Quantitative Measurement of Cerebrospinal Fluid Amyloid-β Species by Mass Spectrometry

Seino, Yusuke; Nakamura, Takumi; Harada, Tomoo; Nakahata, Naoko; Kawarabayashi, Tatsuhiko; Ueda, Tetsuya; Takatama, Masamitsu; Shoji, Mikio

doi:10.3233/jad-200987

Cited by 18 publications

(14 citation statements)

References 45 publications

(70 reference statements)

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“…The Na + and K + concentrations were determined at 589 and 766.5 nm using an iCE 3300 AAS atomic absorption spectrometer (Thermo, USA). The endogenous ABA content before and after exposure to salt stress was determined with a 5,500 QTRAP(AB SCIEX) mass spectrometer using liquid chromatography–mass spectrometry as previously described (Chen et al, 2003; Seino et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

The basic helix‐loop‐helix transcription factor gene, OsbHLH38, plays a key role in controlling rice salt tolerance

Wang

et al. 2023

JIPB

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The plant hormone abscisic acid (ABA) is crucial for plant seed germination and abiotic stress tolerance. However, the association between ABA sensitivity and plant abiotic stress tolerance remains largely unknown. In this study, 436 rice accessions were assessed for their sensitivity to ABA during seed germination. The considerable diversity in ABA sensitivity among rice germplasm accessions was primarily reflected by the differentiation between the Xian (indica) and Geng (japonica) subspecies and between the upland‐Geng and lowland‐Geng ecotypes. The upland‐Geng accessions were most sensitive to ABA. Genome‐wide association analyses identified four major quantitative trait loci containing 21 candidate genes associated with ABA sensitivity of which a basic helix‐loop‐helix transcription factor gene, OsbHLH38, was the most important for ABA sensitivity. Comprehensive functional analyses using knockout and overexpression transgenic lines revealed that OsbHLH38 expression was responsive to multiple abiotic stresses. Overexpression of OsbHLH38 increased seedling salt tolerance, while knockout of OsbHLH38 increased sensitivity to salt stress. A salt‐responsive transcription factor, OsDREB2A, interacted with OsbHLH38 and was directly regulated by OsbHLH38. Moreover, OsbHLH38 affected rice abiotic stress tolerance by mediating the expression of a large set of transporter genes of phytohormones, transcription factor genes, and many downstream genes with diverse functions, including photosynthesis, redox homeostasis, and abiotic stress responsiveness. These results demonstrated that OsbHLH38 is a key regulator in plant abiotic stress tolerance.

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Section: Methodsmentioning

confidence: 99%

The basic helix‐loop‐helix transcription factor gene, OsbHLH38, plays a key role in controlling rice salt tolerance

Wang

et al. 2023

JIPB

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“…Sandwich ELISA was used to quantify plasma Aβ40 and Aβ42 levels using the Human/Rat ß Amyloid (40) ELISA Kit Wako II and Human/Rat ß Amyloid (42) ELISA Kit Wako High‐Sensitive (Wako Pure Chemical Industries, Ltd., Osaka, Japan). The antibodies used and assay sensitivities were previously described 15,20–22 . The 129 outliers of plasma Aβ40 or Aβ42 levels were excluded by the ROUT method ( Q = 1%) 23 …”

Section: Methodsmentioning

confidence: 99%

Annual stability of the plasma Aß40/42 ratio and associated factors

Nakamura

Kawarabayashi

Nakahata

et al. 2023

Ann Clin Transl Neurol

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Objective: The plasma Aß40/42 ratio is a biomarker of brain amyloidosis. However, the threshold difference between amyloid positivity and negativity is only 10-20% and fluctuates with circadian rhythms, aging, and APOE-e4 during the decades of evolution of Alzheimer's disease. Methods: Plasma Aß40 and Aß42 levels in 1472 participants aged between 19 and 93 years in the Iwaki Health Promotion Project for 4 years were statistically analyzed. Results: The means and standard deviations of annual inter-individual coefficients of variation were 5.3 AE 3.2% for Aß40, 7.8 AE 4.6% for Aß42, and 6.4 AE 4.1% for the Aß40/42 ratio. No significant age-dependent changes were observed in interindividual coefficients of variation. Age-dependent increases in Ab42 levels were suppressed, whereas those in the Ab40/42 ratio were enhanced in APOE-e4 carriers. The change points of Aß42, Aß40, and the Aß40/42 ratio were 36.4, 38.2, and 43.5 years, respectively. In the presence of APOE-e4, the Aß40/42 ratio increased in middle-aged and elderly subjects while Ab42 levels decreased in elderly subjects. Interpretation: Individual values for Aß40, Aß42, and the Aß40/42 ratio did not fluctuate annually or in an age-dependent manner. If the plasma Ab40/42 ratio changes by more than 14.7% (+2 standard deviations) relative to age-and APOE-e4-adjusted normal annual fluctuations, other biomarkers also need to be examined.

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“…CSF total tau and phosphorylated-tau181 were analyzed by electrochemiluminescence immunoassay following a Roche Studying Protocol in UPenn/ADNI biomarker Laboratory ( Hansson et al, 2018 ), which were derived from UPENNBIOMK9_04_19_17.csv file. CSF Aβ42 and Aβ40 concentration were analyzed using 2D-UPLC tandem mass spectrometry, which was also widely used in measuring CSF biomarkers and its reproducibility and accuracy in measuring CSF Aβ42 and Aβ40 have also been confirmed ( Korecka et al, 2014 ; Weber et al, 2019 ; Seino et al, 2021 ). Then, Aβ42/Aβ40 ratio was calculated for each subject and a published cut-off point of ratio (<0.138) was applied to identify positive amyloid deposition.…”

Section: Methodsmentioning

confidence: 99%

Microglial Activation, Tau Pathology, and Neurodegeneration Biomarkers Predict Longitudinal Cognitive Decline in Alzheimer’s Disease Continuum

Chen

Lin

Huang

et al. 2022

Front. Aging Neurosci.

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PurposeBiomarkers used for predicting longitudinal cognitive change in Alzheimer’s disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort.Patients and MethodsA total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer’s Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.ResultsBaseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.ConclusionOur study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.

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Quantitative Measurement of Cerebrospinal Fluid Amyloid-β Species by Mass Spectrometry

Cited by 18 publications

References 45 publications

The basic helix‐loop‐helix transcription factor gene, OsbHLH38, plays a key role in controlling rice salt tolerance

The basic helix‐loop‐helix transcription factor gene, OsbHLH38, plays a key role in controlling rice salt tolerance

Annual stability of the plasma Aß40/42 ratio and associated factors

Microglial Activation, Tau Pathology, and Neurodegeneration Biomarkers Predict Longitudinal Cognitive Decline in Alzheimer’s Disease Continuum

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