Peripheral Iron and Immune Markers Are Associated With Levodopa-Induced Dyskinesia Severity in Parkinson’s Disease

Peripheral Iron and Immune Markers Are Associated With Levodopa-Induced Dyskinesia Severity in Parkinson’s Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Peripheral Iron and Immune Markers Are Associated With Levodopa-Induced Dyskinesia Severity in Parkinson’s Disease Farrukh Saidvaliyev, Dilyora Pulatova, Ibodulla Kilichev, Adkham Yusupov, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8934743/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Levodopa-induced dyskinesia (LID) is a common motor complication of Parkinson’s disease (PD), yet peripheral biological factors associated with dyskinesia severity remain insufficiently characterized. Systemic inflammation and iron dysregulation have been implicated in PD, but their relationship with LID expression is unclear. We investigated the association between serum ferritin, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and the presence and severity of LID. Methods In this study, 302 patients with idiopathic PD receiving stable levodopa therapy for at least 24 months were evaluated. Dyskinesia severity was assessed in the medication “ON” state using the Unified Dyskinesia Rating Scale (UDysRS). Serum ferritin and complete blood counts were obtained from fasting samples, and NLR and LMR were calculated. Multivariable regression analyses were performed adjusting for age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, motor severity, C-reactive protein, and amantadine use. Results LID was present in 158 patients (52.3%). Patients with dyskinesia had higher median ferritin levels (152 vs. 104 ng/mL, p < 0.001) and NLR (2.8 vs. 2.0, p < 0.001), and lower LMR (3.5 vs. 4.3, p < 0.001) compared with those without dyskinesia. In adjusted analyses, the highest ferritin quartile was associated with greater UDysRS scores (β = 6.4, p < 0.001), as were the highest NLR quartile (β = 4.9, p = 0.001). Conversely, higher LMR was independently associated with lower dyskinesia severity (β=−4.1, p = 0.006). Conclusions. Elevated serum ferritin and altered leukocyte-derived ratios (NLR, LMR) were independently associated with increased levodopa-induced dyskinesia severity in Parkinson’s disease. These biomarkers may reflect systemic biological processes linked to dyskinesia burden and warrant further evaluation in longitudinal studies. Parkinson’s disease levodopa-induced dyskinesia serum ferritin neutrophil-to-lymphocyte ratio lymphocyte-to-monocyte ratio Figures Figure 1 Introduction Levodopa-induced dyskinesia (LID) is a frequent and disabling motor complication of Parkinson’s disease (PD), characterized by involuntary hyperkinetic movements that emerge during chronic dopaminergic treatment and are commonly accompanied by fluctuations in motor control, functional impairment, and a marked reduction in quality of life 1 . Around 30% of patients develop levodopa-induced dyskinesia within 5 years of starting treatment, and the prevalence increases to approximately 70% after 10 years of continued therapy 2 . Although levodopa remains the most effective therapy for the cardinal motor symptoms of PD, the development of dyskinesia represents a major limitation of long-term dopaminergic treatment and often necessitates complex medication adjustments, thereby compromising sustained therapeutic benefit 3 . Beyond its clinical expression as a motor complication, LID reflects broader pathophysiological processes involving dopaminergic dysregulation, maladaptive neural plasticity, and biological mechanisms extending beyond the central nervous system 2 . Growing evidence indicates that systemic inflammation and altered iron metabolism contribute to PD pathophysiology beyond dopaminergic neurodegeneration 4 , 5 . Ferritin, a peripheral marker of iron storage, has been associated with neurodegenerative processes and inflammatory states and may reflect dysregulated iron homeostasis relevant to oxidative stress and neuronal vulnerability 6 . Neuroimaging and pathological studies have consistently demonstrated abnormal iron accumulation in PD-related brain regions, supporting a potential link between iron metabolism and disease progression 7 , 8 . In parallel, low-grade systemic inflammation, commonly assessed using C-reactive protein (CRP), has been associated with motor severity, non-motor symptoms, and longitudinal disease progression in PD 9 . These findings suggest that inflammatory and iron-related pathways may interact and modulate the development of treatment-related motor complications, including LID, although direct clinical evidence remains scarce. The neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR), derived from routine blood counts, are practical indicators of systemic inflammatory status. Neutrophils contribute to systemic inflammation through the release of cytokines, reactive oxygen species, and proteolytic enzymes, which may enhance blood–brain barrier permeability and facilitate neuroinflammatory cascades 10 , 11 . In contrast, lymphocytes, particularly regulatory T cells, are involved in modulating immune responses and maintaining immune homeostasis. A relative reduction in lymphocyte counts may therefore indicate impaired immunoregulatory capacity 12 . Monocytes, as precursors of macrophages and microglia-like cells, can migrate into the central nervous system and amplify neuroinflammation through cytokine production and activation of resident glial cells 13 . Recent studies have demonstrated that elevated NLR and altered LMR values are associated with greater disease severity, more rapid progression, and poorer clinical outcomes in Parkinson’s disease 14 , 15 . However, the relationship between NLR, LMR, peripheral iron metabolism, and levodopa-induced dyskinesia has not been examined in a PD population. The aim of this study was to investigate the association between serum ferritin levels, NLR, LMR and the presence and severity of levodopa-induced dyskinesia in patients with idiopathic Parkinson’s disease. Methods Study design and participants We consecutively recruited patients with idiopathic Parkinson’s disease from the neurology department at Tashkent Medical Academy between January 2021 and September 2025. Inclusion criteria were a clinical diagnosis of Parkinson’s disease according to the Movement Disorder Society criteria 16 , age between 40 and 80 years, and treatment with levodopa for at least 24 months with no change in dopaminergic medication during the preceding 30 days. Patients were included irrespective of the presence of levodopa-induced dyskinesia. Conditions known to affect ferritin levels or systemic inflammatory markers were excluded, including recent infection or antibiotic use, active inflammatory or autoimmune disease, malignancy, hematologic disorders, blood transfusion, iron supplementation, significant hepatic or renal dysfunction, atypical or secondary parkinsonism, and a history within the preceding month of chronic inflammatory or inflammatory-related conditions such as osteoarthritis, osteoporosis, fever, or allergic conditions. The study protocol was reviewed and approved by the Ethics Committee of Tashkent Medical Academy (approval No. TMA-IRB/2020-12). All procedures were conducted in accordance with the Declaration of Helsinki (2013 revision). Written informed consent was obtained from all participants prior to enrollment. Assessment of clinical symptoms All clinical evaluations were performed by a movement disorder specialists through face‒to-face interviews and detailed questionnaires. Demographic and clinical data, including age, sex, disease duration, disease stage, motor severity, levodopa equivalent daily dose, and current antiparkinsonian medications, were recorded. Evaluations were conducted in the medication “ON” state, defined as 60–90 minutes after intake of the patient’s usual levodopa dose, to ensure consistent assessment of peak-dose motor complications. Levodopa-induced dyskinesia was assessed using the Unified Dyskinesia Rating Scale (UDysRS) 17 , which served as the measure of dyskinesia severity and functional impact. For phenotypic classification, patients were categorized according to the presence or absence of levodopa-induced dyskinesia based on clinical observation and UDysRS scoring. Patients with any clinically detectable dyskinesia were classified as dyskinesia-positive, whereas those without observable dyskinesia during assessment and without reported dyskinesia episodes in the preceding month were classified as dyskinesia-negative. Clinical assessment additionally encompassed motor complications evaluated using the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale part IV (MDS-UPDRS part IV) 18 , disease stage determined according to the Hoehn and Yahr scale 19 , and motor severity quantified using the Movement Disorder Society–Unified Parkinson’s Disease Rating Scale part III 18 . Laboratory measurements and biomarker assessment Venous blood samples were collected during the same study visit, in the morning (06:00–08:00 a.m.) after an 8 h overnight fasting period. Samples were collected in clot activator tubes, centrifuged at 3,000 rpm for 10 minutes, and analyzed within 4 hours in a single laboratory. Serum ferritin levels were assessed using an automated chemiluminescent immunoassay (Cobas e411, Germany). Complete blood counts were performed on the same blood draw using an automated hematology analyzer (Sysmex XN-1000, Japan). The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. LMR was calculated by dividing the absolute lymphocyte count by the absolute monocyte count. Serum C-reactive protein levels were measured concurrently. Medication exposure and covariates Dopaminergic medication exposure was standardized