Skip to content
2000
image of Peripheral Inflammation Profile of Cerebellar Ataxia

Abstract

Objectives

The objective of this study is to determine the characteristics of peripheral inflammatory profiles and their correlations with the clinical features in patients with cerebellar ataxia.

Methods

We conducted a cross-sectional study on a cohort of 140 cerebellar ataxia patients, including 74 patients with spinocerebellar ataxia (SCA), 66 patients with multiple system atrophy with predominant cerebellar ataxia (MSA-C), and 145 healthy controls (HCs). Inflammatory profiles (PLT, MPV, NLR, PLR, MLR, SII, AISI and ESR) were measured in peripheral blood, and were compared by ANOVA and Kruskal-Wallis test. The receiver operating characteristic (ROC) curve and the area under curve (AUC) were performed to determine the sensitivity and specificity of the inflammatory markers. Spearman correlation and partial correlation analysis were performed to detect the association between inflammatory profiles and clinical scales in cerebellar ataxia.

Results

Inflammatory profiles from peripheral blood showed significant difference between different groups. Significant variations were observed in MPV, NLR, MLR, SII, AISI and ESR between cerebellar ataxia and HCs groups (<0.05). NLR and ESR in both SCA and MSA-C groups were increased compared with HCs (<0.05). The difference of MHR between SCA and MSA-C groups was observed based on HDL variation (<0.05). The combination of ESR and PLT distinguished SCA from MSA-C (AUC=0.800). In addition, MLR was significantly corelated with clinical scales, including SARA and ICARS in SCA group as well as UMSARS and FAB in MSA-C group (r>0.3/r<-0.3).

Conclusion

Significant variation in peripheral inflammatory profiles was firstly identified in Chinese genetic ataxias and non-genetic cerebellar ataxia cohort, which showed the potential clinical correlations between peripheral inflammatory phenotype and severity of ataxia.

Loading

Article metrics loading...

/content/journals/cn/10.2174/011570159X379620250225075810
2025-02-28
2025-03-27
Loading full text...

Full text loading...

