Cell-free RNA signatures predict Alzheimer's disease

Alejandro Cisterna-García; Aleksandra Beric; Muhammad Ali; Jose Adrian Pardo; Hsiang Han Chen; Maria Victoria Fernandez; Joanne Norton; Jen Gentsch; Kristy Bergmann; John Budde; Joel S. Perlmutter; John C. Morris; Carlos Cruchaga; Juan A. Botia; Laura Ibanez

doi:10.1016/j.isci.2023.108534

Cell-free RNA signatures predict Alzheimer's disease

Alejandro Cisterna-García, Aleksandra Beric, Muhammad Ali, Jose Adrian Pardo, Hsiang Han Chen, Maria Victoria Fernandez, Joanne Norton, Jen Gentsch, Kristy Bergmann, John Budde, Joel S. Perlmutter, John C. Morris, Carlos Cruchaga, Juan A. Botia, Laura Ibanez^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.

Original language	English
Article number	108534
Journal	iScience
Volume	26
Issue number	12
DOIs	https://doi.org/10.1016/j.isci.2023.108534
Publication status	Published - 2023 Dec 15
Externally published	Yes

Keywords

Biochemistry
Clinical finding
Disease
Molecular biology

ASJC Scopus subject areas

General

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10.1016/j.isci.2023.108534

Cite this

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title = "Cell-free RNA signatures predict Alzheimer's disease",

abstract = "There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.",

keywords = "Biochemistry, Clinical finding, Disease, Molecular biology",

author = "Alejandro Cisterna-Garc{\'i}a and Aleksandra Beric and Muhammad Ali and Pardo, {Jose Adrian} and Chen, {Hsiang Han} and Fernandez, {Maria Victoria} and Joanne Norton and Jen Gentsch and Kristy Bergmann and John Budde and Perlmutter, {Joel S.} and Morris, {John C.} and Carlos Cruchaga and Botia, {Juan A.} and Laura Ibanez",

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doi = "10.1016/j.isci.2023.108534",

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T1 - Cell-free RNA signatures predict Alzheimer's disease

AU - Cisterna-García, Alejandro

AU - Beric, Aleksandra

AU - Ali, Muhammad

AU - Pardo, Jose Adrian

AU - Chen, Hsiang Han

AU - Fernandez, Maria Victoria

AU - Norton, Joanne

AU - Gentsch, Jen

AU - Bergmann, Kristy

AU - Budde, John

AU - Perlmutter, Joel S.

AU - Morris, John C.

AU - Cruchaga, Carlos

AU - Botia, Juan A.

AU - Ibanez, Laura

PY - 2023/12/15

Y1 - 2023/12/15

N2 - There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.

AB - There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.

KW - Biochemistry

KW - Clinical finding

KW - Disease

KW - Molecular biology

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VL - 26

JO - iScience

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Cell-free RNA signatures predict Alzheimer's disease

Abstract

Keywords

ASJC Scopus subject areas

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