Developing a Novel Reference Region for PI‐2620‐PET Imaging to Facilitate Assessment of 4‐Repeat Tauopathies - DZNEPUB

Neurodegenerative 4-repeat (4R) tauopathies commonly manifest as progressive supranuclear palsy (PSP). PSP patients show elevated PI-2620-PET in subcortical 4R tau predilection sites (e.g., globus pallidus), suggesting PI-2620-PET as a promising 4R tau neuroimaging candidate. However, optimal quantification of PI-2620-PET in 4R tauopathies remains challenging, as conventional cerebellar tau-PET reference regions also accumulate 4R tau. We aimed to use unbiased image-derived input function (IDIF) PET data to determine an optimized PET reference region for in vivo quantification of 4R tau.We obtained 60-minute dynamic PI-2620-PET in 54 PSP Richardson Syndrome (PSP-RS) patients and 19 healthy controls (HC), applying IDIF-modeling using carotid timeseries to assess unbiased PI-2620-PET binding and determine total distribution volume (VT). Through an iterative approach, we intensity-normalized VT-images against white-matter regions in the Hammers brain atlas, identifying regions where intensity-normalized pallidum PET values showed the largest PSP-RS vs. HC differences. White-matter regions with strongest PSP-RS vs. HC differences surviving multiple-comparison correction were summarized into a single reference region spanning bilateral temporo-orbital white-matter. This ROI was then used to determine SUVRs using conventional 20-40 minute PI-2620-PET data in PSP-RS, a PSP-non-RS validation sample (n = 63), as well as non-tau disease controls (i.e., alpha-synucleinopathies, n = 20; Alzheimer's disease, n = 23).Using PI-2620 SUVRs obtained with the temporo-orbital white-matter reference, we detected strong PSP-RS vs. HC group differences in basal ganglia SUVRs using voxel-wise comparisons (p <0.001, FWE-cluster corrected). Similar basal ganglia differences were detected for PSP-non-RS vs. HC, but not for alpha-syn (no group differences) or AD vs. HC (cortical AD-like group differences). In contrast, minimal group differences were found using a conventional inferior cerebellar grey matter reference region.Our findings strongly suggest temporo-orbital white-matter is superior to inferior cerebellum as a reference region for PI-2620-PET imaging in 4R tauopathies, due to increased sensitivity and purported specificity for 4R tau. Frontzkowski, Lukas; Gross, Mattes; Roemer-Cassiano, Sebastian; Palleis, Carla; Dehsarvi, Amir; Katzdobler, Sabrina; Dewenter, Anna; Steward, Anna; Biel, Davina; Hirsch, Fabian; Gnoerich, Johannes; Levin, Johannes; Stephens, Andrew W.; Mueller, Andre; Koglin, Norman; Bischof, Gérard N; Kovacs, Gabor G.; Höglinger, Günter U; Brendel, Matthias; Franzmeier, Nicolai

Polygenic risk for psychiatric disorders and its association with neuropsychiatric symptoms in dementia. - DZNEPUB

Neuropsychiatric symptoms are common in Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), yet their genetic underpinnings remain unclear. To gain insight into biological processes related to neuropsychiatric symptoms in dementia, we investigated whether polygenic risk scores (PRS) for psychiatric disorders - major depressive disorder (MDD), schizophrenia (SCZ), bipolar disorder (BD), and autism spectrum disorder (ASD) - are associated with neuropsychiatric symptoms in dementia. Data included genetic and neuropsychiatric data of 6240 AD patients, 428 FTD patients and 390 DLB patients from five European cohorts (ADC, GR@ACE, DELCODE, AgeCoDe, and DCN). PRS for MDD, BD, SCZ, and ASD were calculated using LDpred2. Neuropsychiatric symptoms were assessed using total scores from the Neuropsychiatric Inventory (NPI) (NPI-12 and NPI-Q) and Geriatric Depression scale (GDS). Associations between PRS and symptoms were examined using linear regression models, followed by meta-analyses. In FTD, higher SCZ-PRS associated with lower NPI scores in the meta-analysis (β = -0.12, p = .001). No associations were found in AD and DLB. This is the first study to show that genetic liability for SCZ associates with lower NPI in FTD, warranting further investigation. Najar, Jenna; de Rojas, Itziar; Dalmasso, Maria Carolina; Fernandez, Maria Victoria; de Boer, Sterre C M; Ramirez, Alfredo; Priller, Josef; Laske, Christoph; Kleineidam, Luca; Schneider, Anja; Wagner, Michael; Heilmann-Heimbach, Stefanie; Scherer, Martin; Froelich, Lutz; Peters, Oliver; Hellmann-Regen, Julian David Nicolai; Wiltfang, Jens; Düzel, Emrah; Buerger, Katharina; Perneczky, Robert; Teipel, Stefan; Jessen, Frank; Kornhuber, Johannes; Lemstra, Afina W; Pijnenburg, Yolande A L; van der Lee, Sven J; Reus, Lianne M