References

  1. Ramirez-Zamora A. Zeigler W. Desai N. Biller J. Treatable causes of cerebellar ataxia. Mov. Disord. 2015 30 5 614 623 10.1002/mds.26158 25757427
    [Google Scholar]
  2. Pavone P. Praticò A.D. Pavone V. Lubrano R. Falsaperla R. Rizzo R. Ruggieri M. Ataxia in children: Early recognition and clinical evaluation. Ital. J. Pediatr. 2017 43 1 6 10.1186/s13052‑016‑0325‑9 28257643
    [Google Scholar]
  3. Klockgether T. Mariotti C. Paulson H.L. Spinocerebellar ataxia. Nat. Rev. Dis. Primers 2019 5 1 24 10.1038/s41572‑019‑0074‑3 30975995
    [Google Scholar]
  4. Poewe W. Stankovic I. Halliday G. Meissner W.G. Wenning G.K. Pellecchia M.T. Seppi K. Palma J.A. Kaufmann H. Multiple system atrophy. Nat. Rev. Dis. Primers 2022 8 1 56 10.1038/s41572‑022‑00382‑6 36008429
    [Google Scholar]
  5. Diener H.C. Dichgans J. Pathophysiology of cerebellar ataxia. Mov. Disord. 1992 7 2 95 109 10.1002/mds.870070202 1584245
    [Google Scholar]
  6. Coarelli G. Wirth T. Tranchant C. Koenig M. Durr A. Anheim M. The inherited cerebellar ataxias: An update. J. Neurol. 2023 270 1 208 222 10.1007/s00415‑022‑11383‑6 36152050
    [Google Scholar]
  7. Raposo M. Hübener-Schmid J. Ferreira A.F. Vieira Melo A.R. Vasconcelos J. Pires P. Kay T. Garcia-Moreno H. Giunti P. Santana M.M. Pereira de Almeida L. Infante J. van de Warrenburg B.P. de Vries J.J. Faber J. Klockgether T. Casadei N. Admard J. Schöls L. Krahe J. Reetz K. González J. Gonzalez C. Baptista C. Lemos J. Giordano I. Grobe-Einsler M. Önder D. Silva P. Januário C. Ribeiro J. Cunha I. Lemos J. Pinto M.M. Timmann D. Steiner K.M. Thieme A. Ernst T.M. Jacobi H. Solanky N. Gonzalez-Robles C. Van Gaalen J. Pelayo-Negro A.L. Manrique L. Hengel H. Synofzik M. Ilg W. Riess O. Lima M. Blood transcriptome sequencing identifies biomarkers able to track disease stages in spinocerebellar ataxia type 3. Brain 2023 146 10 4132 4143 10.1093/brain/awad128 37071051
    [Google Scholar]
  8. Chen Z. Liao G. Wan N. He Z. Chen D. Tang Z. Long Z. Zou G. Peng L. Wan L. Wang C. Peng H. Shi Y. Tang Y. Li J. Li Y. Long T. Hou X. He L. Qiu R. Chen D. Wang J. Guo J. Shen L. Huang Y. Ashizawa T. Klockgether T. Tang B. Zhou M. Hu S. Jiang H. Synaptic loss in spinocerebellar ataxia type 3 revealed by SV2A positron emission tomography. Mov. Disord. 2023 38 6 978 989 10.1002/mds.29395 37023261
    [Google Scholar]
  9. O’Hearn E. Holmes S.E. Calvert P.C. Ross C.A. Margolis R.L. SCA-12: Tremor with cerebellar and cortical atrophy is associated with a CAG repeat expansion. Neurology 2001 56 3 299 303 10.1212/WNL.56.3.299 11171892
    [Google Scholar]
  10. Karamazovova S. Matuskova V. Ismail Z. Vyhnalek M. Neuropsychiatric symptoms in spinocerebellar ataxias and Friedreich ataxia. Neurosci. Biobehav. Rev. 2023 150 105205 10.1016/j.neubiorev.2023.105205 37137435
    [Google Scholar]
  11. Faber J. Berger M. Wilke C. Hubener-Schmid J. Schaprian T. Santana M.M. Grobe-Einsler M. Onder D. Koyak B. Giunti P. Garcia-Moreno H. Gonzalez-Robles C. Lima M. Raposo M. Melo A.R.V. de Almeida L.P. Silva P. Pinto M.M. van de Warrenburg B.P. van Gaalen J. de Vries J. Oz G. Joers J.M. Synofzik M. Schols L. Riess O. Infante J. Manrique L. Timmann D. Thieme A. Jacobi H. Reetz K. Dogan I. Onyike C. Povazan M. Schmahmann J. Ratai E.M. Schmid M. Klockgether T. Stage‐dependent biomarker changes in spinocerebellar ataxia Type 3. Ann. Neurol. 2024 95 2 400 406 10.1002/ana.26824 37962377
