Biology subjects

Wang, M.-Y.

Publications and source records attributed to Wang, M.-Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Population-wide variation in connectopic organization of cerebral language hubs

The uniquely human capacity for language is supported by a distributed brain network with cerebral cortical hubs in the left inferior frontal gyrus (LIFG) and left superior temporal sulcus (LSTS). Individual differences in the graded spatial organization of function across these regions may provide sensitive phenotypes for behavioural and genetic association analyses, to better understand the biological underpinnings of language. In 41,437 UK Biobank participants we applied connectopic mapping to the LIFG and LSTS. This approach maps spatial changes across a region in terms of connectivity with the rest of the brain, based on resting state functional imaging. On average, we found that Brodmann Area (BA) 44, BA 45 and the posterior LSTS were strongly connected to the superior and inferior parietal lobe and the dorsal attention and frontoparietal networks, whereas BA 47 and the medial LSTS were strongly connected to superior frontal areas BA 8B and BA 9, and the default mode network more broadly. However, there was extensive population-wide variation in these graded connectopic patterns, which significantly mediated the effects of polygenic scores for reading ability and educational attainment on performance on a vocabulary task. Furthermore we identified 3 genomic loci displaying multivariate association patterns with these connectopic maps, one of which coincides with a long non-coding RNA, LINC01165, with potential relevance in human evolution. Overall, connectopic mapping produced fewer significant genetic association findings and lower heritability (range from 0.3 to 9.4%) than previous parcel-based approaches for mapping language network connectivity. These observations suggest higher genetic complexity and/or prominent roles for environmental or random developmental effects on these connectopic maps.

neuroscience↗

bioRxiv2025

Integrating brain structure and function for the neurobiology and genetics of language

Brain structure and function have largely been studied separately in relation to the neurobiology and genetics of language. Here we used linked independent component analysis to integrate language network functional connectivity with brain volumetric and white matter structure in 32,677 UK Biobank participants, followed by analysis of behavioural, neurobiological and genetic correlates of the derived multimodal structure-function imaging components. Stronger functional connectivity between brain language areas was associated with increased volume of parts of the cerebellum and motor cortex, together with smaller ventricles and sensory parietal and occipital areas. The brain structure-function language components mediated an association between vocabulary level and polygenic scores for reading ability. We report 18 genomic loci associated with brain structure-function language components. Single-nucleotide polymorphism (SNP)-based heritability estimates for these components were 23-30%, and there was significant enrichment of heritability in primate-conserved genomic loci and fetal brain human-gained enhancer elements. This study revealed that structural correlates of functional language network connectivity extend well beyond previously defined language areas of the brain, and highlights the value of multimodal brain phenotyping for human neurogenetic discovery.

neuroscience↗

bioRxiv2025

Structural and functional brain asymmetry in relation to heterogeneous causes of situs inversus totalis

Various aspects of brain organization differ between the left and right hemispheres. Clues to the developmental origins of these asymmetries may be gained through associations with situs inversus totalis (SIT), a rare condition in which visceral organs are reversed on the left-right axis. In the largest previous brain imaging analyses of SIT (38 cases, 38 controls from Belgium), typical functional asymmetries such as left-hemisphere language dominance were mostly unaltered, but various aspects of asymmetrical cerebral structure - petalia, bending, and posterior venous anatomy - were often reversed in this condition. SIT can be a monogenic trait that arises from rare genetic variants, usually affecting motile cilia which help to create the embryonic left-right body axis. However, most SIT cases do not have obvious genetic causes and may arise from environmental or random effects during embryogenesis. We sequenced the genomes of 23 SIT cases and 23 controls from the Belgian brain imaging dataset and pooled with prior data from 15 cases and 15 controls. We aimed to discover whether there are altered brain asymmetries in SIT cases with disruptive DNA variants in ciliary genes, or in other types of genes, as compared to genetically unsolved cases. In total, 19 cases had likely causal variants affecting ciliary function, while 19 cases remained genetically unsolved. Functional and structural brain asymmetries were not significantly different in genetically solved versus unsolved SIT cases. Therefore, functional brain asymmetries seem largely independent of known mechanisms of visceral situs formation, while structural brain torque is altered in SIT regardless of the presence or absence of overt genetic causes.

neuroscience↗

bioRxiv2025

Perfect imperfections: seeking molecular and cellular asymmetries in the mouse brain

