Cited by 1Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchPharmacological Receptor Mechanisms and Effects

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Impact of zervimesine on the neuroinflammatory biomarker GFAP and related proteomic molecular correlates in plasma of participants from a phase 2 clinical trial in Alzheimer’s disease

Open access

Abstract

Background: Zervimesine (CT1812) is an investigational brain-penetrant small molecule modulator of the sigma-2 receptor (S2R/ TMEM97 ), currently in clinical development for the treatment of Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) that selectively prevents and displaces the binding of amyloid beta (Aβ) and α-synuclein oligomers from neuronal synapses. Given the mechanism of action, it was hypothesized that zervimesine might be more effective in patients with lower levels of AD pathology. Indeed, in the SHINE trial, a completed Phase 2, randomized, double-blind, clinical trial conducted in participants with AD, a robust, 95%, slowing of cognitive decline, as assessed via ADAS-Cog11, was observed in a pre-specified subgroup of participants with lesser AD pathology (i.e., low p-tau217 subgroup) compared to a 38% slowing in the overall modified intent-to-treat (mITT)) population. Methods: In SHINE, exploratory plasma biomarkers were assessed using both a targeted and an unbiased, proteomics discovery approach in plasma from participants at baseline and end of study. Treatment effects of zervimesine relative to placebo were assessed in both the mITT population and in a low p-tau217 subgroup, who entered the study with lower (< 1pg/ml) plasma p-tau217 concentrations. Plasma biomarkers Aβ40, Aβ42, GFAP, NfL and BD-tau were assessed using clinically validated targeted assays, along with untargeted TMT-mass spectrometry (MS)-based discovery proteomics followed by bioinformatic, pathway and correlation analyses. Results: Collectively, plasma biomarker findings in the low p-tau217 subgroup were more robust than in the mITT population. Levels of GFAP were significantly decreased and NfL, Aβ42 and Aβ40 levels trended towards a decrease with zervimesine compared to placebo. Proteomics analyses identified candidate pharmacodynamic biomarkers of zervimesine, and gene ontology and pathway analyses pointed to an impact on amyloid biology, trafficking, lipid metabolism, and immune response. Bioinformatics and correlation analyses with GFAP identified biomarkers that may reflect pathway engagement of S2R and/or decreased neuroinflammation. Conclusions: Exploratory plasma biomarker findings align with the degree of clinical benefit in SHINE mITT and low p-tau217 populations, and support future trial enrichment with patients with lower levels of pathology as defined by lower baseline plasma levels of p-tau217. Trial registration: July 20th, 2018 ClinicalTrials.gov Identifier NCT03507790 https://clinicaltrials.gov/study/NCT03507790 .

Overview

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TL;DR

In the SHINE Phase 2 trial, exploratory plasma biomarker and proteomic analyses showed that zervimesine treatment effects were more robust in participants with low baseline plasma p-tau217 (<1 pg/ml) than in the overall mITT population. In that low p-tau217 subgroup, plasma GFAP significantly decreased with zervimesine versus placebo, with trends toward decreases in Aβ42, Aβ40, and NfL.

Key findings

  • In the low p-tau217 subgroup, zervimesine significantly decreased plasma GFAP versus placebo (LS mean −28.35; SE 11.687; p = 0.0186), with trends (p ≤ 0.10) toward reductions in Aβ42, Aβ40, and NfL; no treatment effects or trends were observed in the high p-tau217 subgroup (N = 60).
  • In the mITT population, only plasma BD-tau showed a trend toward reduction versus placebo (p = 0.09); no treatment-related changes were observed in GFAP, NfL, Aβ42, or Aβ40, and no change was seen in Aβ42/40 ratio (LS mean 0.0019; SE 0.00148; p = 0.2048).
  • TMT-MS proteomics detected more than 2000 proteins in mITT plasma; 58 proteins were significantly differentially abundant with zervimesine (53 increased, 5 decreased; p ≤ 0.05), while 103 were differentially abundant in the low p-tau217 subgroup (75 increased, 28 decreased; p ≤ 0.05). Pathway analyses implicated amyloid biology, trafficking, lipid metabolism, and immune response.
  • In the low p-tau217 subgroup, 286 TMT-MS proteins correlated with plasma GFAP in zervimesine-treated participants; after removing 3 shared with placebo, 283 “Drug Selective” correlates remained, and 15 of these were also differentially abundant (zervimesine vs placebo, p ≤ 0.10), including GPX3 and CTSG.