Supplementation with short-chain fatty acids and a prebiotic improves clinical outcome in Parkinson's disease: a randomized double-blind prospective study. - DZNEPUB

Parkinson's disease is associated with a dysbiotic, proinflammatory gut microbiome, disruptions to intestinal barrier functions, and immunological imbalance. Microbiota-produced short-chain fatty acids, such as propionic and butyric acid promote gut barrier integrity and immune regulation, but their impact on Parkinson's disease pathology remains mostly unknown.In a randomized double-blind prospective study, 72 people with Parkinson's disease received propionic and butyric acid and/or the prebiotic fiber 2'-fucosyllactose supplementation over 6 months in combination with existing Parkinson's disease-specific therapy. Patients underwent complete neurological assessment and provided blood and stool samples before as well as 3 and 6 months after supplementation.We observed a robust improvement in motor symptoms, with all intervention groups achieving clinically meaningful reductions. These motor benefits were paralleled by clinically relevant reductions in levodopa medication. In contrast, effects on nonmotor symptoms were more heterogeneous. Notably, the interventions also modulated peripheral immune responses and enhanced mitochondrial respiration in immunocytes. Postintervention microbiota remodeled inflammatory and barrier-related gene sets in gut organ cultures and improved in vitro barrier functions. Treatment response was associated with microbiome composition, distinct patterns of colonic transcription and permeability ex vivo. Multiobjective analysis revealed immune parameters associated with an optimal response to supplementation.Short-chain fatty acids ameliorate clinical symptoms in Parkinson's disease patients and modulate intestinal and peripheral immunity.This clinical trial was retrospectively registered with the German Clinical Trials Register (DRKS), registration number DRKS00027061 on 11/19/2021. Hegelmaier, Tobias; Duscha, Alexander; Desel, Christiane; Fuchs, Sabrina; Shapira, Michal; Amidror, Sivan; Shan, Qihao; Stangl, Gabriele I; Hirche, Frank; Kempa, Stefan; Maifeld, András; Würtele, Lisa-Marie; Peplinski, Jana; Jauk, Diana; Naim, Gitali; Shidlovsky, Nuphar; Cohen, Adva; Bennet, Yifat; Paschold, Lisa; Dumitru, Claudia A; Obermüller-Jevic, Ute; Hustvedt, Svein-Olaf; Timmesfeld, Nina; Gold, Ralf; Zapf, Antonia; Binder, Mascha; Sandalcioglu, Ibrahim E; Mostaghim, Sanaz; Przuntek, Horst; Segal, Eran; Yissachar, Nissan; Haghikia, Aiden

Dementia with lewy bodies and Alzheimer´s Disease overlap syndrome with PSP-like phenotype caused by co-pathologies - a case report. - DZNEPUB

Häfner, Friederike; Bernhardt, Alexander; Goldschagg, Nicolina; Hopfner, Franziska; Gnoerich, Johannes; Brendel, Matthias; Levin, Johannes; Strupp, Michael; Höglinger, Günter

Plasma p ‐tau 217 as a suitable biomarker for monitoring cognitive changes in Alzheimer's disease - DZNEPUB