Although perfect symmetry is a mathematical ideal, many Bilateria exhibit left-right asymmetries of body, brain and behavior that are adaptive 1-3. In the human brain, various aspects of cognition are lateralized, including language 4 and handedness 5, which rely on left hemisphere dominance in most people. Brain hemispheric specialization can support parallel processing, neural efficiency, and action selection 3,6, while atypical structural or functional asymmetries are often found in neuropsychiatric disorders 7-10. Mice may be useful models for studying brain asymmetry because they show hemispheric differences of structure 11,12 and neurophysiology 13, but the extent to which molecular and cellular differences are involved remains unknown. We applied spatial transcriptomics with single molecule resolution to coronal sections from 31 adult mouse brains, to assess left-right differences of gene expression and cell types. Sections were chosen to capture the hippocampus and auditory cortex, as these two regions have shown the most prior evidence for functional asymmetry 13-15. In the hippocampus, Crhr1 (Corticotropin-Releasing Hormone Receptor 1) was more highly expressed in the pyramidal layers of CA1, CA3 and the dentate gyrus of the left hemisphere compared to the right. In the auditory cortex, three principal components capturing transcriptomic variation showed hemispheric differences, including prominent contributions from genes that have shown associations with human brain asymmetry. Overall cellular density and cell type proportions generally showed no significant hemispheric differences, with Car3 cortical excitatory neurons showing the most laterality. The transcriptional left-right differences that we found may relate to functional asymmetries for learning, memory and hearing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/675542v1_ufig1.gif" ALT="Figure 1"> View larger version (119K): org.highwire.dtl.DTLVardef@1530502org.highwire.dtl.DTLVardef@16dd244org.highwire.dtl.DTLVardef@107950corg.highwire.dtl.DTLVardef@ca52a3_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMolecular and cellular basis of functional brain asymmetry is barely known C_LIO_LISpatial transcriptomics with cellular resolution applied to mouse brain coronal sections C_LIO_LIGenes implicated in human brain asymmetry showed hemispheric differences in mice C_LIO_LINo hemispheric differences of cell type abundances C_LI

neuroscience↗

bioRxiv2025

A comparison of adiponectin-deficient mice reveals the fundamental role of intracellular adiponectin

Adiponectin is an important adipokine with insulin-sensitizing, anti-inflammatory, and anti-fibrotic properties. The physiological roles of adiponectin have been studied using global adiponectin knockout (KO) mice. However, the reported phenotypes of adiponectin KO mice vary based on the mouse lines generated by different strategies and investigators. We performed a head-to-head comparison of the adiponectin KO mice that were generated in Dallas, Houston and Osaka. RNAseq revealed that the expression of the bioactive domain of adiponectin - the globular domain - was preserved in the Houston and Osaka KO mice. A complete adiponectin KO model, such as the Dallas KO mouse, exhibits a lower body weight, the highest adipocyte mitochondrial function and displays a susceptibility to DNA damage-mediated lung fibrosis. The reconstitution of globular adiponectin into the Dallas KO mice prompted an increase in body weight and a partial recapitulation of the Osaka KO model transcriptome signature. The intracellular globular adiponectin form is important, as we found that globular adiponectin enhances PPAR{gamma} activity by modulating the coregulators interacting with PPAR{gamma}. Overall, the residual expression of globular adiponectin regulates adipose tissue metabolism by altering PPAR{gamma} activity, highlighting an important novel role of intracellular adiponectin.

physiology↗

bioRxiv2024

White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life

Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organization and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complemen-tary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno-and phenotypes is still debated. Hence, we inves-tigate how tract-based and whole WM skeleton parameters from different single- and multi-compartment dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52, 140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5, 844). Multi-compartment dMRI approaches provided the strongest WM associations with age, and unique insights into brain asymmetry. Kurto-sis was most indicative of PP and BMI. WM-based sex classifications and polygenic score associations for common psychiatric disorders and Alzheimers disease were similar across diffusion approaches. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life. Multi-compartment dMRI approaches, and particularly the examined Bayesian approach, provide additional information to conventional approaches in such examinations.

neuroscience↗

bioRxiv2024

Cross-sectional brain age assessments are limited in predicting future brain change

The concept of brain age (BA) describes an integrative imaging marker of brain health, often suggested to reflect ageing processes. However, the degree to which cross-sectional MRI features, including BA, reflect past, ongoing and future brain changes across different tissue types from macro-to microstructure remains controversial (Vidal-Pineiro et al. 2021). Here, we advance these findings by using multimodal imaging data of 39, 325 UK Biobank participants, aged 44 - 82 years at baseline and 2, 520 follow-ups within 1.12 - 6.90 years. In concordance with the original findings, we find insufficient evidence that BA reflects the rate of brain ageing. However, modality-specific differences in brain ages reflected the state of the brain, highlighting diffusion and multimodal MRI brain age as potentially useful cross-sectional markers.