    [Google Scholar]
  12. Brooker S.M. Edamakanti C.R. Akasha S.M. Kuo S.H. Opal P. Spinocerebellar ataxia clinical trials: Opportunities and challenges. Ann. Clin. Transl. Neurol. 2021 8 7 1543 1556 10.1002/acn3.51370 34019331
    [Google Scholar]
  13. Paulson H.L. Shakkottai V.G. Clark H.B. Orr H.T. Polyglutamine spinocerebellar ataxias — From genes to potential treatments. Nat. Rev. Neurosci. 2017 18 10 613 626 10.1038/nrn.2017.92 28855740
    [Google Scholar]
  14. Swinnen B. Robberecht W. Van Den Bosch L. RNA toxicity in non‐coding repeat expansion disorders. EMBO J. 2020 39 1 e101112 10.15252/embj.2018101112 31721251
    [Google Scholar]
  15. Nikonishyna Y.V. Ortner N.J. Kaserer T. Hoffmann J. Biskup S. Dafotakis M. Reetz K. Schulz J.B. Striessnig J. Dohrn M.F. Novel CACNA1A variant p.Cys256Phe disrupts disulfide bonds and causes spinocerebellar ataxia. Mov. Disord. 2022 37 2 401 404 10.1002/mds.28835 34647648
    [Google Scholar]
  16. Coarelli G. Coutelier M. Durr A. Autosomal dominant cerebellar ataxias: New genes and progress towards treatments. Lancet Neurol. 2023 22 8 735 749 10.1016/S1474‑4422(23)00068‑6 37479376
    [Google Scholar]
  17. Pellerin D. Danzi M.C. Renaud M. Houlden H. Synofzik M. Zuchner S. Brais B. Spinocerebellar ataxia 27B: A novel, frequent and potentially treatable ataxia. Clin. Transl. Med. 2024 14 1 e1504 10.1002/ctm2.1504 38279833
    [Google Scholar]
  18. Beaudin M. Manto M. Schmahmann J.D. Pandolfo M. Dupre N. Recessive cerebellar and afferent ataxias — Clinical challenges and future directions. Nat. Rev. Neurol. 2022 18 5 257 272 10.1038/s41582‑022‑00634‑9 35332317
    [Google Scholar]
  19. Gellersen H.M. Guo C.C. O’Callaghan C. Tan R.H. Sami S. Hornberger M. Cerebellar atrophy in neurodegeneration—A meta-analysis. J. Neurol. Neurosurg. Psychiatry 2017 88 9 780 788 10.1136/jnnp‑2017‑315607 28501823
    [Google Scholar]
  20. Pasquini J. Firbank M.J. Ceravolo R. Silani V. Pavese N. Diffusion magnetic resonance imaging microstructural abnormalities in multiple system atrophy: A comprehensive review. Mov. Disord. 2022 37 10 1963 1984 10.1002/mds.29195 36036378
    [Google Scholar]
  21. Wong Y.C. Krainc D. α-synuclein toxicity in neurodegeneration: Mechanism and therapeutic strategies. Nat. Med. 2017 23 2 1 13 10.1038/nm.4269 28170377
    [Google Scholar]
  22. Stefanova N. Wenning G.K. Multiple system atrophy: At the crossroads of cellular, molecular and genetic mechanisms. Nat. Rev. Neurosci. 2023 24 6 334 346 10.1038/s41583‑023‑00697‑7 37085728
    [Google Scholar]
  23. Koga S. Sekiya H. Kondru N. Ross O.A. Dickson D.W. Neuropathology and molecular diagnosis of Synucleinopathies. Mol. Neurodegener. 2021 16 1 83 10.1186/s13024‑021‑00501‑z 34922583
    [Google Scholar]
  24. Koga S. Dickson D.W. Recent advances in neuropathology, biomarkers and therapeutic approach of multiple system atrophy. J. Neurol. Neurosurg. Psychiatry 2018 89 2 175 184 10.1136/jnnp‑2017‑315813 28860330
    [Google Scholar]
  25. Ravichandran K.A. Heneka M.T. Inflammasome activation in neurodegenerative diseases. Essays Biochem. 2021 65 7 885 904 10.1042/EBC20210021 34846519
    [Google Scholar]
  26. Gao C. Jiang J. Tan Y. Chen S. Microglia in neurodegenerative diseases: Mechanism and potential therapeutic targets. Signal Transduct. Target. Ther. 2023 8 1 359 10.1038/s41392‑023‑01588‑0 37735487
