Biology subjects

Jucker, M.

Publications and source records attributed to Jucker, M..

12 recordsLinked to original sources

bioRxiv2026

Biomarker Variability Limits Individualized Amyloid Time Estimation in Alzheimer Disease

ObjectiveDisease progression modeling (DPM) or "amyloid time" is increasingly used to stage Alzheimer disease (AD). DPM performance depends on within-individual heterogeneity in rates of pathological accumulation as well as test-retest reliability of the biomarker. The relative contributions of these variabilities have not been systematically assessed. This would be particularly relevant if extrapolations from DPM were to be used to make individual-level predictions for research, clinical trials, or potentially future clinical practice. MethodsWe conducted simulation studies incorporating empirically-derived noise properties from amyloid biomarkers to assess the contributions of inter- and intra-individual variability. Findings generalized in an autosomal dominant AD cohort with amyloid positron emission tomography (PET), cerebrospinal fluid (CSF), and plasma biomarkers and in a sporadic AD cohort with both amyloid PET and plasma biomarkers. We assessed group level DPM performance via mean average error (MAE) and root mean squared error (RMSE). At the individual level, we evaluated distinctness of distributions of biomarker levels associated with specific disease timings. ResultsInter-individual variability was the dominant source of error in temporal estimates. Intra-individual variability reduced estimate stability. Optimal performance occurred in biomarkers with positive average accumulation rates where a subset of individuals had exceptionally high levels of accumulation. In research study data, amyloid PET outperformed CSF and plasma biomarkers. InterpretationDPM is fundamentally constrained by dynamic range, variability, and test-retest reliability of the biomarker of interest. Current DPM approaches are more robust at the group level, particularly when applied to biomarkers with more than 10-15% variability like fluid biomarkers. FundingNational Institute on Aging, Alzheimers Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Korean Ministry of Health & Welfare and Ministry of Science and ICT, Spanish Institute of Health.

bioinformatics↗

bioRxiv2025

Real-time Malaria Detection in the Amazon Rainforest via Drone-Collected eDNA and Portable qPCR

Emerging zoonotic parasites such as Plasmodium spp. in remote ecosystems demand rapid, field-deployable surveillance. We developed a drone-based environmental DNA (eDNA) sampling approach integrated with a portable quantitative PCR (qPCR) assay for in situ detection of Plasmodium DNA. Field trials confirmed malaria parasite DNA in canopy swabs, coinciding spatially with acoustic detection of howler monkeys (Alouatta sp.), suspected reservoir hosts. No Anopheles mosquitoes were captured in simultaneously deployed insect traps. The end-to-end workflow, from drone deployment to diagnostic readout, averaged 1.5 hours per assay, required only basic mobile-laboratory infrastructure, and bypassed cold-chain logistics. This rapid, non-invasive method delivers actionable surveillance data in real-time, enabling near-real-time trigger points for vector-control interventions and clinical response in remote settings. By merging environmental genomics with portable diagnostics, we establish a scalable One Health framework adaptable to diverse vector-borne parasites and ecosystems, with potential for early detection and spillover risk mitigation in under-monitored, high-risk environments.

molecular biology↗

bioRxiv2023

Polyglucosan body density in the aged mouse hippocampus is controlled by a novel modifier locus on chromosome 1

In aged humans and mice, aggregates of hypobranched glycogen molecules called polyglucosan bodies (PGBs) accumulate in hippocampal astrocytes. PGBs are known to drive cognitive decline in neurological diseases but remain largely unstudied in the context of typical brain aging. Here, we show that PGBs arise in autophagy-dysregulated astrocytes of the aged C57BL/6J mouse hippocampus. To map the genetic cause of age-related PGB accumulation, we quantified PGB burden in 32 fully sequenced BXD-recombinant inbred mouse strains, which display a 400-fold variation in hippocampal PGB burden at 16-18 months of age. A major modifier locus was mapped to chromosome 1 at 72-75 Mb, which we defined as the Pgb1 locus. To evaluate candidate genes and downstream mechanisms by which Pgb1 controls the aggregation of glycogen, extensive hippocampal transcriptomic and proteomic datasets were produced for aged mice of the BXD family. We utilized these datasets to identify Smarcal1 and Usp37 as potential regulators of PGB accumulation. To assess the effect of PGB burden on age-related cognitive decline, we performed phenome-wide association scans, transcriptomic analyses as well as conditioned fear memory and Y-maze testing. Importantly, we did not find any evidence suggesting a negative impact of PGBs on cognition. Taken together, our study demonstrates that the Pgb1 locus controls glycogen aggregation in astrocytes of the aged hippocampus without affecting age-related cognitive decline.

