Martínez‑Horta et al. BMC Neurology (2021) 21:477 https://doi.org/10.1186/s12883-021-02485-1 RESEARCH Open Access Identifying comorbidities and lifestyle factors contributing to the cognitive profile of early Parkinson’s disease Saul Martínez‑Horta1,2,3, Helena Bejr‑Kasem1,2,3, Andrea Horta‑Barba1,2,3, Berta Pascual‑Sedano1,2,3, Diego Santos‑García4, Teresa de Deus‑Fonticoba5, Silvia Jesús3,6, Miquel Aguilar7, Lluis Planellas8, Juan García‑Caldentey9, Nuria Caballol10, Bárbara Vives‑Pastor11, Jorge Hernández‑Vara12, Iria Cabo‑Lopez13, Lydia López‑Manzanares14, Isabel González‑Aramburu15, Maria Asunción Ávila‑Rivera10, Maria Jose Catalán16, Luis Manuel López‑Díaz17, Victor Puente18, Jose Manuel García‑Moreno19, Carmen Borrué20, Berta Solano‑Vila21, Maria Álvarez‑Sauco22, Lydia Vela23, Sonia Escalante24, Esther Cubo25, Francisco Carrillo‑Padilla26, Juan Carlos Martínez‑Castrillo27, Pilar Sánchez‑Alonso28, Maria Gema Alonso‑Losada29, Nuria López‑Ariztegui30, Itziar Gastón31, Marta Blázquez‑Estrada32, Manual Seijo‑Martínez13, Javier Rúiz‑Martínez33, Caridad Valero‑Merino34, Monica Kurtis35, Oriol de Fábregues‑Boixar12, Jessica González‑Ardura36, Cristina Prieto‑Jurczynska37, Pablo Martinez‑Martin3,38, Pablo Mir3,6,39 and Jaime Kulisevsky1,2,3* COPPADIS Study Group Abstract Background: Identifying modifiable risk factors for cognitive impairment in the early stages of Parkinson’s disease (PD) and estimating their impact on cognitive status may help prevent dementia (PDD) and the design of cognitive trials. Methods: Using a standard approach for the assessment of global cognition in PD and controlling for the effects of age, education and disease duration, we explored the associations between cognitive status, comorbidities, meta‑ bolic variables and lifestyle variables in 533 PD participants from the COPPADIS study. Results: Among the overall sample, 21% of participants were classified as PD-MCI (n = 114) and 4% as PDD (n = 26). The prevalence of hypertension, diabetes and dyslipidemia was significantly higher in cognitively impaired patients while no between-group differences were found for smoking, alcohol intake or use of supplementary vitamins. Bet‑ ter cognitive scores were significantly associated with regular physical exercise (p < 0.05) and cognitive stimulation (< 0.01). Cognitive performance was negatively associated with interleukin 2 (Il2) (p < 0.05), Il6 (p < 0.05), iron (p < 0.05), and homocysteine (p < 0.005) levels, and positively associated with vitamin B12 levels (p < 0.005). Conclusions: We extend previous findings regarding the positive and negative influence of various comorbidities and lifestyle factors on cognitive status in early PD patients, and reinforce the need to identify and treat potentially *Correspondence: jkulisevsky@santpau.cat 1 Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Mas Casanovas 90, 08041 Barcelona, Spain Full list of author information is available at the end of the article © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 2 of 10 modifiable variables with the intention of exploring the possible improvement of the global cognitive status of patients with PD. Keywords: Parkinson’s disease, PD-MCI, Cognition, Lifestyle, Coppadis Introduction slow the progression dementia, and optimize sample Cognitive impairment has long been considered a late selection for cognitive trials. complication of Parkinson’s disease (PD) [1, 2]. However, For this purpose, we used the basal assessments of the it is currently accepted that cognitive changes of vary- COPPADIS study (COhort of Patients with PArkinson’s ing severity can be detected from the onset of the dis- DIsease in Spain) [22, 23]. The COPPADIS is an obser- ease, and that a significant proportion of PD patients will vational, 5-year follow-up, nationwide, multicenter study develop dementia (PDD) during the course of the illness aimed to further clarify the course of PD. It provides [1–5]. data related to a patient’s lifestyle, the presence of other Among the early and heterogeneous cognitive mani- associated comorbidities, and multiple measurements festations of PD, alterations that fulfill criteria for mild obtained from plasma. The study was designed to use a cognitive impairment (PD-MCI) are associated with an global cognitive instrument to assess participants’ cogni- increased risk of PDD [6–8]. At diagnosis, PD-MCI is tive status: the PD-specific Parkinson’s Disease-Cognitive found in up to 36% of PD patients. Prevalence increases Rating Scale (PD-CRS) [24]. Recent guidelines from the up to 57% after 3.5 years, and progresses to dementia in Movement Disorders Society (MDS) include the PD-CRS around 36% of patients within 4 years of diagnosis [3, (as ‘recommended’) among the instruments suitable for 9]. The long-term prevalence of PDD is about 80% [2]. PD [21]. Based on a large and representative sample of Accordingly, both PD-MCI and PDD are frequent fea- patients with early-stage PD, our main objectives were to tures of PD. However, although both entities -especially explore the possible contribution of potentially modifia- dementia- have a devastating impact, treatments to delay ble comorbid variables and lifestyle factors to global cog- or prevent the progression of cognitive deterioration in nitive functioning. PD are lacking [10]. Recognizing and understanding the mechanisms underlying the development and progres- Methods sion of cognitive impairment in PD is therefore an urgent unmet need. Identifying potentially modifiable variables Participants and variables that may contribute to the progression of cognitive dete- Cross-sectional data from the COPPADIS study (data- rioration could improve clinical practice and benefit cog- base released on May 2019) were used. Details regarding nitive trials. the methods used in the COPPADIS study can be found Among the universe of PD patients who will develop in the original publications [22, 23]. From the cross-sec- dementia, the range of patterns and trajectories in which tional database of 901 participants (207 healthy controls the