using the levodopa equivalent daily dose (LEDD), calculated according to the conversion factors proposed by Tomlinson et al. (2010) and analyzed as a continuous variable 20 . All antiparkinsonian medications, including levodopa formulations, dopamine agonists, monoamine oxidase B inhibitors, catechol-O-methyltransferase inhibitors, and amantadine, were recorded at the time of clinical assessment. Medication regimens were considered stable if no changes in drug type, daily dose, or dosing frequency had occurred within the 30 days preceding enrollment. Clinical covariates were selected a priori based on their known associations with dyskinesia and included age, sex, disease duration, Hoehn and Yahr stage, and motor severity assessed by the MDS-UPDRS part III. Current use of amantadine was included as a binary covariate given its potential influence on dyskinesia severity. These variables were incorporated into multivariable models to control for confounding effects. Statistical analysis Continuous variables are presented as mean ± standard deviation or median with interquartile range (IQR), as appropriate, and categorical variables as counts and percentages. Comparisons between patients with and without levodopa-induced dyskinesia were conducted using the Student’s t test or Mann–Whitney U test for continuous variables and the chi-square test or Fisher’s exact test for categorical variables. Associations between serum ferritin levels, NLR, LMR, and dyskinesia-related outcomes were evaluated using multivariable regression models. Dyskinesia severity was analyzed as a continuous outcome using linear regression with the total Unified Dyskinesia Rating Scale score as the dependent variable, whereas the presence of dyskinesia was examined using logistic regression. Ferritin, NLR and LMR were analyzed in quartiles. All models were adjusted for covariates, including age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, MDS-UPDRS part III score, serum C-reactive protein level, and current amantadine use. An interaction term between ferritin and inflammatory ratios (NLR and LMR) were included in the regression models to assess potential effect modification. Model assumptions were evaluated by inspection of residuals, multicollinearity was assessed using variance inflation factors, and sensitivity analyses excluded patients with elevated C-reactive protein levels (> 5 mg/L) 21 . All tests were two-sided, with a p value < 0.05 considered statistically significant. Statistical analyses were performed using SPSS software (version 26.0; IBM Corp., Armonk, NY, USA). Results Demographic and clinical characteristics and biomarker distribution Table 1 summarizes the demographic and clinical characteristics of the 302 patients with Parkinson’s disease included in the analysis. The mean age of the study population was 64.7 ± 8.9 years, and 176 patients (58.3%) were male. There were no statistically significant differences between groups with respect to age (65.1 ± 8.7 vs. 64.2 ± 9.1 years; p = 0.41) or sex distribution (60.1% vs. 56.3% male; p = 0.52). The median disease duration was 7.1 years (4.2–10.3). The median LEDD was 720 mg/day (520–980). According to dyskinesia status, 158 patients (52.3%) were classified as dyskinesia-positive and 144 patients (47.7%) as dyskinesia-negative. Patients with dyskinesia had a longer disease duration (8.6 [5.9–12.1] vs. 5.4 [3.6–7.8] years; p < 0.001) and higher LEDD (860 [650–1,120] vs. 590 [450–760] mg/day; p < 0.001) compared with those without dyskinesia. Hoehn and Yahr stage was also higher in the dyskinesia-positive group (median 2.5 [2.0–3.0] vs. 2.0 [1.5–2.5]; p = 0.002), as were MDS-UPDRS part III motor scores (38.4 ± 11.2 vs. 32.1 ± 10.6; p < 0.001). Table 1 Clinical characteristics and biomarker distribution according to dyskinesia status Characteristic Total (n = 302) Dyskinesia-Positive (n = 158) Dyskinesia-Negative (n = 144) p-value Age (years) 64.7 ± 8.9 65.1 ± 8.7 64.2 ± 9.1 0.41 Male sex, n (%) 176 (58.3%) 95 (60.1%) 81 (56.3%) 0.52 Disease Duration (years) 7.1 (4.2–10.3) 8.6 (5.9–12.1) 5.4 (3.6–7.8) < 0.001 LEDD (mg/day) 720 (520–980) 860 (650-1,120) 590 (450–760) < 0.001 Hoehn and Yahr Stage 2.3 (2.0–3.0) 2.5 (2.0–3.0) 2.0 (1.5–2.5) 0.002 MDS-UPDRS Part III Motor Score 35.5 ± 11.8 38.4 ± 11.2 32.1 ± 10.6 < 0.001 WBC (×10 9 /L) 7.3 ± 1.8 7.9 ± 1.9 6.6 ± 1.5 < 0.001 Neutrophils (×10 9 /L) 4.5 (3.6–5.4) 5.1 (4.3-6.0) 3.9 (3.2–4.7) < 0.001 Lymphocytes (×10 9 /L) 1.9 (1.5–2.3) 1.7 (1.3-2.0) 2.1 (1.7–2.5) < 0.001 Monocytes (×10 9 /L) 0.50 (0.50–0.62) 0.55 (0.45–0.68) 0.44 (0.36–0.55) < 0.001 Serum ferritin (ng/mL) 128 (82–196) 152 (101–228) 104 (71–156) < 0.001 NLR 2.4 (1.8–3.2) 2.8 (2.1–3.7) 2.0 (1.5–2.6) < 0.001 LMR 3.9 (3.1–4.8) 3.5 (2.8–4.2) 4.3 (3.5–5.2) < 0.001 Serum C-Reactive Protein (mg/L) 2.5 (1.3–4.8) 3.0 (1.8–5.5) 2.1 (1.2–3.5) < 0.001 LEDD, levodopa equivalent daily dose; MDS-UPDRS, Movement Disorder Society-Unified Parkinson’s Disease Rating Scale; WBC, white blood cells; NLR, neutrophil-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio. The distribution of biomarkers was also assessed based on dyskinesia status. The median serum ferritin level in the overall cohort was 128 ng/mL (82–196), the median NLR was 2.4 (1.8–3.2), and the median LMR was 3.9 (3.1–4.8). Patients with dyskinesia had significantly higher serum ferritin levels (152 [101–228] vs. 104 [71–156] ng/mL; p < 0.001) and NLR (2.8 [2.1–3.7] vs. 2.0 [1.5–2.6]; p < 0.001) compared to those without dyskinesia (Fig. 1 ). In contrast, LMR was lower in the dyskinesia-positive group (3.5 [2.8–4.2] vs. 4.3 [3.5–5.2]; p < 0.001). The distribution of both biomarkers showed greater variability in the dyskinesia-positive group, whereas values in the dyskinesia-negative group clustered within lower ranges. Multivariable regression analyses In the multivariable regression analysis, higher serum ferritin levels were significantly associated with increased dyskinesia severity as measured by the total UdysRS (Table 2 ). After adjusting for age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, MDS-UPDRS part III score, serum C-reactive protein level, and current amantadine use, patients in the highest quartile of ferritin had significantly higher UDysRS scores compared to those in the lowest quartile (β = 6.4, 95% confidence interval [CI] 3.1–9.7; p < 0.001). A similar trend was observed for the NLR, where patients in the highest quartile had significantly higher UDysRS scores compared to the lowest quartile (β = 4.9, 95% CI 2.0–7.8; p = 0.001). In contrast, higher LMR was independently associated with lower dyskinesia severity (β = −4.1, 95% CI − 7.0 to − 1.2; p = 0.006). Table 2 Multivariable linear regression analysis of factors associated with dyskinesia severity Variable β coefficient 95% Confidence Interval p-value Serum ferritin (quartiles) Q1 (lowest) Reference — — Q2 2.1 0.3 to 3.9 0.024 Q3 4.2 1.8 to 6.6 0.001 Q4 (highest) 6.4 3.1 to 9.7 < 0.001 NLR (quartiles) Q1 (lowest) Reference — — Q2 1.6 -0.2 to 3.4 0.08 Q3 3.1 1.0 to 5.2 0.004 Q4 (highest) 4.9 2.0 to 7.8 0.001 LMR (quartiles) Q1 (lowest) Reference — — Q2 -1.2 -3.0 to 0.6 0.19 Q3 -2.8 -4.9 to -0.7 0.009 Q4 (highest) -4.1 -7.0 to -1.2 0.006 Age (per year) 0.04 -0.06 to 0.14 0.43 Male sex 0.9 -0.8 to 2.6 0.29 Disease duration (per year) 0.72 0.45 to 0.99 < 0.001 LEDD (per 100 mg/day) 0.83 0.55 to 1.11 < 0.001 Hoehn and Yahr stage 2.1 0.8 to 3.4 0.002 MDS-UPDRS part III score 0.18 0.09 to 0.27 < 0.001 C-reactive protein (mg/L) 0.21 -0.05 to 0.47 0.11 Amantadine use (yes) -1.9 -3.6 to -0.2 0.028 NLR, neutrophil-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio; LEDD, levodopa equivalent daily dose;MDS-UPDRS = Movement Disorder Society-Unified Parkinson’s Disease Rating Scale. Sensitivity and subgroup analyses Ferritin, NLR, and LMR remained independently associated with dyskinesia severity when included in the same regression model, and no significant attenuation of the effect estimates was observed. No significant interaction was observed between ferritin and inflammatory ratios (p for interaction > 0.05). Results were unchanged after exclusion of patients with C-reactive protein levels > 5 mg/L. Subgroup analyses stratified by disease duration and LEDD showed effect modification. The association between ferritin and dyskinesia severity was stronger in patients with longer disease duration (≥ 7 years; β = 1.25, 95% CI 0.85–1.65; p < 0.001). Similarly, the association between NLR and dyskinesia severity was more pronounced in those receiving higher LEDD (≥ 800 mg/day; β = 1.15, 95% CI 0.95–1.45; p < 0.001). Conversely, the inverse association between LMR and dyskinesia severity remained significant in patients with longer disease duration (β = −1.02, 95% CI − 1.68 to − 0.36; p = 0.003), whereas the association was attenuated and no longer significant among those with shorter disease duration (β = −0.38, 95% CI − 1.10 to 0.34; p = 0.29). Discussion Our analysis focused on the variation in serum ferritin levels and inflammatory cell ratios in relation to levodopa-induced dyskinesia among 302 patients with Parkinson’s disease. Dyskinesia was present in 158 patients (52.3%) and was characterized by higher ferritin concentrations and elevated neutrophil-to-lymphocyte ratios, accompanied by lower lymphocyte-to-monocyte ratios compared with patients without dyskinesia. Higher ferritin and NLR, as well as lower LMR, remained independently associated with greater dyskinesia severity after adjustment for disease duration, dopaminergic exposure, and motor impairment. These results align with prior evidence implicating systemic inflammation and iron dysregulation in Parkinson’s disease 22 , 23 and indicate that peripheral immune markers capture biological processes relevant to dyskinesia expression 