genetics↗

bioRxiv2023

Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels--a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasnt definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruptions severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in A{beta} PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.

neuroscience↗

bioRxiv2023

Divergent age-dependent conformational rearrangement within Aβ-amyloid deposits in APP23, APPPS1, and AppNL-F mice

Amyloid plaques composed of fibrils of misfolded A{beta} peptides are pathological hallmarks of Alzheimers disease (AD). A{beta} fibrils are polymorphic in their tertiary and quaternary molecular structures. This structural polymorphism may carry different pathologic potency and can putatively contribute to clinical phenotypes of AD. Therefore, mapping of structural polymorphism of A{beta} fibrils is valuable to understand disease mechanisms. Here, we investigated how A{beta} fibril morphology in situ differs in A{beta} plaque of different mouse models expressing familial mutations in the A{beta}PP gene. We used a combination of conformation-sensitive luminescent conjugated oligothiophene (LCO) ligands, A{beta}-specific antibodies, and different fluorescence microscopy techniques. LCO fluorescence mapping revealed that mouse models APP23, APPPS1, and AppNL-F have different fibril structures depending on A{beta}PP-processing genotype. Co-staining of A{beta}-specific antibodies showed that individual plaques from APP23 mice, expressing Swedish mutations (NL) have two distinct fibril polymorph regions of core and corona. The plaque core is predominantly composed of compact A{beta}40 fibrils and the corona region is dominated by diffusely packed A{beta}40 fibrils. On the other hand, the APP knock-in mouse AppNL-F, expressing Iberian mutation (F) along with Swedish mutation has tiny, cored plaques consisting mainly of compact A{beta}42 fibrils, vastly different from APP23 even at elevated age up to 21 months. Age dependent polymorph maturation of plaque cores observed for APP23 and APPPS1 mice >12 months, was minuscule in AppNL-F. These structural studies of amyloid plaques in situ can map disease-relevant fibril polymorph distributions to guide the design of diagnostic and therapeutic molecules. SignificanceAlzheimers disease (AD) is associated with the formation of deposits in the brain known as A{beta}-amyloid plaques. AD can emerge as a sporadic disease or due to familial mutations in genes encoding for A{beta} precursor and processing proteins. The A{beta}-amyloid found in plaques displays different structures in sporadic AD and in various types of familial AD. We hypothesize that understanding plaque morphology and development is crucial for understanding the initiation and progression of AD. We here compared amyloid structures in three of the most used mouse models of human A{beta}-plaque formation. Our findings suggest significant differences in plaque morphologies and structural maturation processes during aging. Our results emphasize that strain-like differences of A{beta}-amyloids develop as a function of A{beta} precursor protein-processing genetics and age.

neuroscience↗

bioRxiv2023

Functional variations in gamma-secretase activity are critical determinants of the clinical, biomarker, and cognitive progression of autosomal dominant Alzheimer's disease

BackgroundThe balance between production, clearance, and toxicity of A{beta} peptides is central to Alzheimers disease (AD) pathobiology. Though highly variable in terms of age at symptom onset (AAO), hundreds of variants in PSEN1 cause autosomal dominant forms of AD (ADAD) with nearly complete penetrance. PSEN1 forms the catalytic core of the {gamma}-secretase complex and thereby directly mediates the production of longer, aggregation-prone A{beta} peptides relative to shorter, non-aggregating peptides. We hypothesized that the broad AAO and biomarker heterogeneity seen across ADAD would be predictable based on mutation-specific differences in the production of A{beta} species. MethodsA{beta}-37, 38, 40, 42, and 43 production was quantified from 161 unique PSEN1 variants expressed in HEK293 cells. Prediction of AAO was carried out in 106 variants with available AAO and then replicated in 55 variants represented across 190 PSEN1 mutation carriers who have detailed cognitive and biomarker data from the Dominantly Inherited Alzheimers Network (DIAN). ResultsVariations in A{beta} production across the 161 mutations examined in cell-based models were highly predictive of AAO. In those with corresponding in vivo data from the DIAN study, our cell-based {gamma}-secretase composite was strongly associated with biomarker and cognitive trajectories. ConclusionsThese findings elucidate the critical link between {gamma}-secretase function, A{beta} production, and AD progression and offer mechanistic support for the amyloid hypothesis. The approach used here represents a powerful tool to account for heterogeneity in disease progression in ADAD clinical trials and to assess the pathogenicity of variants of unknown significance or with limited family history.