    [Google Scholar]
  27. Zhang L. Hu K. Shao T. Hou L. Zhang S. Ye W. Josephson L. Meyer J.H. Zhang M.R. Vasdev N. Wang J. Xu H. Wang L. Liang S.H. Recent developments on PET radiotracers for TSPO and their applications in neuroimaging. Acta Pharm. Sin. B 2021 11 2 373 393 10.1016/j.apsb.2020.08.006 33643818
    [Google Scholar]
  28. Turchi R. Sciarretta F. Ceci V. Tiberi M. Audano M. Pedretti S. Panebianco C. Nesci V. Pazienza V. Ferri A. Carotti S. Chiurchiù V. Mitro N. Lettieri-Barbato D. Aquilano K. Butyrate prevents visceral adipose tissue inflammation and metabolic alterations in a Friedreich’s ataxia mouse model. iScience 2023 26 10 107713 10.1016/j.isci.2023.107713 37701569
    [Google Scholar]
  29. Khan W. Corben L.A. Bilal H. Vivash L. Delatycki M.B. Egan G.F. Harding I.H. Neuroinflammation in the cerebellum and brainstem in friedreich ataxia: An [18 F ]‐ FEMPA PET study. Mov. Disord. 2022 37 1 218 224 10.1002/mds.28825 34643298
    [Google Scholar]
  30. Leng F. Edison P. Neuroinflammation and microglial activation in Alzheimer disease: Where do we go from here? Nat. Rev. Neurol. 2021 17 3 157 172 10.1038/s41582‑020‑00435‑y 33318676
    [Google Scholar]
  31. Pelkmans W. Shekari M. Brugulat-Serrat A. Sánchez-Benavides G. Minguillón C. Fauria K. Molinuevo J.L. Grau-Rivera O. González Escalante A. Kollmorgen G. Carboni M. Ashton N.J. Zetterberg H. Blennow K. Suarez-Calvet M. Gispert J.D. ALFA study Astrocyte biomarkers GFAP and YKL‐40 mediate early Alzheimer’s disease progression. Alzheimers Dement. 2024 20 1 483 493 10.1002/alz.13450 37690071
    [Google Scholar]
  32. Bairamian D. Sha S. Rolhion N. Sokol H. Dorothée G. Lemere C.A. Krantic S. Microbiota in neuroinflammation and synaptic dysfunction: A focus on Alzheimer’s disease. Mol. Neurodegener. 2022 17 1 19 10.1186/s13024‑022‑00522‑2 35248147
    [Google Scholar]
  33. Hinkle J.T. Patel J. Panicker N. Karuppagounder S.S. Biswas D. Belingon B. Chen R. Brahmachari S. Pletnikova O. Troncoso J.C. Dawson V.L. Dawson T.M. STING mediates neurodegeneration and neuroinflammation in nigrostriatal α-synucleinopathy. Proc. Natl. Acad. Sci. USA 2022 119 15 e2118819119 10.1073/pnas.2118819119 35394877
    [Google Scholar]
  34. Li Z. Du X. Yang Y. Zhang L. Chen P. Kan Y. Pan J. Lin L. Liu D. Jiang X. Zhang C.Y. Pei Z. Chen X. Treatment of neurological pathology and inflammation in Machado–Joseph disease through in vivo self-assembled siRNA. Brain 2024 awae304 10.1093/brain/awae304 39315766
    [Google Scholar]
  35. Ndayisaba A. Halliday G.M. Khurana V. Multiple system atrophy: Pathology, pathogenesis, and path forward. Annu. Rev. Pathol. 2025 20 1 245 273 10.1146/annurev‑pathmechdis‑051122‑104528 39405585
    [Google Scholar]
  36. Dutta D. Jana M. Majumder M. Mondal S. Roy A. Pahan K. Selective targeting of the TLR2/MyD88/NF-κB pathway reduces α-synuclein spreading in vitro and in vivo. Nat. Commun. 2021 12 1 5382 10.1038/s41467‑021‑25767‑1 34508096
    [Google Scholar]
  37. Dick F. Johanson G.A.S. Tysnes O.B. Alves G. Dölle C. Tzoulis C. Brain proteome profiling reveals common and divergent signatures in Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy. Mol. Neurobiol. 2024 10.1007/s12035‑024‑04422‑y 39164482
    [Google Scholar]
  38. Sowa A.S. Haas E. Hübener-Schmid J. Lorentz A. Ataxin-3, the spinocerebellar ataxia type 3 neurodegenerative disorder protein, affects mast cell functions. Front. Immunol. 2022 13 870966 10.3389/fimmu.2022.870966 35558088
