Prediction of amyloid β accumulation from multiple biomarkers using a hierarchical Bayesian model

Yada, Y.; Naoki, H.

doi:10.1101/2022.10.21.513271

Home/Archive/bioRxiv

bioRxiv · 10.1101/2022.10.21.513271

Prediction of amyloid β accumulation from multiple biomarkers using a hierarchical Bayesian model

Yada, Y.·Naoki, H.

View original source ↗Export metadata ↓

Abstract

Accumulation of amyloid-beta (A{beta}) in the brain is associated with neurodegeneration in Alzheimers disease and can be an indicator of early disease progression. Thus, the non-invasively and inexpensively observable features related to A{beta} accumulation are promising biomarkers. However, in the experimental discovery of biomarkers in preclinical models, A{beta} and biomarker candidates are usually not observed in identical sample populations. This study established a hierarchical Bayesian model that predicts A{beta} accumulation level solely from biomarker candidates by integrating incomplete information. The model was applied to 5xFAD mouse behavioral experimental data. The predicted A{beta} accumulation level obeyed the observed amount of A{beta} when multiple features were used for learning and prediction. Based on the evaluation of predictability, the results suggest that the proposed model can contribute to discovering novel biomarkers, that is, multivariate biomarkers relevant to the accumulation state of abnormal proteins.

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Yada, Y., Naoki, H.. 2022-10-24. Prediction of amyloid β accumulation from multiple biomarkers using a hierarchical Bayesian model. https://doi.org/10.1101/2022.10.21.513271

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Different hippocampal subfield volumes predict source memory performance and general cognitive ability in an adult lifespan sample

Modest positive associations between episodic memory performance and whole hippocampal and hippocampal subfield volumes have been reported in numerous prior studies. A smaller number of studies have reported associations between hippocampal volume and performance on tests of non-mnemonic cognition. The present study examined whether these associations were evident in a lifespan sample of cognitively healthy adults. Of particular interest was whether any identified associations were sensitive to age, and whether associations between subfield volumes and mnemonic and non-mnemonic performance were subfield dependent. We acquired high-resolution T1- and T2-weighted structural images from 163 adults (18-87 years of age). Participants also undertook a comprehensive neuropsychological test battery and an in-scanner test of source memory. Principal components analysis was employed to reduce the neuropsychological test scores to 5 cognitive components. Two components reflected memory performance while the other three reflected different aspects of non-mnemonic cognition. Hippocampal subfields (Cornu Ammonis (CA)1, CA2-3, dentate gyrus (DG) and subiculum) were segmented and measured with the Automated Segmentation of Hippocampus Subfields (ASHS) package. Source memory performance was selectively associated across participants with CA2-3 volume. By contrast, both mnemonic and non-mnemonic component scores derived from the test battery were associated exclusively with the volume of the DG. All associations were age-invariant. The findings indicate that different cognitive domains can be dissociated by virtue of their associations with different hippocampal subfields. Of importance, these associations appear to be life-long and hence are unlikely to reflect individual differences in age-related decline in structural integrity.

neuroscience↗

bioRxiv2026

Cell type specific astrocytic feedback regulates excitation inhibition balance and cortical network dynamics

Astrocytes actively regulate synaptic transmission and neuronal excitability, yet their role in orchestrating macroscopic cortical network regimes and slow-wave oscillations remains an active area of reasearch. This study investigates how bidirectional neuron astrocyte interactions shape emergent population dynamics using a computational network model of excitatory and inhibitory neurons coupled to an astrocyte. The results identify astrocytic feedback topology, rather than astrocytic coupling strength alone, as a key determinant of emergent cortical network dynamics. By systematically dissecting pathway-specific connectivity, it has been shown that the neuronal population driving astrocytic activation and the neuronal population receiving gliotransmission jointly determine whether the network occupies asynchronous irregular (AI), synchronous irregular (SI), synchronous regular(SR), asynchronous regular(AR) or quiescent regimes.Directing gliotransmission selectively onto excitatory neurons consistently promotes population synchrony regardless of the population influencing astrocytic dynamics, whereas selective modulation of inhibitory interneurons induces network quiescence via strong suppression. Under dual-target gliotransmission, network synchrony is dictated by the population driving astrocytic dynamics: excitatory-only drive promotes synchrony, while combined or inhibitory-specific drive preserves asynchronous states. Furthermore, the model reveals that astrocytic signaling kinetics provide an additional temporal control mechanism that regulates the frequency and persistence of self sustained up states.

neuroscience↗

bioRxiv2026

VCP inhibition prevents cone photoreceptor degeneration in the cpfl1 mouse model of achromatopsia

Achromatopsia (ACHM) is a rare autosomal recessive retinal disorder characterized by absent cone photoreceptor function from early life, leading to severe visual impairment. Mutations in genes involved in the cone phototransduction cascade frequently result in elevated cyclic guanosine monophosphate (cGMP) levels and activation of stress pathways, including endoplasmic reticulum (ER) stress and the unfolded protein response. Targeting common downstream mechanisms rather than individual mutations may provide a broadly applicable therapeutic strategy. Here, we investigated whether pharmacological inhibition of valosin-containing protein (VCP), a key regulator of ER and protein homeostasis, can prevent cone degeneration in the spontaneous cone photoreceptor function loss 1 (cpfl1) mouse model of ACHM. Organotypic culture of retinal explants from cpfl1 mice were treated with the selective VCP inhibitor ML240. Cone survival, cell death, opsin expression and localization were assessed by TUNEL assay, immunohistochemistry, and quantitative image analysis. ML240 treatment significantly increased cone density and improved cone opsin expression and trafficking to the outer segments (OSs) in cpfl1 explants compared to controls. Importantly, rhodopsin trafficking in rod photoreceptors was unaffected, indicating that VCP inhibition did not impair normal rod phototransduction. These findings demonstrate that VCP inhibition by ML240 effectively preserves cone photoreceptors and improves cone-specific functional markers in the cpfl1 model. Targeting VCP may represent a mutation-independent therapeutic strategy for preventing cone death in ACHM.

neuroscience↗