Evidence map›Paper›PMID 42410965›Full record

ArticleMolecular genetics & genomic medicine2026

Correlation Analysis of Clinical, Imaging, and Genetic Etiologies in Pediatric Hereditary Cerebellar Atrophy: A Single-Center Study.

Luyao Jin, Shuling Chen, Ying Liu, Renyi She, Wei Jiang

Abstract read
In one paragraph

Article in Molecular genetics & genomic medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Luyao JinDepartment of Rehabilitation, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing City, China.ORCID https://orcid.org/0009-0008-9582-4024
Shuling ChenPeople's Hospital of Kaizhou District, Chongqing City, China.ORCID https://orcid.org/0000-0002-1596-3171
Ying LiuChongqing Maternal and Child Health Hospital, Chongqing City, China.ORCID https://orcid.org/0009-0000-0775-3193
Renyi SheChongqing Maternal and Child Health Hospital, Chongqing City, China.ORCID https://orcid.org/0009-0004-3766-8909
Wei JiangDepartment of Rehabilitation, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing City, China.ORCID https://orcid.org/0000-0002-0999-8132

Funding

Chongqing Science and Technology Commission and Health Commission Joint Research Project (Grant/Award Number: 2018ZDXM029) 2018ZDXM029National Natural Science Foundation of China (Grant/Award Number: 81571091) 81571091
6 · The paper itself

Abstract

objectiveTo investigate the associations among clinical features, neuroimaging findings, and genetic data in children with hereditary cerebellar atrophy (CA).

methodA cohort of 102 pediatric patients diagnosed with hereditary CA was enrolled at the Children's Hospital of Chongqing Medical University (2015-2024). Univariate and multivariate analyses assessed clinical-neuroimaging-genetic correlations.

resultsEarlier onset correlated with prematurity (p = 0.039) and negative family history (p = 0.042); diagnostic delay with unremarkable perinatal history (p = 0.038). Motor delay was more prevalent in males (100% vs. 91.1%). Gross motor scores were lower in membrane transporters (26.78 ± 17.90, p = 0.027) and metabolic diseases (28.09 ± 26.26, p = 0.025) compared to cytoskeletal proteinopathies (47.81 ± 13.55). Multivariate analysis identified age at onset and diagnostic delay as independent predictors of motor and cognitive development delay and enzymopathies/glycoprotein disorders for global developmental delay (OR = 4.4, p = 0.042). Early onset (≤ 6 months) elevated the risk of ataxia (OR = 6.75, p = 0.021). Atrophy severity independently predicted motor and cognitive impairment.

conclusionPreterm birth, male sex, and negative family history predicted earlier onset, urging early neuroimaging. Early onset and severe/complex cerebellar atrophy indicated poorer prognosis. While ataxia was uncommon overall, onset ≤ 6 months increased its risk. Metabolic disorders contributed to significant motor deficits, underscoring the need for early genetic testing and targeted management.

Indexed as

Spinocerebellar DegenerationsAdolescentAge of OnsetChildChild, PreschoolFemaleHumansInfantInfant, NewbornMagnetic Resonance ImagingMaleNeuroimagingataxiacerebellar atrophychildrengene mutationhereditary

Identifiers

PMID42410965
PMCPMC13338570

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.