# Project 2 > **NIH NIH U19** · MAYO CLINIC ROCHESTER · 2020 · $376,374 ## Abstract ABSTRACT – ARTFL LEFFTDS Longitudinal FTLD: Project 2 Improvements in understanding the biology of FTLD, combined with revolutionary advancements in drug development, have created new compounds that can alter the fundamental biological mechanisms that cause FTLD. FTLD is most commonly associated with either underlying tau (FTLD-tau) or TAR DNA binding protein 43 (FTLD-TDP) brain neuropathology and many new treatments that are now entering clinical trials target one or the other of these molecular pathologies. This creates a major challenge for designing clinical trials: how to measure the effects of these new molecularly-targeted therapies in clinically heterogeneous, symptomatic FTLD populations. The first goal of this project is to develop new clinical tools and surrogate endpoints that can measure disease progression in heterogeneous FTLD clinical populations. The second goal is to develop methods to stratify patients at the time of clinical trial enrollment to define populations with more predictable rates of change or responses to specific therapeutic strategies. We will develop optimized clinical, imaging and biomarker endpoints for symptomatic FTLD clinical trials that could include multiple clinical and genetic variants with a single molecular pathology (referred to as a basket trial design) or could be deployed in patients with a common phenotype (standard parallel design) to improve power to detect treatment effects. Longitudinal clinical, imaging and fluid biomarker data will be collected in a multicenter clinical trial-ready population representing the full clinical spectrum of FTLD, including both sporadic FTLD (n=600) and symptomatic f-FTLD (n=167) from the ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) consortium, which constitutes the core group of centers that will support recruitment for FTLD clinical trials in North America. We will also examine the impact of developing personalized outcomes in a trial by using each patient's baseline characteristics to predict which measures will decline over time, with a particular emphasis on maximizing what is most clinically meaningful to that patient. The specific aims are to: (1) identify the best clinical and MRI-based endpoints to measure efficacy in “basket design” clinical trials that enroll patients according to predicted underlying protein pathology, (2) develop trial enrichment strategies that combine multiple baseline characteristics to predict clinical change in FTLD, and (3) investigate inflammation as a potential late stage therapeutic target in symptomatic FTLD. ## Key facts - **NIH application ID:** 10017899 - **Project number:** 5U19AG063911-02 - **Recipient organization:** MAYO CLINIC ROCHESTER - **Principal Investigator:** ADAM L. BOXER - **Activity code:** U19 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $376,374 - **Award type:** 5 - **Project period:** — → — ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10017899 ## Citation > US National Institutes of Health, RePORTER application 10017899, Project 2 (5U19AG063911-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10017899. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*