condition will progress is wide. The challenge is to and 694 PD patients) we included only PD participants predict which early PD patients are likely to develop inci- for whom the following variables were available: age, dent dementia at a more rapid rate. The severity of cog- disease duration, body weight, L-dopa (LD) daily dose, nitive changes occurring in PD has been attributed to dopamine agonist (DA) daily dose, and LD equivalent several neuropathological mechanisms that influence the daily dose, Hoehn &Yahr (H&Y) stage [25], the Unified extent and the progression of brain damage [11]. Genetic Parkinson’s Disease Rating Scale part III (UPDRS-III) factors such as MAPT haplotypes [12–14], GBA muta- [26], the Neuropsychiatric Inventory (NPI) [27], and the tions or variants of the nurturin gene [15], age, disease Parkinson’s Disease - Cognitive Rating Scale (PD-CRS) duration, protein misfolding and aggregation, synaptic [24]. We also collected data regarding the regularity of dysfunction and loss, neuroinflammation, and epigenet- physical exercise and cognitive stimulation throughout ics are all known to contribute to cognitive changes in PD the previous year. We also recorded any history of hyper- [16–20]. However, the association between potentially tension, diabetes, dyslipidemia, cardiopathy, arrythmia, treatable comorbidities, lifestyle factors and cognitive smoking, alcohol consumption and supplementary vita- deterioration has been little explored in large samples of mins intake. Several blood testing variables were also early-PD populations, and even less explored using PD- collected: levels of protein s100B, TNF alpha, IL-1, IL-2, validated and recommended cognitive instruments [17, IL-6, vitamin B12, methylmalonic acid, homocysteine, 21]. Refining such information could enable the design of CRP, uric acid, ferritin, and iron. We excluded patients strategies to prevent key risk factors, improve therapies, with a history of chronic anemia, other neurologic Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 3 of 10 diseases, or severe non-compensated diseases. Written Table 1 Clinical and sociodemographic characteristics of the informed consent was obtained from all participants and sample all procedures were performed in accordance with the N = 533 Mean ± SD Range standards of the ethics committee at each study site, and in accordance with the 1964 Declaration of Helsinki and Age 62.5 ± 8.6 35–75 its later amendments. Disease duration (months) 5.52 ± 6 0–114 UPDRS-IIIa (off ) 21.9 ± 11 2–78 H&Yb (off ) 2 1–4 Statistical analysis Stage 1 14.7% – Data are expressed as means ± standard deviations (SDs) Stage 1.5 9.2% – for continuous variables and as percentages for the cat- Stage 2 60% – egorical variables. Taking into account the normal distri- Stage 2.5 7.1% – bution of the scores according to the Shapiro-Wilk test, Stage 3 7.8% – we performed group comparisons using independent Stage 4 1.3% – t tests and analyses of variance (ANOVAs) for continu- LDDc 527 ± 420 0–2220 ous variables, Mann–Whitney for ordinal data, and the χ2 DAd equivalent daily dose 182 ± 172 0–1387 test for categorical variables. Descriptive analysis of the clinical and sociodemo- PD-CRSe Total 91.8 ± 15.4 44–135 a graphic characteristics of the sample was performed. UPDRS: Unified Parkinson’s Disease Rating Scale; bH & Y: Hoehn and Yahr; cLDD: L-dopa daily dose; dDA: Dopaminergic agonist; ePD-CRS: Parkinson’s Disease – According to the PD-CRS, the sample was grouped as Cognitive Rating Scale cognitively preserved (PD-NC=PD-CRS total score > 80), PD-MCI (PD-CRS total score < 81 and > 64), and PD- dementia (PDD) (PD-CRS total score < 65) [24, 28]. studies was also higher in the PD-NC group than in the One-way ANOVA and subsequent post-hoc t-test and PDD group (χ2 < 0.001). No differences in education were chi-square comparisons were performed to assess group found between the PD-MCI and PDD groups (χ2 = 0.203). differences. Bivariate Pearson’s correlation coefficient Bivariate correlation analysis showed a significant analysis, logistic regression analysis and linear regres- moderate association between older age and worse cog- sion analysis (Mild = 0.20–0.35; Moderate = 0.36–0.60; nitive status (r = − 0.410; p < 0.001). However, disease and High > 0.60) were used controlling the effect of age, duration was not significantly associated with global cog- education or other potentially confounding variables to nitive performance. explore possible associations between the variables of interest. Cognitive and neuropsychiatric profile Significant differences were found between groups in Results the total PD-CRS score [F(1,532) = 430.2; p < 0.001] and Clinical and sociodemographic characteristics in related sub-scores. We found a clear pattern of worse The sample consisted of 533 participants performance in the PD-CRS total score in the PD-MCI (mean age = 62.5 ± 8.6; mean disease dura- group with respect to the PD-NC group [t(507) = 34.2; tion = 5.52 ± 6 months; median H&Y stage = 2; p < 0.001], and in the PDD group with respect to the PD- IQR = 1–4). Table 1 includes all data regarding the par- MCI [t(140) = 15.6; p < 0.001] and PD-NC [t(419) = 32.1; ticipants´ main clinical and sociodemographic charac- p < 0.001] groups. As depicted in Table 2, we also found teristics. Using the PD-CRS, among the total sample we significant differences between patients in the PD-NC found = 114 (21%) were PD-MCI, and 26 (4.8%) were and PD-MCI groups, and between patients in the PD- PDD. MCI and PDD groups in the scores from all the subtests As seen in Table 2, no significant differences were comprising the PD-CRS. found between cognitive groups regarding disease dura- The prevalence of neuropsychiatric symptoms (Table 3) tion, body weight, or medication. Patients in the PD-MCI presenting with sufficient severity to be considered clini- and the PDD groups were significantly older than those cally relevant (NPI > 1) differed significantly between in the PD-NC group [F(1,532) = 31.8; p < 0.001]. No dif- groups for dysphoria (p < 0.05) and for apathy (p < 0.005). ferences were found regarding age between PD-MCI These differences were driven by an increased preva- and PDD groups [t(140) = − 0.81; p = 0.419]. Regarding lence of dysphoria in the PD-MCI group (41.8%) with education level, the proportion of patients with second- respect to the PD-NC (28.8%) and PDD groups (33.3%), ary and university studies was significantly higher in the and by a progressively higher prevalence of apathy in PD-NC group than in the PD-MCI group (χ2 < 0.001). the three groups (PD-NC = 21.4% vs PD-MCI = 35.4% The proportion of patients with secondary and university vs PDD = 42.9%). Post-hoc comparisons determined Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 4 of 10 Table 2 Clinical, sociodemographic and assessment values for each cognitive group PD-NC (n = 393) PD-MCI (n = 114) PDD (n = 26) p-value Post-hoc a Age 60.8 ± 8.8 67.1 ± 6.4 68.1 ± 8.6 < 0.001 < 0.001; b0.876 Education Primary (%) 32.1 68.4 84.6 < 0.001 – Secondary (%) 35.1 26.3 15.4 < 0.001 – University (%) 32.6 5.3 0 < 0.001 – a Disease duration (months) 5.59 ± 6.6 5.42 ± 3.5 4.96 ± 4.3 0.858 0.962; b0.964 a Hypertension (% yes) 30.3 45.6 34.6 < 0.05 < 0.05; 0.212 a Diabetes mellitus (% yes) 5.6 15.8 15.4 < 0.005 < 0.05; b0.613 a Dyslipidaemia (% yes) 28.8 39.5 38.5 0.070 < 0.05; b0.554 a Cardiopathy (% yes) 7.9 11.4 3.8 0.340 0.162; b0.221 Arrhythmia (% yes) 4.3 7 3.8 0.486 0.176; b0.475 a Smoking (% yes)) 9.7 9.6 15.4 0.828 0.347; b0.521 a Alcohol (% yes) 21.6 19.3 23.1 0.842 0.347; b0.422 a Vitamin supplementation (% yes) 5.9 2.6 7.7 0.338 0.126; b0.232 a TSREM (% yes) 37.7 39.5 46.2 0.888 < 0.818; b0.341 a UPDRS-III (off ) 21.1 ± 11 23.4 ± 11 27.3 ± 11 0.006 0.117; b0.016 a H&Y (off ) 1.9 ± 0.5 1.9 ± 0.6 2.2 ± 0.6 0.006 0.608; b0.039 a LD equivalent daily dose 506 ± 398 567 ± 462 627 ± 530 0.088 0.382; b0.500 a DA equivalent daily dose 179 ± 169 182 ± 184 223 ± 177 0.486 0.986; b0.453 a Cognitive stimulation (%) 18.1% 12.3% 11.5% 0.268 0.092; b0.610 a Exercise (%) 69.7% 64% 50% 0.077 0.150; b0.135 a PD-CRS Total 98.8 ± 10 75.1 ± 4 58.8 ± 5 < 0.001 < 0.001; b < 0.001 a Fronto-subcortical 70.2 ± 10.4 49.1 ± 5.2 36 ± 6.8 < 0.001 < 0.001; b < 0.001 a   Immediate verbal memory 8.6 ± 1.8 6.7 ± 2.1 5.7 ± 1.7 < 0.001 < 0.001; b0.039 a   Sustained attention 9 ± 1.2 7.4 ± 2 5.2 ± 3 < 0.001 < 0.001; b < 0.001 a   Working memory 7.7 ± 2 5.2 ± 2 3.6 ± 2 < 0.001 < 0.001; b < 0.001 a   Clock draw 9.4 ± 1.4 8.3 ± 1.4 7 ± 2.3 < 0.001 < 0.001; b < 0.001 a   Delayed free recall 6.2 ± 2.5 4.1 ± 2 2.3 ± 2 < 0.001 < 0.001; b < 0.001 a   Alternating verbal fluency 12.8 ± 3.7 7.2 ± 2.6 5.5 ± 3.3 < 0.001 < 0.001; b0.078 a   Action verbal fluency 16.4 ± 5.3 10 ± 3.1 7.6 ± 3.3 < 0.001 < 0.001; b0.059 a Posterior-cortical 28.5 ± 2.6 26 ± 3.6 22.8 ± 4 < 0.001 < 0.001; b < 0.001 a   Confrontation naming 18.7 ± 2.4 16.9 ± 3.6 14.8 ± 3.9 < 0.001 < 0.001; b0.002 a   Clock copy 9.8 ± 1 9±1 8±2 < 0.001 < 0.001; b < 0.001 a Protein S100B 0.125 ± 0.6 0.094 ± 0.10 0.086 ± 0.01 0.932 0.941; b0.999 a TNF alpha 7.2 ± 3 7.5 ± 4.5 6.4 ± 3.5 0.701 0.903; b0.684 a IL-1 3.8 ± 15.1 4.4 ± 6.7 6.5 ± 7.3 0.849 0.969; b0.917 a IL-2 1.9 ± 7.5 6.4 ± 33.8 30.5 ± 79.4 < 0.005 0.529; b< 0.005 a IL-6 2.3 ± 3.5 4.2 ± 9.6 9 ± 17.7 < 0.01 0.242; b< 0.05 a Vitamin B12 396.4 ± 152.2 395.4 ± 209.9 358 ± 137.48 0.817 0.999; b0.831 a Methylmalonic acid 0.16 ± 0.1 0.17 ± 0.1 0.26 ± 0.26 0.070 0.767; b0.168 a Homocysteine 14 ± 5.3 15.3 ± 7.7 16.2 ± 4 0.355 0.488; b0.914 a CRP 0.2 ± 0.3 0.22 ± 0.29 0.19 ± 0.34 0.922 0.917; b0.974 a Uric acid 5.5 ± 2.2 5.5 ± 1.6 5.8 ± 0.9 0.916 0.999; b0.927 a Ferritin 126.6 ± 110 117 ± 163 60 ± 58 0.367 0.906; b0.500 a Iron 91.7 ± 36.7 80 ± 31.4 80 ± 30.5 0.158 0.174; b0.999 a p ≤ 0.05 significance based on paired t-test. (PD-NC vs PD-MCI) b p ≤ 0.05 significance based on paired t-test. (PD-MCI vs PDD) Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 5 of 10 Table 3 Neuropsychiatric symptoms PD-NC PD-MCI PDD p-value Post-hoc a NPI Total (frequency x severity) 5.4 ± 7.3 7.7 ± 8.7 9 ± 9.9 0.007 < 0.001; b0.721 a % NPI total > 1 60.4 70.2 72.7 0.126 0.05; 0.518 a Delirium 0.1 ± 0.9 0.2 ± 0.9 0±0 0.586 0.726; b0.619 a % NPI > 1 2.3 4.3 0 0.432 0.246; b0.441 a Hallucinations 0.1 ± 0.7 0.3 ± 1.5 0.3 ± 0.8 0.162 0.150; b0.951 a % NPI > 1 3.3 7.1 9.5 0.138 0.088; b0.496 a Agitation 0.4 ± 1.2 0.5 ± 1.3 0.9 ± 1.7 0.183 0.585; b0.525 a % NPI > 1 9.1 13.5 19 0.198 0.141; b0.362 a Depression/dysphoria 1.3 ± 2.1 2 ± 2.9 2.2 ± 3.4 0.020 0.034; b0.258 a % NPI > 1 21.8 41.8 33.8 0.055 < 0.05; b0.320 a Anxiety 1.4 ± 2.3 1.6 ± 2.3 1.5 ± 2.1 0.708 0.684; b0.988 a % NPI > 1 33 39.2 34.8 0.537 0.160; b0.445 a Euphoria 0.2 ± 0.9 0.2 ± 0.8 0±0 0.666 0.934; b0.548 a % NPI > 1 4.7 6.3 0 0.460 0.340; b0.293 a Apathy 0.9 ± 2 1.9 ± 3 2.3 ± 2.7 < 0.001 < 0.001; b0.839 a % NPI > 1 21.4 35.4 42.9 < 0.005 < 0.005; b0.341 a Disinhibition 0.06 ± 0.4 0.1 ± 0.6 0±0 0.183 0.230; b0.341 a % NPI > 1 1.7 3.2 0 0.520 0.294; b0.543 a Irritability 0.8 ± 1.6 1.1 ± 2 1.3 ± 2.3 0.132 0.207; b0.930 a % NPI > 1 20 27.4 27.3 0.265 0.086; b0.610 a Aberrant motor behaviour 0.2 ± 1 0.2 ± 0.7 0.7 ± 2.1 0.102 0.985; b0.134 a % NPI > 1 4 6.4 9.5 0.373 0.238; b0.448 a p ≤ 0.05 significance based on paired t-test. (PD-NC vs PD-MCI) b p ≤ 0.05 significance based on paired t-test. (PD-MCI vs PDD) higher scores for dysphoria in the PD-MCI group than in PD-MCI [OR = 1.9; 95% CI = 1.2–2.9]. The prevalence the PD-NC group [t(507) = − 2.17; p < 0.05], and higher of diabetes was significantly increased in the PD-MCI scores for apathy in the PD-MCI group than in the o (15.8%) and PDD (15.4%) groups with respect to the PD-NC group [t(507) = − 2.98; p < 0.005]. Higher apathy PD-NC group (5.6%), and it was associated with a three scores were also found in the PDD group with respect times greater risk for PD-MCI [OR = 3.1; CI = 1.6– to the PD-NC group [t(419) = − 2; p < 0.05]. Clinically 6.1] and a two times greater risk for PDD [OR = 2.1; relevant apathy increased the odds ratio for being clas- CI = 0.6–6.4]. Dyslipidemia was also significantly sified