    [Google Scholar]
  39. Bettcher B.M. Tansey M.G. Dorothée G. Heneka M.T. Peripheral and central immune system crosstalk in Alzheimer disease — A research prospectus. Nat. Rev. Neurol. 2021 17 11 689 701 10.1038/s41582‑021‑00549‑x 34522039
    [Google Scholar]
  40. Sanmarco L.M. Polonio C.M. Wheeler M.A. Quintana F.J. Functional immune cell–astrocyte interactions. J. Exp. Med. 2021 218 9 e20202715 10.1084/jem.20202715 34292315
    [Google Scholar]
  41. Vázquez-Mojena Y. Rodríguez-Córdova Y. Dominguez-Barrios Y. León-Arcia K. Miranda-Becerra D. Gonzalez-Zaldivar Y. Guerra-Bustillos G. Ziemann U. Auburger G. Rodríguez-Labrada R. Robinson-Agramonte M.Á. Velázquez-Pérez L. Peripheral inflammation links with the severity of clinical phenotype in spinocerebellar ataxia 2. Mov. Disord. 2023 38 5 880 885 10.1002/mds.29359 36811296
    [Google Scholar]
  42. Williams G.P. Schonhoff A.M. Sette A. Lindestam Arlehamn C.S. Central and peripheral inflammation: Connecting the immune responses of Parkinson’s disease. J. Parkinsons Dis. 2022 12 s1 S129 S136 10.3233/JPD‑223241 35754290
    [Google Scholar]
  43. Yuan X. Wan L. Chen Z. Long Z. Chen D. Liu P. Fu Y. Zhu S. Peng L. Qiu R. Tang B. Jiang H. Peripheral inflammatory and immune landscape in multiple system atrophy: A cross‐sectional study. Mov. Disord. 2024 39 2 391 399 10.1002/mds.29674 38155513
    [Google Scholar]
  44. Zhang X. Wei R. Wang X. Zhang W. Li M. Ni T. Weng W. Li Q. The neutrophil-to-lymphocyte ratio is associated with all-cause and cardiovascular mortality among individuals with hypertension. Cardiovasc. Diabetol. 2024 23 1 117 10.1186/s12933‑024‑02191‑5 38566082
    [Google Scholar]
  45. Capone M. Giannarelli D. Mallardo D. Madonna G. Festino L. Grimaldi A.M. Vanella V. Simeone E. Paone M. Palmieri G. Cavalcanti E. Caracò C. Ascierto P.A. Baseline neutrophil-to-lymphocyte ratio (NLR) and derived NLR could predict overall survival in patients with advanced melanoma treated with nivolumab. J. Immunother. Cancer 2018 6 1 74 10.1186/s40425‑018‑0383‑1 30012216
    [Google Scholar]
  46. Cheng X. Wei Y. Wang R. Jia C. Zhang Z. An J. Li W. Zhang J. He M. Associations of essential trace elements with epigenetic aging indicators and the potential mediating role of inflammation. Redox Biol. 2023 67 102910 10.1016/j.redox.2023.102910 37793240
    [Google Scholar]
  47. Russell C.D. Parajuli A. Gale H.J. Bulteel N.S. Schuetz P. de Jager C.P.C. Loonen A.J.M. Merekoulias G.I. Baillie J.K. The utility of peripheral blood leucocyte ratios as biomarkers in infectious diseases: A systematic review and meta-analysis. J. Infect. 2019 78 5 339 348 10.1016/j.jinf.2019.02.006 30802469
    [Google Scholar]
  48. Velasco A. Lengvenyte A. Rodriguez-Revuelta J. Jimenez-Treviño L. Courtet P. Garcia-Portilla M.P. Bobes J. Sáiz P.A. Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio in depressed patients with suicidal behavior: A systematic review. Eur. Psychiatry 2023 67 1 1 25 37062531
    [Google Scholar]
  49. Clausen M. Christensen R.H.B. da Re M. Benros M.E. Immune cell alterations in psychotic disorders: A comprehensive systematic review and meta-analysis. Biol. Psychiatry 2024 96 5 331 341 10.1016/j.biopsych.2023.11.029 38185237
    [Google Scholar]
