Ask about this productRelated genes to: NPTX2 Blocking Peptide
- Gene:
- NPTX2 NIH gene
- Name:
- neuronal pentraxin 2
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 7q22.1
- Locus Type:
- gene with protein product
- Date approved:
- 1995-05-12
- Date modifiied:
- 2016-10-05
Related products to: NPTX2 Blocking Peptide
Related articles to: NPTX2 Blocking Peptide
- Lower levels of several synaptic proteins in cerebrospinal fluid (CSF) have been associated with greater cognitive decline among older adults, but there is limited understanding of their associations with brain structure. This study is among the first to examine the cross-sectional relationship between levels of three synaptic proteins (VGF, NPTX2, and GluA4) with magnetic resonance imaging (MRI) measures of white matter microstructure and volumes, and with cognitive performance. We also examined whether relationships between synaptic protein levels and white matter measures are influenced by CSF Alzheimer's disease (AD) biomarker levels [ratio of p-tau/(Aβ/Aβ)]. - Source: PubMed
Publication date: 2026/06/15
Paitel Elizabeth RPettigrew CorinneMoghekar AbhayMiller Michael IFaria Andreia VAlbert MarilynNa Chan HyunWorley PaulSoldan Anja - Herein, we describe the identification of protein biomarkers in the cerebrospinal fluid (CSF) of Alzheimer's disease (AD) patients that enable the differentiation of Responders from Non-Responders to lymphatic-venous anastomosis (LVA). Discovery of these potential biomarkers was achieved by deep proteomic analysis on the pre-LVA cerebrospinal fluid in a cohort of 90 patients. A combination of two CSF processing modalities and two computational platforms allowed us to secure the largest CSF proteome ever reported (6711 proteins identified with 4506 proteins quantified at a false-discovery rate of ≤1%). Importantly, we discovered 16 CSF proteins that are expressed differentially between patients who showed documented improvements after LVA (the Responders) and those who showed no improvements (the Non-Responders). Pairing of two of the best-performing potential biomarkers─NPTX2 and IGSF10─gave an accuracy of 0.790 (AUC = 0.854) in correctly identifying Responders and Non-Responders, which improved to 0.827 (AUC = 0.880) after we added a second pair of classical AD biomarkers─p-tau181 and Aβ42─to the test. We found that the classical ELISA biomarker ratio p-tau181/Aβ42 has, by itself, a marginally acceptable accuracy of 0.644 (AUC = 0.662). Our reported observation (in 2025) of a correlation between elevated p-tau181/Aβ42 and responding to LVA is in accordance with the interpretation that Responders have a higher abundance of NPTX2, which indicates better synaptic health. Apparently, the Responders are more resilient, despite an indication of more advanced pathology. In a simulation of the performance in future testing, we performed a 5-fold cross-validation that gave an AUC of 0.859 ± 0.074 and an accuracy of 0.740 ± 0.048 for the small testing group. - Source: PubMed
Publication date: 2026/06/25
Li YinanDu AnqiZhang QinghuaXu GuangqiXu XiaonaMa XiaoxueChu Joey C HThiyagarajan VengatesenYu ZhaoyanChu Ivan KSiu K W Michael - Accurate prediction of which patients with mild cognitive impairment (MCI) will progress to dementia remains a major challenge. Current biomarkers detect amyloid pathology with high accuracy but offer limited prognostic value for disease progression. We conducted a prospective analysis in the multicentre BALTAZAR cohort, all diagnosed with MCI at baseline and followed for 3 years. Paired cerebrospinal fluid (CSF) and plasma samples were analysed with the NULISA ultrasensitive multiplex platform quantifying more than 120 central nervous system biomarkers. Prognostic performance was assessed using area under the curve (AUC) and hazard ratios (HRs), both for individual markers and for elastic-net-derived biomarker combinations validated by bootstrap and survival analyses. During the 3-year follow-up, 36% of participants converted to dementia. Plasma p-tau biomarkers showed strong accuracy for detecting amyloid positivity (AUC > 0.90) but limited prognostic value for conversion (AUC < 0.75). In CSF, markers of neurodegeneration (tau, NfL) and synaptic dysfunction (NPTX2 encoding the Neuronal Pentraxin 2) predicted conversion with higher accuracy, exceeding p-tau217 performance. The best-performing CSF combination (IL-16, tau, NPTX2) achieved an AUC of 0.86 (95%CI 0.80-0.91) and an HR of 39.8 (95%CI 9.6-165.2). Plasma combinations (p-tau181 or p-tau217 with YWHAG encoding for 14-3-3 protein gamma, a member of the 14-3-3 protein family) provided only modest improvement, likely reflecting the absence of robust synaptic markers in blood. Prognostic assessment of MCI progression to dementia is best achieved through CSF biomarker combinations reflecting neurodegeneration and synaptic dysfunction, complemented by inflammatory markers. These findings emphasize the clinical and pathophysiological relevance of downstream processes beyond amyloid and tau, and support the implementation of multimarker panels for prognosis and therapeutic monitoring. - Source: PubMed
Publication date: 2026/06/24
Delaby ConstanceSchraen-Maschke SusannaPaquet ClaireBlanc FrédéricVidal Jean-SébastienHirtz ChristopheAssou SaidAllinquant BernadetteBombois StéphanieGabelle AudreyHanon OlivierLehmann Sylvain - Neuronal pentraxin 2 (NPTX2) and its use as a ratio with other synaptic proteins has emerged as a prognostic cerebrospinal fluid (CSF) biomarker across neurodegenerative diseases. - Source: PubMed
Publication date: 2026/06/18
Gomes Bárbara FernandesSauer MathiasMontoliu-Gaya LaiaFranquesa-Mullerat MariaBejanin AlexandreAlcolea DanielLleó AlbertoIllán-Gala IgnacioFortea JuanBlennow KajZetterberg HenrikNilsson JohannaBelbin OliviaAshton Nicholas J - Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication. - Source: PubMed
Publication date: 2026/06/15
Donmez Turker BerkMansour Mohammed