Browsing by Subject "Diagnostic"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Blood Biomarkers from Research Use to Clinical Practice: What Must Be Done? A Report from the EU/US CTAD Task Force
    (Springer, 2022) Angioni, D.; Delrieu, J.; Hansson, O.; Fillit, H.; Aisen, P.; Cummings, J.; Sim, J. R.; Braunstein, J. B.; Sabbagh, M.; Bittner, T.; Pontecorvo, M.; Bozeat, S.; Dage, J. L.; Largent, E.; Mattke, S.; Correa, O.; Gutierrez Robledo, L. M.; Baldivieso, V.; Willis, D. R.; Atri, A.; Bateman, R. J.; Ousset, P-J.; Vellas, B.; Weiner, M.; Neurology, School of Medicine
    Timely and accurate diagnosis of Alzheimer’s disease (AD) in clinical practice remains challenging. PET and CSF biomarkers are the most widely used biomarkers to aid diagnosis in clinical research but present limitations for clinical practice (i.e., cost, accessibility). Emerging blood-based markers have the potential to be accurate, cost-effective, and easily accessible for widespread clinical use, and could facilitate timely diagnosis. The EU/US CTAD Task Force met in May 2022 in a virtual meeting to discuss pathways to implementation of blood-based markers in clinical practice. Specifically, the CTAD Task Force assessed: the state-of-art for blood-based markers, the current use of blood-based markers in clinical trials, the potential use of blood-based markers in clinical practice, the current challenges with blood-based markers, and the next steps needed for broader adoption in clinical practice.
  • Thumbnail Image
    Item
    Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies
    (Elsevier, 2023) Lowther, Chelsea; Valkanas, Elise; Giordano, Jessica L.; Wang, Harold Z.; Currall, Benjamin B.; O'Keefe, Kathryn; Pierce-Hoffman, Emma; Kurtas, Nehir E.; Whelan, Christopher W.; Hao, Stephanie P.; Weisburd, Ben; Jalili, Vahid; Fu, Jack; Wong, Isaac; Collins, Ryan L.; Zhao, Xuefang; Austin-Tse, Christina A.; Evangelista, Emily; Lemire, Gabrielle; Aggarwal, Vimla S.; Lucente, Diane; Gauthier, Laura D.; Tolonen, Charlotte; Sahakian, Nareh; Stevens, Christine; An, Joon-Yong; Dong, Shan; Norton, Mary E.; MacKenzie, Tippi C.; Devlin, Bernie; Gilmore, Kelly; Powell, Bradford C.; Brandt, Alicia; Vetrini, Francesco; DiVito, Michelle; Sanders, Stephan J.; MacArthur, Daniel G.; Hodge, Jennelle C.; O'Donnell-Luria, Anne; Rehm, Heidi L.; Vora, Neeta L.; Levy, Brynn; Brand, Harrison; Wapner, Ronald J.; Talkowski, Michael E.; Medical and Molecular Genetics, School of Medicine
    Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.