as PD-MCI by 2 [OR = 2.01; 95% CI = 1.2–3.2] increased in both the PD-MCI (39.5%) and the PDD and for being classified as PDD by 2.2 [OR = 2.2; 95% (38.5%; p < 0.05) groups with respect to PD-NC group CI = 0.9–5.5]. (28.8%). No between-group differences were found for the other comorbidities, including history of smok- Comorbidities and lifestyle factors ing, alcohol intake and use of supplementary vitamins. No differences were found between cognitive groups Regarding values collected in blood samples, these were regarding the proportion of patients performing regular available for the 33.6% of the sample (74.4% PD-NC; physical exercise, or between those performing regular 21.2% PD-MCI; 4.3% PDD). Between-group differences cognitive stimulation during the previous year. However, were significant for IL-2 [F(1,532) = 6.1; p < 0.05] and in the total sample, the PD-CRS total score was signifi- for IL-6 [F(1,532) = 4.9; p < 0.01] levels, and a tendency cantly associated with the regularity of physical exercise was found for methylmalonic acid levels [F(1,532) = 2.7; (β = 0.105; p < 0.05) and cognitive stimulation (β = 0.120; p = 0.07]. Post-hoc comparisons determined that p < 0.01). these differences were driven by higher IL-2 levels in The prevalence of hypertension was significantly PDD with respect to both PD-MCI [t(507) = − 4.4; higher in the PD-MCI group (45.6%) than in the PD-NC p < 0.05] and PD-NC [t(507) = − 28; p < 0.005], and (30.3%; p < 0.005) and PDD groups (34.6%; p < 0.05) by higher IL-6 values in PDD with respect to PD-NC and was associated with an increased risk of 1.9 for [t(507) = − 6.6; p < 0.05]. Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 6 of 10 Correlates and predictors analysis impairment are equivalent to those reported in other Linear regression analysis showed significant associa- cohorts of early-stage PD patients [29–31]. Our data tions between higher PD-CRS total score and younger thus highlight the number of subjects in a representative age (β = − 0.416; p < 0.001), education level (β = − 0.451; population of early PD patients who meet criteria for PD- p < 0.001) and lower UPDRS-III (β = − 0.102; p < 0.05). MCI and even PDD. Significant associations independent of age, educa- As expected, older age was significantly associated with tion and motor status were also found between the PD- worse cognitive status, but disease duration was not, sup- CRS total score and the NPI apathy score (β = − 0.173; porting the idea that disease duration is not necessarily p < 0.005). associated with the extent of cognitive deterioration, at In the bivariate Pearson’s correlation analysis per- least during the early stages of PD, and that other factors formed in the total sample, the PD-CRS total score was intervene in this population. negatively associated in an almost negligible range with PD-MCI and PDD were associated with older age the levels of Il2 (r = − 0.146; p < 0.05), Il6 (r = − 0.178; and with education level, but no differences were found p < 0.05), homocysteine (r = − 0.172; p < 0.05) and iron between PD-NC and PD-MCI groups regarding motor (r = − 0.171; p < 0.05). However, these values were also status and disease stage. Conversely, although the strongly associated with age and LD daily dose. Accord- range was similar in terms of disease duration, the PDD ingly, to prevent the potential influence of age and LD, group scored significantly worse in the UPDRS and had these variables were included as covariates in a linear a greater H&Y staging than the PD-NC and PD-MCI regression model. This analysis showed a significant asso- groups. This again suggests that other mechanisms, not ciation between PD-CRS total score and vitamin B12 val- necessarily related to disease duration only, participate in ues (β = 0.169; p < 0.05), homocysteine levels (β = − 0.194; the exacerbation of PD both at motor and cognitive levels p < 0.05) and iron levels (β = 0.177; p < 0.05), and a specific [32–34]. mild association between PD-CRS posterior-cortical per- Among the potentially treatable comorbidities, hyper- formance and IL2 values (β = − 0.269; p < 0.005). tension, diabetes mellitus, and dyslipidemia appeared Logistic regression analysis (step forward conditional) to be more frequent among patients with PD-MCI and was used to explore the classification ability of the vari- PDD. These variables play a critical role in the develop- ous measures. Along with age, the model included edu- ment of vascular lesions and alterations of white matter cation, UPDRS-III, measures regarding comorbidities, in the general population. This type of injury is usually non-motor symptoms, neuropsychiatric symptoms, cog- accompanied by cognitive signs that may trigger cognitive nitive performance, lifestyle factors (smoking, alcohol impairment and dementia. In future studies, therefore, it intake, regularity of exercise), and blood-sample meas- is necessary to emphasize the contribution of brain anom- urements. Focusing on the PD-NC and PD-MCI groups, alies secondary to these variables in the development of we observed that beyond the PD-CRS, age (β = 0.091; cognitive impairment in PD. Focusing on lifestyle factors, p < 0.001), education level (β = − 1.06; p < 0.001) and dys- we found no significant differences between groups in phoria (β = 0.058; p < 0.01) were the strongest contribu- terms of regularity of physical exercise, cognitive stimu- tors to PD-MCI classification. Regarding the PDD group, lation, smoking, or alcohol intake. However, in the over- the strongest associations were found with age (β = 0.102; all sample, there was a positive association between the p < 0.05), education level (β = − 2; p < 0.001), UPDRS- regularity of physical exercise, cognitive stimulation, and III (β = 0.056; p < 0.05), and apathy severity (β = 0.197; global cognitive status. Unfortunately, the data analyzed p < 0.05). Regarding blood-sample values, no significant do not allow us to specify which type of physical and cog- associations were found with PD-MCI. However, Il6 val- nitive exercise, or