With the approval of anti-amyloid therapies in Alzheimer's disease (AD), surrogate biomarkers are urgently needed to monitor treatment effects that translate into clinical benefits. Candidate biomarkers, including amyloid-PET, tau-PET, plasma phosphorylated tau (p-tau), and MRI-assessed atrophy, capture core pathophysiological changes in AD. While cross-sectional biomarker assessments are critical for diagnosis and staging, biomarker change rates may better reflect disease dynamics, making them more suitable for monitoring treatment efficacy. Therefore, we determined which biomarker most effectively tracks cognitive changes in AD, identifying those best suited for efficient monitoring of disease-modifying treatments.We leveraged ADNI (N = 108) and A4 (N = 151) participants with longitudinal AD biomarker data (global amyloid-PET, temporal meta tau-PET, plasma p-tau217, MRI-assessed cortical thickness in the AD signature region) together with cognitive assessments (ADNI: MMSE, ADAS13, CDR-SB; A4: MMSE, PACC). Linear mixed models were used to calculate change rates for biomarkers and cognition. To test whether biomarker changes track cognitive decline, linear models were applied, to test biomarker change rates as a predictor of cognitive change rates. Standardized beta values from bootstrapped linear models were extracted to compare the strengths of correlations between biomarkers and cognitive decline. For non-parametric comparisons, 95% confidence intervals (CIs) of standardized beta values were compared. Models were controlled for age, sex, education, and baseline cognition, with ADNI models additionally adjusted for clinical status.In both cohorts, changes in temporal tau-PET, plasma p-tau217, and MRI-assessed cortical thickness were associated with cognitive decline (ADNI: Figure 1; A4: Figure 2). Amyloid-PET changes showed no significant association with cognitive changes (ADNI: Figure 1A+F+K; A4: Figure 2A+F). Bootstrapping confirmed that tau-PET, plasma p-tau217, and cortical thickness track cognitive decline, but not amyloid-PET (ADNI: Figure 1E+J+O; A4: Figure 2E+J). Overlapping CIs for tau-PET and plasma p-tau217 indicated comparable predictive accuracy.Our findings demonstrate that tau-PET and plasma p-tau217 are robust biomarkers for monitoring cognitive changes, with plasma p-tau217 offering a cost-effective, scalable alternative for clinical use. Changes in amyloid-PET do not reliably reflect cognitive decline, limiting its utility as a treatment monitoring tool. Although cortical thickness correlates with cognitive changes, its application is limited by pseudoatrophy and volume loss induced by anti-amyloid antibody treatments. Biel, Davina; Steward, Anna; Dewenter, Anna; Dehsarvi, Amir; Zhu, Zeyu; Roemer-Cassiano, Sebastian; Frontzkowski, Lukas; Hirsch, Fabian; Brendel, Matthias; Franzmeier, Nicolai

Multi‐tracer PET monitoring of an immunomodulatory therapy in 4R tauopathy: Evaluating a novel drug's impact on glial function and protein pathology - DZNEPUB

The prevalence of neurodegenerative diseases (ND), including Alzheimer's disease (AD) and non-AD tauopathies, is projected to rise significantly by 2050 due to an aging global population. Chronic neuroinflammation, driven by glial activation in response to protein pathologies, is a major contributor to disease progression. Targeting glial dysfunction through immunomodulatory therapies offers a promising approach to mitigate the effects of tauopathies and other ND.PS19 mice receive chronic treatment with GV1001 over 5 months. Serial neuroimaging techniques, including PET scans targeting tau protein, microglial activation, and astrocytic responses, are employed to assess treatment effects in vivo (Figure 1). Postmortem validation is performed using immunohistochemistry and biochemical methods, comparing treated mice to placebo and non-transgenic controls.The research scope is to monitor the efficacy of GV1001 in a transgenic tau mouse model (PS19) with an early-intervention biomarker study using molecular biology and neuroimaging techniques including TSPO (microglia) PET, deprenyl (astroglia) PET, tau PET (perfusion and retention) and CSF markers of inflammation (e.g. sTREM2) and neurodegeneration (NfL). Preliminary findings, expected to be presented at the conference, will provide insights into the drug's ability to modulate glial activity, restore homeostasis, and reduce tau pathology.This study highlights the potential of monitoring immunomodulatory strategies to address the complex interplay between chronic neuroinflammation and protein aggregation in ND. If successful, these findings could inform the development of novel therapeutic approaches for AD and related disorders, bridging the gap between preclinical research and clinical application. Bathe, Tim; Salomasova, Svetlana; Lalia, Manvir; Kunze, Lea; Palumbo, Giovanna; Oos, Rosel; Joseph, Emanuel; Brendel, Matthias

