Biology subjects

Chin, R.

Publications and source records attributed to Chin, R..

9 recordsLinked to original sources

bioRxiv2026

Microstructural heterogeneity of white-matter aging and its age-dependent coupling to cognition

Brain white matter (WM) microstructure undergoes extensive changes with age, yet the regional and cellular heterogeneity of age-related WM alterations and their impact on cognition remain unclear. Leveraging Neurite Orientation Dispersion and Density Imaging (NODDI), an advanced microstructural modelling to capture specific WM cellular properties, we investigated age-dependent relationships between advanced microstructural markers and cognitive performance, indexed by six cognitive domains derived from principal component analysis. Using a suite of standard diffusion tensor imaging (DTI) and NODDI techniques in eighty-six cognitively normal adults (Young: n=33, Older: n=53), we show that age group differences are widespread across whole brain white matter, with converging region-based and voxel-level evidence implicating commissural, association, and limbic pathways. Older adults exhibited significant and widespread reductions in global fractional anisotropy (FA) and neurite density index (NDI), concomitant with increases in mean diffusivity (MD), orientation density index (ODI), and free water fraction (FWF). Critically, age moderated WM-cognition associations in a domain- and tract-specific manner: younger adults exhibited stronger coupling between commissural and association tract microstructure and language and visual memory, whereas older adults showed greater dependence on projection and limbic tracts for executive and language function. The observed age-dependent coupling between specific microstructural metrics and cognition underscores the value of advanced diffusion models for capturing heterogeneity in brain aging, reveals age-specific biomarkers of cognitive health. These patterns align with phylogenetic and ontogenetic patterns of white matter vulnerability in callosal, long-range association, and limbic pathways, and suggest cellular specificity in white matter changes associated with cognitive decline.

neuroscience↗

bioRxiv2025

The cellular associates of late life changes in white matter microstructure

The microstructural architecture of white matter supporting information flow across local circuits and large-scale networks changes throughout the lifespan. However, the genetic and cellular factors underlying age-related variations in white matter microstructure have yet to be established. Here, we examined the genetic associates of individual differences in diffusion-based measures of white matter in a population-based cohort (N=29,862) from the UK Biobank. Estimates of heritability from Genome-Wide Association Study (GWAS) data revealed that genetic factors are linked to population variability in 96.1% of 432 tract microstructural measures. The presence of shared genetic influences was observed to be greater within, relative to between, broad tract classes (commissural, association, projection, and complex cerebellar). Age associations with microstructural changes were estimated across diffusivity measures, with association class tracts showing the greatest vulnerability to age-related decline in older adults. Analyses of imputed cellular associates of age-related changes in white matter revealed a preferential relationship with cell gene markers of oligodendrocytes and other glial cell types, with sparse relationships observed for inhibitory and excitatory cells. These data indicate that white matter tract microstructure is shaped by genetic factors and suggest a role for glial cell-related transcripts in late-life changes in the structural wiring properties of the human brain. Significance StatementThe structural wiring of the human brain supports interregional communication and is essential for cognition, yet the genetic and cellular drivers underlying age-related changes are not well understood. Here, we characterize the extent to which genetic factors follow the major organizational patterns of white matter connectivity and associated age-related changes in late life. Age-related changes were most pronounced in late-developing association tracts, key pathways for higher cognitive functions. By integrating genetic and transcriptomic data, we show that genetic variation linked to glial cell markers accounts for a substantial proportion of age-related white matter changes. These findings provide a mechanistic framework for understanding genetic and cellular determinants of structural brain aging.

neuroscience↗

bioRxiv2025

Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease

The network organization of the human brain dynamically reconfigures in response to changing environmental demands, an adaptive process that may be disrupted in a symptom-relevant manner across psychiatric illnesses. Here, in a transdiagnostic sample of participants with (n=134) and without (n=85) psychiatric diagnoses, functional connectomes from intrinsic (resting-state) and task-evoked fMRI were decomposed to identify constraints on brain network dynamics across six cognitive states. Hierarchical clustering of 110 clinical, behavioral, and cognitive measures identified participant-specific symptom profiles, revealing four core dimensions of functioning: internalizing, externalizing, cognitive, and social/reward. Brain network dynamics were flattened across cognitive states in individuals with psychiatric illness and could be used to accurately separate dimensional symptom profiles more robustly than both case-control status and primary diagnostic grouping. A key role of inhibitory cognitive control and frontoparietal network interactions was uncovered through systematic model comparison. We provide novel evidence that brain network dynamics can accurately differentiate the extent that psychiatrically-relevant dimensions of functioning are exhibited across health and disease.

neuroscience↗

bioRxiv2024

Lymphatic endothelial cell-targeting lipid nanoparticles delivering VEGFC mRNA improve lymphatic function after injury

Dysfunction of the lymphatic system following injury, disease, or cancer treatment can lead to lymphedema, a debilitating condition with no cure. Advances in targeted therapy have shown promise for treating diseases where conventional therapies have been ineffective and lymphatic vessels have recently emerged as a new therapeutic target. Lipid nanoparticles (LNPs) have emerged as a promising strategy for tissue specific delivery of nucleic acids. Currently, there are no approaches to target LNPs to lymphatic endothelial cells, although it is well established that intradermal (ID) injection of nanoparticles will drain to lymphatics with remarkable efficiency. To design an LNP that would effectively deliver mRNA to LEC after ID delivery, we screened a library of 150 LNPs loaded with a reporter mRNA, for both self-assembly and delivery in vivo to lymphatic endothelial cells (LECs). We identified and validated several LNP formulations optimized for high LEC uptake when administered ID and compared their efficacy for delivery of functional mRNA with that of free mRNA and mRNA delivered with a commercially available MC3-based LNP (Onpattro). The lead LEC-specific LNP was then loaded with VEGFC mRNA to test the therapeutic advantage of the LEC-specific LNP (namely, LNP7) for treating a mouse tail lymphatic injury model. A single dose of VEGFC mRNA delivered via LNP7 resulted in enhanced LEC proliferation at the site of injury, and an increase in lymphatic function up to 14-days post-surgery. Our results suggest a therapeutic potential of VEGFC mRNA lymphatic-specific targeted delivery in alleviating lymphatic dysfunction observed during lymphatic injury and could provide a promising approach for targeted, transient lymphangiogenic therapy. One Sentence SummaryDevelopment of a novel lymphatic endothelial cell-targeting lipid nanoparticle via in vivo screening for mRNA delivery improves lymphatic regeneration and function after injury.

bioengineering↗

bioRxiv2023

Antagonistic regulation of salt and sugar chemotaxis plasticity by a single chemosensory neuron in Caenorhabditis elegans

The nematode Caenorhabditis elegans memorizes various external chemicals, such as ions and odorants, during feeding. Here we find that C. elegans is attracted to the monosaccharides glucose and fructose after exposure to these monosaccharides in the presence of food; however, it avoids them without conditioning. The attraction to glucose requires a left-sided ASE gustatory neuron called ASEL. ASEL activity increases when glucose concentration decreases. Optogenetic ASEL stimulation promotes forward movements; however, after glucose conditioning, it promotes turning, suggesting that after glucose conditioning, the behavioral output of ASEL activation switches toward glucose. We previously reported that chemotaxis toward sodium ion (Na+), which is sensed by ASEL, increases after Na+ conditioning in the presence of food. Interestingly, glucose conditioning decreases Na+ chemotaxis, and conversely, Na+ conditioning decreases glucose chemotaxis, suggesting the reciprocal inhibition of learned chemotaxis to distinct chemicals. The activation of PKC-1, an nPKC {varepsilon}/{eta} ortholog, in ASEL promotes glucose chemotaxis and decreases Na+ chemotaxis after glucose conditioning. Furthermore, genetic screening identified ENSA-1, an ortholog of the protein phosphatase inhibitor ARPP-16/19, which functions in parallel with PKC-1 in glucose-induced chemotactic learning toward distinct chemicals. These findings suggest that kinase-phosphatase signaling regulates the balance between learned behaviors based on glucose conditioning in ASEL, which might contribute to migration toward chemical compositions where the animals were previously fed. Author summaryCaenorhabditis elegans responds to compounds that taste salty, bitter, sour, etc. However, its response to sweet compounds is unclear. Here, we show that C. elegans responds to glucose through a chemosensory neuron called ASEL. C. elegans avoids high concentrations of glucose and learns to approach glucose after feeding in the presence of high glucose, dependent on the action of ASEL. The ASEL neuron has been reported to respond to salt and promotes salt attraction after feeding in the presence of high salt. We find that the feeding-associated attractive responses to glucose and salt are antagonistic. When encountered with a mixture of salt and glucose during feeding, C. elegans changes its chemotactic response toward those chemicals according to the balance of each chemical in the mixture. C. elegans may memorize the concentrations of the chemical mixture during feeding and migrates to the chemical composition previously fed, which may promote opportunities obtaining food. Furthermore, we find that kinase-phosphatase signaling, which modulates neurotransmission, in ASEL is required for chemotaxis based on information processing of salt and glucose.

neuroscience↗

bioRxiv2022

Proportional intracranial volume correction differentially biases behavioral predictions across neuroanatomical features and populations