the frequency of such activities, could ues were associated with PDD (β = 0.076; p < 0.05). be potentially beneficial. In this sense, our results justify more detailed future study concerning the potential ben- Discussion eficial effect of physical and cognitive exercise programs. Our main findings confirm that metabolic variables such Evidence suggesting that exercise may positively influ- as interleukins, homocysteine, iron, and vitamin B12 ence the general management and the cognitive out- have an impact on cognitive status in early PD patients, comes in PD is increasing. Intervention programs of while physical exercise and cognitive stimulation have a moderate intensity aerobic exercise 2–3 times per week protective effect. can lead to long-term improvement in attention/working According to the recommended Level I instrument (the memory and executive function [35] in non-demented PD-CRS), the prevalence of PD-MCI in the COPPADIS patients with mild-to-moderate PD. The association sample at baseline was 21%, whereas the prevalence of between higher cognitive scores and regularity of physi- PDD was 4%. In the main, these prevalences of cognitive cal exercise found in the present study concurs with this Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 7 of 10 information and supports the implementation of strate- less well understood, the reported findings reinforce the gies to motivate adherence to regular exercise programs. need to explore the mechanisms involved in the increase Although the body of evidence is not large, a small ben- in plasma iron levels and the possible contribution of eficial effect on cognition can still be demonstrated with these levels to cognitive impairment in PD. Both Il2 and cognitive training in non-demented PD patients [36–38]. Il6 pro-inflammatory cytokines that stimulate the inflam- Notably, as is the case of physical exercise, most gains matory and auto-immune processes have been suggested were noted in selected tests of attention, working mem- to contribute to apoptosis and neurodegeneration in sev- ory and executive skills, while not improvement was eral diseases, including multiple sclerosis [47], Alzhei- noted in global cognition. mer’s disease [48], and PD [49], and to play a possible role From the values collected in blood samples, interleu- in exacerbating cognitive decline in relatively early stages. kins IL-2 and IL-6 levels were significantly increased in The major strength of this study is the use of a large the PDD group compared to those in the PD-MCI and and representative observational sample recruited from PD-NC groups. The association of these values with the different practice settings to establish the influence of LD daily dose regime suggested that these results could modifiable risk factors on the cognitive profile of early- be influenced by drug treatment. However, when con- PD patients. A second strength is the use of a PD-specific trolling for this effect we still found a significant associa- and recommended cognitive assessment instrument. tion between PD-CRS total score and levels of vitamin Some limitations should be acknowledged. The COP- B12, homocysteine and iron, and a specific association PADIS cohort is not a de novo cohort, and patients less between Il2 levels and PD-CRS posterior-cortical per- than 6 years from diagnosis were enrolled at all levels of formance. Both increased homocysteine and decreased cognitive impairment and disease duration. The study vitamin B12 levels have been associated with mild cog- does not include data on other potential modifiers of nitive impairment and risk of progression to Alzhei- cognitive status such as Mediterranean diet, caloric mer’s type dementia, vascular dementia, and cognitive restriction, or social engagement that were not part of impairment in PD [39–42]. Homocysteine, the meta- the COPPADIS sample, and it does not explore the effect bolic product of methionine, has toxic effects on neurons of the considered variables on the structural integrity of and vascular walls, and its levels are regulated by several grey matter and white matter tracts. pathways, which in turn are conditioned by factors such Undoubtedly, any attempt to mechanistically explain as age, genetics, diet, gender and pharmacological treat- the translation between the values detected in our meas- ments. In PD, treatment with LD has been found to con- urements and their partial effect on the progression tribute to hyperhomocysteinemia [43]. Therefore, it is of cognitive impairment in PD - which appears to be especially relevant to take into account that in addition mainly linked to the multiple processes involved in the to the cardiovascular risk factors that patients with PD pathogenesis of the disease -, could be an oversimplifi- may have, treatment has an effect on metabolism that cation. Nevertheless, while we await the development of can add complexity to the relationship between PD, car- more specific treatments, our data support the need for diovascular pathology and cognitive impairment. In this a global prevention strategy to manage cognitive impair- sense, it is also important to take into account that our ment in early-PD, targeting the identified risk factors. results show a relationship between homocysteine lev- Early identification of cognitive impairment in PD must els, vitamin B12 and cognitive status that is independ- be carried out using adequate screening instruments. ent of age and LD treatment. Therefore, it is necessary to Prevention and treatment of metabolic aspects and other emphasize that abnormalities in homocysteine values in corrective measures, and stronger strategies to motivate PD may not respond exclusively to the effect dictated by practice and adherence to regular exercise and cognitive dopaminergic treatment. In any case, taking into account stimulation programs should be encouraged. this relationship and that found in previous studies, On the basis of our results, future research regarding the need to consider the effect of this variable when we cognitive