Methods

  • SHINE (NCT03507790) was a completed international, multicenter, randomized, double-blind, placebo-controlled 36-week Phase 2 trial in adults aged 50–85 years with mild to moderate AD (MMSE 18–26); participants were randomized 1:1:1 to placebo, 100 mg, or 300 mg zervimesine orally once daily for 6 months. Plasma biomarker analyses included participants with baseline and 6-month plasma (mITT N = 117; low p-tau217 subgroup N = 57; high p-tau217 subgroup N = 60), with p-tau217 subgroups defined by baseline plasma p-tau217 below versus at/above the median of 1.0 pg/ml.
  • Targeted plasma biomarkers Aβ40, Aβ42, GFAP, and NfL were measured with the SIMOA Neuro4-Plex E Kit, and brain-derived tau with a SIMOA-based assay; change from baseline was calculated.
  • Untargeted discovery proteomics used TMT-MS on the first 57 treatment-compliant participants (n = 20 placebo, n = 37 pooled zervimesine) with baseline and 6-month plasma; low p-tau217 subgroup N = 24 (n = 8 placebo, n = 16 zervimesine). Differential abundance was assessed by ANOVA with unadjusted p ≤ 0.05, followed by GO, STRING, MetaCore pathway analyses, and Pearson correlation of protein change from baseline with plasma GFAP change from baseline in the low p-tau217 subgroup.

Limitations

  • The paper states limited sample size, with even smaller subgroups, which may affect differential abundance analysis and lead to false positives or negatives.
  • The paper states that proteomics differential abundance and correlation analyses used unadjusted p-values without controlling for multiple comparisons, increasing type 1 error risk; candidate biomarkers should be viewed with caution until replicated.
  • The paper states that the p-tau217 subgroup analysis was prespecified but not the primary analysis, and that plasma biomarkers may reflect peripheral changes rather than brain-relevant disease processes; replication in larger trials is warranted.

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Crossref · 10.1186/s13195-026-02025-4

Cites

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Figures

Fig. 1 Clinical trial design, robust canonical biomarker effects in low p-tau217 subgroup. A SHINE clinical trial design, and previously reported summary of clinical and CSF biomarker outcomes. Patients treated with zervimesine showed a slower cognitive decline (% slowing shown) compared to placebo in mITT, an effect that was more pronounced in the low p-tau217 subgroup. B AD plasma biomarker findings listing the LS mean (SE) change from placebo, 95% confidence interval (CI), and significance after 6 months treatment with zervimesine in the SHINE trial participants. Statistical significance of a decrease in GFAP (p ≤ 0.05, bolded in green) and positive trends for decreases in Aβ42, Aβ40 and NfL (​p ≤ 0.10, bolded in purple) were seen in the low p-tau217 subgroup (N = 69; size of population included in the below median (low) p-tau217 subgroup). None of these differences were significant compared to placebo in the mITT (N = 150; size of participants included in the trial) and in the high p-tau217 subgroup (N = 69; size of population included in the above median (high) p-tau217 subgroup). C Representative graphs showing the robust effect sizes observed across biomarkers measured in below median (low) p-tau217 subgroup (N = 57; actual number of participants included in the analysis)
Fig. 1 Clinical trial design, robust canonical biomarker effects in low p-tau217 subgroup. A SHINE clinical trial design, and previously reported summary of clinical and CSF biomarker outcomes. Patients treated with zervimesine showed a slower cognitive decline (% slowing shown) compared to placebo in mITT, an effect that was more pronounced in the low p-tau217 subgroup. B AD plasma biomarker findings listing the LS mean (SE) change from placebo, 95% confidence interval (CI), and significance after 6 months treatment with zervimesine in the SHINE trial participants. Statistical significance of a decrease in GFAP (p ≤ 0.05, bolded in green) and positive trends for decreases in Aβ42, Aβ40 and NfL (​p ≤ 0.10, bolded in purple) were seen in the low p-tau217 subgroup (N = 69; size of population included in the below median (low) p-tau217 subgroup). None of these differences were significant compared to placebo in the mITT (N = 150; size of participants included in the trial) and in the high p-tau217 subgroup (N = 69; size of population included in the above median (high) p-tau217 subgroup). C Representative graphs showing the robust effect sizes observed across biomarkers measured in below median (low) p-tau217 subgroup (N = 57; actual number of participants included in the analysis)CC BY · PubMed Central
Fig. 2 Analysis of differentially abundant proteins in zervimesine vs. placebo-treated patient plasma proteomes in mITT population. A Abundances of proteins measured using TMT-MS were compared between zervimesine and placebo-treated patient plasma after 6 months. Proteins that were significantly differentially abundant in zervimesine vs. placebo plasma proteomes are shown on the volcano plot to visualize directionality (58 proteins met significance criterion of p ≤ 0.05 for zervimesine vs. placebo; 5 decreased (upper left quadrant, green dots), 53 increased, (upper right quadrant, red dots)). Each colored dot corresponds to a protein, larger yellow circles indicate “AD Priority biomarkers”. Proteins of interest are indicated with black arrows. B Example box plots of proteins of interest demonstrate the log2 abundance and variance across individuals. Zervimesine vs. placebo log2 fold-change (FC) and p-values as indicated. C Top 25 most significant differential abundant proteins (zervimesine vs. placebo, p ≤ 0.05); in bold, “AD Priority biomarkers”. D STRING PPI map of the significantly (p ≤ 0.05) differentially abundant proteins (medium confidence threshold 0.4; PPI enrichment p-value = 6.31e-11). Colored nodes refer to GO Cellular Component as indicated in key. E-F Pathway analyses via STRING (sorted by FDR) (E) and MetaCore (sorted by p-value) (F) of differentially abundant proteins in plasma proteome show vesicle, transport, immune response and lipoprotein metabolism to be most significantly altered pathways
Fig. 2 Analysis of differentially abundant proteins in zervimesine vs. placebo-treated patient plasma proteomes in mITT population. A Abundances of proteins measured using TMT-MS were compared between zervimesine and placebo-treated patient plasma after 6 months. Proteins that were significantly differentially abundant in zervimesine vs. placebo plasma proteomes are shown on the volcano plot to visualize directionality (58 proteins met significance criterion of p ≤ 0.05 for zervimesine vs. placebo; 5 decreased (upper left quadrant, green dots), 53 increased, (upper right quadrant, red dots)). Each colored dot corresponds to a protein, larger yellow circles indicate “AD Priority biomarkers”. Proteins of interest are indicated with black arrows. B Example box plots of proteins of interest demonstrate the log2 abundance and variance across individuals. Zervimesine vs. placebo log2 fold-change (FC) and p-values as indicated. C Top 25 most significant differential abundant proteins (zervimesine vs. placebo, p ≤ 0.05); in bold, “AD Priority biomarkers”. D STRING PPI map of the significantly (p ≤ 0.05) differentially abundant proteins (medium confidence threshold 0.4; PPI enrichment p-value = 6.31e-11). Colored nodes refer to GO Cellular Component as indicated in key. E-F Pathway analyses via STRING (sorted by FDR) (E) and MetaCore (sorted by p-value) (F) of differentially abundant proteins in plasma proteome show vesicle, transport, immune response and lipoprotein metabolism to be most significantly altered pathwaysCC BY · PubMed Central
Fig. 3 Analysis of differentially abundant proteins in zervimesine- and placebo-treated patient plasma proteomes in the low p-tau217 subgroup. A Abundances of proteins measured using TMT-MS were compared between zervimesine-treated and placebo-treated patient plasma after 6 months in the low p-tau217 subgroup. Proteins that were significantly differentially abundant in zervimesine vs. placebo plasma proteomes are shown on the volcano plot to visualize directionality (103 proteins met significance of p ≤ 0.05 for zervimesine vs. placebo, in the low p-tau217 group; 28 decreased (upper left quadrant, green dots), 75 increased, (upper right quadrant, red dots)). Each colored dot corresponds to a protein, larger yellow circles indicate “AD Priority biomarkers”; proteins of interest are indicated with black arrows. B STRING PPI map of the significantly (p ≤ 0.05) differentially abundant proteins in the low p-tau217 subgroup (medium confidence threshold 0.4; unconnected proteins not shown; PPI enrichment p-value = 1.41e− 12). Colored nodes refer to GO Biological Process Terms as indicated in key. C Pathway analyses using MetaCore (sorted by p-value) of differentially abundant proteins at p ≤ 0.05 in plasma proteome in the low p-tau217 group show transport, immune response and apoptosis and survival to be most significantly altered pathways
Fig. 3 Analysis of differentially abundant proteins in zervimesine- and placebo-treated patient plasma proteomes in the low p-tau217 subgroup. A Abundances of proteins measured using TMT-MS were compared between zervimesine-treated and placebo-treated patient plasma after 6 months in the low p-tau217 subgroup. Proteins that were significantly differentially abundant in zervimesine vs. placebo plasma proteomes are shown on the volcano plot to visualize directionality (103 proteins met significance of p ≤ 0.05 for zervimesine vs. placebo, in the low p-tau217 group; 28 decreased (upper left quadrant, green dots), 75 increased, (upper right quadrant, red dots)). Each colored dot corresponds to a protein, larger yellow circles indicate “AD Priority biomarkers”; proteins of interest are indicated with black arrows. B STRING PPI map of the significantly (p ≤ 0.05) differentially abundant proteins in the low p-tau217 subgroup (medium confidence threshold 0.4; unconnected proteins not shown; PPI enrichment p-value = 1.41e− 12). Colored nodes refer to GO Biological Process Terms as indicated in key. C Pathway analyses using MetaCore (sorted by p-value) of differentially abundant proteins at p ≤ 0.05 in plasma proteome in the low p-tau217 group show transport, immune response and apoptosis and survival to be most significantly altered pathwaysCC BY · PubMed Central
Fig. 4 Proteomic correlates of plasma GFAP in low p-tau217 subgroup. A Proteomic change from baseline (CFB) abundances correlated with CFB plasma GFAP levels were identified in the low p-tau217 subgroup based off treatment, Placebo treated “Placebo only” (purple circle, 25 total correlates) and drug treated “Drug only” (orange circle, 286 correlates), via Pearson correlation analysis. Correlates identified irrespective of treatment (dark orange overlap, 3 correlates) were removed from “Drug only” plasma GFAP correlates to facilitate analysis of correlates that were treatment (drug)-selective (orange semicircle, 283 correlates). B The 283 “Drug Selective” protein correlates were analyzed using STRING and MetaCore. Tables display top-ranked Reactome terms identified by STRING (top panel; sorted by FDR) and MetaCore pathways (bottom panel; sorted by p-value). Proteins associated with STRING included RAB10, RAB14, RAB7A for “Vesicle-mediated transport” and HSP90AA1, ITGB1, LAMP1 and IGF2R for “Immune System”. C Of the 283 “Drug Selective” proteins identified that are correlated with plasma GFAP levels, 15 were determined to also be differentially abundant (zervimesine vs. placebo, p ≤ 0.10 in the low p-tau217 subgroup). D Scatter plots of two representative proteins of the 15, GPX3 and CTSG, show favorable correlation of GPX3 and CTSG CFB log2 abundance levels with plasma CFB GFAP levels across individual zervimesine-treated patients
Fig. 4 Proteomic correlates of plasma GFAP in low p-tau217 subgroup. A Proteomic change from baseline (CFB) abundances correlated with CFB plasma GFAP levels were identified in the low p-tau217 subgroup based off treatment, Placebo treated “Placebo only” (purple circle, 25 total correlates) and drug treated “Drug only” (orange circle, 286 correlates), via Pearson correlation analysis. Correlates identified irrespective of treatment (dark orange overlap, 3 correlates) were removed from “Drug only” plasma GFAP correlates to facilitate analysis of correlates that were treatment (drug)-selective (orange semicircle, 283 correlates). B The 283 “Drug Selective” protein correlates were analyzed using STRING and MetaCore. Tables display top-ranked Reactome terms identified by STRING (top panel; sorted by FDR) and MetaCore pathways (bottom panel; sorted by p-value). Proteins associated with STRING included RAB10, RAB14, RAB7A for “Vesicle-mediated transport” and HSP90AA1, ITGB1, LAMP1 and IGF2R for “Immune System”. C Of the 283 “Drug Selective” proteins identified that are correlated with plasma GFAP levels, 15 were determined to also be differentially abundant (zervimesine vs. placebo, p ≤ 0.10 in the low p-tau217 subgroup). D Scatter plots of two representative proteins of the 15, GPX3 and CTSG, show favorable correlation of GPX3 and CTSG CFB log2 abundance levels with plasma CFB GFAP levels across individual zervimesine-treated patientsCC BY · PubMed Central
Fig. 5 “Drug selective” correlates of plasma GFAP levels in the low p-tau217 subgroup relate to S2R biology. S2R complex components (indicated by red ovals) were manually added to the list of 283 “drug selective” correlates for STRING protein-protein interaction (PPI) mapping. A PPI map shows only the “Drug Selective” correlates that were found to be interact with S2R components (medium confidence threshold 0.4). B Table of the 21 correlates with plasma GFAP levels found to interact with the S2R complex components and their known biological functions relevant to AD or the zervimesine mechanism of action through S2R
Fig. 5 “Drug selective” correlates of plasma GFAP levels in the low p-tau217 subgroup relate to S2R biology. S2R complex components (indicated by red ovals) were manually added to the list of 283 “drug selective” correlates for STRING protein-protein interaction (PPI) mapping. A PPI map shows only the “Drug Selective” correlates that were found to be interact with S2R components (medium confidence threshold 0.4). B Table of the 21 correlates with plasma GFAP levels found to interact with the S2R complex components and their known biological functions relevant to AD or the zervimesine mechanism of action through S2RCC BY · PubMed Central
Fig. 6 Summary of candidate biomarkers of zervimesine related to AD and neuroinflammation. A. Schema to summarize candidate biomarkers of pathway/target engagement related to zervimesine mechanism of action through S2R. Zervimesine (light green) binds S2R/TMEM97 (purple), which is localized on synapses in a complex with the oligomer receptor (prion protein; PRNP) the LDL receptor (LDLR) and PGRMC1. Binding of zervimesine to S2R induces a conformational change in the oligomer receptor complex (blue), disengaging the Aβ oligomers (red) from the synapse. Dark yellow and blue allows indicate directionality for differentially abundant proteins in the low p-tau217 subgroup and mITT population, respectively; two-color arrow indicates differential abundant proteins in both groups, “*”=protein is correlated with GFAP plasma levels. B. Canonical biomarkers (pink font) found to be trending (NfL, Aβ40, Aβ42, brain-derived tau) or affected (GFAP) with zervimesine treatment using targeted assays in either the mITT (blue arrow) or low p-tau217 group (yellow arrow; all decreased) (Fig. 1B schema) in relation to cell type and amyloid pathology (Aβ oligomers and plaques). In the left table, biomarker correlates with GFAP plasma levels in low p-tau217 subgroup (p ≤ 0.05) (left table) and correlates that are differentially abundant (p ≤ 0.05), sorted by p-value, along with pharmacodynamic biomarkers related to immune function identified in the differential abundance analyses in the mITT population and/or p-tau217 subgroup (right table; “ns”= nonsignificant; thus, “-” no Log2FC reported
Fig. 6 Summary of candidate biomarkers of zervimesine related to AD and neuroinflammation. A. Schema to summarize candidate biomarkers of pathway/target engagement related to zervimesine mechanism of action through S2R. Zervimesine (light green) binds S2R/TMEM97 (purple), which is localized on synapses in a complex with the oligomer receptor (prion protein; PRNP) the LDL receptor (LDLR) and PGRMC1. Binding of zervimesine to S2R induces a conformational change in the oligomer receptor complex (blue), disengaging the Aβ oligomers (red) from the synapse. Dark yellow and blue allows indicate directionality for differentially abundant proteins in the low p-tau217 subgroup and mITT population, respectively; two-color arrow indicates differential abundant proteins in both groups, “*”=protein is correlated with GFAP plasma levels. B. Canonical biomarkers (pink font) found to be trending (NfL, Aβ40, Aβ42, brain-derived tau) or affected (GFAP) with zervimesine treatment using targeted assays in either the mITT (blue arrow) or low p-tau217 group (yellow arrow; all decreased) (Fig. 1B schema) in relation to cell type and amyloid pathology (Aβ oligomers and plaques). In the left table, biomarker correlates with GFAP plasma levels in low p-tau217 subgroup (p ≤ 0.05) (left table) and correlates that are differentially abundant (p ≤ 0.05), sorted by p-value, along with pharmacodynamic biomarkers related to immune function identified in the differential abundance analyses in the mITT population and/or p-tau217 subgroup (right table; “ns”= nonsignificant; thus, “-” no Log2FC reportedCC BY · PubMed Central