neuroscience↗

bioRxiv2021

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying the diversity of species in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, the reliability of biodiversity detection from eDNA samples can be low in marine environments because eDNA density is low and certainly patchy in this vast, heterogenous and dynamic environment. So, the number of sampling replicates and filtered volume necessary to obtain accurate estimates of biodiversity in rich tropical marine environments using eDNA metabarcoding is still unknown. Here, we used a paired sampling design of 30L per replicate on 68 reef transects from 8 sites in three tropical regions and identified fish Molecular Taxonomic Units (MOTUs) using a 12S marker. We quantified local biodiversity variation as MOTU richness, compositional turnover and compositional nestedness between replicated pairs of seawater samples. We report strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non-overlapping assemblages rather than subsets of one-another. As a result, localised diversity accumulation curves showed that even 6 replicates (180L) in the same location underestimated local diversity (for an area <1km). However, sampling of regional diversity using [~]25 replicates in variable locations (often covering 10s of km) achieved saturation of biodiversity accumulation curves. Our results demonstrate high variability of diversity estimates perhaps arising from heterogeneous and local distribution of eDNA distribution in seawater or highly skewed frequencies of eDNA traces. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes of local assemblages. Future biomonitoring efforts could be strongly undermined by a high level of false-negative detections under low replication protocols. We reveal the need to increase replicates or increase sampled water volume to better inform management of marine biodiversity using eDNA.

ecology↗

bioRxiv2021

LAG3 is not expressed in human and murine neurons and does not modulate α-synucleinopathies

While the initial pathology of Parkinsons disease and other -synucleinopathies is often confined to circumscribed brain regions, it can spread and progressively affect adjacent and distant brain locales. This process may be controlled by cellular receptors of -synuclein fibrils, one of which was proposed to be the LAG3 immune checkpoint molecule. Here, we analyzed the expression pattern of LAG3 in human and mouse brains. Using a variety of methods and model systems, we found no evidence for LAG3 expression by neurons. While we confirmed that LAG3 interacts with -synuclein fibrils, the specificity of this interaction appears limited. Moreover, overexpression of LAG3 in cultured human neural cells did not cause any worsening of -synuclein pathology ex vivo. The overall survival of A53T -synuclein transgenic mice was unaffected by LAG3 depletion and the seeded induction of -synuclein lesions in hippocampal slice cultures was unaffected by LAG3 knockout. These data suggest that the proposed role of LAG3 in the spreading of -synucleinopathies is not universally valid.

neuroscience↗

bioRxiv2021

Deletion of Serf2 shifts amyloid conformation in an Aβ amyloid mouse model

In age-related neurodegenerative disease, like Alzheimers and Parkinsons disease, disease-specific proteins become aggregation-prone and form amyloid-like deposits. Depletion of SERF proteins ameliorates this toxic process in worm- and human cell models for disease. Whether SERF modifies amyloid pathology in mammalian brain, however, has remained unknown. Here, we generated SERF2 brain-specific knockout mice which, unlike full body knockout mice, were viable, and showed no major behavioral and cognitive abnormalities. We combined these knockout mice with the APPPS1 mouse model for human amyloid beta aggregation. Using structure-specific amyloid dyes, previously used to distinguish amyloid polymorphisms in human brain, we show that knockout of SERF2 alters the structure of amyloid fibrils and deposits. Moreover, scanning transmission electron microscopy revealed thicker, shorter and more densely packed amyloid in absence of SERF2. Altogether, our data reveal pleiotropic functions of SERF in development and aging and support a function as a modifier of amyloid aggregation in mammalian brain. Our results indicate that single cellular factors like SERF can determine the structural outcome of amyloid aggregation, offering possibilities for polymorphism-based disease interventions.