impairment in PD should take into account explore cognition in PD and the mechanisms that associ- the role of the comorbidities described here. Spe- ate more aggressive cognitive phenotypes is indisputable. cifically, it would be especially relevant to explore the Recently, a relationship between levels of iron accumula- cognitive progression profile of the participants in the tion and cognitive changes in PD has also been demon- COPPADIS study based on the variables identified in strated [44, 45]. Iron is ubiquitous in numerous normal the present study. Likewise, it would be interesting to biological processes and in neurodegeneration [46], and explore the brain correlates that could accompany the undoubtably, brain iron accumulation exerts significant way in which these variables are expressed. In addition, deleterious effects on cognition. Although the relation- the effect mediated by comorbidities should be taken ship between plasma iron levels and cognition is much into account when designing clinical trials. Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 8 of 10 Conclusions Declarations Metabolic variables such as interleukins, homocysteine, Ethics approval and consent to participate iron, and vitamin B12 have an impact on cognitive sta- All procedures were performed in accordance with the standards of the tus in early PD patients, and physical exercise and cog- Ethics Committee at each study site, and in accordance with the 1964 nitive stimulation have a protective effect. Beyond the Declaration of Helsinki and its later amendments. For this study, we received approval from the Galician Ethics Committee for Clinical Research in Spain main neuropathological mechanisms. (2014/534; 02/DEC/2014). Written informed consent was obtained from all that influence the progression of cognitive impair- participants in this study before the start of the study. COPPADIS-2015 was ment in PD, our data also support the need to con- classified by the AEMPS (Agencia Española del Medicamento y Productos Sanitarios) as a Post-authorization Prospective Follow-up study with the code sider other frequent comorbidities and variables COH-PAK-2014-01. related to lifestyle when addressing cognitive impair- ment in PD. Consent for publication Not applicable. Supplementary Information Competing interests The online version contains supplementary material available at https://​doi.​ The authors declare no conflict of interest. org/​10.​1186/​s12883-​021-​02485-1. Author details 1 Movement Disorders Unit, Neurology Department, Hospital de la Santa Additional file 1. Creu i Sant Pau, Mas Casanovas 90, 08041 Barcelona, Spain. 2 Biomedi‑ cal Research Institute Sant Pau (IIB-Sant Pau), Barcelona, Spain. 3 Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Acknowledgments Madrid, Spain. 4 CHUAC, Complejo Hospitalario Universitario de A Coruña, We would like to thank all patients and their caregivers who collaborated A Coruña, Spain. 5 Complejo Hospitalario Universitario de Ferrol (CHUF), in this study. We extend our grateful to “Fundación Española de Ayuda Ferrol, A Coruña, Spain. 6 Unidad de Trastornos del Movimiento, Servicio de a la Investigación en Parkinson y otras Enfermedades Neurodegenerati‑ Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, vas” (Curemos el Parkinson; www.​curem​oselp​arkin​son.​org), and to Alpha Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Sevilla, Bioresearch (www.​alpha​biore​search.​com). The complete list with all the Spain. 7 Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain. 8 researchers of the COPPADIS Study Group can be found in supplementary Hospital Clínic de Barcelona, Barcelona, Spain. 9 Hospital Quiron Palma‑ material. planas, Clínica Rotger y Centro Neurológico Oms 42, Palma de Mallorca, Spain. 10 Consorci Sanitari Integral, Hospital Moisés Broggi, Sant Joan Despí, Authors’ contributions Barcelona, Spain. 11 Hospital Universitario Son Espases, Palma de Mallorca, SMH: Conception; Design; Acquisition; Analysis; Interpretation; Draft. HBK: Spain. 12 Neurology Department and Neurodegenerative Diseases Research Acquisition; Interpretation; Draft. AHB: Acquisition; Interpretation; Draft. Group, Vall D’Hebron Universitari Campus, Barcelona, Spain. 13 Complejo BPS: Acquisition; Interpretation; Draft. DSG: Conception; Design; Acquisi‑ Hospitalario Universitario de Pontevedra (CHOP), Pontevedra, Spain. 14 tion; Analysis; Interpretation; Draft. TDF: Acquisition; Interpretation; Draft. Hospital La Princesa, Madrid, Spain. 15 Hospital Universitario Marqués de SJ: Acquisition; Interpretation; Draft. MA: Acquisition; Interpretation; Draft. Valdecilla, Santander, Spain. 16 Hospital Universitario Clínico San Carlos, LP: Acquisition; Interpretation; Draft. JGC: Acquisition; Interpretation; Draft. Madrid, Spain. 17 Hospital Da Costa de Burela, Lugo, Spain. 18 Hospital del Mar, NC: Acquisition; Interpretation; Draft. BVP: Acquisition; Interpretation; Draft. Barcelona, Spain. 19 Hospital Universitario Virgen Macarena, Sevilla, Spain. 20 JHV: Acquisition; Interpretation; Draft. ICL: Acquisition; Interpretation; Draft. Hospital Universitario Infanta Sofía, San Sebastián de los Reyes, Madrid, LLM: Acquisition; Interpretation; Draft. IGA: Acquisition; Interpretation; Draft. Spain. 21 Hospital Universitari Josep Trueta y Hospital Santa Caterina, Girona, AAR: Acquisition; Interpretation; Draft. MJC: Acquisition; Interpretation; Spain. 22 Hospital General Universitario de Elche, Alicante, Spain. 23 Fundación Draft. LLD: Acquisition; Interpretation; Draft. VP: Acquisition; Interpretation; Hospital de Alcorcón, Madrid, Spain. 24 Hospital de Tortosa Verge de la Cinta Draft. JGM: Acquisition; Interpretation; Draft. CB: Acquisition; Interpre‑ (HTVC), Tortosa, Tarragona, Spain. 25 Complejo Asistencial Universitario de tation; Draft. BSV: Acquisition; Interpretation; Draft. MAS: Acquisition; Burgos, Burgos, Spain. 26 Unidad de Trastornos del Movimiento, Servicio de Interpretation; Draft. LV: Acquisition; Interpretation; Draft. SE: Acquisition; Neurología y Neurofisiología Clínica. Hospital Universitario de Canarias, Ten‑ Interpretation; Draft. EC: Acquisition; Interpretation; Draft. FCP: Acquisition; erife, Spain. 