Biology subjects

Ohta, H.

Publications and source records attributed to Ohta, H..

12 recordsLinked to original sources

bioRxiv2026

Reduced EEG Complexity and Its Association with Social Communication in Adults with Autism Spectrum Disorder: A Multiscale Entropy Study

Background: Brain functions emerge from temporally organized neural dynamics, and an appropriate level of neural complexity may support flexible information processing. Electroencephalographic (EEG) studies using multiscale entropy (MSE), which quantifies signal complexity across multiple temporal scales, have reported reduced MSE at longer scales in individuals with autism spectrum disorder (ASD). However, most evidence comes from studies of infant and child samples, leaving adult data scarce, and the associations between reduced MSE, clinical symptoms, and social information processing are insufficiently understood. Methods: We recorded and analyzed EEG data from adults with ASD (n = 47) and typically developing (TD) controls (n = 40) during eyes-closed rest and two movie viewing conditions: Inscapes, comprising dynamically changing abstract visual patterns, and Partly Cloudy, an emotionally engaging animated social narrative. Group and condition effects were assessed using cluster-based permutation tests, and associations between MSE and Social Affect (SA) scores from the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), as well as group differences in event-related MSE changes, were examined using linear mixed-effects models. Results: Across conditions, adults with ASD showed lower MSE at longer scales ({tau} = 16-30), corresponding to effective sampling rates of 12.50-6.67 Hz in the coarse-grained time series, than TD adults. Longer-scale MSE within the ASD-TD difference cluster was negatively associated with ADOS-2 SA scores across diagnostic groups. The difference in event-related MSE change between Social and Non-Social conditions, comparing empathic-pain and mentalizing events in Partly Cloudy with temporally matched non-social windows in Inscapes, was smaller in ASD participants than in TD participants. No significant difference between Social and Non-Social windows was observed among ASD participants, whereas TD participants showed significantly greater MSE change during Social than Non-Social windows. Limitations: This study used a modest sample without an independent replication cohort, and the short event windows limited the precision of the MSE estimation. Conclusions: Reduced longer-scale MSE extends to adults with ASD and is associated with higher ADOS-2 SA scores across diagnostic groups. Event-related findings further suggest attenuated differentiation of longer-scale MSE between socially relevant and matched non-social windows in ASD.

neuroscience↗

bioRxiv2025

Iron deposition and functional connectivity alterations in the right substantia nigra of adult males with autism

The substantia nigra (SN) is a midbrain nucleus implicated not only in motor control and reward processing but also in higher-order cognitive functions. Iron homeostasis in this region is essential for neurotransmitter synthesis, especially for dopamine, and thus, iron dysregulation may contribute to the symptomatology of autism spectrum disorder (ASD). However, iron deposition and functional circuits of the SN in the autistic brain remain underexplored. This study investigated iron deposition and functional connectivity (FC) of the SN in 53 adult males with ASD and 99 typically developing controls using quantitative susceptibility mapping and resting-state fMRI. Compared to controls, the ASD group exhibited higher magnetic susceptibility in the right SN, suggesting elevated iron deposition. Within the ASD group, higher iron deposition was associated with more severe socio-communicative deficits and reduced sensory-seeking behavior. Seed-based FC analyses further revealed that the ASD group exhibited stronger FC between the right SN and bilateral visual cortices and reduced FC with the right superior frontal gyrus. These results highlight the critical role of SN in the autistic brain and indicate that altered iron homeostasis in the SN may contribute to disruptions in the dopaminergic system that underlie the core symptoms of ASD.

neuroscience↗

bioRxiv2024

Stress-induced brain extracellular vesicles ameliorate anxiety behaviour.

