At the second annual Holloway Summit, held November 30 to December 1 in Miami, frontotemporal dementia researchers showcased the current state of knowledge in finding biomarkers that identify different underlying pathologies of the disease. For broad-based, routine clinical applications, fluid biomarkers will be crucial. In this area, researchers now have candidates that could distinguish between tau and TDP-43 deposits (see Part 1 of this series).
- Tau tracer APN-1607 binds all types of fibrils, distinguishes tauopathies by uptake pattern.
- PET tracer for TDP-43 deposits is entering trials.
- FDG-PET scans analyzed by machine learning can discriminate neurodegenerative diseases.
Their other ask is to come up with reliable imaging biomarkers for research and some narrower clinical applications. Here too, attendees had recent developments to highlight. PET tracers for both pathologies are in clinical trials, while the old-fashioned FDG-PET scan has been given a boost into the 21st-century courtesy of machine learning algorithms. With this enhancement, such scans can differentiate multiple neurodegenerative diseases.
Even so, attendees agreed that more is needed to power FTD research. In particular, new biomarkers should be integrated into natural history studies to generate detailed biologic staging schemes. This would put FTD closer to the standard set by Alzheimer’s and Parkinson’s research, and enable disease-modifying trials.
Telltale Uptake. Different brain structures light up with tau tracer APN-1607 in CBD (left), PSP (middle), and Pick’s disease (right). [Courtesy of Tagai et al., Neuron.]
One Tau Tracer to Bind Them All?
Researchers have made progress on PET for each of the two main FTD proteopathies. In Miami, Brad Navia of Aprinoia Therapeutics showed data on the company’s tau tracer APN-1607. It is one of two tracers, along with Life Molecular Imaging’s PI-2620, which detects 4R fibrils, and its uptake correlates with disease severity in PSP patients (Mar 2020 conference news).
APN-1607 binds all types of tau fibrils, but it lights up distinct areas of the brain in different tauopathies, Navia noted. For example, in PSP the signal emanates from deep brain regions, whereas in AD it is most prominent in the temporal cortex. These patterns could help determine which pathology underlies a broad clinical syndrome such as bvFTD, Navia said. He showed APN-1607 scans of four bvFTD patients in whom one had more cortical uptake, suggesting a 3R tauopathy like Pick’s disease, and another had primarily subcortical uptake, suggesting a 4R tauopathy. A third had an AD-like pattern, and the fourth had no tracer uptake, potentially indicating the presence of another pathology such as TDP-43 (image below).
Thus far, Aprinoia has scanned about 400 people with PSP and 50 MAPT mutation carriers, most of whom are still living and being followed. APN-1607 distinguishes PSP cases from controls with 94 and 96 percent sensitivity and specificity, respectively, Navia said. Unlike some tau tracers, APN-1607 does not bind off-target to monoamine oxidase. In addition, autopsy studies have confirmed that the PET signal matches tau deposits in PSP, CBD, and Pick’s disease brains (Tagai et al., 2021). Navia said Aprinoia will start a Phase 3 registration study for APN-1607’s use in PSP in 2024.
A TDP-43 Tracer on the Horizon?
In Miami, Navia also reminded the audience of AC Immune’s nascent TDP-43 PET tracer, ACI-19278. This tracer sticks to TDP-43 deposits in FTLD brain sections with 15 nM affinity, with little binding to Aβ and α-synuclein deposits, according to data AC Immune had presented at the 2023 AD/PD conference in Gothenberg, Sweden. Among the different known varieties of TDP-43 fibrils, “Type A” fibrils appear to have had the highest affinity for ACI-19278, Navia said. These occur in FTD brains with GRN mutations, in cases of limbic-predominant age-related TDP-43 encephalopathy (LATE), and as a co-pathology in AD (Aug 2023 news).
At AD/PD, AC Immune had also shown ACI-19278 binding TDP-43 Type B fibrils, which are present in amyotrophic lateral sclerosis and some FTD cases (Dec 2021 news). In nonhuman primates, ACI-19278 entered the brain within minutes and washed out within an hour, making it suitable for live imaging. A clinical trial will start in the second quarter of 2024.