27 Hospital Ramón y Cajal, Madrid, Spain. 28 Hospital Universitario Interpretation; Draft. JMC: Acquisition; Interpretation; Draft. PSA: Acquisi‑ Puerta de Hierro, Majadahonda, Madrid, Spain. 29 Hospital Álvaro Cunqueiro, tion; Interpretation; Draft. MAL: Acquisition; Interpretation; Draft. NLA: Complejo Hospitalario Universitario de Vigo (CHUVI), Vigo, Spain. 30 Servi‑ Acquisition; Interpretation; Draft. IG: Acquisition; Interpretation; Draft. MBE: cio de Neurología, Complejo Hospitalario Universitario de Toledo, Toledo, Acquisition; Interpretation; Draft. MS: Acquisition; Interpretation; Draft. JRM: Spain. 31 Complejo Hospitalario de Navarra, Pamplona, Spain. 32 Hospital Acquisition; Interpretation; Draft. CVM: Acquisition; Interpretation; Draft. Universitario Central de Asturias, Oviedo, Spain. 33 Hospital Universitario MK: Acquisition; Interpretation; Draft. OFB: Acquisition; Interpretation; Draft. Donostia, San Sebastián, Spain. 34 Servicio de Neurología, Hospital Arnau JGA: Acquisition; Interpretation; Draft. CPJ: Acquisition; Interpretation; Draft. de Vilanova, Valencia, Spain. 35 Hospital Ruber Internacional, Madrid, Spain. 36 PMM: Conception; Design; Acquisition; Analysis; Interpretation; Draft. PM: Hospital Lucus Augusti, Lugo, Spain. 37 Hospital Rey Juan Carlos, Madrid, Conception; Design; Acquisition; Analysis; Interpretation; Draft; JK: Concep‑ Spain. 38 Centro Nacional de Epidemiología y CIBERNED, Instituto de Salud tion; Design; Acquisition; Analysis; Interpretation; Draft. The authors read Carlos III, Madrid, Spain. 39 Departamento de Medicina, Facultad de Medicina, and approved the final manuscript. Universidad de Sevilla, Sevilla, Spain. Funding Received: 10 May 2021 Accepted: 8 November 2021 Fundación Curemos el Parkinson (https://​curem​oselp​arkin​son.​org/) covered the expenses derived from hiring a CRO and from carrying out complemen‑ tary tests. Availability of data and materials References The protocol and the statistical analysis plan are available on request from the 1. Aarsland D, Andersen K, Larsen JP, Lolk A, Nielsen H, Kragh-Sorensen P. corresponding author. De-identified participant data are not available for legal Risk of dementia in Parkinson’s disease: a community-based, prospective and ethical reasons. study. Neurology. 2001;56(6):730–6. Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 9 of 10 2. Hely MA, Reid WG, Adena MA, Halliday GM, Morris JG. The Sydney mul‑ 25. Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. ticenter study of Parkinson’s disease: the inevitability of dementia at 20 Neurology. 1967;17(5):427–42. years. Mov Disord. 2008;23(6):837–44. 26. Goetz CG, Fahn S, Martinez-Martin P, Poewe W, Sampaio C, Stebbins 3. Aarsland D, Andersen K, Larsen JP, Lolk A, Kragh-Sorensen P. Prevalence GT, et al. Movement Disorder Society-sponsored revision of the unified and characteristics of dementia in Parkinson disease: an 8-year prospec‑ Parkinson’s disease rating scale (MDS-UPDRS): process, format, and clini‑ tive study. Arch Neurol. 2003;60(3):387–92. metric testing plan. Mov Disord. 2007;22(1):41–7. 4. Aarsland D, Andersen K, Larsen JP, Perry R, Wentzel-Larsen T, Lolk A, 27. Cummings JL, Mega M, Gray K, Rosenberg-Thompson S, Carusi et al. The rate of cognitive decline in Parkinson disease. Arch Neurol. DA, Gornbein J. The neuropsychiatric inventory: comprehen‑ 2004;61(12):1906–11. sive assessment of psychopathology in dementia. Neurology. 5. Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, et al. 1994;44(12):2308–14. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 28. Fernandez de Bobadilla R, Pagonabarraga J, Martinez-Horta S, Pascual- 2015;30(12):1591–601. Sedano B, Campolongo A, Kulisevsky J. Parkinson’s disease-cognitive 6. Hoogland J, Boel JA, de Bie RMA, Geskus RB, Schmand BA, Dalrymple- rating scale: psychometrics for mild cognitive impairment. Mov Disord. Alford JC, et al. Mild cognitive impairment as a risk factor for Parkinson’s 2013;28(10):1376–83. disease dementia. Mov Disord. 2017;32(7):1056–65. 29. Aarsland D, Bronnick K, Williams-Gray C, Weintraub D, Marder K, Kulisevsky 7. Goldman JG, Litvan I. Mild cognitive impairment in Parkinson’s disease. J, et al. Mild cognitive impairment in Parkinson disease: a multicenter Minerva Med. 2011;102(6):441–59. pooled analysis. Neurology. 2010;75(12):1062–9. 8. Martinez-Horta S, Kulisevsky J. Mild cognitive impairment in Parkinson’s 30. Muslimovic D, Post B, Speelman JD, Schmand B. Cognitive profile disease. J Neural Transm (Vienna). 2019;126(7):897–904. of patients with newly diagnosed Parkinson disease. Neurology. 9. Aarsland D, Zaccai J, Brayne C. A systematic review of prevalence studies 2005;65(8):1239–45. of dementia in Parkinson’s disease. Mov Disord. 2005;20(10):1255–63. 31. Yarnall AJ, Breen DP, Duncan GW, Khoo TK, Coleman SY, Firbank MJ, et al. 10. Obeso JA, Stamelou M, Goetz CG, Poewe W, Lang AE, Weintraub D, et al. Characterizing mild cognitive impairment in incident Parkinson disease: Past, present, and future of Parkinson’s disease: a special essay on the the ICICLE-PD study. Neurology. 2014;82(4):308–16. 200th anniversary of the shaking palsy. Mov Disord. 2017;32(9):1264–310. 32. Domellof ME, Ekman U, Forsgren L, Elgh E. Cognitive function in the early 11. Aarsland D, Creese B, Politis M, Chaudhuri KR, Ffytche DH, Wein‑ phase of Parkinson’s disease, a five-year follow-up. Acta Neurol Scand. traub D, et al. Cognitive decline in Parkinson disease. Nat Rev Neurol. 2015;132(2):79–88. 2017;13(4):217–31. 33. Pedersen KF, Larsen JP, Tysnes OB, Alves G. Natural course of mild cogni‑ 12. Seto-Salvia N, Clarimon J, Pagonabarraga J, Pascual-Sedano B, Campo‑ tive impairment in Parkinson disease: a 5-year population-based study. longo A, Combarros O, et al. Dementia risk in Parkinson disease: disentan‑ Neurology. 2017;88(8):767–74. gling the role of MAPT haplotypes. Arch Neurol. 2011;68(3):359–64. 