Extracellular vesicles (EVs), nano particles secreted by all types of cells, serve as a communication network, carrying information through the bloodstream to distant cells1,2. Notably, brain cells secrete EVs that play a crucial role in regulating neurological functions3-5. Meanwhile the brain detects acute stress and activates mechanisms to enhance stress resistance and maintain homeostasis6,7. However, the specific contribution of brain-derived extracellular vesicles (BDEVs) in modulating the stress response remains elusive. Here we found that administration of the acute stress-induced BDEVs to mice reduced anxiety-related behaviours, and this reduction was also induced by the administration of only three microRNAs (miRNAs) (miR-199a-3p, miR-99b-3p and miR-140-5p) included in the acute stress-induced BDEVs. Furthermore, we showed that miR-199a-3p contributes to the mechanism of the anxiolytic effect through the suppression of Mecp2 in neurons. These findings elucidate the role of BDEVs in modulating mental activity under acute stress and provide insights into the underlying molecular mechanisms. Our results open up new avenues for therapeutic strategies in the treatment of anxiety disorders using EVs or miRNAs.

animal behavior and cognition↗

bioRxiv2023

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P<0.05, family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

neuroscience↗

bioRxiv2021

Effects of upgrading acquisition-techniques and harmonization methods: A multi-modal MRI study with implications for longitudinal designs

A downside of upgrading MRI acquisition sequences is the discontinuity of technological homogeneity of the MRI data. It hampers combining new and old datasets, especially in a longitudinal design. Characterizing upgrading effects on multiple brain parameters and examining the efficacy of harmonization methods are essential. This study investigated the upgrading effects on three structural parameters, including cortical thickness (CT), surface area (SA), cortical volume (CV), and resting-state functional connectivity (rs-FC) collected from 64 healthy volunteers. We used two evaluation metrics, Cohens d and classification accuracy, to quantify the effects. In classification analyses, we built classifiers for differentiating the protocols from brain parameters. We investigated the efficacy of three harmonization methods, including traveling subject (TS), TS-ComBat, and ComBat methods, and the sufficient number of participants for eliminating the effects on the evaluation metrics. Finally, we performed age prediction as an example to confirm that harmonization methods retained biological information. The results without harmonization methods revealed small to large mean Cohens d values on brain parameters (CT:0.85, SA:0.66, CV:0.68, and rs-FC:0.24) with better classification accuracy (>92% accuracy). With harmonization methods, Cohens d values approached zero. Classification performance reached the chance level with TS-based techniques when data from less than 26 participants were used for estimating the effects, while the Combat method required more participants. Furthermore, harmonization methods improved age prediction performance, except for the ComBat method. These results suggest that acquiring TS data is essential to preserve the continuity of MRI data.

neuroscience↗

bioRxiv2021

Excretion of triacylglycerol as a matrix lipid facilitating apoplastic accumulation of a lipophilic metabolite shikonin.

Plants produce a large variety of lipophilic metabolites, many of which are secreted by cells and accumulated in apoplasts. The mechanism of secretion remains largely unknown, because hydrophobic metabolites, which may form oil droplets or crystals in cytosol, inducing cell death, cannot be directly secreted by transporters. Moreover, some secondary metabolic lipids react with cytosolic components leading to their decomposition. Lipophilic metabolites should thus be solubilized by matrix lipids and compartmentalized by membrane lipids. The mechanism of lipophilic metabolite secretion was assessed using shikonin, a red naphthoquinone lipid, in Lithospermum erythrorhizon. Cell secretion of shikonin also involved the secretion of about 30% of triacylglycerol (TAG), composed predominantly of saturated fatty acids. Shikonin production was associated with the induction of large amounts of the membrane lipid phosphatidylcholine. Together with in vitro reconstitution, these findings suggest a novel role for TAG as a matrix lipid for the secretion of lipophilic metabolites.

plant biology↗

bioRxiv2021

Whole-genome sequencing and analysis of two azaleas, Rhododendron ripense and Rhododendron kiyosumense

To enhance the genomics and genetics of azalea, the whole-genome sequences of two species of Rhododendron were determined and analyzed in this study: Rhododendron ripense, the cytoplasmic donor and ancestral species of large-flowered and evergreen azalea cultivars, respectively; and Rhododendron kiyosumense, a native of Chiba prefecture (Japan) seldomly bred and cultivated. A chromosome-level genome sequence assembly of R. ripense was constructed by single-molecule real-time (SMRT) sequencing and genetic mapping, while the genome sequence of R. kiyosumense was assembled using the single-tube long fragment read (stLFR) sequencing technology. The R. ripense genome assembly contained 319 contigs (506.7 Mb; N50 length: 2.5 Mb) and was assigned to the genetic map to establish 13 pseudomolecule sequences. On the other hand, the genome of R. kiyosumense was assembled into 32,308 contigs (601.9 Mb; N50 length: 245.7 kb). A total of 34,606 genes were predicted in the R. ripense genome, while 35,785 flower and 48,041 leaf transcript isoforms were identified in R. kiyosumense through Iso-Seq analysis. Overall, the genome sequence information generated in this study enhances our understanding of genome evolution in the Ericales and reveals the phylogenetic relationship of closely-related species. This information will also facilitate the development of phenotypically attractive azalea cultivars.

genomics↗

bioRxiv2021

Transcriptomic analysis of resistant and susceptible responses in a new model root-knot nematode infection system using Solanum torvum and Meloidogyne arenaria

Root-knot nematodes (RKNs) are among the most devastating pests in agriculture. Solanum torvum Sw. (turkey berry) has been used as a rootstock for eggplant (aubergine) cultivation because of its resistance to RKNs, including Meloidogyne incognita and M. arenaria. We previously found that a pathotype of M. arenaria, A2-J, is able to infect and propagate in S. torvum. In vitro infection assays showed that S. torvum induces the accumulation of brown pigments during avirulent pathotype A2-O infection, but not during virulent A2-J infection. This experimental system is advantageous because resistant and susceptible responses can be distinguished within a few days, and because a single plant genome can yield information about both resistant and susceptible responses. Comparative RNA-sequencing analysis of S. torvum inoculated with A2-J and A2-O at early stages of infection was used to parse the specific resistance and susceptible responses. Infection with A2-J did not induce statistically significant changes in gene expression within one day post-inoculation (DPI), but afterward, A2-J specifically induced the expression of chalcone synthase, spermidine synthase, and genes related to cell wall modification and transmembrane transport. Infection with A2-O rapidly induced the expression of genes encoding class III peroxidases, sesquiterpene synthases, and fatty acid desaturases at 1 DPI, followed by genes involved in defense, hormone signaling, and the biosynthesis of lignin at 3 DPI. Both isolates induced the expression of suberin biosynthetic genes, which may be triggered by wounding during nematode infection. Histochemical analysis revealed that A2-O, but not A2-J, induced lignin accumulation at the root tip, suggesting that physical reinforcement of cell walls with lignin is an important defense response against nematodes. The S. torvum-RKN system can provide a molecular basis for understanding plant-nematode interactions.

plant biology↗

bioRxiv2020

The Japan Monkey Centre Primates Brain Imaging Repository of high-resolution postmortem magnetic resonance imaging: the second phase of the archive of digital records

A comparison of neuroanatomical features of the brain between humans and our evolutionary relatives, nonhuman primates, is key to understanding the human brain system and the neural basis of mental and neurological disorders. Although most comparative MRI studies of human and nonhuman primate brains have been based on brains of primates that had been used as subjects in experiments, it is essential to investigate various species of nonhuman primates in order to elucidate and interpret the diversity of neuroanatomy features among humans and nonhuman primates. To develop a research platform for this purpose, it is necessary to harmonize the scientific contributions of studies with the standards of animal ethics, animal welfare, and the conservation of brain information for long-term continuation of the field. In previous research, we first developed an open-resource repository of anatomical images obtained using 9.4-T ex vivo MRI of postmortem brain samples from 12 nonhuman primate species, and which are stored at the Japan Monkey Centre. In the present study, as a second phase, we released a collection of T2-weighted images and diffusion tensor images obtained in nine species: white-throated capuchin, Bolivian squirrel monkey, stump-tailed macaque, Tibet monkey, Sykes monkey, Assamese macaque, pig-tailed macaque, crested macaque, and chimpanzee. Our image repository should facilitate scientific discoveries in the field of comparative neuroscience. This repository can also promote animal ethics and animal welfare in experiments with nonhuman primate models by optimizing methods for in vivo and ex vivo MRI scanning of brains and supporting veterinary neuroradiological education. In addition, the repository is expected to contribute to conservation, preserving information about the brains of various primates, including endangered species, in a permanent digital form.

neuroscience↗

bioRxiv2019

White matter alterations in autism spectrum disorder and attention-deficit/hyperactivity disorder in relation to sensory profile

BackgroundAutism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) have high rates of co-occurrence and share atypical behavioral characteristics, including sensory problems. The present diffusion tensor imaging (DTI) study was conducted to examine whether and how white matter abnormalities are observed in adult populations with developmental disabilities (DD) and to determine how brain-sensory relationships are either shared between or distinct to ASD and ADHD.\n\nMethodsWe collected DTI data from adult developmental disorder (DD) populations (a primary diagnosis of ASD: n=105, ADHD: n=55) as well as age and sex matched typically developed (TD) participants (n=58). Voxel-wise fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity (RD) were analyzed using tract-based spatial statistics. The severities of sensory problems were assessed using the Adolescent/Adult Sensory Profile (AASP).\n\nResultsCategorical analyses identified voxel clusters showing significant effects of DD on FA and RD in the posterior portion of the corpus callosum and its extension in the right hemisphere. Furthermore, regression analyses using the AASP scores revealed that slopes in relationships of FA or RD with the degree of sensory problems were parallel between the two DDs in large parts of the affected corpus callosum regions, although a small but significant cluster did exist showing interaction between the diagnosis of DD and an AASP subscale score on RD.\n\nConclusionsThese results indicate that white matter abnormalities and their relationships to sensory problems are largely shared between ASD and ADHD, with localized abnormalities showing significant between-diagnosis differences within DD. (247 words)

neuroscience↗

bioRxiv2019

Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder

AimPrior structural MRI studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter presents the endophenotype. Further, because they did not enroll siblings of TD people, they underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to solve these questions.\n\nMethodsWe recruited 30 pairs of adult male siblings (15 of them have an ASD endophenotype, other 15 pairs not) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings.\n\nResultsA sparse logistic regression with a leave-one-pair-out cross-validation showed the highest accuracy for the identification of an ASD endophenotype (73.3%) with the SD compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions-of-interest accounting for multiple comparisons.\n\nConclusionsThis proof-of-concept study suggests that an ASD endophenotype emerges in SD and that neural correlates for the clinical diagnosis can be dissociated from the endophenotype when we accounted for the difference between TD siblings. (248/250 words)

neuroscience↗

bioRxiv2018

Machine learning approach to identify resting-state functional connectivity pattern serving as an endophenotype of autism spectrum disorder

Endophenotype refers to a measurable and heritable component between genetics and diagnosis and exists in both individuals with a diagnosis and their unaffected siblings. We aimed to identify a pattern of endophenotype consisted of multiple connections. We enrolled adult male individuals with autism spectrum disorder (ASD) endophenotype (i.e., individuals with ASD and their unaffected siblings) and individuals without ASD endophenotype (i.e., pairs of typical development (TD) siblings) and utilized a machine learning approach to classify people with and without endophenotypes, based on resting-state functional connections (FCs). A sparse logistic regression successfully classified people as to the endophenotype (area under the curve=0.78, classification accuracy=75%), suggesting the existence of endophenotype pattern. A binomial test identified that nine FCs were consistently selected as inputs for the classifier. The least absolute shrinkage and selection operator with these nine FCs predicted severity of communication impairment among individuals with ASD (r=0.68, p=0.021). In addition, two of the nine FCs were statistically significantly correlated with the severity of communication impairment (r=0.81, p=0.0026 and r=-0.60, p=0.049). The current findings suggest that an ASD endophenotype pattern exists in FCs with a multivariate manner and is associated with clinical ASD phenotype.

neuroscience↗