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Item A framework for translating tauopathy therapeutics: Drug discovery to clinical trials(Wiley, 2024) Feldman, Howard H.; Cummings, Jeffrey L.; Boxer, Adam L.; Staffaroni, Adam M.; Knopman, David S.; Sukoff Rizzo, Stacey J.; Territo, Paul R.; Arnold, Steven E.; Ballard, Clive; Beher, Dirk; Boeve, Bradley F.; Dacks, Penny A.; Diaz, Kristophe; Ewen, Colin; Fiske, Brian; Gonzalez, M. Isabel; Harris, Glenn A.; Hoffman, Beth J.; Martinez, Terina N.; McDade, Eric; Nisenbaum, Laura K.; Palma, Jose-Alberto; Quintana, Melanie; Rabinovici, Gil D.; Rohrer, Jonathan D.; Rosen, Howard J.; Troyer, Matthew D.; Kim, Doo Yeon; Tanzi, Rudolph E.; Zetterberg, Henrik; Ziogas, Nick K.; May, Patrick C.; Rommel, Amy; Medicine, School of MedicineThe tauopathies are defined by pathological tau protein aggregates within a spectrum of clinically heterogeneous neurodegenerative diseases. The primary tauopathies meet the definition of rare diseases in the United States. There is no approved treatment for primary tauopathies. In this context, designing the most efficient development programs to translate promising targets and treatments from preclinical studies to early-phase clinical trials is vital. In September 2022, the Rainwater Charitable Foundation convened an international expert workshop focused on the translation of tauopathy therapeutics through early-phase trials. Our report on the workshop recommends a framework for principled drug development and a companion lexicon to facilitate communication focusing on reproducibility and achieving common elements. Topics include the selection of targets, drugs, biomarkers, participants, and study designs. The maturation of pharmacodynamic biomarkers to demonstrate target engagement and surrogate disease biomarkers is a crucial unmet need. HIGHLIGHTS: Experts provided a framework to translate therapeutics (discovery to clinical trials). Experts focused on the "5 Rights" (target, drug, biomarker, participants, trial). Current research on frontotemporal degeneration, progressive supranuclear palsy, and corticobasal syndrome therapeutics includes 32 trials (37% on biologics) Tau therapeutics are being tested in Alzheimer's disease; primary tauopathies have a large unmet need.Item Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease(Elsevier, 2020) Dincer, Aylin; Gordon, Brian A.; Hari-Raj, Amrita; Keefe, Sarah J.; Flores, Shaney; McKay, Nicole S.; Paulick, Angela M.; Shady Lewis, Kristine E.; Feldman, Rebecca L.; Hornbeck, Russ C.; Allegri, Ricardo; Ances, Beau M.; Berman, Sarah B.; Brickman, Adam M.; Brooks, William S.; Cash, David M.; Chhatwal, Jasmeer P.; Farlow, Martin R.; la Fougère, Christian; Fox, Nick C.; Fulham, Michael J.; Jack, Clifford R., Jr.; Joseph-Mathurin, Nelly; Karch, Celeste M.; Lee, Athene; Levin, Johannes; Masters, Colin L.; McDade, Eric M.; Oh, Hwamee; Perrin, Richard J.; Raji, Cyrus; Salloway, Stephen P.; Schofield, Peter R.; Su, Yi; Villemagne, Victor L.; Wang, Qing; Weiner, Michael W.; Xiong, Chengjie; Yakushev, Igor; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.; Neurology, School of MedicineDefining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Item Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging(Wiley, 2025) Jelescu, Ileana O.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea; Jeurissen, Ben; Verhoye, Marleen; Frydman, Lucio; van de Looij, Yohan; Hike, David; Dunn, Jeff F.; Miller, Karla; Landman, Bennett A.; Shemesh, Noam; Anderson, Adam; McKinnon, Emilie; Farquharson, Shawna; Dell'Acqua, Flavio; Pierpaoli, Carlo; Drobnjak, Ivana; Leemans, Alexander; Harkins, Kevin D.; Descoteaux, Maxime; Xu, Duan; Huang, Hao; Santin, Mathieu D.; Grant, Samuel C.; Obenaus, Andre; Kim, Gene S.; Wu, Dan; Le Bihan, Denis; Blackband, Stephen J.; Ciobanu, Luisa; Fieremans, Els; Bai, Ruiliang; Leergaard, Trygve B.; Zhang, Jiangyang; Dyrby, Tim