Introduction: CT1812 is in clinical development for the treatment of Alzheimer's disease (AD). Cerebrospinal fluid (CSF) exploratory proteomics was employed to identify pharmacodynamic biomarkers of CT1812 in mild to moderate AD from two independent clinical trials.
Methods: Unbiased analysis of tandem-mass tag mass spectrometry (TMT-MS) quantitative proteomics, pathway analysis and correlation analyses with volumetric magnetic resonance imaging (vMRI) were performed for the SPARC cohort (NCT03493282). Comparative analyses and a meta-analysis with the interim SHINE cohort (NCT03507790; SHINE-A) followed by network analysis (weighted gene co-expression network analysis [WGCNA]) were used to understand the biological impact of CT1812.
Results: CT1812 pharmacodynamic biomarkers and biological pathways were identified that replicate across two clinical cohorts. The meta-analysis revealed novel candidate biomarkers linked to S2R biology and AD, and network analysis revealed treatment-associated networks driven by S2R. DISCUSSION: Early clinical validation of CT1812 candidate biomarkers replicating in independent cohorts strengthens the understanding of the biological impact of CT1812 in patients with AD, and supports CT1812's synaptoprotective mechanism of action and its continued clinical development.
Highlights: This exploratory proteomics study identified candidate biomarkers of CT1812 in SPARC (NCT03493282) Comparative analyses identified biomarkers replicating across trials/cohorts Two independent Ph2 trial cohorts (SPARC and interim SHINE [NCT03507790; SHINE-A]) were used in a meta-analysis Amyloid beta (Aβ) & synaptic biology impacted by CT1812 and volumetric magnetic resonance imaging (vMRI) treatment-related correlates emerge Network analyses revealed sigma-2 receptor (S2R)-interacting proteins that may be "drivers" of changes.
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http://dx.doi.org/10.1002/alz.14152 | DOI Listing |
Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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December 2024
College of Information Engineering, SuQian University, SuQian, 223800, China.
The safety and reliability of rotating machinery hinge significantly on the proper functioning of rolling bearings. In the last few years, there have been significant advances in the algorithms for intelligent fault diagnosis of bearings. However, the vibration signals collected by machines are inevitably affected by irrelevant noise because of the complex working environments of bearings.
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December 2024
Department of Internal Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Republic of Korea.
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Department for Evidence-based Medicine and Evaluation, University for Continuing Education Krems (Danube University Krems), Krems, Austria.
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December 2024
Academy of Medical Engineering and Translational Medicine (AMT), Tianjin University, Tianjin, China.
Generalization is central to motor learning. However, few studies are on the learning generalization of BCI-actuated supernumerary robotic finger (BCI-SRF) for human-machine interaction training, and no studies have explored its longitudinal neuroplasticity mechanisms. Here, 20 healthy right-handed participants were recruited and randomly assigned to BCI-SRF group or inborn finger group (Finger) for 4-week training and measured by novel SRF-finger opposition sequences and multimodal MRI.
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