  50. Wang L. Li X. Liu M. Zhou H. Shao J. Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: A population-based study. Front. Cell Dev. Biol. 2024 12 1372731 10.3389/fcell.2024.1372731 38645410
    [Google Scholar]
  51. Hu B. Yang X.R. Xu Y. Sun Y.F. Sun C. Guo W. Zhang X. Wang W.M. Qiu S.J. Zhou J. Fan J. Systemic immune-inflammation index predicts prognosis of patients after curative resection for hepatocellular carcinoma. Clin. Cancer Res. 2014 20 23 6212 6222 10.1158/1078‑0432.CCR‑14‑0442 25271081
    [Google Scholar]
  52. Cao Y. Li P. Zhang Y. Qiu M. Li J. Ma S. Yan Y. Li Y. Han Y. Association of systemic immune inflammatory index with all-cause and cause-specific mortality in hypertensive individuals: Results from NHANES. Front. Immunol. 2023 14 1087345 10.3389/fimmu.2023.1087345 36817427
    [Google Scholar]
  53. Tuzimek A. Dziedzic E. Beck J. Kochman W. Correlations between acute coronary syndrome and novel inflammatory markers (systemic immune-inflammation index, systemic inflammation response index, and aggregate index of systemic inflammation) in patients with and without diabetes or prediabetes. J. Inflamm. Res. 2024 17 2623 2632 10.2147/JIR.S454117 38707954
    [Google Scholar]
  54. Xu Q. Wu Q. Chen L. Li H. Tian X. Xia X. Zhang Y. Zhang X. Lin Y. Wu Y. Wang Y. Meng X. Wang A. Monocyte to high‐density lipoprotein ratio predicts clinical outcomes after acute ischemic stroke or transient ischemic attack. CNS Neurosci. Ther. 2023 29 7 1953 1964 10.1111/cns.14152 36914580
    [Google Scholar]
  55. De Matteis C. Crudele L. Cariello M. Battaglia S. Piazzolla G. Suppressa P. Sabbà C. Piccinin E. Moschetta A. Monocyte-to-HDL ratio (MHR) predicts vitamin D deficiency in healthy and metabolic women: A cross-sectional study in 1048 subjects. Nutrients 2022 14 2 347 10.3390/nu14020347 35057532
    [Google Scholar]
  56. Liu Z. Fan Q. Wu S. Wan Y. Lei Y. Compared with the monocyte to high-density lipoprotein ratio (MHR) and the neutrophil to lymphocyte ratio (NLR), the neutrophil to high-density lipoprotein ratio (NHR) is more valuable for assessing the inflammatory process in Parkinson’s disease. Lipids Health Dis. 2021 20 1 35 10.1186/s12944‑021‑01462‑4 33874966
    [Google Scholar]
  57. Yang L. He C. Wang W. Association between neutrophil to high-density lipoprotein cholesterol ratio and disease severity in patients with acute biliary pancreatitis. Ann. Med. 2024 56 1 2315225 10.1080/07853890.2024.2315225 38335727
    [Google Scholar]
  58. Kang H. Sample size determination and power analysis using the G*Power software. J. Educ. Eval. Health Prof. 2021 18 17 10.3352/jeehp.2021.18.17 34325496
    [Google Scholar]
  59. Murayama K. Usami S. Sakaki M. Summary-statistics-based power analysis: A new and practical method to determine sample size for mixed-effects modeling. Psychol. Methods 2022 27 6 1014 1038 10.1037/met0000330 35099237
    [Google Scholar]
  60. Cáceres-Matos R. Gil-García E. Vázquez-Santiago S. Cabrera-León A. Factors that influence the impact of Chronic Non-Cancer Pain on daily life: A partial least squares modelling approach. Int. J. Nurs. Stud. 2023 138 104383 10.1016/j.ijnurstu.2022.104383 36481597
    [Google Scholar]
  61. Wenning G.K. Stankovic I. Vignatelli L. Fanciulli A. Calandra-Buonaura G. Seppi K. Palma J.A. Meissner W.G. Krismer F. Berg D. Cortelli P. Freeman R. Halliday G. Höglinger G. Lang A. Ling H. Litvan I. Low P. Miki Y. Panicker J. Pellecchia M.T. Quinn N. Sakakibara R. Stamelou M. Tolosa E. Tsuji S. Warner T. Poewe W. Kaufmann H. The movement disorder society criteria for the diagnosis of multiple system atrophy. Mov. Disord. 2022 37 6 1131 1148 10.1002/mds.29005 35445419