24 , 25 . Ferritin increased progressively across quartiles in relation to dyskinesia severity, demonstrating a dose-dependent association. Beyond its role in iron storage, ferritin acts as an acute-phase protein reflecting inflammatory activation 26 . Iron dysregulation has been consistently demonstrated in Parkinson’s disease, particularly in basal ganglia regions susceptible to oxidative stress 27 , 28 . Excess iron promotes reactive oxygen species generation, lipid peroxidation, and mitochondrial dysfunction within dopaminergic terminals 29 , 30 , increasing oxidative burden during chronic levodopa exposure. Neuroimaging and experimental studies have demonstrated that increased regional iron deposition is associated with greater motor severity and faster disease progression in Parkinson’s disease 31 , 32 . However, evidence directly linking iron metabolism to dyskinesia remains limited. Elevated serum ferritin may therefore represent a peripheral indicator of iron-driven oxidative processes associated with dyskinesia severity, without directly quantifying regional brain iron deposition. NLR was independently associated with dyskinesia severity, with significant effects observed predominantly in the highest quartiles, indicating that clinically relevant differences emerged at elevated levels of systemic inflammation. As a composite index integrating neutrophil predominance and relative lymphocyte reduction, NLR reflects a shift toward innate immune activation. Previous studies have linked elevated NLR to greater motor severity and faster progression in Parkinson’s disease 14 , 33 ; however, its relationship with levodopa-induced dyskinesia has not been specifically examined. Our findings extend these observations to dyskinesia severity. Neutrophils contribute to inflammatory amplification through reactive oxygen species generation, myeloperoxidase activity, proteolytic enzyme release, and formation of neutrophil extracellular traps, mechanisms that promote endothelial activation and increased blood–brain barrier permeability 34 , 35 . Peripheral immune activation has been shown to enhance microglial priming and central cytokine signaling within nigrostriatal circuits, including IL-1β and TNF-α pathways implicated in synaptic remodeling 6 , 23 . In the striatum, inflammatory signaling may modulate glutamatergic transmission and D1 receptor–dependent intracellular cascades, processes central to maladaptive corticostriatal plasticity underlying dyskinesia 36 , 37 . Elevated NLR may therefore represent a neutrophil-dominant inflammatory state associated with increased vulnerability to aberrant plastic responses during chronic pulsatile dopaminergic stimulation. LMR demonstrated an inverse association with dyskinesia severity that remained significant after adjustment for clinical covariates and in models including ferritin and NLR, indicating an independent association with LID expression. Significant effects were observed in the upper quartiles, consistent with a graded relationship across the distribution. While peripheral leukocyte ratios have been examined in relation to both the presence of Parkinson’s disease and overall motor severity 14 , 38 , data specifically addressing LMR in levodopa-induced dyskinesia are limited. LMR reflects the relative balance between circulating lymphocytes and monocytes. Lower LMR implies relative monocyte predominance, a state associated with enhanced inflammasome activation and increased production of IL-1β and TNF-α. Circulating monocytes can infiltrate the central nervous system under inflammatory conditions and amplify microglial activation within basal ganglia circuits 39 . Proinflammatory cytokines modulate striatal intracellular signaling pathways, including ERK- and DARPP-32–dependent cascades implicated in corticostriatal plasticity 40 . Reduced LMR may therefore represent a peripheral correlate of monocyte-driven inflammatory signaling associated with enhanced maladaptive plasticity during chronic dopaminergic stimulation. The associations of ferritin, NLR, and LMR with dyskinesia severity remained significant after adjustment for age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, motor severity, C-reactive protein, and amantadine use, indicating independence from overall disease burden and dopaminergic exposure. C-reactive protein was not significantly associated with dyskinesia severity (p = 0.11), indicating that ferritin and leukocyte-derived ratios reflect inflammatory and iron-related pathways not captured by CRP. The limited variability of CRP in this cohort may have reduced its discriminatory capacity. No significant interaction was observed between ferritin and inflammatory ratios (p > 0.05), supporting independent contributions of iron-related and immune-related pathways. Subgroup analyses demonstrated effect modification: ferritin showed stronger associations in patients with longer disease duration (≥ 7 years), whereas NLR effects were more pronounced at higher dopaminergic doses (LEDD ≥ 800 mg/day). The inverse association of LMR was attenuated in earlier disease stages. These patterns are consistent with increased dyskinesia susceptibility in patients with prolonged disease exposure and higher dopaminergic load. The present findings have clinical implications. Serum ferritin and leukocyte-derived ratios are routinely available, minimally invasive measures independently associated with UDysRS-defined dyskinesia severity, beyond disease duration and dopaminergic exposure. Elevated ferritin and NLR, together with reduced LMR, may identify a systemic profile linked to greater dyskinesia burden. Incorporation of these markers into clinical assessment may support risk stratification, particularly in patients with longer disease duration or higher levodopa equivalent doses, in whom dyskinesia susceptibility is increased. Given the observational design, these findings do not justify therapeutic modification of iron metabolism or systemic inflammation. Rather, ferritin and leukocyte-derived ratios may serve as accessible indicators of systemic processes associated with LID severity, requiring validation in longitudinal studies. This study has several limitations. Although conducted within a prospective cohort framework, biomarker measurements and dyskinesia assessments were obtained at a single time point, limiting temporal inference and precluding causal interpretation. Ferritin, as an acute-phase reactant, may be influenced by occult inflammatory or metabolic conditions despite predefined exclusion criteria, and residual confounding cannot be fully excluded. NLR and LMR are nonspecific systemic immune indices and do not directly quantify central neuroinflammatory activity; peripheral alterations should not be assumed to reflect intranigrostriatal processes. Although dyskinesia severity was assessed in a standardized medication “ON” state, interindividual variability in peak-dose timing may have introduced measurement heterogeneity. Future studies should incorporate longitudinal designs with repeated biomarker assessments to determine temporal trajectories and predictive value for incident dyskinesia. Expanded iron metabolism profiling, including transferrin saturation, serum iron, and hepcidin, together with broader inflammatory panels, may enhance mechanistic specificity and strengthen model performance. In conclusion, our findings demonstrate an association between serum ferritin, NLR, LMR and the severity of levodopa-induced dyskinesia in Parkinson’s disease. Elevated ferritin and NLR, together with reduced LMR, were linked to greater dyskinesia burden. These routinely available biomarkers may have potential utility in identifying patients with more severe dyskinesia and may contribute to clinical risk assessment. Further longitudinal studies are required to validate these observations and to clarify the biological mechanisms underlying LID. Abbreviations LID Levodopa-induced dyskinesia PD Parkinson’s disease NLR Neutrophil-to-lymphocyte ratio LMR Lymphocyte-to-monocyte ratio UDysRS Unified Dyskinesia Rating Scale CRP C-reactive protein MDS-UPDRS Movement Disorder Society–Unified Parkinson’s Disease Rating Scale MDS-UPDRS IV Movement Disorder Society–Unified Parkinson’s Disease Rating Scale part IV MDS-UPDRS III Movement Disorder Society–Unified Parkinson’s Disease Rating Scale part III LEDD Levodopa equivalent daily dose IQR Interquartile range WBC White blood cells CI Confidence interval IL-1β Interleukin-1 beta TNF-α Tumor necrosis factor alpha ERK Extracellular signal-regulated kinase DARPP-32 Dopamine- and cAMP-regulated phosphoprotein of 32 kDa Declarations Ethics approval and consent to participate This study was conducted ethically in accordance with the guidelines of the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of Tashkent Medical Academy (approval No. TMA-IRB/2020-12). Written informed consent was obtained from all participants prior to enrollment. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests Funding: Not applicable. Author Contribution FS IK: conceptualization, methodology, formal analysis, supervision, project administration and writing (review and editing); DP MP NM YA JS: investigation and resources; AY DA: software and data curation; GS XT: validation; FS DP AY: writing (original draft); IK GS: writing (review and editing); MP NM: visualization. All authors read and approved the final manuscript and are responsible for the overall content. Acknowledgements Not applicable. Data Availability Data can be obtained by contacting the first author or corresponding author by email. References Santos-García D, De Deus T, Cores C, et al. 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MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015;30(12):1591–601. 