{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T11:06:29Z","timestamp":1790420789882,"version":"4.1.0"},"reference-count":30,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"5","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,9]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>Genetically defined spinocerebellar ataxia (SCA) type 1 and 2 patients have differential clinical profile along with probable distinctive cortical and subcortical neurodegeneration. We compared the degree of brain atrophy in the two subtypes with their phenotypic and genotypic parameters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>\n                      MRI was performed using a 3T scanner (Philips, Achieva) to obtain 3D T1-weighted scans of the whole brain and analyzed by FreeSurfer (version 5.3 and 6 dev.) software. Genetically proven SCA1 (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 18) and SCA2 (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 25) patients with age-matched healthy controls (\n                      <jats:italic toggle=\"yes\">n<\/jats:italic>\n                      = 8) were recruited. Clinical severity was assessed by the International Cooperative Ataxia Rating Scale (ICARS). To know the differential pattern of atrophy, the groups were compared using ANOVA\/Kruskal-Wallis test and followed by correlation analysis with multiple corrections. Further, machine learning-based classification of SCA subtypes was carried out.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Result:<\/jats:title>\n                    <jats:p>We found (i) bilateral frontal, parietal, temporal, and occipital atrophy in SCA1 and SCA2 patients; (ii) reduced volume of cerebellum, regions of brain stem, basal ganglia along with the certain subcortical areas such as hippocampus, amygdala, thalamus, diencephalon, and corpus callosum in SCA1 and SCA2 subtypes; (iii) higher subcortical atrophy SCA2 than SCA1 (iv) correlation between brain atrophy and disease attributes; (v) differential predictive pattern of two SCA subtypes using machine learning approach.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>The present study suggests that SCA1 and SCA2 do not differ in cortical thinning while a characteristic pattern of subcortical atrophy SCA2 &gt; SCA1 is observed along with correlation of brain atrophy and disease attributes. This may provide the diagnostic guidance of MRI to SCA subtypes and differential therapies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/0028-3886.329596","type":"journal-article","created":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T15:06:21Z","timestamp":1725721581000},"page":"1318-1325","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":11,"title":["Cortical and Subcortical Brain Area Atrophy in SCA1 and SCA2 Patients in India: The Structural MRI Underpinnings and Correlative Insight Among the Atrophy and Disease Attributes"],"prefix":"10.4103","volume":"69","author":[{"given":"Dibashree","family":"Tamuli","sequence":"first","affiliation":[{"name":"Department of Zoology, Nalbari College, Assam, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manpreet","family":"Kaur","sequence":"additional","affiliation":[{"name":"Department of Physiology, VMMC & Safdarjung Hospital, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tavpritesh","family":"Sethi","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anup","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, India"},{"name":"Center for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Faruq","sequence":"additional","affiliation":[{"name":"Genomics and Molecular Medicine, CSIR-Institute of Genomics and Integrative Biology (CSIR -IGIB), New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashok K","family":"Jaryal","sequence":"additional","affiliation":[{"name":"Department of Physiology, All India Institute of Medical Sciences, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Achal K","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Department of Neurology, All India Institute of Medical Sciences, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Senthil S","family":"Kumaran","sequence":"additional","affiliation":[{"name":"Department of NMR, All India Institute of Medical Sciences, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kishore K","family":"Deepak","sequence":"additional","affiliation":[{"name":"Department of Physiology, All India Institute of Medical Sciences, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"R1-20250925","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/S1474-4422(04)00737-9","article-title":"Autosomal dominant cerebellar ataxias: Clinical features, genetics, and pathogenesis","volume":"3","author":"Sch\u00f6ls","year":"2004","journal-title":"Lancet Neurol"},{"key":"R2-20250925","doi-asserted-by":"crossref","DOI":"10.1111\/ane.13151","article-title":"Depressed baroreflex sensitivity from spontaneous oscillations of heart-rate and blood-pressure in SCA1 and SCA2","author":"Tamuli","year":"2019","journal-title":"Acta Neurol Scand"},{"key":"R3-20250925","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1093\/hmg\/6.5.709","article-title":"Molecular and clinical correlations in spinocerebellar ataxia 2: A study of 32 families","volume":"6","author":"Cancel","year":"1997","journal-title":"Hum Mol Genet"},{"key":"R4-20250925","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1001\/archneur.62.4.630","article-title":"Autonomic dysfunction in Machado-Joseph disease","volume":"62","author":"Yeh","year":"2005","journal-title":"Arch Neurol"},{"key":"R5-20250925","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1111\/j.1600-0404.2007.00945.x","article-title":"Spinocerebellar ataxias type 1, 2 and 3: A study of heart rate variability","volume":"117","author":"Pradhan","year":"2008","journal-title":"Acta Neurol Scand"},{"key":"R6-20250925","first-page":"329","article-title":"Heart rate variability in type 2 spinocerebellar ataxia","volume":"122","author":"Montes-Brown","year":"2010","journal-title":"Acta Neurol Scand"},{"key":"R7-20250925","doi-asserted-by":"crossref","first-page":"1785","DOI":"10.1093\/brain\/awh201","article-title":"Brainstem neurodegeneration correlates with clinical dysfunction in SCA1 but not in SCA2. 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