    [Google Scholar]
  62. Schmitz-Hübsch T. du Montcel S.T. Baliko L. Berciano J. Boesch S. Depondt C. Giunti P. Globas C. Infante J. Kang J.S. Kremer B. Mariotti C. Melegh B. Pandolfo M. Rakowicz M. Ribai P. Rola R. Schöls L. Szymanski S. van de Warrenburg B.P. Dürr A. Klockgether T. Fancellu R. Scale for the assessment and rating of ataxia. Neurology 2006 66 11 1717 1720 10.1212/01.wnl.0000219042.60538.92 16769946
    [Google Scholar]
  63. Traschütz A. Adarmes-Gómez A.D. Anheim M. Baets J. Brais B. Gagnon C. Gburek-Augustat J. Doss S. Hanağası H.A. Kamm C. Klivenyi P. Klockgether T. Klopstock T. Minnerop M. Münchau A. Renaud M. Santorelli F.M. Schöls L. Thieme A. Vielhaber S. van de Warrenburg B.P. Zanni G. Hilgers R.D. Synofzik M. PREPARE Consortium Responsiveness of the scale for the assessment and rating of ataxia and natural history in 884 recessive and early onset ataxia patients. Ann. Neurol. 2023 94 3 470 485 10.1002/ana.26712 37243847
    [Google Scholar]
  64. Metz G. Coppard N. Cooper J.M. Delatycki M.B. Dürr A. Di Prospero N.A. Giunti P. Lynch D.R. Schulz J.B. Rummey C. Meier T. Rating disease progression of Friedreich’s ataxia by the International Cooperative Ataxia Rating Scale: Analysis of a 603-patient database. Brain 2013 136 1 259 268 10.1093/brain/aws309 23365101
    [Google Scholar]
  65. Della Pietra G.L. Savio K. Oddone E. Reggiani M. Monaco F. Leone M.A. Validity and reliability of the Barthel index administered by telephone. Stroke 2011 42 7 2077 2079 10.1161/STROKEAHA.111.613521 21527755
    [Google Scholar]
  66. Jannati A. Toro-Serey C. Gomes-Osman J. Banks R. Ciesla M. Showalter J. Bates D. Tobyne S. Pascual-Leone A. Digital clock and recall is superior to the mini-mental state examination for the detection of mild cognitive impairment and mild dementia. Alzheimers Res. Ther. 2024 16 1 2 10.1186/s13195‑023‑01367‑7 38167251
    [Google Scholar]
  67. Krismer F. Palma J.A. Calandra-Buonaura G. Stankovic I. Vignatelli L. Berger A.K. Falup-Pecurariu C. Foubert-Samier A. Höglinger G. Kaufmann H. Kellerman L. Kim H.J. Klockgether T. Levin J. Martinez-Martin P. Mestre T.A. Pellecchia M.T. Perlman S. Qureshi I. Rascol O. Schrag A. Seppi K. Shang H. Stebbins G.T. Wenning G.K. Singer W. Meissner W.G. The unified multiple system atrophy rating scale: Status, critique, and recommendations. Mov. Disord. 2022 37 12 2336 2341 10.1002/mds.29215 36074648
    [Google Scholar]
  68. Elliott J.E. Bryant-Ekstrand M.D. Keil A.T. Ligman B.R. Lim M.M. Zitser J. During E.H. Gagnon J.F. St Louis E.K. Fields J.A. Huddleston D.E. Bliwise D.L. Avidan A.Y. Schenck C.H. McLeland J. Criswell S.R. Davis A.A. Videnovic A. Lee-Iannotti J.K. Postuma R. Boeve B.F. Ju Y.E.S. Miglis M.G. Choudhury P. Forsberg L.K. Howell M.J. Shprecher D.R. Amudson-Huffmaster S. Arik A. Brushaber N. Chung J.W. De Kam J. Ekelmans A. Fischbach E. Keane M. Kraft R. MacKinnon C. Miner-Rose D. Murphy S. Olivo C. Pelletier A. Powers K.L.M. Rivera A.M. Sanchez S. Stauder M. Summers R. Taylor L. Tiegan L. Timm P. Tucker K.A. Tran P. Galasko D. Mignot E. Frequency of orthostatic hypotension in isolated REM sleep behavior disorder. Neurology 2023 101 24 e2545 e2559 10.1212/WNL.0000000000207883 37857496
