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Updated: Jan 29, 2026

High Content Screening in Neurodegenerative Diseases
Published on: January 6, 2012
Gene Panel Approach to Screen for Hereditary Cerebral Small Vessel Disease: A Proof-of-Concept Study
Chiara Ferraro1, Silvia Giliani2, Alessandro Pezzini3,4
1Neurology Clinic, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy.
Insights
A new algorithm helps identify patients with hereditary cerebral small vessel disease (cSVD). This approach successfully detected pathogenic genetic variants exclusively in high-probability individuals, improving diagnostic yield for monogenic conditions.
Area of Science:
- Neurology
- Genetics
- Medical Diagnostics
Background:
- Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia.
- Identifying patients with hereditary cSVD (hcSVD) is challenging due to poorly defined predictive algorithms.
- Selecting patients for genetic screening requires improved pre-screening methods.
Purpose of the Study:
- To evaluate the predictive performance of a phenotype-based algorithm for identifying patients with hcSVD.
- To assess the yield of a high-throughput gene panel in detecting clinically relevant genetic variants (CRGVs) in cSVD patients.
- To compare the prevalence of CRGVs and variants of unknown significance (VUSs) between high-probability and low-probability groups.
Main Methods:
- A phenotype-based algorithm was used to select patients for genetic screening.
- A high-throughput gene panel targeting 27 candidate genes associated with cSVD was employed.
- Patients were categorized into High-Probability Group (HPG) and Low-Probability Group (LPG) for molecular analysis.
Main Results:
- Among 65 probands, 16.9% had CRGVs or VUSs.
- Pathogenic CRGVs were found in 18.2% of the HPG (4/22 probands), with none in the LPG.
- VUSs were more frequent in the HPG (22.7%) compared to the LPG (4.6%).
Conclusions:
- The proposed pragmatic algorithm effectively identifies patients with a higher likelihood of harboring monogenic cSVD.
- This approach enhances the diagnostic yield for hereditary forms of cSVD.
- The findings support the use of phenotype-based algorithms to guide genetic testing in cSVD patients.
Abstract:
Background: The predictive performance of pre-screening phenotype-based algorithms in selecting patients with cerebral small vessel disease (cSVD), one of the main causes of ischaemic and haemorrhagic stroke and dementia, more likely to harbor clinically relevant genetic variants (CRGVs) has to date been poorly defined, making it a clinical challenge to decide which patients to screen for hereditary cSVD (hcSVD). Methods: We designed a high-throughput gene panel to identify variants in 27 candidate genes associated with cSVD and screened patients selected by a specific phenotype-based algorithm at one comprehensive stroke center from 2020 to 2023. We categorized participants into two sub-groups defined by pre-screening likelihood of hcSVD (hcSVD; High-Probability Group, HPG vs. Low-Probability Group, LPG) and compared the results of molecular analysis. Results: Among 65 probands, we detected four (6.1%) pathogenic CRGVs and seven (10.7%) variants of unknown significance (VUSs) in 11 (16.9%) patients. Pathogenic CRGVs were exclusively detected in the HPG (4/22 probands), corresponding to an 18.2% prevalence of hcSVD in this group. Of the seven VUSs, five (22.7%) were detected in the HPG vs. two (4.6%) in the LPG. Conclusions: The pragmatic algorithm we are proposing has the potential to help clinicians in identifying patients who are more likely to harbor monogenic disease.
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