B.; Johnson, G. Allan; Cohen-Adad, Julien; Budde, Matthew D.; Schilling, Kurt G.; Neurology, School of MedicineSmall-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected considerations and recommendations from the diffusion community on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We, then, give recommendations for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including preprocessing, model-fitting, and tractography. Finally, we provide an online resource that lists publicly available preclinical dMRI datasets and software packages to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. Although we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Item Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2-Ex vivo imaging: Added value and acquisition(Wiley, 2025) Schilling, Kurt G.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Howard, Amy F. D.; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea; Jeurissen, Ben; Verhoye, Marleen; Frydman, Lucio; van de Looij, Yohan; Hike, David; Dunn, Jeff F.; Miller, Karla; Landman, Bennett A.; Shemesh, Noam; Anderson, Adam; McKinnon, Emilie; Farquharson, Shawna; Dell'Acqua, Flavio; Pierpaoli, Carlo; Drobnjak, Ivana; Leemans, Alexander; Harkins, Kevin D.; Descoteaux, Maxime; Xu, Duan; Huang, Hao; Santin, Mathieu D.; Grant, Samuel C.; Obenaus, Andre; Kim, Gene S.; Wu, Dan; Le Bihan, Denis; Blackband, Stephen J.; Ciobanu, Luisa; Fieremans, Els; Bai, Ruiliang; Leergaard, Trygve B.; Zhang, Jiangyang; Dyrby, Tim B.; Johnson, G. Allan; Cohen-Adad, Julien; Budde, Matthew D.; Jelescu, Ileana O.; Neurology, School of MedicineThe value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher SNR and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents "Part 2" of a three-part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge.Item Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3-Ex vivo imaging: Data processing, comparisons with microscopy, and tractography(Wiley, 2025) Schilling, Kurt G.; Howard, Amy F. D.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Barrett, Rachel L. C.; Aggarwal, Manisha; Michielse, Stijn; Nasrallah, Fatima; Syeda, Warda; Wang, Nian; Veraart, Jelle; Roebroeck, Alard; Bagdasarian, Andrew F.; Eichner, Cornelius; Sepehrband, Farshid; Zimmermann, Jan; Soustelle, Lucas; Bowman, Christien; Tendler, Benjamin C.; Hertanu, Andreea; Jeurissen, Ben; Verhoye, Marleen; Frydman, Lucio; van de Looij, Yohan; Hike, David; Dunn, Jeff F.; Miller, Karla; Landman, Bennett A.; Shemesh, Noam; Anderson, Adam; McKinnon, Emilie; Farquharson, Shawna; Dell'Acqua, Flavio; Pierpaoli, Carlo; Drobnjak, Ivana; Leemans, Alexander; Harkins, Kevin D.; Descoteaux, Maxime; Xu, Duan; Huang, Hao; Santin, Mathieu D.; Grant, Samuel C.; Obenaus, Andre; Kim, Gene S.; Wu, Dan; Le Bihan, Denis; Blackband, Stephen J.; Ciobanu, Luisa; Fieremans, Els; Bai, Ruiliang; Leergaard, Trygve B.; Zhang, Jiangyang; Dyrby, Tim B.; Johnson, G. Allan; Cohen-Adad, Julien; Budde, Matthew D.; Jelescu, Ileana O.; Neurology, School of MedicinePreclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high SNR images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a three-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing, and comparisons with microscopy. In each section, we attempt to provide guidelines and recommendations but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing and point toward open-source software and databases specific to small animal and ex vivo imaging.Item Implementation of Subjective Cognitive Decline criteria in research studies(Elsevier, 2017-03) Molinuevo, José L; Rabin, Laura A.; Amariglio, Rebecca; Buckley, Rachel; Dubois, Bruno; Ellis, Kathryn A.; Ewers, Michael; Hampel, Harald; Klöppel, Stefan; Rami, Lorena; Reisberg, Barry; Saykin, Andrew J.; Sikkes, Sietske; Smart, Colette M.; Snitz, Beth E.; Sperling, Reisa; van der Flier, Wiesje M.; Wagner, Michael; Jessen, Frank; Radiology and Imaging