Integrating simulated and experimental data to identify mitochondrial bioenergetic defects in Parkinson's Disease models. - DZNEPUB

Mitochondrial bioenergetics are vital for ATP production and are associated with several diseases, including Parkinson's Disease (PD). Here, we simulated a computational model of mitochondrial ATP production to interrogate mitochondrial bioenergetics under physiological and pathophysiological conditions, and provide a data resource that can be used to interpret mitochondrial bioenergetics experiments. We first characterised the impact of several common electron transport chain (ETC) impairments on experimentally-observable bioenergetic parameters. We then established an analysis pipeline to integrate simulations with experimental data and predict the molecular defects underlying experimental bioenergetic phenotypes. We applied the pipeline to data from PD models. We verified that the impaired bioenergetic profile previously measured in Parkin knockout (KO) neurons can be explained by increased mitochondrial uncoupling. We then generated primary cortical neurons from a Pink1 KO mouse model of PD, and measured reduced oxygen consumption rate (OCR) capacity and increased resistance to Complex III inhibition. Here, our pipeline predicted that multiple impairments are required to explain this bioenergetic phenotype. Finally, we provide all simulated data as a user-friendly resource that can be used to interpret mitochondrial bioenergetics experiments, predict underlying molecular defects, and inform experimental design. Chenna, Sandeep; Joselin, Alvin; Theurey, Pierre; Bano, Daniele; Pizzo, Paola; Ankarcrona, Maria; Park, David S; Prehn, Jochen H; Connolly, Niamh M C

How to lead a journal club you won’t be embarrassed by later – fsolt

AI Superresolution: Converting T1‐weighted MRI from 3T to 7T resolution toward enhanced imaging biomarkers for Alzheimer's disease - DZNEPUB

Background:High-resolution (7T) MRI facilitates in vivo imaging of fine anatomical structures selectively affected in Alzheimer's disease (AD), including medial temporal lobe subregions. However, 7T data is challenging to acquire and largely unavailable in clinical settings. Here, we use deep learning to synthesize 7T resolution T1-weighted MRI images from lower-resolution (3T) images.Method:Paired 7T and 3T T1-weighted images were acquired from 178 participants (134 clinically unimpaired, 48 impaired) from the Swedish BioFINDER-2 study. To synthesize 7T-resolution images from 3T images, we trained two models: a specialized U-Net, and a U-Net mixed with a generative adversarial network (U-Net-GAN) on 80% of the data. We evaluated model performance on the remaining 20%, compared to models from the literature (V-Net, WATNet), using image-based performance metrics and by surveying five blinded MRI professionals based on subjective quality. For n = 11 participants, amygdalae were automatically segmented with FastSurfer on 3T and synthetic-7T images, and compared to a manually segmented “ground truth”. To assess downstream performance, FastSurfer was run on n = 3,168 triplets of matched 3T and AI-generated synthetic-7T images, and a multi-class random forest model classifying clinical diagnosis was trained on both datasets.Result:Synthetic-7T images were generated for images in the test set (Figure 1A). Image metrics suggested the U-Net as the top performing model (Figure 1B), though blinded experts qualitatively rated the GAN-U-Net as the best looking images, exceeding even real 7T images (Figure 1C). Automated segmentations of amygdalae from the synthetic GAN-U-Net model were more similar to manually segmented amygdalae, compared to the original 3T they were synthesized from, in 9/11 images (Figure 2). Classification obtained modest performance (accuracy∼60%) but did not differ across real or synthetic images (Figure 3A). Synthetic image models used slightly different features for classification (Figure 3B).Conclusion:Synthetic T1-weighted images approaching 7T resolution can be generated from 3T images, which may improve image quality and segmentation, without compromising performance in downstream tasks. This approach holds promise for better measurement of deep cortical or subcortical structures relevant to AD. Work is ongoing toward improving performance, generalizability and clinical utility. Gicquel, Malo; Flood, Gabrielle; Zhao, Ruoyi; Wuestefeld, Anika; Spotorno, Nicola; Strandberg, Olof; Xiao, Yu; Åström, Kalle; Wisse, Laura E. M.; van Westen, Danielle; Berron, David; Hansson, Oskar; Vogel, Jacob W.