3042 To the scanner ASAP!

undergo telehealth assessments at baseline, 18 and 36 months and surveys to assess utility of and attitudes toward genomic testing.Whole genome sequencing will be performed through GP2 and genetic results returned to participants.Cost-effectiveness will be assessed.Results Approximately 2200 APGS participants are eligible for MonoPDAus based on onset age and family history.Recruitment from APGS to MonoPDAus will commence this year.Direct recruitment to the GP2 Monogenic Network has commenced (n = 50)sequencing data for these participants is undergoing variant filtration.Conclusion By offering the genetic sequencing capabilities of GP2 to a large Australian PD population, MonoPDAus promises to provide a comprehensive characterisation of monogenic PD.

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Publication Details

Published
2024-08-01
DOI
https://doi.org/10.1136/bmjno-2024-anzan.63
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

3042 To the scanner ASAP!

Mina Botrous, Erin EC Casey, Jane JP Prosser, Louise Allport
1 links
Radiomics and Machine Learning in Medical Imaging
article

3042 To the scanner ASAP!

Mina Botrous, Erin EC Casey, Jane JP Prosser, Louise Allport
article en

Abstract

undergo telehealth assessments at baseline, 18 and 36 months and surveys to assess utility of and attitudes toward genomic testing.Whole genome sequencing will be performed through GP2 and genetic results returned to participants.Cost-effectiveness will be assessed.Results Approximately 2200 APGS participants are eligible for MonoPDAus based on onset age and family history.Recruitment from APGS to MonoPDAus will commence this year.Direct recruitment to the GP2 Monogenic Network has commenced (n = 50)sequencing data for these participants is undergoing variant filtration.Conclusion By offering the genetic sequencing capabilities of GP2 to a large Australian PD population, MonoPDAus promises to provide a comprehensive characterisation of monogenic PD.

St George Hospital (AU)
Openalex Percentile: Top 78%
Radiomics and Machine Learning in Medical Imaging
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