    [Google Scholar]
  69. Carod-Artal F.J. da Silveira Ribeiro L. Kummer W. Martinez-Martin P. Psychometric properties of the SCOPA‐AUT Brazilian Portuguese version. Mov. Disord. 2010 25 2 205 212 10.1002/mds.22882 19938162
    [Google Scholar]
  70. Essangri H. Majbar M.A. Benkabbou A. Amrani L. Mohsine R. Souadka A. Transcultural adaptation and validation of the Moroccan Arabic dialect version of the Wexner incontinence score in patients with low anterior resection syndrome after rectal surgery. Surgery 2021 170 1 47 52 10.1016/j.surg.2021.01.029 33674127
    [Google Scholar]
  71. Ogawa T. Sawane K. Ookoshi K. Kawashima R. Supplementation with flaxseed oil rich in alpha-linolenic acid improves verbal fluency in healthy older adults. Nutrients 2023 15 6 1499 10.3390/nu15061499 36986229
    [Google Scholar]
  72. Laferrière F. Claverol S. Bezard E. De Giorgi F. Ichas F. Similar neuronal imprint and no cross-seeded fibrils in α-synuclein aggregates from MSA and Parkinson’s disease. NPJ Parkinsons Dis. 2022 8 1 10 10.1038/s41531‑021‑00264‑w 35027576
    [Google Scholar]
  73. Yang Y. Shi Y. Schweighauser M. Zhang X. Kotecha A. Murzin A.G. Garringer H.J. Cullinane P.W. Saito Y. Foroud T. Warner T.T. Hasegawa K. Vidal R. Murayama S. Revesz T. Ghetti B. Hasegawa M. Lashley T. Scheres S.H.W. Goedert M. Structures of α-synuclein filaments from human brains with Lewy pathology. Nature 2022 610 7933 791 795 10.1038/s41586‑022‑05319‑3 36108674
    [Google Scholar]
  74. Reddy K. Dieriks B.V. Multiple system atrophy: α-Synuclein strains at the neuron-oligodendrocyte crossroad. Mol. Neurodegener. 2022 17 1 77 10.1186/s13024‑022‑00579‑z 36435784
    [Google Scholar]
  75. Wang J. Li Y. Lai K. Zhong Q. Demin K.A. Kalueff A.V. Song C. High-glucose/high-cholesterol diet in zebrafish evokes diabetic and affective pathogenesis: The role of peripheral and central inflammation, microglia and apoptosis. Prog. Neuropsychopharmacol. Biol. Psychiatry 2020 96 109752 10.1016/j.pnpbp.2019.109752 31446160
    [Google Scholar]
  76. Lüscher T.F. Preventive cardiology in adolescents and the elderly: LDL, HDL, and inflammation. Eur. Heart J. 2019 40 43 3503 3506 10.1093/eurheartj/ehz824 31725892
    [Google Scholar]
  77. Chiesa S.T. Charakida M. McLoughlin E. Nguyen H.C. Georgiopoulos G. Motran L. Elia Y. Marcovecchio M.L. Dunger D.B. Dalton R.N. Daneman D. Sochett E. Mahmud F.H. Deanfield J.E. Elevated high-density lipoprotein in adolescents with Type 1 diabetes is associated with endothelial dysfunction in the presence of systemic inflammation. Eur. Heart J. 2019 40 43 3559 3566 10.1093/eurheartj/ehz114 30863865
    [Google Scholar]
  78. Cao B. Guo X. Chen K. Song W. Huang R. Wei Q.Q. Zhao B. Shang H.F. Serum lipid levels are associated with the prevalence but not with the disease progression of multiple system atrophy in a Chinese population. Neurol. Res. 2014 36 2 150 156 10.1179/1743132813Y.0000000277 24172715
    [Google Scholar]
/content/journals/cn/10.2174/011570159X379620250225075810
Loading
/content/journals/cn/10.2174/011570159X379620250225075810
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher's website along with the published article.


  • Article Type:
    Research Article
Keywords: blood routine examination ; biomarkers ; peripheral inflammation ; Cerebellar ataxia
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test