neuroscience↗

bioRxiv2024

Adipogenin Dictates Adipose Tissue Expansion by Facilitating the Assembly of a Dodecameric Seipin Complex

Adipogenin (Adig) is an evolutionarily conserved microprotein and is highly expressed in adipose tissues and testis. Here, we identify Adig as a critical regulator for lipid droplet formation in adipocytes. We determine that Adig interacts directly with seipin, leading to the formation of a rigid complex. We solve the structure of the seipin/Adig complex by Cryo-EM at 2.98[A] overall resolution. Surprisingly, seipin can form two unique oligomers, undecamers and dodecamers. Adig selectively binds to the dodecameric seipin complex. We further find that Adig promotes seipin assembly by stabilizing and bridging adjacent seipin subunits. Functionally, Adig plays a key role in generating lipid droplets in adipocytes. In mice, inducible overexpression of Adig in adipocytes substantially increases fat mass, with enlarged lipid droplets. It also elevates thermogenesis during cold exposure. In contrast, inducible adipocyte-specific Adig knockout mice manifest aberrant lipid droplet formation in brown adipose tissues and impaired cold tolerance.

cell biology↗

bioRxiv2024

The within-subject stability of cortical thickness, surface area, and brain volumes across one year

T1-weighted (T1w) imaging is widely used to examine brain structure based on image-derived phenotypes (IDPs) such as cortical thickness, surface area, and brain volumes. The reliability of these IDPs has been extensively explored, mainly focusing on the inter-subject variations, whereas the stability of the within-subject variations has often been overlooked. Additionally, how environmental factors such as time of day and daylight hours impact the structural brain is poorly understood. Therefore, we aimed to address the stability of T1w-derived phenotypes and explore the effecting factors including processing stream, brain region size, time of day, daylight hours, and head movement. Three subjects in their late 20s, early 30s, and early 40s were scanned repeatedly on the same scanner over one year, from which a densely sampled dataset was acquired with 38, 40, and 25 sessions for subjects 1, 2, and 3, respectively. The temporal stability was evaluated using within-subject percentage change and coefficients of variation (CV). The effects of time of day and daylight hours were assessed by fitting general linear models, aggregating the effect size with meta-analysis, and equivalent analysis. The longitudinal processing stream generates more stable results than the cross-sectional processing stream, hence the following results are all derived from the longitudinal processing stream. First and foremost, most IDPs demonstrated percentage changes within 5% and CVs within 2% for almost all brain regions, indicating high stability. Interestingly, we found that the brain region size negatively correlates with the CVs. Specifically, several small brain regions, including the temporal pole, frontal pole, pericalcarine, entorhinal cortex, and accumbens area, showed low stability. In addition, cortical thickness change was strongly and positively correlated with that of volume change while being negatively correlated with change in surface area, illustrating their distinct roles in brain anatomy. Moreover, the time of day could be ignored when evaluating the total surface area and total cortical brain volume but not the average cortical thickness and total subcortical brain volume. Furthermore, daylight hours could be left out when evaluating IDPs since there was no appreciable effect of daylight hours on the IDPs stability. Lastly, apparent head motion causes cortical thickness and volume underestimated and surface area overestimated.

neuroscience↗

bioRxiv2024

Wounding perception by jasmonate-mediated JAZ condensation in plants

Wounding is a common stress experienced by plants, resulting in a quick elicitation of jasmonates (JAs). The widely accepted mechanism of COI1-JAZ coreceptor posits that COI1 directly interacts with the active ligand of JAs, whereas JAZs facilitate to trap the ligand in the binding pocket. Here we show that the multiple JAZs of Arabidopsis undergo phase separation in response to wounding. Taking JAZ1 as an example, we found it is an independent sensor of JA-Ile, the active ligand in most plants. Under basal condition, dispersed JAZ1 interacts with MYC2 to inhibit downstream gene expressions. Upon wounding, JAZ1 binds to JA-Ile and forms condensates, reducing its affinity with MYC2 and tending to recruit COI1 as well as other proteasome related components for quick degradation, thereby accelerating signaling output. Our investigation unveils the underlying mechanism by which JAZ1 regulates swift signaling transduction via phase separation upon the direct perception of JA-Ile.

plant biology↗

bioRxiv2024

Conditional knockout of Shank3 in the ventral CA1 by quantitative in vivo genome-editing impairs social memory