Sciences, School of MedicineINTRODUCTION Subjective Cognitive Decline (SCD) manifesting prior to clinical impairment could serve as a target population for early intervention trials in Alzheimer’s disease (AD). A working group, the Subjective Cognitive Decline Initiative (SCD-I), published SCD research criteria in the context of preclinical AD. To successfully apply them, a number of issues regarding assessment and implementation of SCD needed to be addressed. METHODS Members of the SCD-I met to identify and agree upon topics relevant to SCD criteria operationalization in research settings. Initial ideas and recommendations were discussed with other SCD-I working group members and modified accordingly. RESULTS Topics included SCD inclusion and exclusion criteria, together with the informant’s role in defining SCD presence and the impact of demographic factors. DISCUSSION Recommendations for the operationalization of SCD in differing research settings, with the aim of harmonization of SCD measurement across studies are proposed, to enhance comparability and generalizability across studies.Item In vivo validation of late-onset Alzheimer's disease genetic risk factors(bioRxiv, 2023-12-24) Sasner, Michael; Preuss, Christoph; Pandey, Ravi S.; Uyar, Asli; Garceau, Dylan; Kotredes, Kevin P.; Williams, Harriet; Oblak, Adrian L.; Lin, Peter Bor-Chian; Perkins, Bridget; Soni, Disha; Ingraham, Cindy; Lee-Gosselin, Audrey; Lamb, Bruce T.; Howell, Gareth R.; Carter, Gregory W.; Radiology and Imaging Sciences, School of MedicineIntroduction: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Methods: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. Results: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. Discussion: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.Item MEDI1814 selectively reduces free Aβ42 in cerebrospinal fluid of non-clinical species and Alzheimer's disease patients(Wiley, 2024) Lloyd, Christopher; Freskgård, Per-Ola; Newton, Philip; Lowne, David; Nickson, Adrian; Bogstedt, Anna; Eketjäll, Susanna; Höglund, Kina; Gustavsson, Susanne; Welsh, Fraser; Chessell, Tharani; McFarlane, Mary; Bhat, Ratan V.; Turner, Richard; Perkinton, Michael S.; Valencia, Zulma Santisteban; Lindqvist, Eva; Pomfret, Michael; Dudley, Amanda D.; Vaughan, Tristan J.; Groves, Maria T.; Natanegara, Fanni; Feng, Yingdong; Sims, John R.; Proctor, Nicholas Kyle; Dage, Jeffrey L.; Shering, Craig; Tan, Keith; Ostenfeld, Thor; Billinton, Andy; Chessell, Iain P.; Neurology, School of MedicineIntroduction: Small molecules and antibodies are being developed to lower amyloid beta (Aβ) peptides. Methods: We describe MEDI1814, a fully human high-affinity monoclonal antibody selective for Aβ42, the pathogenic self-aggregating species of Aβ. Results: MEDI1814 reduces free Aβ42 without impacting Aβ40 in the cerebrospinal fluid of rats and cynomolgus monkeys after systemic administration. MEDI1814 administration to patients with Alzheimer's disease (AD; n = 57) in single or repeat doses up to 1800 mg intravenously or 200 mg subcutaneously was associated with a favorable safety and tolerability profile. No cases of amyloid-related imaging abnormalities were observed. Predictable dose-proportional changes in serum exposures for MEDI1814 were observed across cohorts. Cerebrospinal fluid (CSF) analysis demonstrated central nervous system penetration of MEDI1814. Pharmacodynamic data showed dose-dependent suppression of free Aβ42, increases in total (bound and free) Aβ42, but no change in total Aβ40 in CSF across doses. Discussion: MEDI1814 offers a differentiated approach to impacting Aβ in AD via selective reduction of free Aβ42.Item Model organism development and evaluation for late‐onset Alzheimer's disease: MODEL‐AD(Wiley, 2020-11-23) Oblak, Adrian L.; Forner, Stefania; Territo, Paul R.; Sasner, Michael; Carter, Gregory W.; Howell, Gareth R.; Sukoff-Rizzo, Stacey J.; Logsdon, Benjamin