FDG-PET as Differential Diagnostic
With most FTD biomarkers still in early development stages, could an existing technology fill the gap? In Miami, David Jones of the Mayo Clinic in Rochester, Minnesota, made a case for using machine learning to distinguish dementias based on FDG-PET scans. Because the FDG-PET signal falls in brain regions with little metabolic activity, it can flag areas of poor health or degeneration.
The Mayo Clinic developed a web-based application, StateViewer, and trained it on 3,000 PET scans to find patterns representing different diseases. Next, StateViewer was tested on scans from 304 people with AD, 151 with dementia with Lewy bodies, 102 PSP, 97 bvFTD, 77 semantic and 106 logopenic variant primary progressive aphasia, 75 posterior cortical atrophy, 38 semantic dementia, 27 CBD, and 1,706 healthy controls. In this study, the app’s diagnostic accuracy varied from a low of 0.90 for bvFTD to a high of 0.99 for semantic dementia. An earlier version of these data, comprising fewer cases, was presented at the 2022 AAIC in Amsterdam (Barnard et al., 2022).
How does machine learning improve on visual reads? Jones said StateViewer integrates global patterns of change, which are difficult for the human eye to pick out. For example, DLB and PCA look similar to the human eye on FDG scans. Both have the so-called “cingulate island” sign, i.e., a sparing of metabolism in the cingulate relative to dampening in the surrounding precuneus and cuneus. StateViewer easily distinguishes the two diseases based on frontal cortex activity, which is down in the former and up in the latter, Jones said.
Some Holloway attendees were interested in following up on how machine learning can improve diagnosis, and Jones said the software will be widely available soon.
Despite some progress, much more is needed. Billy Dunn, who left the U.S. Food and Drug Administration in February 2023 and is now on the board of Prothena Biosciences, believes the FTD field needs to move toward a biologic definition of disease with a staging system, such as AD has. To do this, promising biomarkers will have to be studied in observational cohorts to find out how they change over the course of the disease, similar to the ADNI and DIAN studies in AD and PPMI in Parkinson’s. In this way, biomarkers will become able to track progression or predict outcomes. Lacking such data, the current batch of markers will be useful as enrollment criteria to select participants who have the pathology being studied, Dunn said. Some such cohorts are in place, e.g. GENFI and ALLFTD, but FTD biomarkers for them are still emerging. Observational FTD cohorts also need more participants and, at the summit, extensive discussion revolved around ways to increase recruitment.
Other talks described large institutional programs, such as the National ALS Biorepository, the CReATe Consortium funded by NIH, and the Bluefield Project to Cure FTD (Mar 2021 news), that seek to accelerate research by providing biological samples, tools, and funding.
Attendees left the summit charged up. Olivier Piguet at the University of Sydney, paraphrasing a previous line from Leonard Petrucelli at the Mayo Clinic in Jacksonville, Florida, said, “A few years ago we were crawling. Now we’re walking. Soon we may be running.”—Madolyn Bowman Rogers
- Second Holloway Summit Showcases Intense Search for FTD Biomarkers
- Primary Tauopathies Get New PET Ligands
- In Frontotemporal Lobar Dementia, TDP-43 Snaps into a Chevron Shape
- Double Spiral Sets TDP-43 Apart from Other Amyloids
- Cohorts Band Together to Get Global FTD Trials Going
- Tagai K, Ono M, Kubota M, Kitamura S, Takahata K, Seki C, Takado Y, Shinotoh H, Sano Y, Yamamoto Y, Matsuoka K, Takuwa H, Shimojo M, Takahashi M, Kawamura K, Kikuchi T, Okada M, Akiyama H, Suzuki H, Onaya M, Takeda T, Arai K, Arai N, Araki N, Saito Y, Trojanowski JQ, Lee VM, Mishra SK, Yamaguchi Y, Kimura Y, Ichise M, Tomita Y, Zhang MR, Suhara T, Shigeta M, Sahara N, Higuchi M, Shimada H. High-Contrast In Vivo Imaging of Tau Pathologies in Alzheimer's and Non-Alzheimer's Disease Tauopathies. Neuron. 2021 Jan 6;109(1):42-58.e8. Epub 2020 Oct 29 PubMed.