34. Munhoz RP, Teive HA, Eleftherohorinou H, Coin LJ, Lees AJ, Silveira-Moriy‑ 13. Williams-Gray CH, Evans JR, Goris A, Foltynie T, Ban M, Robbins TW, et al. ama L. Demographic and motor features associated with the occurrence The distinct cognitive syndromes of Parkinson’s disease: 5 year follow-up of neuropsychiatric and sleep complications of Parkinson’s disease. J of the CamPaIGN cohort. Brain. 2009;132(Pt 11):2958–69. Neurol Neurosurg Psychiatry. 2013;84(8):883–7. 14. Sampedro F, Marin-Lahoz J, Martinez-Horta S, Pagonabarraga J, Kulisevsky 35. David FJ, Robichaud JA, Leurgans SE, Poon C, Kohrt WM, Goldman JG, J. Early Gray matter volume loss in MAPT H1H1 de novo PD patients: a et al. Exercise improves cognition in Parkinson’s disease: the PRET-PD possible association with cognitive decline. Front Neurol. 2018;9:394. randomized, clinical trial. Mov Disord. 2015;30(12):1657–63. 15. Sampedro F, Marin-Lahoz J, Martinez-Horta S, Perez-Gonzalez R, Pagona‑ 36. Leung IH, Walton CC, Hallock H, Lewis SJ, Valenzuela M, Lampit A. Cogni‑ barraga J, Kulisevsky J. CLU rs11136000 promotes early cognitive decline tive training in Parkinson disease: a systematic review and meta-analysis. in Parkinson’s disease. Mov Disord. 2020;35(3):508–13. Neurology. 2015;85(21):1843–51. 16. Emre M, Aarsland D, Brown R, Burn DJ, Duyckaerts C, Mizuno Y, et al. Clini‑ 37. Kampling H, Brendel LK, Mittag O. (Neuro) psychological interven‑ cal diagnostic criteria for dementia associated with Parkinson’s disease. tions for non-motor symptoms in the treatment of patients with Mov Disord. 2007;22(12):1689–707 quiz 837. Parkinson’s disease: a systematic umbrella review. Neuropsychol Rev. 17. Litvan I, Aarsland D, Adler CH, Goldman JG, Kulisevsky J, Mollenhauer B, 2019;29(2):166–80. et al. MDS task force on mild cognitive impairment in Parkinson’s disease: 38. Orgeta V, McDonald KR, Poliakoff E, Hindle JV, Clare L, Leroi I. Cognitive critical review of PD-MCI. Mov Disord. 2011;26(10):1814–24. training interventions for dementia and mild cognitive impairment in 18. Halliday GM, Leverenz JB, Schneider JS, Adler CH. The neurobiologi‑ Parkinson’s disease. Cochrane Database Syst Rev. 2020;2:CD011961. cal basis of cognitive impairment in Parkinson’s disease. Mov Disord. 39. Seshadri S. Elevated plasma homocysteine levels: risk factor or risk marker 2014;29(5):634–50. for the development of dementia and Alzheimer’s disease? J Alzheimers 19. Hepp DH, Vergoossen DL, Huisman E, Lemstra AW, Netherlands Brain B, Dis. 2006;9(4):393–8. Berendse HW, et al. Distribution and load of amyloid-beta pathology in 40. White AR, Huang X, Jobling MF, Barrow CJ, Beyreuther K, Masters CL, Parkinson disease and dementia with Lewy bodies. J Neuropathol Exp et al. Homocysteine potentiates copper- and amyloid beta peptide- Neurol. 2016;75(10):936–45. mediated toxicity in primary neuronal cultures: possible risk factors 20. Johar I, Mollenhauer B, Aarsland D. Cerebrospinal fluid biomarkers of cog‑ in the Alzheimer’s-type neurodegenerative pathways. J Neurochem. nitive decline in Parkinson’s disease. Int Rev Neurobiol. 2017;132:275–94. 2001;76(5):1509–20. 21. Skorvanek M, Goldman JG, Jahanshahi M, Marras C, Rektorova I, Schmand 41. Jacobsen DW. Homocysteine and vitamins in cardiovascular disease. Clin B, et al. Global scales for cognitive screening in Parkinson’s disease: Chem. 1998;44(8 Pt 2):1833–43. critique and recommendations. Mov Disord. 2018;33(2):208–18. 42. Xie Y, Feng H, Peng S, Xiao J, Zhang J. Association of plasma homocyst‑ 22. Santos Garcia D, Jesus S, Aguilar M, Planellas LL, Garcia Caldentey J, eine, vitamin B12 and folate levels with cognitive function in Parkinson’s Caballol N, et al. COPPADIS-2015 (COhort of patients with PArkinson’s DIs‑ disease: a meta-analysis. Neurosci Lett. 2017;636:190–5. ease in Spain, 2015): an ongoing global Parkinson’s disease project about 43. Rogers JD, Sanchez-Saffon A, Frol AB, Diaz-Arrastia R. Elevated plasma disease progression with more than 1000 subjects included. Results from homocysteine levels in patients treated with levodopa: association with the baseline evaluation. Eur J Neurol. 2019;26(11):1399–407. vascular disease. Arch Neurol. 2003;60(1):59–64. 23. Santos-Garcia D, Mir P, Cubo E, Vela L, Rodriguez-Oroz MC, Marti MJ, et al. 44. Wood H. Brain iron correlates with cognitive change in Parkinson disease. COPPADIS-2015 (COhort of Patients with PArkinson’s DIsease in Spain, Nat Rev Neurol. 2020;16(4):184. 2015), a global--clinical evaluations, serum biomarkers, genetic studies 45. Thomas GEC, Leyland LA, Schrag AE, Lees AJ, Acosta-Cabronero J, Weil and neuroimaging--prospective, multicenter, non-interventional, long- RS. Brain iron deposition is linked with cognitive severity in Parkinson’s term study on Parkinson’s disease progression. BMC Neurol. 2016;16:26. disease. J Neurol Neurosurg Psychiatry. 2020;91(4):418–25. 24. Pagonabarraga J, Kulisevsky J, Llebaria G, Garcia-Sanchez C, Pascual-Sedano 46. Ward RJ, Zucca FA, Duyn JH, Crichton RR, Zecca L. The role of iron B, Gironell A. Parkinson’s disease-cognitive rating scale: a new cognitive in brain ageing and neurodegenerative disorders. Lancet Neurol. scale specific for Parkinson’s disease. Mov Disord. 2008;23(7):998–1005. 2014;13(10):1045–60. Martínez‑Horta et al. BMC Neurology (2021) 21:477 Page 10 of 10 47. Kong BS, Kim Y, Kim GY, Hyun JW, Kim SH, Jeong A, et al. Increased frequency of IL-6-producing non-classical monocytes in neuromyelitis optica spectrum disorder. J Neuroinflammation. 2017;14(1):191. 48. Swardfager W, Lanctot K, Rothenburg L, Wong A, Cappell J, Herrmann N. A meta-analysis of cytokines in Alzheimer’s disease. Biol Psychiatry. 2010;68(10):930–41. 49. Reale M, Iarlori C, Thomas A, Gambi D, Perfetti B, Di Nicola M, et al. Peripheral cytokines profile in Parkinson’s disease. Brain Behav Immun. 2009;23(1):55–63. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub‑ lished maps and institutional affiliations. Ready to submit your research ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations • maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions