Biomarkers are critically important for Alzheimer's Disease (AD) drug development. They have a role in patient diagnosis and trial eligibility, pharmacodynamic changes, safety, monitoring, disease modification, and target engagement. In AD clinical trials, biomarkers are vital in determining the treatment efficacy, reliability, and safety.
We created the Biomarker Observatory (BMO) to provide curated information on AD biomarkers for drug developers and clinical trialists. From the BMO, our aim is to explore and present the biomarkers that are currently being used in active AD intervention trials. We extract information from clinicaltrials.gov and annotate the eligibility, primary, secondary, and other biomarkers from each trial. Together with information from the Clinical Trial Observatory, we explore the imaging, fluid, and digital biomarkers being measured in active AD clinical trials, the trial characteristics, and influence of biomarkers on trials.
For active trials in the year 2024 (January 1 to December 30, 2024), we found that 57% of the clinical trials used a biomarker as an eligibility criterion for patient participation. Imaging was the most common type of marker, with magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) most used as eligibility and primary outcome biomarkers. Fluid biomarkers (CSF, blood, plasma, or serum) were used in 28% of AD clinical trials as eligibility biomarkers and in 12% of trials as a primary outcome measure. Seventeen AD clinical trials measured amyloid beta protein (Aβ) in fluid samples as a criterion for eligibility and 17 evaluated hyperphosphorylated tau (p-tau). As a primary outcome measure, 2 trials measured Aβ in fluid samples and 7 investigated p-tau levels. Total tau and neurofilament light chain (NfL) were included as primary outcome measures in 2 and 3 trials, respectively.
Our data demonstrate how imaging, fluid, and digital biomarkers are used in current AD clinical trials and the impact they have on trial design and outcomes. We provide current biomarker information to advance AD drug development, aiming to increase trial success rates and reducing the time it takes for new AD therapeutics to reach patients.
The tau PET imaging with 18F-flortacipir (18F-FTP) has focused interest in accurately tracking longitudinal tau changes in Alzheimer's disease [1]. Thus, minimizing variability is critical. Off-target signal has the potential to complicate interpretation of tau-PET imaging due to potential spillover or bleed-in effects, with increased effects seen in later stages of Alzheimer's due to cerebral atrophy and proximity of off-target areas to relevant cortical areas[2]. Previously, we demonstrated the effect of uptake period activity on 18F-FTP signal. With increasing recent interest in demographic factors that may affect off-target binding, we investigated the effect of age in extra-cerebral off-target signal in 18F-FTP PET imaging.
Standard 18F-FTP PET protocol was performed in 330 participants. Two independent readers measured tau uptake in predetermined off-target regions, including extraocular muscle, meninges, and occipital bone among others. Linear regression models assessed the relationship between participants’ age, sex, and tau uptake values (SUV and SUVr) (SUV = (Tissue radioactivity concentration / Injected dose) / Body weight & SUVr = SUV of target region/ SUV of reference region.)
Sex had a significant effect on off-target signal in most brain regions, with variable positive or negative correlation based on area. Notably, SUV in the eyeball-retina, occipital bone, upper skull meninges all showed significant positive correlation with sex, with ‘male’ status generally associated with lower SUV. The greatest effect of sex was observed in superior skull meninges, occipital bone, and internal carotid artery (p <0.001). Age showed minimally affected SUV and SUVr in off-target regions. SUVr values show a significant correlation with SUV values of upper skull meninges in sex. Cognitive status did not significantly affect off-target SUV.
We observed that sex significantly affected extra-brain off-target signal in 18F-FTP PET imaging, while age has minimal effect, adding to previous evidence of off-target binding within brain regions. Further evaluation is necessary to understand the age-related effects on off-target regions. As a result, the variability introduced by sex may pose challenges to studying tau accumulation.
Type II Diabetes Mellitus (T2DM) remains one of the strongest comorbidities associated with the development of AD. Use of fluid-based biomarker assays allows for quick, inexpensive, and accurate identification of those at high risk for developing AD or likely already have the disease. While AD and related dementias (ADRD) fluid biomarkers are well characterized during aging and cognitive impairment, little is known about the effects of T2DM on ADRD fluid biomarkers, especially those related to tau.