Verification

Claims the paper makes

38 Own result · 20 Own interpretation · 19 Not checked yet · 13 Partly supported · 7 Own method · 4 No full text of the sources · 4 No basis given · 2 Supported · accuracy not yet measured

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  • Probably not a substantial claim. 19
  • It may state two separate claims as one. 28
  • The quote only partly states this claim. 3
38 of 38
  • The paper relies on this without support.

    Zervimesine is a modulator of the sigma-2 receptor (S2R/TMEM97).

    “Zervimesine (CT1812) is an orally administered small molecule modulator of the sigma-2 receptor (S2R/TMEM97) in clinical development for treatment of Alzheimer’s disease (AD; NCT03507790; NCT05531656) and dementia with Lewy bodies (DLB; NCT05225415).”
  • The paper relies on this without support.

    GFAP is a neuroinflammatory biomarker.

    “the neuroinflammatory marker GFAP”
  • The paper relies on this without support.

    NfL is a recognized biomarker of neurodegeneration for multiple neurodegenerative disorders, including AD, in which CSF levels are elevated relative to healthy non-demented control.

    “NfL is a recognized biomarker of neurodegeneration for multiple neurodegenerative disorders, including AD, in which CSF levels are elevated relative to healthy non-demented control.”
  • The paper relies on this without support.

    HSPA5 and HSP90AB1 are members of the heat shock protein family and as chaperone proteins are involved in controlling protein folding and ER homeostasis.

    “HSPA5, HSP90AB1are both members of the heat shock protein family and as chaperone proteins are involved in controlling protein folding and ER homeostasis.”
  • The paper relies on this without support.

    Elevated secreted GFAP levels is a well-established marker of astrogliosis, detectable in plasma due to blood-brain-barrier disruption, and elevated in plasma of patients with AD.

    “Elevated secreted GFAP levels is a well-established marker of astrogliosis, detectable in plasma due to blood-brain-barrier disruption, and elevated in plasma of patients with AD.”
5 of 5

