have shown varying associations. Wu et al. (2023) showed that both current and passive smoking developed active disease and worse disability, while snuff users had less disability and better cognitive performance at baseline ( Wu et al., 2023 ). Consistent with our findings, Lie et al.’s 10-year longitudinal study, although showing slightly higher EDSS progression in smokers with RRMS, found no overall association between smoking, measured by cotinine levels, and EDSS score change over the follow-up period ( Lie et al., 2022 ). In line with our results, a recent retrospective study by Dörtkol et al. (2026) also reported no significant association between smoking status and disability progression. However, these findings should be interpreted with caution, as several methodological factors may influence the observed relationship. In particular, the retrospective nature of data collection and the potential underreporting or misclassification of smoking habits may have limited the ability to detect a true effect ( Dörtkol et al., 2026 ). It should be mentioned that based on the recent evidence, EDSS has lower sensitivity for detecting disability progression ( Lie et al., 2022 ; Meyer-Moock et al., 2014 ). Moreover, the lack of an EDSS difference in our sample may be attributed to the small sample size and overall low disability levels in our sample of patients. Smoking is suggested to harm dual-task finger dexterity, potentially due to its effects on neurocognition and neurobiology ( Kaushik et al., 2025 ). Hand dysfunction is one of the most prevalent symptoms associated with MS, which directly affects daily functioning and patients’ quality of life ( Abraham et al., 2024 ). Patients with MS can experience reduced skill when performing basic activities such as maintaining, grasping, and controlling items ( Huertas-Hoyas et al., 2020 ). So far, the 9HPT is considered the gold standard quantitative measure for upper limb dexterity, which requires an integration of motor and cognitive processes ( Cutter et al., 1999 ; Feys et al., 2017 ; Mistri et al., 2022 ). Consequently, reduced cognitive functioning may manifest as poorer hand skills and diminished dexterity, indicating a potential association between cognition and manual dexterity. Both cognitive and dexterity impairments have been linked to white matter lesions in patients with MS ( Mistri et al., 2022 ). An important and relatively novel aspect of the present study was the investigation of hand dexterity as an outcome in relation to smoking; however, performance did not differ between smokers and non-smokers in our sample. Thus, our negative finding should be interpreted cautiously as preliminary rather than evidence of no effect. Oxidative stress, an imbalance that disrupts redox signaling and causes molecular damage, apparently plays a major role in the neurodegenerative processes associated with MS ( Jones, 2006 ; Piñar-Morales et al., 2025 ). Piñar-Morales et al. (2025) reported that patients with MS exhibit increased activation of specific antioxidant defenses, particularly SOD, while other markers, such as TAC, are reduced. These findings suggest that heightened oxidative stress in patients with MS may result in accelerated utilization of antioxidant reserves, ultimately leading to lower circulating levels of oxidative degradation products ( Piñar-Morales et al., 2025 ). Numerous studies have shown that smoking is associated with higher oxidative stress due to decreased plasma antioxidants and weakened antioxidant defenses, such as SOD ( Ayaori et al., 2000 ; Carnevale et al., 2018 ; Dietrich et al., 2003 ). In contrast, in the present study, no statistically significant differences were observed between groups for any of the assessed oxidative markers, although SOD activity was numerically higher among smokers. SOD is a core component of the physiological response to oxidative stress ( Ibitoye et al., 2016 ), and it has been reported that SOD activity is elevated in active demyelinating lesions compared with normal-appearing white matter and healthy controls ( Moezzi et al., 2022 ; van Horssen et al., 2008 ). Consistent with this, several studies reported higher SOD activity in patients with MS ( Acar et al., 2012 ; Ljubisavljevic et al., 2013 ; Obradovic et al., 2021 ). Nonetheless, the literature remains inconsistent. One study reported that higher SOD levels were associated with greater lesion burden ( Piñar-Morales et al., 2025 ), whereas Ljubisavljevic et al. observed increased SOD activity in patients with a lower T2 lesion load and further suggested a negative association between SOD activity and EDSS scores ( Ljubisavljevic et al., 2013 ). In this context, our findings may indicate a compensatory upregulation of SOD in response to an increased oxidative burden. Regarding the fatigue and its related factors, we only observed higher levels of anxiety scores in smokers. A cross-sectional study of 279 patients with MS by Kahraman et al. (2021) reported that smoker patients experienced a higher rate of fatigue and depression and lower health-related quality of life ( Kahraman et al., 2021 ). Similarly, a Latin-American web-based survey of 425 individuals with a mean age of 43.6 ± 11 years showed that current smokers experienced significant physical worsening, fatigue, and anxiety ( Rojas et al., 2024 ). Lack of significant findings in this regard can be attributed to the small sample size of this study, and the different sample of the current research which was only men patients with RRMS. In this exploratory cross-sectional study of male patients with RRMS, regular cigarette smoking was suggested to be associated with a higher burden of anxiety, while disability level, hand dexterity, fatigue, and most circulating oxidative stress markers remained comparable between smokers and non-smokers. Also, higher SOD activity in smokers is found. Together, these findings suggest that the detrimental effects of smoking in RRMS may initially manifest at the cognitive and psychological levels before becoming detectable in physical disability or peripheral biochemical markers. Given that smoking is a modifiable risk factor, targeted smoking-cessation interventions should be emphasized in the clinical management of MS, particularly to preserve cognitive function and mental well-being. Larger longitudinal studies are warranted to clarify the temporal relationship between smoking, oxidative stress, and disease progression in MS. Acknowledgments This research was approved and financially supported by the Student Research Committee of Tabriz University of Medical Sciences (grant number 78123). The authors would like to thank all the participants who contributed to this study. Also, the authors would like to thank the Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran, for their assistance in this research. Footnotes ORCID iDs: Reza Mosaddeghi-Heris https://orcid.org/0000-0002-3353-1102 Amirreza Naseri https://orcid.org/0000-0001-9723-0109 Ethical Considerations: The study protocol was reviewed and approved by the Ethics Committee of Tabriz University of Medical Sciences (ethics code: IR.TBZMED.REC.1404.896). Consent for Participation: Written informed consent was obtained from all participants prior to participation in the study. Consent for Publication: Informed consent for publication of anonymized data was obtained from all participants. Author Contributions: M.A.B.: Methodology; Writing – Original Draft; Project administration; Funding acquisition; Read and approved the final manuscript. R.M.-H.: Writing – original draft; Investigation; Data curation; Visualization; Read and approved the final manuscript. N.T.: Writing – original draft; Investigation; Data curation; Formal analysis; Read and approved the final manuscript. M.T.: Conceptualization; Methodology; Validation; Investigation; Resources; Writing – review & editing; Supervision; Project administration; Funding acquisition; Read and approved the final manuscript. A.N.: Conceptualization; Methodology; Formal analysis; Investigation; Resources; Data curation; Writing – original draft; Visualization; Project administration; Funding acquisition; Read and approved the final manuscript. Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was financially supported by the Student Research Committee of Tabriz University of Medical Sciences (grant number 78123). The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Data Availability Statement: The data that support the findings of this study are available from the corresponding author (A.N.) upon reasonable request. References Abraham R., Waldman-Levi A., Barrera M. A., Bogaardt H., Golan D., Bergmann C., Sullivan C., Wilken J., Zarif M., Bumstead B., Buhse M., Covey T. J., Doniger G. M., Penner I.-K., Hancock L. M., Morrow S. A., Giroux E., Gudesblatt M. (2024). Exploring the relationship between manual dexterity and cognition in people with multiple sclerosis: 9-hole peg and multiple cognitive functions. 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