10.1002/mds.26424 . Goetz CG, Nutt JG, Stebbins GT. The Unified Dyskinesia Rating Scale: Presentation and clinimetric profile. Mov Disord. 2008;23(16):2398–403. 10.1002/mds.22341 . Goetz CG, Tilley BC, Shaftman SR, et al. Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS‐UPDRS): Scale presentation and clinimetric testing results. Mov Disord. 2008;23(15):2129–70. 10.1002/mds.22340 . Stebbins GT, Goetz CG, Burn DJ, Jankovic J, Khoo TK, Tilley BC. How to identify tremor dominant and postural instability/gait difficulty groups with the movement disorder society unified Parkinson’s disease rating scale: Comparison with the unified Parkinson’s disease rating scale. Mov Disord. 2013;28(5):668–70. 10.1002/mds.25383 . Tomlinson CL, Stowe R, Patel S, Rick C, Gray R, Clarke CE. Systematic review of levodopa dose equivalency reporting in Parkinson’s disease. Mov Disord. 2010;25(15):2649–53. 10.1002/mds.23429 . Pepys MB, Hirschfield GM. C-reactive protein: a critical update. J Clin Invest. 2003;111(12):1805–12. 10.1172/JCI200318921 . Ward RJ, Zucca FA, Duyn JH, Crichton RR, Zecca L. The role of iron in brain ageing and neurodegenerative disorders. Lancet Neurol. 2014;13(10):1045–60. 10.1016/S1474-4422(14)70117-6 . Tansey MG, Romero-Ramos M. Immune system responses in Parkinson’s disease: Early and dynamic. Eur J Neurosci. 2019;49(3):364–83. 10.1111/ejn.14290 . Muñoz-Delgado L, Macías‐García D, Jesús S, et al. Peripheral Immune Profile and Neutrophil‐to‐Lymphocyte Ratio in Parkinson’s Disease. Mov Disord. 2021;36(10):2426–30. 10.1002/mds.28685 . Madetko N, Migda B, Alster P, Turski P, Koziorowski D, Friedman A. Platelet-to-lymphocyte ratio and neutrophil-tolymphocyte ratio may reflect differences in PD and MSA-P neuroinflammation patterns. Neurol Neurochir Pol. 2022;56(2):148–55. 10.5603/PJNNS.a2022.0014 . Kernan KF, Carcillo JA. Hyperferritinemia and inflammation. Int Immunol. 2017;29(9):401–9. 10.1093/intimm/dxx031 . He N, Ling H, Ding B, et al. Region-specific disturbed iron distribution in early idiopathic P arkinson’s disease measured by quantitative susceptibility mapping. Hum Brain Mapp. 2015;36(11):4407–20. 10.1002/hbm.22928 . Guan X, Xuan M, Gu Q, et al. Regionally progressive accumulation of iron in Parkinson’s disease as measured by quantitative susceptibility mapping. NMR Biomed. 2017;30(4):e3489. 10.1002/nbm.3489 . Mochizuki H, Yasuda T. Iron accumulation in Parkinson’s disease. J Neural Transm. 2012;119(12):1511–4. 10.1007/s00702-012-0905-9 . Belaidi AA, Bush AI. Iron neurochemistry in Alzheimer’s disease and Parkinson’s disease: targets for therapeutics. J Neurochem. 2016;139(S1):179–97. 10.1111/jnc.13425 . Hartono S, Chen RC, Welton T, et al. Quantitative iron–neuromelanin MRI associates with motor severity in Parkinson’s disease and matches radiological disease classification. Front Aging Neurosci. 2023;15:1287917. 10.3389/fnagi.2023.1287917 . Thomas GEC, Leyland LA, Schrag AE, Lees AJ, Acosta-Cabronero J, Weil RS. Brain iron deposition is linked with cognitive severity in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2020;91(4):418–25. 10.1136/jnnp-2019-322042 . Yi H, Liang X, Xu F, et al. Association between neutrophil-to-lymphocyte ratio and motor subtypes in idiopathic Parkinson’s disease: a prospective observational study. BMC Neurol. 2024;24(1):379. 10.1186/s12883-024-03887-7 . Kolaczkowska E, Kubes P. Neutrophil recruitment and function in health and inflammation. Nat Rev Immunol. 2013;13(3):159–75. 10.1038/nri3399 . Allen C, Thornton P, Denes A, et al. Neutrophil Cerebrovascular Transmigration Triggers Rapid Neurotoxicity through Release of Proteases Associated with Decondensed DNA. J Immunol. 2012;189(1):381–92. 10.4049/jimmunol.1200409 . Bandopadhyay R, Mishra N, Rana R, et al. Molecular Mechanisms and Therapeutic Strategies for Levodopa-Induced Dyskinesia in Parkinson’s Disease: A Perspective Through Preclinical and Clinical Evidence. Front Pharmacol. 2022;13:805388. 10.3389/fphar.2022.805388 . Calabresi P, Picconi B, Tozzi A, Di Filippo M. Dopamine-mediated regulation of corticostriatal synaptic plasticity. Trends Neurosci. 2007;30(5):211–9. 10.1016/j.tins.2007.03.001 . Sun Y, Li S, Shi S, Liu Y. Association between inflammatory markers and Parkinson’s disease risk: a cross-sectional, propensity score-matched analysis of NHANES data. BMC Neurol. 2025;26(1):55. 10.1186/s12883-025-04598-3 . Harms AS, Thome AD, Yan Z, et al. Peripheral monocyte entry is required for alpha-Synuclein induced inflammation and Neurodegeneration in a model of Parkinson disease. Exp Neurol. 2018;300:179–87. 10.1016/j.expneurol.2017.11.010 . Santini E, Feyder M, Gangarossa G, Bateup HS, Greengard P, Fisone G. Dopamine- and cAMP-regulated Phosphoprotein of 32-kDa (DARPP-32)-dependent Activation of Extracellular Signal-regulated Kinase (ERK) and Mammalian Target of Rapamycin Complex 1 (mTORC1) Signaling in Experimental Parkinsonism. J Biol Chem. 2012;287(33):27806–12. 10.1074/jbc.M112.388413 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8934743","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604919318,"identity":"7d37e983-76f1-4d9e-b8db-ce49e9a7ac17","order_by":0,"name":"Farrukh Saidvaliyev","email":"","orcid":"","institution":"Tashkent Medical Academy","correspondingAuthor":false,"prefix":"","firstName":"Farrukh","middleName":"","lastName":"Saidvaliyev","suffix":""},{"id":604919319,"identity":"bc602852-027c-4db1-895e-64c0954784d7","order_by":1,"name":"Dilyora Pulatova","email":"","orcid":"","institution":"Tashkent Medical Academy","correspondingAuthor":false,"prefix":"","firstName":"Dilyora","middleName":"","lastName":"Pulatova","suffix":""},{"id":604919320,"identity":"2dac770b-9d93-41a5-8faa-41e034293da6","order_by":2,"name":"Ibodulla Kilichev","email":"","orcid":"","institution":"Urgench Branch of Tashkent Medical Academy","correspondingAuthor":false,"prefix":"","firstName":"Ibodulla","middleName":"","lastName":"Kilichev","suffix":""},{"id":604919321,"identity":"1ddbabe2-883d-4e9b-a3d2-2d44b887f5d7","order_by":3,"name":"Adkham Yusupov","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYFCCHBSeTT0/kDzwgAQtaQmSDUAtCSRoOZxgcABI4dPC35578NMNhsOJ82fkHnzMw3A4z/ja4YdAW+4lNuDQInHmXbJ0DlDLhht5ycY8DOnFZrfTDIBainFqYbiRYwDRIpFjJjmDwZpx2+0EkJYEnFrkb+QY/84BOwyshZlx8+z0D3i1GNzIMQPb0gBkSHxgcE7cIJ2D3xbDM2/MrHMM0o03AD1l8MEgzVjidk7BgQSDBGNcWuSO5xjfzqmwlp0PDLoHCRU2cvyz0zd/+FCRIIvT+xDnNQMJHhADLoJXPQjUQbWMglEwCkbBKMACAHPxXnw/YAPOAAAAAElFTkSuQmCC","orcid":"","institution":"Urgench Branch of Tashkent Medical Academy","correspondingAuthor":true,"prefix":"","firstName":"Adkham","middleName":"","lastName":"Yusupov","suffix":""},{"id":604919322,"identity":"0e9f382c-1952-4d09-bae8-e276566cbdf2","order_by":4,"name":"Gulnora Shamuratova","email":"","orcid":"","institution":"Mamun University","correspondingAuthor":false,"prefix":"","firstName":"Gulnora","middleName":"","lastName":"Shamuratova","suffix":""},{"id":604919323,"identity":"8c9bf0c7-57e3-4f54-b205-fbe009334582","order_by":5,"name":"Xusan Turdibekov","email":"","orcid":"","institution":"Samarkand State Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xusan","middleName":"","lastName":"Turdibekov","suffix":""},{"id":604919324,"identity":"d1862959-5bcd-4778-b0c2-380af42e7777","order_by":6,"name":"Mukhriddin Pulatov","email":"","orcid":"","institution":"Termez University of Economics and Service","correspondingAuthor":false,"prefix":"","firstName":"Mukhriddin","middleName":"","lastName":"Pulatov","suffix":""},{"id":604919325,"identity":"013c75a3-d390-4b53-9eb8-6f4e34a967ac","order_by":7,"name":"Jasur Saidov","email":"","orcid":"","institution":"Termez University of Economics and Service","correspondingAuthor":false,"prefix":"","firstName":"Jasur","middleName":"","lastName":"Saidov","suffix":""},{"id":604919326,"identity":"d84a8d3e-7398-41fa-ad21-2f82aadc23d2","order_by":8,"name":"Nozimakhon Mirhayotova","email":"","orcid":"","institution":"Tashkent Medical Academy","correspondingAuthor":false,"prefix":"","firstName":"Nozimakhon","middleName":"","lastName":"Mirhayotova","suffix":""},{"id":604919327,"identity":"e4dd45ad-31f8-4d9e-9fcc-fa166b3212d2","order_by":9,"name":"Yulduz Axmedova","email":"","orcid":"","institution":"Urgench Branch of Tashkent Medical Academy","correspondingAuthor":false,"prefix":"","firstName":"Yulduz","middleName":"","lastName":"Axmedova","suffix":""},{"id":604919328,"identity":"7c040b94-3242-4c7c-9d74-58b8106d670d","order_by":10,"name":"Dilnoza Abdullayeva","email":"","orcid":"","institution":"Urgench Branch of Tashkent Medical Academy","correspondingAuthor":false,"prefix":"","firstName":"Dilnoza","middleName":"","lastName":"Abdullayeva","suffix":""}],"badges":[],"createdAt":"2026-02-21 16:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8934743/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8934743/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104668757,"identity":"e99c019c-3c06-4875-a51e-34b84c88baa8","added_by":"auto","created_at":"2026-03-15 16:54:58","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":200414,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots of peripheral iron and inflammatory biomarkers according to levodopa-induced dyskinesia status. (\u003cstrong\u003ea\u003c/strong\u003e) Serum ferritin levels in LID-negative and LID-positive patients. (\u003cstrong\u003eb\u003c/strong\u003e) Neutrophil-to-lymphocyte ratio (NLR) in LID-negative and LID-positive patients. (\u003cstrong\u003ec\u003c/strong\u003e) Lymphocyte-to-monocyte ratio (LMR) in LID-negative and LID-positive patients.