A.; Mangravite, Lara M.; Mortazavi, Ali; Baglietto-Vargas, David; Green, Kim N.; MacGregor, Grant R.; Wood, Marcelo A.; Tenner, Andrea J.; LaFerla, Frank M.; Lamb, Bruce T.; Radiology and Imaging Sciences, School of MedicineAlzheimer's disease (AD) is a major cause of dementia, disability, and death in the elderly. Despite recent advances in our understanding of the basic biological mechanisms underlying AD, we do not know how to prevent it, nor do we have an approved disease‐modifying intervention. Both are essential to slow or stop the growth in dementia prevalence. While our current animal models of AD have provided novel insights into AD disease mechanisms, thus far, they have not been successfully used to predict the effectiveness of therapies that have moved into AD clinical trials. The Model Organism Development and Evaluation for Late‐onset Alzheimer's Disease (MODEL‐AD; www.model-ad.org) Consortium was established to maximize human datasets to identify putative variants, genes, and biomarkers for AD; to generate, characterize, and validate the next generation of mouse models of AD; and to develop a preclinical testing pipeline. MODEL‐AD is a collaboration among Indiana University (IU); The Jackson Laboratory (JAX); University of Pittsburgh School of Medicine (Pitt); Sage BioNetworks (Sage); and the University of California, Irvine (UCI) that will generate new AD modeling processes and pipelines, data resources, research results, standardized protocols, and models that will be shared through JAX's and Sage's proven dissemination pipelines with the National Institute on Aging–supported AD Centers, academic and medical research centers, research institutions, and the pharmaceutical industry worldwide.Item Neurostimulation devices to treat Alzheimer’s disease(Open Exploration, 2025) Perez, Felipe P.; Walker, Brett; Morisaki, Jorge; Kanakri, Haitham; Rizkalla, Maher; Medicine, School of MedicineThe use of neurostimulation devices for the treatment of Alzheimer's disease (AD) is a growing field. In this review, we examine the mechanism of action and therapeutic indications of these neurostimulation devices in the AD process. Rapid advancements in neurostimulation technologies are providing non-pharmacological relief to patients affected by AD pathology. Neurostimulation therapies include electrical stimulation that targets the circuitry-level connection in important brain areas such as the hippocampus to induce therapeutic neuromodulation of dysfunctional neural circuitry and electromagnetic field (EMF) stimulation that targets anti-amyloid molecular pathways to promote the degradation of beta-amyloid (Aβ). These devices target specific or diffuse cortical and subcortical brain areas to modulate neuronal activity at the electrophysiological or molecular pathway level, providing therapeutic effects for AD. This review attempts to determine the most effective and safe neurostimulation device for AD and provides an overview of potential and current clinical indications. Several EMF devices have shown a beneficial or harmful effect in cell cultures and animal models but not in AD human studies. These contradictory results may be related to the stimulation parameters of these devices, such as frequency, penetration depth, power deposition measured by specific absorption rate, time of exposure, type of cell, and tissue dielectric properties. Based on this, determining the optimal stimulation parameters for EMF devices in AD and understanding their mechanism of action is essential to promote their clinical application, our review suggests that repeated EMF stimulation (REMFS) is the most appropriate device for human AD treatments. Before its clinical application, it is necessary to consider the complicated and interconnected genetic and epigenetic effects of REMFS-biological system interaction. This will move forward the urgently needed therapy of EMF in human AD.