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1 of 1

Citations

Cites

Show all 44 references

Research works printed but not linked: 7

  1. Ashton NJ, Brum WS, Molfetta GD, Benedet AL, Arslan B, Jonaitis E, et al. Diagnostic accuracy of a plasma phosphorylated tau 217 immunoassay for Alzheimer disease pathology. JAMA Neurol. 2024;81:255–63. https://doi.org/10.1001/jamaneurol.2023.5319. · DOI · Paper page
  2. Sperling RA, Selkoe DJ, Reyderman L, Cao Y, van Dyck CH. Does the Current Evidence Base Support Lecanemab Continued Dosing for Early Alzheimer’s Disease? [Perspectives Session]. Alzheimer’s Assoc Int Conf. Philadelphia, PA; 2024.
  3. Cognition Therapeutics. Cognition Therapeutics Study of Zervimesine (CT1812) in Early Alzheimer’s Disease Surpasses 50% Enrollment Target [Press Release]. 2025 Jul 1; https://ir.cogrx.com/press_releases/cognition-therapeutics-study-of-zervimesine-ct1812-in-early-alzheimers-disease-surpasses-50-enrollment-target/.
  4. Cognition Therapeutics. Cognition Therapeutics’ Analysis Correlates Biomarker Changes with Cognitive Benefit in Alzheimer’s Population [Press Release]. 2024 Nov 25; https://ir.cogrx.com/press_releases/cognition-therapeutics-analysis-correlates-biomarker-changes-with-cognitive-benefit-in-alzheimers-population/.
  5. Cognition Therapeutics. Cognition Therapeutics presents phase 3 plan for zervimesine (CT1812) in Alzheimer’s disease at Clinical Trials on Alzheimer’s Disease (CTAD) conference. [Press Release]. 2025 Dec 1; https://ir.cogrx.com/press_releases/cognition-therapeutics-presents-phase-3-plan-for-zervimesine-ct1812-in-alzheimers-disease-at-clinical-trials-on-alzheimers-disease-ctad-conference/.
  6. Lilly. Results from Lilly’s Landmark Phase 3 Trial of Donanemab Presented at Alzheimer’s Association Conference and Published in JAMA [Press Release]. 2023 Jul 17; https://investor.lilly.com/news-releases/news-release-details/results-lillys-landmark-phase-3-trial-donanemab-presented.
  7. Eisai. New Clinical Data Demonstrates Three Years of Continuous Treatment with Dual-Acting LEQEMBI® (lecanemab-irmb) Continues to Significantly Benefit Early Alzheimer’s Disease Patients Presented at AAIC 2024. [Press Release]. 2024. https://www.eisai.com/news/2024/news202456.html.

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Metadata

Authors
Di Caro, V., Cho, E., Thiel, J., Lizama, B. N., Koel-Simmelink, M. J. A., Pandey, K., Duong, D., Seyfried, N. T., Grundman, M., Teunissen, C. E., Zetterberg, H., Blennow, K., Caggiano, A. O., & Hamby, M. E.
Affiliations
  • Cognition Therapeutics (United States) (US)
  • Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
  • Emory University (US)
  • University of California San Diego (US)
  • University of Wisconsin–Madison (US)
  • Sahlgrenska University Hospital (SE)
Corresponding author
Hamby, Mary E.
Venue
Alzheimer's Research & Therapy
Published
2026-04-06
Volume
18
Issue
1
ISSN
1758-9193 (ISSN-L)
OpenAlex
W7151006868
Cited by
1
References
44
Citations by year
2026: 1
FWCI
1.66
Type
journal article
Language
en
Open access
Locations
  • Alzheimer s Research & Therapy (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • Pure Amsterdam UMC (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Institute on Aging (1R01AG058660)
  • Alzheimer's Drug Discovery Foundation
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacological Receptor Mechanisms and Effects
Keywords
Alzheimer's disease, sigma-2 receptor, TMEM97, neuroinflammation, glial fibrillary acidic protein, plasma biomarkers, phosphorylated tau, amyloid-beta, neurofilament light chain, pharmacodynamic biomarkers, dementia with Lewy bodies, amyloid-beta binding, lipid metabolism, immune response, SHINE trial
MeSH terms
Neuroinflammatory Diseases, Aged, Alzheimer Disease, Double-Blind Method, Female, Glial Fibrillary Acidic Protein, Humans, Male, Biomarkers, Amyloid beta-Peptides, Proteomics

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