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8934743/v1/065a7b82950494242b9cff10.jpeg"},{"id":104668758,"identity":"39783a17-6f88-4bcf-942a-c8bb5f83cfed","added_by":"auto","created_at":"2026-03-15 16:55:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1055414,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8934743/v1/4dd76bae-60ae-4d8d-a746-7682697555aa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Peripheral Iron and Immune Markers Are Associated With Levodopa-Induced Dyskinesia Severity in Parkinson’s Disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLevodopa-induced dyskinesia (LID) is a frequent and disabling motor complication of Parkinson\u0026rsquo;s disease (PD), characterized by involuntary hyperkinetic movements that emerge during chronic dopaminergic treatment and are commonly accompanied by fluctuations in motor control, functional impairment, and a marked reduction in quality of life \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Around 30% of patients develop levodopa-induced dyskinesia within 5 years of starting treatment, and the prevalence increases to approximately 70% after 10 years of continued therapy \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Although levodopa remains the most effective therapy for the cardinal motor symptoms of PD, the development of dyskinesia represents a major limitation of long-term dopaminergic treatment and often necessitates complex medication adjustments, thereby compromising sustained therapeutic benefit \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Beyond its clinical expression as a motor complication, LID reflects broader pathophysiological processes involving dopaminergic dysregulation, maladaptive neural plasticity, and biological mechanisms extending beyond the central nervous system \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGrowing evidence indicates that systemic inflammation and altered iron metabolism contribute to PD pathophysiology beyond dopaminergic neurodegeneration \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Ferritin, a peripheral marker of iron storage, has been associated with neurodegenerative processes and inflammatory states and may reflect dysregulated iron homeostasis relevant to oxidative stress and neuronal vulnerability \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Neuroimaging and pathological studies have consistently demonstrated abnormal iron accumulation in PD-related brain regions, supporting a potential link between iron metabolism and disease progression \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In parallel, low-grade systemic inflammation, commonly assessed using C-reactive protein (CRP), has been associated with motor severity, non-motor symptoms, and longitudinal disease progression in PD \u003csup\u003e9\u003c/sup\u003e. These findings suggest that inflammatory and iron-related pathways may interact and modulate the development of treatment-related motor complications, including LID, although direct clinical evidence remains scarce.\u003c/p\u003e \u003cp\u003eThe neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR), derived from routine blood counts, are practical indicators of systemic inflammatory status. Neutrophils contribute to systemic inflammation through the release of cytokines, reactive oxygen species, and proteolytic enzymes, which may enhance blood\u0026ndash;brain barrier permeability and facilitate neuroinflammatory cascades \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In contrast, lymphocytes, particularly regulatory T cells, are involved in modulating immune responses and maintaining immune homeostasis. A relative reduction in lymphocyte counts may therefore indicate impaired immunoregulatory capacity \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Monocytes, as precursors of macrophages and microglia-like cells, can migrate into the central nervous system and amplify neuroinflammation through cytokine production and activation of resident glial cells \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Recent studies have demonstrated that elevated NLR and altered LMR values are associated with greater disease severity, more rapid progression, and poorer clinical outcomes in Parkinson\u0026rsquo;s disease \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, the relationship between NLR, LMR, peripheral iron metabolism, and levodopa-induced dyskinesia has not been examined in a PD population.\u003c/p\u003e \u003cp\u003eThe aim of this study was to investigate the association between serum ferritin levels, NLR, LMR and the presence and severity of levodopa-induced dyskinesia in patients with idiopathic Parkinson\u0026rsquo;s disease.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eWe consecutively recruited patients with idiopathic Parkinson\u0026rsquo;s disease from the neurology department at Tashkent Medical Academy between January 2021 and September 2025. Inclusion criteria were a clinical diagnosis of Parkinson\u0026rsquo;s disease according to the Movement Disorder Society criteria \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, age between 40 and 80 years, and treatment with levodopa for at least 24 months with no change in dopaminergic medication during the preceding 30 days. Patients were included irrespective of the presence of levodopa-induced dyskinesia. Conditions known to affect ferritin levels or systemic inflammatory markers were excluded, including recent infection or antibiotic use, active inflammatory or autoimmune disease, malignancy, hematologic disorders, blood transfusion, iron supplementation, significant hepatic or renal dysfunction, atypical or secondary parkinsonism, and a history within the preceding month of chronic inflammatory or inflammatory-related conditions such as osteoarthritis, osteoporosis, fever, or allergic conditions. The study protocol was reviewed and approved by the Ethics Committee of Tashkent Medical Academy (approval No. TMA-IRB/2020-12). All procedures were conducted in accordance with the Declaration of Helsinki (2013 revision). Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment of clinical symptoms\u003c/h3\u003e\n\u003cp\u003eAll clinical evaluations were performed by a movement disorder specialists through face‒to-face interviews and detailed questionnaires. Demographic and clinical data, including age, sex, disease duration, disease stage, motor severity, levodopa equivalent daily dose, and current antiparkinsonian medications, were recorded. Evaluations were conducted in the medication \u0026ldquo;ON\u0026rdquo; state, defined as 60\u0026ndash;90 minutes after intake of the patient\u0026rsquo;s usual levodopa dose, to ensure consistent assessment of peak-dose motor complications. Levodopa-induced dyskinesia was assessed using the Unified Dyskinesia Rating Scale (UDysRS) \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, which served as the measure of dyskinesia severity and functional impact. For phenotypic classification, patients were categorized according to the presence or absence of levodopa-induced dyskinesia based on clinical observation and UDysRS scoring. Patients with any clinically detectable dyskinesia were classified as dyskinesia-positive, whereas those without observable dyskinesia during assessment and without reported dyskinesia episodes in the preceding month were classified as dyskinesia-negative. Clinical assessment additionally encompassed motor complications evaluated using the Movement Disorder Society\u0026ndash;Unified Parkinson\u0026rsquo;s Disease Rating Scale part IV (MDS-UPDRS part IV) \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, disease stage determined according to the Hoehn and Yahr scale \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and motor severity quantified using the Movement Disorder Society\u0026ndash;Unified Parkinson\u0026rsquo;s Disease Rating Scale part III \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eLaboratory measurements and biomarker assessment\u003c/h3\u003e\n\u003cp\u003eVenous blood samples were collected during the same study visit, in the morning (06:00\u0026ndash;08:00 a.m.) after an 8 h overnight fasting period. Samples were collected in clot activator tubes, centrifuged at 3,000 rpm for 10 minutes, and analyzed within 4 hours in a single laboratory. Serum ferritin levels were assessed using an automated chemiluminescent immunoassay (Cobas e411, Germany). Complete blood counts were performed on the same blood draw using an automated hematology analyzer (Sysmex XN-1000, Japan). The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. LMR was calculated by dividing the absolute lymphocyte count by the absolute monocyte count. Serum C-reactive protein levels were measured concurrently.\u003c/p\u003e\n\u003ch3\u003eMedication exposure and covariates\u003c/h3\u003e\n\u003cp\u003eDopaminergic medication exposure was standardized using the levodopa equivalent daily dose (LEDD), calculated according to the conversion factors proposed by Tomlinson et al. (2010) and analyzed as a continuous variable \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. All antiparkinsonian medications, including levodopa formulations, dopamine agonists, monoamine oxidase B inhibitors, catechol-O-methyltransferase inhibitors, and amantadine, were recorded at the time of clinical assessment. Medication regimens were considered stable if no changes in drug type, daily dose, or dosing frequency had occurred within the 30 days preceding enrollment.\u003c/p\u003e \u003cp\u003eClinical covariates were selected a priori based on their known associations with dyskinesia and included age, sex, disease duration, Hoehn and Yahr stage, and motor severity assessed by the MDS-UPDRS part III. Current use of amantadine was included as a binary covariate given its potential influence on dyskinesia severity. These variables were incorporated into multivariable models to control for confounding effects.