molecular biology↗

bioRxiv2020

Functional brain age prediction suggests accelerated aging in preclinical familial Alzheimer's disease, irrespective of fibrillar amyloid-beta pathology

We aimed at developing a model able to predict brain aging from resting state functional connectivity (rs-fMRI) and assessing whether genetic risk/determinants of Alzheimers disease (AD) and amyloid (A{beta}) pathology contributes to accelerated brain aging. Using data collected in 1340 cognitively unimpaired participants from 18 to 94 years old selected across multi-site cohorts, we showed that chronological age can be predicted across the whole lifespan from topological properties of graphs constructed from rs-fMRI. We subsequently used the difference between the model-predicted age and the chronological age in pre-symptomatic autosomal dominant AD (ADAD) mutation carriers and asymptomatic individuals at risk of sporadic AD and assessed the influence of genetics and A{beta} pathology on brain age. Applying our predictive model in the context of preclinical AD revealed that the pre-symptomatic phase of ADAD is characterized by accelerated functional brain aging. This phenomenon is independent from, and might precede, detectable fibrillar A{beta} deposition.

neuroscience↗

bioRxiv2020

Loss of function of the mitochondrial peptidase PITRM1 induces proteotoxic stress and Alzheimer's disease-like pathology in human cerebral organoids

Mutations in pitrilysin metallopeptidase 1 (PITRM1), a mitochondrial protease involved in mitochondrial precursor processing and degradation, result in a slow-progressive syndrome, characterized by cerebellar ataxia, psychotic episodes and obsessive behavior as well as cognitive decline. To investigate the pathogenetic mechanisms of mitochondrial presequence processing, we employed cortical neurons and cerebral organoids generated from PITRM1 knockout human induced pluripotent stem cells (iPSCs). PITRM1 deficiency strongly induced mitochondrial unfolded protein response (UPRmt) and enhanced mitochondrial clearance in iPSC-derived neurons. Furthermore, we observed increased levels of amyloid precursor protein and amyloid {beta} in PITRM1 knockout neurons. However, neither cell death nor protein aggregates were observed in 2D iPSC-derived cortical neuronal cultures. On the contrary, cerebral organoids generated from PITRM1 knockout iPSCs spontaneously developed over time pathological features of Alzheimers disease (AD), including accumulation of protein aggregates, tau pathology, and neuronal cell death. Importantly, we provide evidence for a protective role of UPRmt and mitochondrial clearance against impaired mitochondrial presequence processing and proteotoxic stress. In summary, we propose a novel concept of PITRM1-linked neurological syndrome whereby defects of mitochondrial presequence processing induce an early activation of UPRmt that, in turn, modulates cytosolic quality control pathways. Thus our work supports a mechanistic link between mitochondrial function and common neurodegenerative proteinopathies.

neuroscience↗

bioRxiv2019

Prion-like spreading of Alzheimer's disease within the brain's connectome

The prion hypothesis states that misfolded proteins can act as infectious agents that trigger the misfolding and aggregation of healthy proteins to transmit a variety of neurodegenerative diseases. Increasing evidence suggests that pathogenic proteins in Alzheimers disease adapt prion-like mechanisms and spread across the brain along an anatomically connected network. Local kinetics models of protein misfolding and global network models of protein diffusion provide valuable insight into the dynamics of prion-like diseases. Yet, to date, these models have not been combined to simulate how pathological proteins multiply and spread across the human brain. Here we model the prion-like spreading of Alzheimers disease by combining misfolding kinetics and network diffusion through a connectivity-weighted Laplacian graph created from 418 brains of the Human Connectome Project. The nodes of the graph represent anatomic regions of interest and the edges represent their con-nectivity, weighted by the mean fiber number divided by the mean fiber length. We show that our brain network model correctly predicts the neuropathological pattern of Alzheimers disease and captures the key characteristic features of whole brain models at a fraction of their computational cost. To illustrate the potential of brain network modeling in neurodegeneration, we simulate biomarker curves, infection times, and two promising therapeutic strategies to delay the onset of neurodegeneration: reduced production and increased clearance of misfolded protein.

neuroscience↗