Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.
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http://dx.doi.org/10.1093/brain/awac484 | DOI Listing |
BMC Infect Dis
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Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China.
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Sci Rep
January 2025
Department of Genetics, The University of Alabama at Birmingham, Birmingham, AL, USA.
Nowadays, chemotherapy and immunotherapy remain the major treatment strategies for Triple-Negative Breast Cancer (TNBC). Identifying biomarkers to pre-select and subclassify TNBC patients with distinct chemotherapy responses is essential. In the current study, we performed an unbiased Reverse Phase Protein Array (RPPA) on TNBC cells treated with chemotherapy compounds and found a leading significant increase of phosphor-AURKA/B/C, AURKA, AURKB, and PLK1, which fall into the mitotic kinase group.
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February 2025
Department of Pathology, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou 215002, China.
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View Article and Find Full Text PDFJ Prev Alzheimers Dis
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Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA. Electronic address:
Background: Protein abundance levels, sensitive to both physiological changes and external interventions, are useful for assessing the Alzheimer's disease (AD) risk and treatment efficacy. However, identifying proteomic prognostic markers for AD is challenging by their high dimensionality and inherent correlations.
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Matrix Biol
January 2025
Department of Pharmacology & Immunology, Proteomics Center, Medical University of South Carolina, Charleston, SC. Electronic address:
Collagen stroma interactions within the extracellular microenvironment of breast tissue play a significant role in breast cancer, including risk, progression, and outcomes. Hydroxylation of proline (HYP) is a common post-translational modification directly linked to breast cancer survival and progression. Changes in HYP status lead to alterations in epithelial cell signaling, extracellular matrix remodeling, and immune cell recruitment.
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