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median with interquartile range (IQR), as appropriate, and categorical variables as counts and percentages. Comparisons between patients with and without levodopa-induced dyskinesia were conducted using the Student\u0026rsquo;s t test or Mann\u0026ndash;Whitney U test for continuous variables and the chi-square test or Fisher\u0026rsquo;s exact test for categorical variables. Associations between serum ferritin levels, NLR, LMR, and dyskinesia-related outcomes were evaluated using multivariable regression models. Dyskinesia severity was analyzed as a continuous outcome using linear regression with the total Unified Dyskinesia Rating Scale score as the dependent variable, whereas the presence of dyskinesia was examined using logistic regression. Ferritin, NLR and LMR were analyzed in quartiles. All models were adjusted for covariates, including age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, MDS-UPDRS part III score, serum C-reactive protein level, and current amantadine use. An interaction term between ferritin and inflammatory ratios (NLR and LMR) were included in the regression models to assess potential effect modification. Model assumptions were evaluated by inspection of residuals, multicollinearity was assessed using variance inflation factors, and sensitivity analyses excluded patients with elevated C-reactive protein levels (\u0026gt;\u0026thinsp;5 mg/L) \u003csup\u003e21\u003c/sup\u003e. All tests were two-sided, with a p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant. Statistical analyses were performed using SPSS software (version 26.0; IBM Corp., Armonk, NY, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and clinical characteristics and biomarker distribution\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the demographic and clinical characteristics of the 302 patients with Parkinson\u0026rsquo;s disease included in the analysis. The mean age of the study population was 64.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9 years, and 176 patients (58.3%) were male. There were no statistically significant differences between groups with respect to age (65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7 vs. 64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1 years; p\u0026thinsp;=\u0026thinsp;0.41) or sex distribution (60.1% vs. 56.3% male; p\u0026thinsp;=\u0026thinsp;0.52). The median disease duration was 7.1 years (4.2\u0026ndash;10.3). The median LEDD was 720 mg/day (520\u0026ndash;980). According to dyskinesia status, 158 patients (52.3%) were classified as dyskinesia-positive and 144 patients (47.7%) as dyskinesia-negative. Patients with dyskinesia had a longer disease duration (8.6 [5.9\u0026ndash;12.1] vs. 5.4 [3.6\u0026ndash;7.8] years; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher LEDD (860 [650\u0026ndash;1,120] vs. 590 [450\u0026ndash;760] mg/day; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with those without dyskinesia. Hoehn and Yahr stage was also higher in the dyskinesia-positive group (median 2.5 [2.0\u0026ndash;3.0] vs. 2.0 [1.5\u0026ndash;2.5]; p\u0026thinsp;=\u0026thinsp;0.002), as were MDS-UPDRS part III motor scores (38.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2 vs. 32.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics and biomarker distribution according to dyskinesia status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;302)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDyskinesia-Positive (n\u0026thinsp;=\u0026thinsp;158)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDyskinesia-Negative (n\u0026thinsp;=\u0026thinsp;144)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease Duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.1 (4.2\u0026ndash;10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6 (5.9\u0026ndash;12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.4 (3.6\u0026ndash;7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEDD (mg/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e720 (520\u0026ndash;980)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e860 (650-1,120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e590 (450\u0026ndash;760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoehn and Yahr Stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3 (2.0\u0026ndash;3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5 (2.0\u0026ndash;3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 (1.5\u0026ndash;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS-UPDRS Part III Motor Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5 (3.6\u0026ndash;5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.1 (4.3-6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.9 (3.2\u0026ndash;4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocytes (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9 (1.5\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7 (1.3-2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 (1.7\u0026ndash;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocytes (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50 (0.50\u0026ndash;0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55 (0.45\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44 (0.36\u0026ndash;0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (82\u0026ndash;196)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152 (101\u0026ndash;228)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (71\u0026ndash;156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.4 (1.8\u0026ndash;3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8 (2.1\u0026ndash;3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 (1.5\u0026ndash;2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9 (3.1\u0026ndash;4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (2.8\u0026ndash;4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3 (3.5\u0026ndash;5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum C-Reactive Protein (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5 (1.3\u0026ndash;4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0 (1.8\u0026ndash;5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 (1.2\u0026ndash;3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eLEDD, levodopa equivalent daily dose; MDS-UPDRS, Movement Disorder Society-Unified Parkinson\u0026rsquo;s Disease Rating Scale; WBC, white blood cells; NLR, neutrophil-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe distribution of biomarkers was also assessed based on dyskinesia status. The median serum ferritin level in the overall cohort was 128 ng/mL (82\u0026ndash;196), the median NLR was 2.4 (1.8\u0026ndash;3.2), and the median LMR was 3.9 (3.1\u0026ndash;4.8). Patients with dyskinesia had significantly higher serum ferritin levels (152 [101\u0026ndash;228] vs. 104 [71\u0026ndash;156] ng/mL; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and NLR (2.8 [2.1\u0026ndash;3.7] vs. 2.0 [1.5\u0026ndash;2.6]; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those without dyskinesia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, LMR was lower in the dyskinesia-positive group (3.5 [2.8\u0026ndash;4.2] vs. 4.3 [3.5\u0026ndash;5.2]; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The distribution of both biomarkers showed greater variability in the dyskinesia-positive group, whereas values in the dyskinesia-negative group clustered within lower ranges.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMultivariable regression analyses\u003c/h3\u003e\n\u003cp\u003eIn the multivariable regression analysis, higher serum ferritin levels were significantly associated with increased dyskinesia severity as measured by the total UdysRS (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After adjusting for age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, MDS-UPDRS part III score, serum C-reactive protein level, and current amantadine use, patients in the highest quartile of ferritin had significantly higher UDysRS scores compared to those in the lowest quartile (β\u0026thinsp;=\u0026thinsp;6.4, 95% confidence interval [CI] 3.1\u0026ndash;9.7; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A similar trend was observed for the NLR, where patients in the highest quartile had significantly higher UDysRS scores compared to the lowest quartile (β\u0026thinsp;=\u0026thinsp;4.9, 95% CI 2.0\u0026ndash;7.8; p\u0026thinsp;=\u0026thinsp;0.001). In contrast, higher LMR was independently associated with lower dyskinesia severity (β = \u0026minus;4.1, 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;7.0 to \u0026minus;\u0026thinsp;1.2; p\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable linear regression analysis of factors associated with dyskinesia severity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% Confidence Interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin (quartiles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3 to 3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8 to 6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1 to 9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR (quartiles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.2 to 3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0 to 5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 to 7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMR (quartiles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.0 to 0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.9 to -0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.0 to -1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.06 to 0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.8 to 2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration (per year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45 to 0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEDD (per 100 mg/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55 to 1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoehn and Yahr stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 to 3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS-UPDRS part III score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09 to 0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.05 to 0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmantadine use (yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.6 to -0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNLR, neutrophil-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio; LEDD, levodopa equivalent daily dose;MDS-UPDRS\u0026thinsp;=\u0026thinsp;Movement Disorder Society-Unified Parkinson\u0026rsquo;s Disease Rating Scale.