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Browsing by Author "Mattsson-Carlgren, Niklas"
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Item Blood-based biomarkers for Alzheimer's disease(EMBO Press, 2022) Leuzy, Antoine; Mattsson-Carlgren, Niklas; Palmqvist, Sebastian; Janelidze, Shorena; Dage, Jeffrey L.; Hansson, Oskar; Neurology, School of MedicineNeurodegenerative disorders such as Alzheimer's disease (AD) represent a mounting public health challenge. As these diseases are difficult to diagnose clinically, biomarkers of underlying pathophysiology are playing an ever‐increasing role in research, clinical trials, and in the clinical work‐up of patients. Though cerebrospinal fluid (CSF) and positron emission tomography (PET)‐based measures are available, their use is not widespread due to limitations, including high costs and perceived invasiveness. As a result of rapid advances in the development of ultra‐sensitive assays, the levels of pathological brain‐ and AD‐related proteins can now be measured in blood, with recent work showing promising results. Plasma P‐tau appears to be the best candidate marker during symptomatic AD (i.e., prodromal AD and AD dementia) and preclinical AD when combined with Aβ42/Aβ40. Though not AD‐specific, blood NfL appears promising for the detection of neurodegeneration and could potentially be used to detect the effects of disease‐modifying therapies. This review provides an overview of the progress achieved thus far using AD blood‐based biomarkers, highlighting key areas of application and unmet challenges.Item Confounding factors of Alzheimer’s disease plasma biomarkers and their impact on clinical performance(Wiley, 2023) Pichet Binette, Alexa; Janelidze, Shorena; Cullen, Nicholas; Dage, Jeffrey L.; Bateman, Randall J.; Zetterberg, Henrik; Blennow, Kaj; Stomrud, Erik; Mattsson-Carlgren, Niklas; Hansson, Oskar; Neurology, School of MedicineIntroduction: Plasma biomarkers will likely revolutionize the diagnostic work-up of Alzheimer's disease (AD) globally. Before widespread use, we need to determine if confounding factors affect the levels of these biomarkers, and their clinical utility. Methods: Participants with plasma and CSF biomarkers, creatinine, body mass index (BMI), and medical history data were included (BioFINDER-1: n = 748, BioFINDER-2: n = 421). We measured beta-amyloid (Aβ42, Aβ40), phosphorylated tau (p-tau217, p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Results: In both cohorts, creatinine and BMI were the main factors associated with NfL, GFAP, and to a lesser extent with p-tau. However, adjustment for BMI and creatinine had only minor effects in models predicting either the corresponding levels in CSF or subsequent development of dementia. Discussion: Creatinine and BMI are related to certain plasma biomarkers levels, but they do not have clinically relevant confounding effects for the vast majority of individuals. Highlights: Creatinine and body mass index (BMI) are related to certain plasma biomarker levels. Adjusting for creatinine and BMI has minor influence on plasma-cerebrospinal fluid (CSF) associations. Adjusting for creatinine and BMI has minor influence on prediction of dementia using plasma biomarkers.Item Detecting amyloid positivity in early Alzheimer’s disease using combinations of plasma Aβ42/Aβ40 and p-tau(Wiley, 2022-02) Janelidze, Shorena; Palmqvist, Sebastian; Leuzy, Antoine; Stomrud, Erik; Verberk, Inge M.W.; Zetterberg, Henrik; Ashton, Nicholas J.; Pesini, Pedro; Sarasa, Leticia; Allué, José Antonio; Teunissen, Charlotte E.; Dage, Jeffrey L.; Blennow, Kaj; Mattsson-Carlgren, Niklas; Hansson, Oskar; Neurology, School of MedicineIntroduction: We studied usefulness of combining blood amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p-tau)217, and neurofilament light (NfL) to detect abnormal brain Aβ deposition in different stages of early Alzheimer's disease (AD). Methods: Plasma biomarkers were measured using mass spectrometry (Aβ42/Aβ40) and immunoassays (p-tau217 and NfL) in cognitively unimpaired individuals (CU, N = 591) and patients with mild cognitive impairment (MCI, N = 304) from two independent cohorts (BioFINDER-1, BioFINDER-2). Results: In CU, a combination of plasma Aβ42/Aβ40 and p-tau217 detected abnormal brain Aβ status with area under the curve (AUC) of 0.83 to 0.86. In MCI, the models including p-tau217 alone or Aβ42/Aβ40 and p-tau217 had similar AUCs (0.86-0.88); however, the latter showed improved model fit. The models were implemented in an online application providing individualized risk assessments (https://brainapps.shinyapps.io/PredictABplasma/). Discussion: A combination of plasma Aβ42/Aβ40 and p-tau217 discriminated Aβ status with relatively high accuracy, whereas p-tau217 showed strongest associations with Aβ pathology in MCI but not in CU.Item Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures(Nature, 2021-06) Palmqvist, Sebastian; Tideman, Pontus; Cullen, Nicholas; Zetterberg, Henrik; Blennow, Kaj; Dage, Jeffery L.; Stomrud, Erik; Janelidze, Shorena; Mattsson-Carlgren, Niklas; Hansson, Oskar; Neurology, School of MedicineA combination of plasma phospho-tau (P-tau) and other accessible biomarkers might provide accurate prediction about the risk of developing Alzheimer’s disease (AD) dementia. We examined this in participants with subjective cognitive decline and mild cognitive impairment from the BioFINDER (n = 340) and Alzheimer’s Disease Neuroimaging Initiative (ADNI) (n = 543) studies. Plasma P-tau, plasma Aβ42/Aβ40, plasma neurofilament light, APOE genotype, brief cognitive tests and an AD-specific magnetic resonance imaging measure were examined using progression to AD as outcome. Within 4 years, plasma P-tau217 predicted AD accurately (area under the curve (AUC) = 0.83) in BioFINDER. Combining plasma P-tau217, memory, executive function and APOE produced higher accuracy (AUC = 0.91, P < 0.001). In ADNI, this model had similar AUC (0.90) using plasma P-tau181 instead of P-tau217. The model was implemented online for prediction of the individual probability of progressing to AD. Within 2 and 6 years, similar models had AUCs of 0.90–0.91 in both cohorts. Using cerebrospinal fluid P-tau, Aβ42/Aβ40 and neurofilament light instead of plasma biomarkers did not improve the accuracy significantly. The clinical predictions by memory clinic physicians had significantly lower accuracy (4-year AUC = 0.71). In summary, plasma P-tau, in combination with brief cognitive tests and APOE genotyping, might greatly improve the diagnostic prediction of AD and facilitate recruitment for AD trials.