Tohoku University · Biochemistry, Genetics and Molecular Biology
Professor Yuta Takahashi's research lab specializes in the intersection of neuroscience, psychiatry, and molecular biology, focusing on the pathophysiological mechanisms underlying psychiatric disorders and amyloid-related diseases. The lab investigates microglial and monocytic immune activation in psychiatric conditions such as schizophrenia and depression, exploring neuro-immune interactions and their implications for disease progression. Additionally, the lab develops advanced computational and systems biology approaches—such as machine learning and polygenic prediction models—to identify metabolic and genetic biomarkers for psychiatric phenotypes. A significant component of the research also involves the structural engineering of amyloid fibrils for both pathological insight and potential biomaterial applications.
Figures are computed from collected data and may differ slightly.
This large, endoscopy-based study demonstrated that CE prevalence increased in non-HIV-infected patients but decreased in HIV-infected patients over 13 years. Risk analysis revealed that increasing age, HIV infection, and corticosteroids use, particularly at higher doses, were independently associated with CE, but alcohol, other infections, diabetes, anticancer drugs, and PPIs use were not.
The misfolding process of the amyloidogenic proteins such as prion proteins is mimicked by the α- to β-structural transition of a peptide obtained by introducing adamantanecarbonyl groups at the N-terminals of two linked α-helices. The α- to β-transition (left to right of graph) coincided with the formation of fibrils (inset, bottom right), which further assembled into larger amyloid deposits.
A wide variety of studies have identified microglial activation in psychiatric disorders, such as schizophrenia, bipolar disorder, and major depressive disorder. Relatively fewer, but robust, studies have detected activation of peripheral monocytic cells in psychiatric disorders. Considering the origin of microglia, as well as neuropsychoimmune interactions in the context of the pathophysiology of psychiatric disorders, it is reasonable to speculate that microglia interact with peripheral monocy
The amyloid fibril is a misfolded and undesirable state for proteins that has been proposed to be a causative agent for a variety of fatal diseases known as amyloid diseases, such as Alzheimer's and prion diseases. However, the fibril has a highly ordered tertiary structure in which numerous β-strand polypeptide chains align in a regular pattern. Thus, this kind of fibril has the potential to be engineered into proteinaceous materials. Amyloid fibrils of misfolded proteins primarily comprise a s
To solve major limitations in algorithms for the metabolite-based prediction of psychiatric phenotypes, a novel prediction model for depressive symptoms based on nonlinear feature selection machine learning, the Hilbert-Schmidt independence criterion least absolute shrinkage and selection operator (HSIC Lasso) algorithm, was developed and applied to a metabolomic dataset with the largest sample size to date. In total, 897 population-based subjects were recruited from the communities affected by
The accuracy of previous genetic studies in predicting polygenic psychiatric phenotypes has been limited mainly due to the limited power in distinguishing truly susceptible variants from null variants and the resulting overfitting. A novel prediction algorithm, Smooth-Threshold Multivariate Genetic Prediction (STMGP), was applied to improve the genome-based prediction of psychiatric phenotypes by decreasing overfitting through selecting variants and building a penalized regression model. Predict
The mechanism underlying the emergence of emotional categories from visual facial expression information during the developmental process is largely unknown. Therefore, this study proposes a system-level explanation for understanding the facial emotion recognition process and its alteration in autism spectrum disorder (ASD) from the perspective of predictive processing theory. Predictive processing for facial emotion recognition was implemented as a hierarchical recurrent neural network (RNN). T
Upper gastrointestinal (GI) symptoms are common in both HIV and non-HIV-infected patients, but the difference of GI symptom severity between 2 groups remains unknown. Candida esophagitis and erosive esophagitis, 2 major types of esophagitis, are seen in both HIV and non-HIV-infected patients, but differences in GI symptoms that are predictive of esophagitis between 2 groups remain unknown. We aimed to determine whether GI symptoms differ between HIV-infected and non-HIV-infected patients, and id
At the forefront of bridging computational brain modeling with personalized medicine, this study introduces a novel, real-time, electrocorticogram (ECoG) simulator, based on the digital twin brain concept. Utilizing advanced data assimilation techniques, specifically a Variational Bayesian Recurrent Neural Network model with hierarchical latent units, the simulator dynamically predicts ECoG signals reflecting real-time brain latent states. By assimilating broad ECoG signals from macaque monkeys
We produced spherical superconducting submicron particles by laser ablation of their base metal tips in superfluid helium, and trapped them using a quadrupole magnetic field owing to the diamagnetism caused by the Meissner effect. We also measured their critical temperatures of superconductivity, by observing the threshold temperatures for the confinement of superconducting submicron particles in the trap.
The nature of the recovery process of posttraumatic stress disorder (PTSD) symptoms is multifactorial. The Massive Parallel Limitless-Arity Multiple-testing Procedure (MP-LAMP), which was developed to detect significant combinational risk factors comprehensively, was utilized to reveal hidden combinational risk factors to explain the long-term trajectory of the PTSD symptoms. In 624 population-based subjects severely affected by the Great East Japan Earthquake, 61 potential risk factors encompas
Functional connectivity (FC) and neural excitability may interact to affect symptoms of autism spectrum disorder (ASD). We tested this hypothesis with neural network simulations, and applied it with functional magnetic resonance imaging (fMRI). A hierarchical recurrent neural network embodying predictive processing theory was subjected to a facial emotion recognition task. Neural network simulations examined the effects of FC and neural excitability on changes in neural representations by develo
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