Individuals with autism spectrum disorder (ASD) have a higher prevalence of social memory impairment. A series of our previous studies revealed that hippocampal ventral CA1 (vCA1) neurons possess social memory engram and that the neurophysiological representation of social memory in the vCA1 neurons is disrupted in ASD-associated Shank3 knockout mice. However, whether the dysfunction of Shank3 in vCA1 causes the social memory impairment observed in ASD remains unclear. In this study, we found that vCA1-specific Shank3 conditional knockout (cKO) by the adeno-associated virus (AAV)- or specialized extracellular vesicle (EV)-mediated in vivo gene editing was sufficient to recapitulate the social memory impairment in male mice. Furthermore, the utilization of EV-mediated Shank3-cKO allowed us to quantitatively examine the role of Shank3 in social memory. Our results suggested that there is a certain threshold for the proportion of Shank3-cKO neurons required for social memory disruption. Thus, our study provides insight into the population coding of social memory in vCA1, as well as the pathological mechanisms underlying social memory impairment in ASD.

neuroscience↗

bioRxiv2023

Kin selection underpins family dynamics in rural China

The number of co-resident members is an important characteristic of human families and thus plays an important role in human evolution. However, an inclusive fitness model of how many members should co-reside has not been explicitly tested. Here we use an evolutionary game model and a decade of family dynamic data from a rural population of southwestern China (1,110 households) to show that the existence of an evolutionary stable family size can be understood by considering the average local relatedness and average inclusive fitness of the family. Empirical data analyses show that average relatedness [Formula] decreased with increasing family size, and [Formula] was associated with helping behavior (especially for the elders) in the family, so the family tended to keep a higher level of average relatedness by adjusting the number of co-resident members. These findings are helpful to understand the variation in family size in different cultures and to demonstrate the importance of kin selection in regulating family dynamics.

evolutionary biology↗

bioRxiv2023

The intra-individual reliability of 1H-MRS measurement in the anterior cingulate cortex across one year

Magnetic resonance spectroscopy (MRS) is the primary method that can measure the levels of metabolites in the brain in vivo. To achieve its potential in clinical usage, the reliability of the measurement requires further articulation. Although there are many studies that investigate the reliability of gamma-aminobutyric acid (GABA), comparatively few studies have investigated the reliability of other brain metabolites, such as glutamate (Glu), N-acetyl-aspartate (NAA), creatine (Cr), phosphocreatine (PCr), or myo-inositol (mI), which all play a significant role in brain development and functions. In addition, previous studies which predominately used only two measurements (two datapoints) failed to provide the details of the time effect (e.g., time-of-day) on MRS measurement within subjects. Therefore, in this study, MRS data located in the anterior cingulate cortex (ACC) were repeatedly recorded across one year leading to at least 25 sessions for each subject with the aim of exploring the variability of other metabolites by using the index coefficient of variability (CV); the smaller the CV, the more reliable the measurements. We found that the metabolites of NAA, tNAA, and tCr showed the smallest CVs (between 1.61 and 4.90 %), and the metabolites of Glu, Glx, mI, and tCho showed modest CVs (between 4.26 and 7.89 %). Furthermore, we found that the concentration reference of the ratio to water with tissue correction results in smaller CVs compared to the ratio to tCr. In addition, we did not find any time-of-day effect on the MRS measurements. Collectively, the results of this study indicate that the MRS measurement is reasonably reliable in quantifying the levels of metabolites. Key pointsThe MRS measurement is reliable within subject. The ratio to water provides more reliable results compared to the ratio to tCr. The ratio to water is recommended as the internal concentration reference.

neuroscience↗

bioRxiv2023

The Bergen Breakfast Scanning Club dataset: a deep brain imaging dataset

Populational brain imaging methods based on group averages provide valuable insights into the general functions of the brain. However, they often overlook the inherent inter- and intra-subject variability, limiting our understanding of individual differences. To address this limitation, researchers have turned to big datasets and deep brain imaging datasets. Big datasets enable the exploration of inter-subject variations, while deep brain imaging datasets, involving repeated scanning of multiple subjects over time, offer detailed insights into intra-subject variability. Despite the availability of numerous big datasets, the number of deep brain imaging datasets remains limited. In this article, we present a deep brain imaging dataset derived from the Bergen Breakfast Scanning Club (BBSC) project. The dataset comprises data collected from three subjects who underwent repeated scanning over the course of approximately one year. Specifically, three types of data chunks were collected: behavioral data, functional brain data, and structural brain data. Functional brain images, encompassing magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (fMRI), along with their anatomical reference T1-weighted brain images, were collected twice a week during the data collection period. In total, 38, 40, and 25 sessions of functional data were acquired for subjects 1, 2, and 3, respectively. On the other hand, structural brain images, including T2-weighted brain images, diffusion-weighted images (DWI), and fluid-attenuated inversion recovery (FLAIR) images, were obtained once a month. A total of 10, 9, and 6 sessions were collected for subjects 1, 2, and 3, respectively. The primary objective of this article is to provide a comprehensive description of the data acquisition protocol employed in the BBSC project, as well as detailed insights into the preprocessing steps applied to the acquired data.

