Brain最新文献

Computational neuropsychiatry is a leading discipline to explain psychopathology in terms of neuronal message passing, distributed processing, and belief propagation in neuronal networks. Active Inference (AI) has been one of the ways of representing this dysfunctional signal processing. It involves that all neuronal processing and action selection can be explained by maximizing Bayesian model evidence, or minimizing variational free energy. Following these principles, it has been suggest that dysconnection in neuronal network results in aberrant belief updating and erroneous inference, leading to psychiatric and neurologic symptoms. However, there is a classic distinction between disorders of inference (or synaptopathy - including the majority of psychiatric disorders), and disorders of brain function (including vascular neurological pathologies and severe forms of tauopathy and synucleinopathies). This distinction is generally based on the idea that synaptopathies impair neuromodulatory precision weighting, leading to rigid inferences or heightened sensitivity to noise, while disorders of brain function are linked to damage in the nervous system (disconnection). This makes it challenging to apply the logic of the free energy principle. We suggest that this distinction will enable future models of neuropsychiatric symptoms to be improved by considering more than neuronal message passing.

Although the pathophysiology of migraine involves a complex ensemble of peripheral and central nervous system changes that remain incompletely understood, the activation and sensitization of the trigeminovascular system is believed to play a major role. However, non-invasive, in vivo neuroimaging studies investigating the underlying neural mechanisms of trigeminal system abnormalities in human migraine patients are limited. Here, we studied 60 patients with migraine (55 females, mean age ± SD: 36.28 ± 11.95 years) and 20 age-/sex-matched healthy controls (19 females, mean age ± SD: 35.45 ± 13.30 years) using ultra-high field 7 Tesla diffusion tensor imaging and functional MRI, as well as PET with the translocator protein ligand [11C]-PBR28. We evaluated MRI diffusivity measures and PET signal at the trigeminal nerve root, as well as brainstem functional MRI response to innocuous, ophthalmic trigeminal nerve territory stimulation. Patients with migraine demonstrated altered white matter microstructure at the trigeminal nerve root (n=53), including reduced fractional anisotropy, compared to healthy controls (n=18). Furthermore, in patients, lower fractional anisotropy was accompanied by 1) higher neuroinflammation (i.e. elevated [11C]-PBR28 PET signal) at the nerve root (n=36) and 2) lower functional MRI activation in an ipsilateral pontine cluster consistent with spinal trigeminal nucleus (n=51). These findings were more robust on the right side, which was consistent with the observation that right headache dominant patients demonstrated higher migraine severity compared to left headache dominant patients in our cohort. Multimodal imaging of the integrated neural mechanisms that characterize migraine underscores the importance of trigeminal system remodeling as both a key aspect of the dynamics underlying migraine pathophysiology and a target for therapeutic interventions.

Prions are assemblies of misfolded prion protein that cause several fatal and transmissible neurodegenerative diseases, with the most common phenotype in humans being sporadic Creutzfeldt-Jakob disease (sCJD). Aside from variation of the prion protein itself, molecular risk factors are not well understood. Prion and prion-like mechanisms are thought to underpin common neurodegenerative disorders meaning that the elucidation of mechanisms could have broad relevance. Herein we sought to further develop our understanding of the factors that confer risk of sCJD using a systematic gene prioritization and functional interpretation pipeline based on multiomic integrative analyses. We integrated the published sCJD genome-wide association study (GWAS) summary statistics with publicly available bulk brain and brain cell type gene and protein expression datasets. We performed multiple transcriptome and proteome-wide association studies (TWAS & PWAS) and Bayesian genetic colocalization analyses between sCJD risk association signals and multiple brain molecular quantitative trait loci signals. We then applied our systematic gene prioritization pipeline on the obtained results and nominated prioritized sCJD risk genes with risk-associated molecular mechanisms in a transcriptome and proteome-wide manner. Genetic upregulation of both gene and protein expression of syntaxin-6 (STX6) in the brain was associated with sCJD risk in multiple datasets, with a risk-associated gene expression regulation specific to oligodendrocytes. Similarly, increased gene and protein expression of protein disulfide isomerase family A member 4 (PDIA4), involved in the unfolded protein response, was linked to increased disease risk, particularly in excitatory neurons. Protein expression of mesencephalic astrocyte derived neurotrophic factor (MANF), involved in protection against endoplasmic reticulum stress and sulfatide binding (linking to the enzyme in the final step of sulfatide synthesis, encoded by sCJD risk gene GAL3ST1), was identified as protective against sCJD. In total 32 genes were prioritized into two tiers based on the level of evidence and confidence for further studies. This study provides insights into the genetically-associated molecular mechanisms underlying sCJD susceptibility and prioritizes several specific hypotheses for exploration beyond the prion protein itself and beyond the previously highlighted sCJD risk loci through the newly prioritized sCJD risk genes and mechanisms. These findings highlight the importance of glial cells, sulfatides and the excitatory neuron unfolded protein response in sCJD pathogenesis.