Participants with relevant demographic, diagnostic, and ADRD plasma biomarker data from the University of Pittsburgh's Alzheimer's disease Research Center were utilized for this study (N = 1,140). Participants were stratified by cognitive diagnosis [CogDx] (Cognitively unimpaired [CU], MCI, or AD) and diabetes (non-diabetic [ND] or T2DM). ADRD plasma biomarkers were analyzed using single molecule array (Simoa): Brain-derived (BD) tau, p-tau181, p-tau217, NfL, and GFAP. After a log2-transformation, ADRD plasma biomarkers were analyzed via 2-way ANCOVA with a Bonferroni correction while controlling for age.
Of the 1,140 included participants 150 (13.2%) were diagnosed with T2DM. Most participants were classified as AD (523, 45.9%) or MCI (305, 26.8%). There was no mean age difference between participants ± T2DM. There was a stepwise difference in age between CU<MCI<AD participants (p <0.001). 2-way ANCOVA analysis of plasma biomarkers: p-tau181, BDtau, NfL, and GFAP all increased stepwise from CU<MCI<AD, (p <0.001). GFAP (p <0.001) and NfL (p = 0.036) levels were also separately affected by diabetes and were lower in those with T2DM compared to NDs. Lastly, p-tau217 showed an interaction between CogDx and T2DM (p = 0.05), with a stepwise increase from CU to MCI to AD in ND, but similar levels between T2DM+CU and T2DM+MCI and a higher level in T2DM+AD than both groups.
All ADRD plasma biomarkers showed a clear, stepwise increase based on CogDx (CU<MCI<AD), recapitulating previous works. Novel data demonstrated an unanticipated decrease in plasma GFAP and NfL in those with T2DM. Lastly, p-tau217 was preferentially increased in participants with AD+T2DM vs. T2DM participants that were CU or with MCI. These novel findings require further scrutiny within this cohort and others.
In the TRAILBLAZER-ALZ 2 study (NCT04437511), tau pathology at screening was evaluated with flortaucipir Positron Emission Tomography (PET) with a combination of visual read (V) and quantitative (Q) standardized uptake value ratio (SUVr) approaches. In most cases, participants had an advanced Alzheimer's disease (AD) tau visual pattern (AD++) with an AD-signature weighted neocortical SUVr>1.1 (V++/Q+). A minority of participants presented other V/Q profiles, namely an AD++ visual read with an SUVr≤1.1 (V++/Q-) and a moderate AD tau pattern (AD+) with an SUVr>1.1 (V+/Q+). The objective of these analyses was to characterise these populations.
All available TRAILBLAZER-ALZ 2 placebo-treated early symptomatic AD participants were included. Baseline characteristics and progression on both clinical scales (Clinical Dementia Rating - Sum of Boxes [CDR-SB], integrated Alzheimer Disease Rating Scale [iADRS]) and biomarkers (p-tau217, glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL]) at Week 76 (using mixed model repeated measures methodology), of the V++/Q- and V+/Q+ groups were compared to each other and to the rest of the study population (V++/Q+).
The V++/Q- group comprised 15.7% (126/802) and the V+/Q+ group 2.9% (23/802) of the placebo-treated study population with characteristics as shown in the Table. At Week 76, all groups were at risk of clinical progression, although changes from baseline in CDR-SB and iADRS for the V++/Q- and V+/Q+ groups were less compared to the rest of the population (significantly different between the V++/Q- and V++/Q+ groups; p <0.0001 for both CDR-SB and iADRS) (Figure). Progression for both AD-specific and non-AD specific biomarker progression was similar across all groups.
The observation of V++/Q- and V+/Q+ participants being older, milder in AD pathology while at a similar clinical stage at screening compared to V++/Q+ participants may suggest the effect of age-related comorbidities. Participants in the V++/Q- and the V+/Q+ groups showed clinical/pathological progression, although not at the level of those in the V++/Q+ group.
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