neuroscience↗

bioRxiv2023

Brain age predictions in longitudinal data reveal the importance of scan quality and field strength

IntroductionBrain age, the estimation of a persons age from magnetic resonance imaging (MRI) parameters, has been used as a general indicator of health. The marker requires however further validation for application in clinical contexts. Here, we show how brain age predictions perform for for the same individual at various time points and validate our findings with age-matched healthy controls. MethodsWe used densly sampled T1-weighted MRI data from four individuals (from two datasets) to observe how brain age corresponds to age and is influenced by acquision and quality parameters. For validation, we used two cross-sectional datasets. Brain age was predicted by a pre-trained deep learning model. ResultsWe find small within-subject correlations between age and brain age. We also find evidence for the influence of field strength on brain age which replicated in the cross-sectional validation data, and inconclusive effects of scan quality. ConclusionThe absence of maturation effects for the age range in the presented sample, brain age model-bias (including training age distribution and field strength) and model error are potential reasons for small relationships between age and brain age in longitudinal data. Future brain age models should account for differences in field strength and intra-individual differences.

neuroscience↗

bioRxiv2023

Crystal structure of mRNA cap (guanine-N7) methyltransferase E12 subunit from monkeypox virus and discovery of its inhibitors

In July 2022, the World Health Organization announced monkeypox as a public health emergency of international concern (PHEIC), over 85,000 global cases have been reported currently. However, preventive and therapeutic treatments are very limited. The monkeypox virus (MPXV) E12, an mRNA capping enzyme small subunit, is essential for the methyltransferase activity of RNA capping enzymes of MPXV. Here, we solved a 2.16 [A] crystal structure of E12. We also docked the D1 subunit c-terminal domain (D1CTD) of vaccinia virus (VACV) with E12 to analyze the critical residues of interface between them. These residues are used for drug screening. The top six compounds are Rutin, Quercitrin, Epigallocatechin, Rosuvastatin, 5-hydroxy-L-Tryptophan, and Deferasirox. These findings may provide insights into the development of anti-MPXV drugs.

microbiology↗

bioRxiv2021

Disrupted social memory ensembles in the ventral hippocampus underlie social amnesia in autism-associated Shank3 mutant mice

The ability to remember conspecifics is critical for adaptive cognitive functioning and social communication, and impairments of this ability are hallmarks of autism spectrum disorders (ASDs). Although hippocampal ventral CA1 (vCA1) neurons are known to store social memories, how their activities are coordinated remains unclear. Here we show that vCA1 social memory neurons, characterized by enhanced activity in response to memorized individuals, were preferentially reactivated during sharp-wave ripples (SPW-Rs). Spike sequences of these social replays reflected the temporal orders of neuronal activities within theta cycles during social experiences. In ASD model Shank3 knockout mice, the proportion of social memory neurons was reduced, and neuronal ensemble spike sequences during SPW-Rs were disrupted, which correlated with impaired discriminatory social behavior. These results suggest that SPW-R-mediated sequential reactivation of neuronal ensembles is a canonical mechanism for coordinating hippocampus-dependent social memories and its disruption underlies the pathophysiology of social memory defects associated with ASD.

neuroscience↗

bioRxiv2020

EGF-Activated Grb7 Confers to STAT3-Mediated EPHA4 Gene Expression in Regulating Lung Cancer Progression

Growth factor receptor bound protein-7 (Grb7) is a multi-domain signaling adaptor protein that regulates various cellular functions acting as an adaptor protein in relaying signal transduction. Although several studies indicated that Grb7 amplifies EGFR-mediated signaling in cancers, the detailed regulatory mechanism of whether and how Grb7 is involved in EGFR-mediated lung cancer progression remains unclear. Here, we demonstrate that EGF-regulated Grb7 phosphorylation promotes lung cancer progression through phosphorylation of STAT3. Intrinsically, EGF/EGFR signal is required for the formation of Grb7/STAT3 complex as well as its nuclear accumulation. Once in the nucleus, STAT3 interacts with EPHA4 promoter, which in turn affects the gene expression level of EPHA4 through transcriptional regulation. Functionally, EphA4 together with EGFR promotes cancer migration, proliferation, and anchorage-independent growth. Our study reveals a novel mechanism in which Grb7 contribute to lung cancer malignancies through its interaction with STAT3 that leads to sequential regulation of EPHA4 gene expression in an EGF/EGFR signal-dependent manner.

cancer biology↗