Performance of plasma Aβ42/40, measured using a fully automated immunoassay, across a broad patient population in identifying amyloid status.


Journal

Alzheimer's research & therapy
ISSN: 1758-9193
Titre abrégé: Alzheimers Res Ther
Pays: England
ID NLM: 101511643

Informations de publication

Date de publication:
04 09 2023
Historique:
received: 17 06 2023
accepted: 24 08 2023
medline: 6 9 2023
pubmed: 5 9 2023
entrez: 4 9 2023
Statut: epublish

Résumé

Plasma biomarkers have emerged as promising screening tools for Alzheimer's disease (AD) because of their potential to detect amyloid β (Aβ) accumulation in the brain. One such candidate is the plasma Aβ42/40 ratio (Aβ42/40). Unlike previous research that used traditional immunoassay, recent studies that measured plasma Aβ42/40 using fully automated platforms reported promising results. However, its utility should be confirmed using a broader patient population, focusing on the potential for early detection. We recruited 174 participants, including healthy controls (HC) and patients with clinical diagnoses of AD, frontotemporal lobar degeneration, dementia with Lewy bodies/Parkinson's disease, mild cognitive impairment (MCI), and others, from a university memory clinic. We examined the performance of plasma Aβ42/40, measured using the fully automated high-sensitivity chemiluminescence enzyme (HISCL) immunoassay, in detecting amyloid-positron emission tomography (PET)-derived Aβ pathology. We also compared its performance with that of Simoa-based plasma phosphorylated tau at residue 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). Using the best cut-off derived from the Youden Index, plasma Aβ42/40 yielded an area under the receiver operating characteristic curve (AUC) of 0.949 in distinguishing visually assessed Plasma Aβ42/40 measured using the fully automated HISCL platform showed excellent performance in identifying Aβ accumulation in the brain in a well-characterized cohort. This equipment may be useful for screening amyloid pathology because it has the potential to detect early amyloid pathology and is readily applied in clinical settings.

Sections du résumé

BACKGROUND
Plasma biomarkers have emerged as promising screening tools for Alzheimer's disease (AD) because of their potential to detect amyloid β (Aβ) accumulation in the brain. One such candidate is the plasma Aβ42/40 ratio (Aβ42/40). Unlike previous research that used traditional immunoassay, recent studies that measured plasma Aβ42/40 using fully automated platforms reported promising results. However, its utility should be confirmed using a broader patient population, focusing on the potential for early detection.
METHODS
We recruited 174 participants, including healthy controls (HC) and patients with clinical diagnoses of AD, frontotemporal lobar degeneration, dementia with Lewy bodies/Parkinson's disease, mild cognitive impairment (MCI), and others, from a university memory clinic. We examined the performance of plasma Aβ42/40, measured using the fully automated high-sensitivity chemiluminescence enzyme (HISCL) immunoassay, in detecting amyloid-positron emission tomography (PET)-derived Aβ pathology. We also compared its performance with that of Simoa-based plasma phosphorylated tau at residue 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL).
RESULTS
Using the best cut-off derived from the Youden Index, plasma Aβ42/40 yielded an area under the receiver operating characteristic curve (AUC) of 0.949 in distinguishing visually assessed
CONCLUSION
Plasma Aβ42/40 measured using the fully automated HISCL platform showed excellent performance in identifying Aβ accumulation in the brain in a well-characterized cohort. This equipment may be useful for screening amyloid pathology because it has the potential to detect early amyloid pathology and is readily applied in clinical settings.

Identifiants

pubmed: 37667408
doi: 10.1186/s13195-023-01296-5
pii: 10.1186/s13195-023-01296-5
pmc: PMC10476307
doi:

Substances chimiques

amyloid beta-protein (1-42) 0
Amyloid beta-Peptides 0
Amyloidogenic Proteins 0

Banques de données

UMIN-CTR
['UMIN000032027']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

149

Informations de copyright

© 2023. BioMed Central Ltd., part of Springer Nature.

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Auteurs

Shogyoku Bun (S)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan. shogybun@keio.jp.

Daisuke Ito (D)

Memory Center, Keio University School of Medicine, Tokyo, Japan.
Department of Physiology, Keio University School of Medicine, Tokyo, Japan.

Toshiki Tezuka (T)

Department of Neurology, Keio University School of Medicine, Tokyo, Japan.

Masahito Kubota (M)

Department of Neurology, Keio University School of Medicine, Tokyo, Japan.

Ryo Ueda (R)

Office of Radiation Technology, Keio University Hospital, Tokyo, Japan.

Keisuke Takahata (K)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.

Sho Moriguchi (S)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.

Shin Kurose (S)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.

Yuki Momota (Y)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.

Natsumi Suzuki (N)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

Ayaka Morimoto (A)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

Yuka Hoshino (Y)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

Morinobu Seki (M)

Department of Neurology, Keio University School of Medicine, Tokyo, Japan.

Yu Mimura (Y)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

Ryo Shikimoto (R)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

Yasuharu Yamamoto (Y)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.

Takayuki Hoshino (T)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
Graduate School of Media and Governance, Keio University, Kanagawa, Japan.

Yoshiaki Sato (Y)

Eisai-Keio Innovation Laboratory for Dementia, Human Biology Integration Foundation, Eisai Co., Ltd, Tokyo, Japan.

Hajime Tabuchi (H)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

Masaru Mimura (M)

Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.

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