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity and subgroup analyses\u003c/h2\u003e \u003cp\u003eFerritin, NLR, and LMR remained independently associated with dyskinesia severity when included in the same regression model, and no significant attenuation of the effect estimates was observed. No significant interaction was observed between ferritin and inflammatory ratios (p for interaction\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Results were unchanged after exclusion of patients with C-reactive protein levels\u0026thinsp;\u0026gt;\u0026thinsp;5 mg/L.\u003c/p\u003e \u003cp\u003eSubgroup analyses stratified by disease duration and LEDD showed effect modification. The association between ferritin and dyskinesia severity was stronger in patients with longer disease duration (\u0026ge;\u0026thinsp;7 years; β\u0026thinsp;=\u0026thinsp;1.25, 95% CI 0.85\u0026ndash;1.65; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, the association between NLR and dyskinesia severity was more pronounced in those receiving higher LEDD (\u0026ge;\u0026thinsp;800 mg/day; β\u0026thinsp;=\u0026thinsp;1.15, 95% CI 0.95\u0026ndash;1.45; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, the inverse association between LMR and dyskinesia severity remained significant in patients with longer disease duration (β = \u0026minus;1.02, 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;1.68 to \u0026minus;\u0026thinsp;0.36; p\u0026thinsp;=\u0026thinsp;0.003), whereas the association was attenuated and no longer significant among those with shorter disease duration (β = \u0026minus;0.38, 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;1.10 to 0.34; p\u0026thinsp;=\u0026thinsp;0.29).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur analysis focused on the variation in serum ferritin levels and inflammatory cell ratios in relation to levodopa-induced dyskinesia among 302 patients with Parkinson\u0026rsquo;s disease. Dyskinesia was present in 158 patients (52.3%) and was characterized by higher ferritin concentrations and elevated neutrophil-to-lymphocyte ratios, accompanied by lower lymphocyte-to-monocyte ratios compared with patients without dyskinesia. Higher ferritin and NLR, as well as lower LMR, remained independently associated with greater dyskinesia severity after adjustment for disease duration, dopaminergic exposure, and motor impairment. These results align with prior evidence implicating systemic inflammation and iron dysregulation in Parkinson\u0026rsquo;s disease \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and indicate that peripheral immune markers capture biological processes relevant to dyskinesia expression \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFerritin increased progressively across quartiles in relation to dyskinesia severity, demonstrating a dose-dependent association. Beyond its role in iron storage, ferritin acts as an acute-phase protein reflecting inflammatory activation \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Iron dysregulation has been consistently demonstrated in Parkinson\u0026rsquo;s disease, particularly in basal ganglia regions susceptible to oxidative stress \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Excess iron promotes reactive oxygen species generation, lipid peroxidation, and mitochondrial dysfunction within dopaminergic terminals \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, increasing oxidative burden during chronic levodopa exposure. Neuroimaging and experimental studies have demonstrated that increased regional iron deposition is associated with greater motor severity and faster disease progression in Parkinson\u0026rsquo;s disease \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, evidence directly linking iron metabolism to dyskinesia remains limited. Elevated serum ferritin may therefore represent a peripheral indicator of iron-driven oxidative processes associated with dyskinesia severity, without directly quantifying regional brain iron deposition.\u003c/p\u003e \u003cp\u003eNLR was independently associated with dyskinesia severity, with significant effects observed predominantly in the highest quartiles, indicating that clinically relevant differences emerged at elevated levels of systemic inflammation. As a composite index integrating neutrophil predominance and relative lymphocyte reduction, NLR reflects a shift toward innate immune activation. Previous studies have linked elevated NLR to greater motor severity and faster progression in Parkinson\u0026rsquo;s disease \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e; however, its relationship with levodopa-induced dyskinesia has not been specifically examined. Our findings extend these observations to dyskinesia severity. Neutrophils contribute to inflammatory amplification through reactive oxygen species generation, myeloperoxidase activity, proteolytic enzyme release, and formation of neutrophil extracellular traps, mechanisms that promote endothelial activation and increased blood\u0026ndash;brain barrier permeability \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Peripheral immune activation has been shown to enhance microglial priming and central cytokine signaling within nigrostriatal circuits, including IL-1β and TNF-α pathways implicated in synaptic remodeling \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In the striatum, inflammatory signaling may modulate glutamatergic transmission and D1 receptor\u0026ndash;dependent intracellular cascades, processes central to maladaptive corticostriatal plasticity underlying dyskinesia \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Elevated NLR may therefore represent a neutrophil-dominant inflammatory state associated with increased vulnerability to aberrant plastic responses during chronic pulsatile dopaminergic stimulation.\u003c/p\u003e \u003cp\u003eLMR demonstrated an inverse association with dyskinesia severity that remained significant after adjustment for clinical covariates and in models including ferritin and NLR, indicating an independent association with LID expression. Significant effects were observed in the upper quartiles, consistent with a graded relationship across the distribution. While peripheral leukocyte ratios have been examined in relation to both the presence of Parkinson\u0026rsquo;s disease and overall motor severity \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, data specifically addressing LMR in levodopa-induced dyskinesia are limited.\u003c/p\u003e \u003cp\u003eLMR reflects the relative balance between circulating lymphocytes and monocytes. Lower LMR implies relative monocyte predominance, a state associated with enhanced inflammasome activation and increased production of IL-1β and TNF-α. Circulating monocytes can infiltrate the central nervous system under inflammatory conditions and amplify microglial activation within basal ganglia circuits \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Proinflammatory cytokines modulate striatal intracellular signaling pathways, including ERK- and DARPP-32\u0026ndash;dependent cascades implicated in corticostriatal plasticity \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Reduced LMR may therefore represent a peripheral correlate of monocyte-driven inflammatory signaling associated with enhanced maladaptive plasticity during chronic dopaminergic stimulation.\u003c/p\u003e \u003cp\u003eThe associations of ferritin, NLR, and LMR with dyskinesia severity remained significant after adjustment for age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, motor severity, C-reactive protein, and amantadine use, indicating independence from overall disease burden and dopaminergic exposure. C-reactive protein was not significantly associated with dyskinesia severity (p\u0026thinsp;=\u0026thinsp;0.11), indicating that ferritin and leukocyte-derived ratios reflect inflammatory and iron-related pathways not captured by CRP. The limited variability of CRP in this cohort may have reduced its discriminatory capacity. No significant interaction was observed between ferritin and inflammatory ratios (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), supporting independent contributions of iron-related and immune-related pathways. Subgroup analyses demonstrated effect modification: ferritin showed stronger associations in patients with longer disease duration (\u0026ge;\u0026thinsp;7 years), whereas NLR effects were more pronounced at higher dopaminergic doses (LEDD\u0026thinsp;\u0026ge;\u0026thinsp;800 mg/day). The inverse association of LMR was attenuated in earlier disease stages. These patterns are consistent with increased dyskinesia susceptibility in patients with prolonged disease exposure and higher dopaminergic load.