Individual differences in brain anatomy can be used to predict variability in cognitive function. Most studies to date have focused on broad population-level trends, but the extent to which the observed predictive features are shared across sexes and age groups remains to be established. While it is standard practice to account for intracranial volume (ICV) using proportion correction in both regional and whole-brain morphometric analyses, in the context of brain-behavior predictions the possible differential impact of ICV correction on anatomical features and subgroups within the population has yet to be systematically investigated. In this work, we evaluate the effect of proportional ICV correction on sex-independent and sex-specific predictive models of individual cognitive abilities across multiple anatomical properties (surface area, gray matter volume, and cortical thickness) in healthy young adults (Human Connectome Project; n=1013, 548 females) and typically developing children (Adolescent Brain Cognitive Development study; n=1823, 979 females). We demonstrate that ICV correction generally reduces predictive accuracies derived from surface area and gray matter volume, while increasing predictive accuracies based on cortical thickness in both adults and children. Furthermore, the extent to which predictive models generalize across sexes and age groups depends on ICV correction: models based on surface area and gray matter volume are more generalizable without ICV correction, while models based on cortical thickness are more generalizable with ICV correction. Finally, the observed neuroanatomical features predictive of cognitive abilities are unique across age groups regardless of ICV correction, but whether they are shared or unique across sexes (within age groups) depends on ICV correction. These findings highlight the importance of considering individual differences in ICV, and show that proportional ICV correction does not remove the effects of cranium volumes from anatomical measurements and can introduce ICV bias where previously there was none. ICV correction choices affect not just the strength of the relationships captured, but also the conclusions drawn regarding the neuroanatomical features that underlie those relationships.

neuroscience↗

bioRxiv2018

The transcriptional landscape of cortical interneurons underlies in-vivo brain function and schizophrenia risk

Inhibitory interneurons orchestrate information flow across cortex and are implicated in psychiatric illness. Although classes of interneurons have unique functional properties and spatial distributions throughout the brain, the relative influence of interneuron subtypes on brain function, cortical specialization, and illness risk remains elusive. Here, we demonstrate stereotyped organizational properties of somatostatin and parvalbumin related transcripts within human and non-human primates. Interneuron spatial distributions recapitulate cortico-striato-thalamic functional networks and track regional differences in functional MRI signal amplitude. In the general population (n=9,627), parvalbumin-linked genes account for an enriched proportion of genome-wide heritable variance in in-vivo functional MRI signal amplitude. This relationship is spatially dependent, following the topographic organization of parvalbumin expression in independent post-mortem brain tissue. Finally, genetic risk for schizophrenia is enriched among interneuron-linked genes and predictive of cortical signal amplitude in parvalbumin-biased regions. These data indicate that the molecular genetic basis of resting-state brain function across cortex is shaped by the spatial distribution of interneuron-related transcripts and underlies individual differences in risk for schizophrenia.\n\nKey FindingsO_LISpatial distributions of somatostatin (SST) and parvalbumin (PVALB) are negatively correlated in mature human and non-human primate cortex, paralleling patterns observed in utero.\nC_LIO_LISST and PVALB are differentially expressed within distinct limbic and somato/motor cortico-striato-thalamic networks, respectively.\nC_LIO_LIIn-vivo resting-state signal amplitude is heritable in the general population and tracks relative SST/PVALB expression across cortex.\nC_LIO_LISingle-nucleotide polymorphisms tied to PVALB-related genes account for an enriched proportion of the heritable variance in resting-state signal amplitude.\nC_LIO_LIPVALB-mediated heritability of resting-state signal amplitude in the general population is spatially heterogeneous, mirroring the cortical expression of PVALB in independent post-mortem brain tissue.\nC_LIO_LIPolygenic risk for schizophrenia is enriched among interneuron-linked genes and predicts resting-state signal amplitude in a manner that also follows the cortical expression of PVALB.\nC_LI

neuroscience↗

bioRxiv2018

Single tube bead-based DNA co-barcoding for cost effective and accurate sequencing, haplotyping, and assembly

Obtaining accurate sequences from long DNA molecules is very important for genome assembly and other applications. Here we describe single tube long fragment read (stLFR), a technology that enables this a low cost. It is based on adding the same barcode sequence to sub-fragments of the original long DNA molecule (DNA co-barcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process up to 3.6 billion unique barcode sequences were generated on beads, enabling practically non-redundant co-barcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique co-barcoding of over 8 million 20-300 kb genomic DNA fragments. Analysis of the genome of the human genome NA12878 with stLFR demonstrated high quality variant calling and phasing into contigs up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries and their construction did not significantly add to the time or cost of whole genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.

genomics↗

bioRxiv2017

Advanced whole genome sequencing and analysis of fetal genomes from amniotic fluid

Amniocentesis is typically performed to identify large chromosomal abnormalities within the fetus. Here we demonstrate that it is feasible to generate an accurate whole genome sequence (WGS) of a fetus from an amniotic sample. DNA from cells and the amniotic fluid were isolated and sequenced from 31 amniocenteses. Concordance of variant calls between the two DNA sources and with parental libraries was high. Two fetal genomes were found to harbor potentially detrimental variants in CHD8 and LRP1, variations in these genes have been associated with Autism Spectrum Disorder (ASD) and Keratosis pilaris atrophicans, respectively. We also discovered drug sensitivities and carrier information of fetuses for a variety of diseases. In this study, we demonstrate for the first time the sequencing of the whole genome of fetuses from amniotic fluid and show that much more information than large chromosomal abnormalities can be gained from an amniocentesis.

genomics↗