Biology subjects

Yoshimoto, J.

Publications and source records attributed to Yoshimoto, J..

5 recordsLinked to original sources

bioRxiv2024

Prediction of antidepressant treatment response with thalamo-somatomotor functional connectivity revealed by generalizable stratification of depressed patients

Major depressive disorder (MDD) is diagnosed based on symptoms and signs without relying on physical, biological, or cognitive tests. MDD patients exhibit a wide range of complex symptoms, and it is assumed that there are diverse underlying neurobiological backgrounds, possibly composed of several subtypes with relatively homogeneous biological features. Initiatives, including the Research Domain Criteria, emphasize the importance of biologically stratifying MDD patients into homogeneous subtypes using a data-driven approach while utilizing genetic, neuroscience, and cognitive information. If biomarkers can stratify MDD patients into biologically homogeneous subtypes at the first episode of depression, personalized precision medicine may be within our scope. Some pioneering studies have used resting-state functional brain connectivity (rs-FC) for stratification and predicted differential responses to various treatments for different subtypes. However, to our knowledge, little research has demonstrated reproducibility (i.e., generalizability) of stratification markers in independent validation cohorts. This issue may be due to inherent measurement and sampling biases in multi-site fMRI data, or overfitting of machine learning algorithms to discovery cohorts with small sample sizes, i.e., a lack of appropriate machine learning algorithms for generalizable stratification. To address this problem, we have constructed a multi-site, multi-disorder fMRI database with prospectively and retrospectively harmonized data from thousands of samples and proposed a hierarchical supervised/unsupervised learning strategy. In line with this strategy, our previous research first developed generalizable MDD diagnostic biomarkers using this fMRI database of MDD patients via supervised learning. The MDD diagnostic biomarker determines the importance of thousands to tens of thousands of rs-FCs across the whole brain for MDD diagnosis. In this study, we constructed stratification markers for MDD patients using unsupervised learning (Multiple co-clustering) with a subset of top-ranked rs-FCs in the MDD diagnostic biomarker. We developed a method to evaluate the clustering stability between two independent datasets as a generalization metric of stratification biomarkers. To discover stratification biomarkers with high stability across datasets, we utilized two multi-site datasets with substantial differences in data acquisition facilities and fMRI measurement protocols (Dataset-1: a dataset of 138 depressed patients obtained with a unified measurement protocol across three facilities; Dataset-2: a dataset of 181 depressed patients obtained with non-unified measurement protocols across four facilities, distinct from Dataset-1). Starting from several diagnostic biomarkers, we constructed some stratification markers and identified the stratification biomarker with the highest clustering stability between the two datasets. This stratification biomarker was based on several rs-FCs between the thalamus and the postcentral gyrus, and the MDD subgroups stratified by this biomarker showed significantly different treatment responsiveness to a selective serotonin reuptake inhibitor (SSRI). By narrowing down whole-brain rs-FCs using MDD diagnostic biomarkers and further dividing the rs-FCs using multiple co-clustering, the feature dimension was significantly reduced, thereby avoiding overfitting to the training data and successfully constructing stratification biomarkers that are highly stable between independent datasets, i.e., have generalizability. Furthermore, the correlation between MDD subgroups and antidepressant treatment response was demonstrated, suggesting the potential for achieving personalized precision medicine for MDD.

neuroscience↗

bioRxiv2023

Intracellular diversity of WNV within circulating avian peripheral blood mononuclear cells reveals host-dependent patterns of polyinfection

Error-prone replication of RNA viruses generates the genetic diversity required for adaptation within rapidly changing environments. Thus, arthropod-borne virus (arbovirus) populations exist in nature as mutant swarms that are maintained between arthropods and vertebrates. Previous studies have demonstrated that West Nile virus (WNV) population dynamics are host dependent: In American crows, which experience extremely high viremia, purifying selection is weak and population diversity is high compared to American robins, which have 100 to 1000-fold lower viremia. WNV passed in robins experiences fitness gains, whereas that passed in crows does not. Therefore, we tested the hypothesis that high crow viremia allows higher genetic diversity within individual avian peripheral-blood mononuclear cells (PBMCs), reasoning that this could have produced the previously observed host-specific differences in genetic diversity and fitness. Specifically, we infected cells and birds with a novel, barcoded version of WNV and sequenced viral RNA from single cells to quantify the number of WNV barcodes that each contained. Our results demonstrate that the richness of WNV populations within crows far exceeds that in robins. Similarly, rare WNV variants were maintained by crows more frequently than by robins. Our results suggest that increased viremia in crows relative to robins leads to maintenance of defective genomes and less prevalent variants, presumably through complementation. Our findings further suggest that weaker purifying selection in highly susceptible crows is attributable to this higher viremia, polyinfections and complementation. These studies further document the role of particular, ecologically relevant hosts in shaping virus population structure. Author SummaryWNV mutational diversity in vertebrates is species-dependent. In crows, low frequency variants are common, and viral populations are more diverse. In robins, fewer mutations become permanent fixtures of the overall viral population. We infected crows, robins and a chicken cell line with a genetically marked (barcoded) WNV. Higher levels of virus led to multiple unique WNV genomes infecting individual cells, even when a genotype was present at low levels in the input viral stock. Our findings suggest that higher levels of circulating virus in natural hosts allow less fit viruses to survive in RNA virus populations through complementation by more fit viruses. This is significant as it allows less represented and less fit viruses to be maintained at low levels until they potentially emerge when virus environments change. Overall our data reveal new insights on the relationships between host susceptibility to high viremia and virus evolution.

microbiology↗

bioRxiv2022

Primary motor cortex drives expressive facial movements related to reward processing in mice

During reward-based learning tasks, animals make orofacial movements that globally influence brain activity at the timings of reward expectation and acquisition. These orofacial movements are not explicitly instructed and typically appear along with goal-directed behaviors. Here we show that reinforcing optogenetic stimulation of midbrain dopamine neurons (oDAS) in mice is sufficient to induce orofacial movements in the whiskers and nose without accompanying goal-directed behaviors. Pavlovian conditioning with a sensory cue and oDAS elicited cue-locked and oDAS aligned orofacial movements, which were distinguishable by a machine learning model. Inhibition or knock-out of dopamine D1 receptors in the nucleus accumbens inhibited oDAS-induced motion but spared cue-locked motion, suggesting differential neural regulation of these two types of orofacial motions. In contrast, inactivation of the whisker primary motor cortex (wM1) abolished both types of orofacial movements. We found specific neuronal populations in wM1 representing either oDAS-aligned or cue-locked whisker movements. Notably, optogenetic stimulation of wM1 neurons successfully replicated these two types of movements. Our results thus suggest that accumbal D1 receptor-dependent and -independent neuronal signals converge in the wM1 for facilitating uninstructed orofacial movements during a reward-based learning task.

neuroscience↗

bioRxiv2021

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

Neurofeedback (NF) aptitude, which refers to an individuals ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation systems characteristics in task-free resting-state brain activity.

neuroscience↗

bioRxiv2019

Remote control of neural function by X-ray-induced scintillation

Scintillators emit visible luminescence when irradiated with X-rays. Given the unlimited tissue penetration of X-rays, the employment of scintillators could enable remote optogenetic control of neural functions at any depth of the brain. Here we show that a yellow-emitting inorganic scintillator, Ce-doped Gd3(Al,Ga)5O12 (Ce:GAGG), could effectively activate red-shifted excitatory and inhibitory opsins, ChRmine and GtACR1, respectively. Using injectable Ce:GAGG microparticles, we successfully activated and inhibited midbrain dopamine neurons in freely moving mice by X-ray irradiation, producing bidirectional modulation of place preference behavior. Ce:GAGG microparticles were non-cytotoxic and biocompatible, allowing for chronic implantation. Pulsed X-ray irradiation at a clinical dose level was sufficient to elicit behavioral changes without reducing the number of radiosensitive cells in the brain and bone marrow. Thus, scintillator-mediated optogenetics enables less invasive, wireless control of cellular functions at any tissue depth in living animals, expanding X-ray applications to functional studies of biology and medicine.

neuroscience↗