\u003c/p\u003e \u003cp\u003eThe present findings have clinical implications. Serum ferritin and leukocyte-derived ratios are routinely available, minimally invasive measures independently associated with UDysRS-defined dyskinesia severity, beyond disease duration and dopaminergic exposure. Elevated ferritin and NLR, together with reduced LMR, may identify a systemic profile linked to greater dyskinesia burden. Incorporation of these markers into clinical assessment may support risk stratification, particularly in patients with longer disease duration or higher levodopa equivalent doses, in whom dyskinesia susceptibility is increased. Given the observational design, these findings do not justify therapeutic modification of iron metabolism or systemic inflammation. Rather, ferritin and leukocyte-derived ratios may serve as accessible indicators of systemic processes associated with LID severity, requiring validation in longitudinal studies.\u003c/p\u003e \u003cp\u003eThis study has several limitations. Although conducted within a prospective cohort framework, biomarker measurements and dyskinesia assessments were obtained at a single time point, limiting temporal inference and precluding causal interpretation. Ferritin, as an acute-phase reactant, may be influenced by occult inflammatory or metabolic conditions despite predefined exclusion criteria, and residual confounding cannot be fully excluded. NLR and LMR are nonspecific systemic immune indices and do not directly quantify central neuroinflammatory activity; peripheral alterations should not be assumed to reflect intranigrostriatal processes. Although dyskinesia severity was assessed in a standardized medication \u0026ldquo;ON\u0026rdquo; state, interindividual variability in peak-dose timing may have introduced measurement heterogeneity. Future studies should incorporate longitudinal designs with repeated biomarker assessments to determine temporal trajectories and predictive value for incident dyskinesia. Expanded iron metabolism profiling, including transferrin saturation, serum iron, and hepcidin, together with broader inflammatory panels, may enhance mechanistic specificity and strengthen model performance.\u003c/p\u003e \u003cp\u003eIn conclusion, our findings demonstrate an association between serum ferritin, NLR, LMR and the severity of levodopa-induced dyskinesia in Parkinson\u0026rsquo;s disease. Elevated ferritin and NLR, together with reduced LMR, were linked to greater dyskinesia burden. These routinely available biomarkers may have potential utility in identifying patients with more severe dyskinesia and may contribute to clinical risk assessment. Further longitudinal studies are required to validate these observations and to clarify the biological mechanisms underlying LID.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLID\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLevodopa-induced dyskinesia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eParkinson\u0026rsquo;s disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNLR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeutrophil-to-lymphocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLMR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLymphocyte-to-monocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eUDysRS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnified Dyskinesia Rating Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCRP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMDS-UPDRS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMovement Disorder Society\u0026ndash;Unified Parkinson\u0026rsquo;s Disease Rating Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMDS-UPDRS IV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMovement Disorder Society\u0026ndash;Unified Parkinson\u0026rsquo;s Disease Rating Scale part IV\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMDS-UPDRS III\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMovement Disorder Society\u0026ndash;Unified Parkinson\u0026rsquo;s Disease Rating Scale part III\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLEDD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLevodopa equivalent daily dose\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWBC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWhite blood cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIL-1β\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-1 beta\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTNF-α\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor necrosis factor alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eERK\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtracellular signal-regulated kinase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDARPP-32\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDopamine- and cAMP-regulated phosphoprotein of 32 kDa\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003e This study was conducted ethically in accordance with the guidelines of the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of Tashkent Medical Academy (approval No. TMA-IRB/2020-12). Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eFS IK: conceptualization, methodology, formal analysis, supervision, project administration and writing (review and editing); DP MP NM YA JS: investigation and resources; AY DA: software and data curation; GS XT: validation; FS DP AY: writing (original draft); IK GS: writing (review and editing); MP NM: visualization. All authors read and approved the final manuscript and are responsible for the overall content.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003e Data can be obtained by contacting the first author or corresponding author by email.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSantos-Garc\u0026iacute;a D, De Deus T, Cores C, et al. Levodopa‐Induced Dyskinesias are Frequent and Impact Quality of Life in Parkinson\u0026rsquo;s Disease: A 5‐Year Follow‐Up Study. 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J Biol Chem. 2012;287(33):27806\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1074/jbc.M112.388413\u003c/span\u003e\u003cspan address=\"10.1074/jbc.M112.388413\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Parkinson’s disease, levodopa-induced dyskinesia, serum ferritin, neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio","lastPublishedDoi":"10.21203/rs.3.rs-8934743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8934743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLevodopa-induced dyskinesia (LID) is a common motor complication of Parkinson’s disease (PD), yet peripheral biological factors associated with dyskinesia severity remain insufficiently characterized. Systemic inflammation and iron dysregulation have been implicated in PD, but their relationship with LID expression is unclear. We investigated the association between serum ferritin, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and the presence and severity of LID.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, 302 patients with idiopathic PD receiving stable levodopa therapy for at least 24 months were evaluated. Dyskinesia severity was assessed in the medication “ON” state using the Unified Dyskinesia Rating Scale (UDysRS). Serum ferritin and complete blood counts were obtained from fasting samples, and NLR and LMR were calculated. Multivariable regression analyses were performed adjusting for age, sex, disease duration, levodopa equivalent daily dose, Hoehn and Yahr stage, motor severity, C-reactive protein, and amantadine use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLID was present in 158 patients (52.3%). Patients with dyskinesia had higher median ferritin levels (152 vs. 104 ng/mL, p \u0026lt; 0.001) and NLR (2.8 vs. 2.0, p \u0026lt; 0.001), and lower LMR (3.5 vs. 4.3, p \u0026lt; 0.001) compared with those without dyskinesia. In adjusted analyses, the highest ferritin quartile was associated with greater UDysRS scores (β = 6.4, p \u0026lt; 0.001), as were the highest NLR quartile (β = 4.9, p = 0.001). Conversely, higher LMR was independently associated with lower dyskinesia severity (β=−4.1, p = 0.006).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eElevated serum ferritin and altered leukocyte-derived ratios (NLR, LMR) were independently associated with increased levodopa-induced dyskinesia severity in Parkinson’s disease. These biomarkers may reflect systemic biological processes linked to dyskinesia burden and warrant further evaluation in longitudinal studies.\u003c/p\u003e","manuscriptTitle":"Peripheral Iron and Immune Markers Are Associated With Levodopa-Induced Dyskinesia Severity in Parkinson’s Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-15 16:54:53","doi":"10.21203/rs.3.rs-8934743/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-14T09:55:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-10T10:33:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44901256437830705074190974822685190537","date":"2026-04-03T01:25:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-16T12:59:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71716356560355147875898308958735364460","date":"2026-03-15T06:25:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-11T06:33:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-06T06:08:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-02T05:59:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-27T22:53:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Neurology","date":"2026-02-27T17:21:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e2dab8f-9ea6-4a38-a273-daf3d8b988e9","owner":[],"postedDate":"March 15th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T07:10:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-15 16:54:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8934743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8934743","identity":"rs-8934743","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}