Biology subjects

Moon, H. S.

Publications and source records attributed to Moon, H. S..

4 recordsLinked to original sources

bioRxiv2022

Genetic Substrates of Brain Vulnerability and Resilience in APOE2 Mice Transitioning from Midlife to Old Age

Understanding the interplay between genotype, age, and sex has potential to reveal factors that determine the switch between successful and pathological aging. APOE allelic variation modulate brain vulnerability and cognitive resilience during aging and Alzheimer disease (AD). The APOE4 allele confers the most risk and has been extensively studied with respect to the control APOE3 allele. The APOE2 allele has been less studied, and the mechanisms by which it confers cognitive resilience and neuroprotection remain largely unknown. Using mouse models with targeted replacement of the murine APOE gene with the human major APOE2 alleles we sought to identify changes during a critical period of middle to old age transition, in a mouse model of resilience to AD. Age but not female sex was important in modulating learning and memory estimates based on Morris water maze metrics. A small but significant 3% global brain atrophy due to aging was reflected by regional atrophy in the cingulate cortex 24, fornix and hippocampal commissure (>9%). Females had larger regional volumes relative to males for the bed nucleus of stria terminalis, subbrachial nucleus, postsubiculum (~10%), and claustrum (>5%), while males had larger volumes for the orbitofrontal cortex, frontal association cortex, and the longitudinal fasciculus of pons (>9%). Age promoted atrophy in both white (anterior commissure, corpus callosum, etc.), and gray matter, in particular the olfactory cortex, frontal association area 3, thalamus, hippocampus and cerebellum. A negative age by sex interaction was noted for the olfactory areas, piriform cortex, amygdala, ventral hippocampus, entorhinal cortex, and cerebellum, suggesting faster decline in females. Fractional anisotropy indicated an advantage for younger females for the cingulate cortex, insula, dorsal thalamus, ventral hippocampus, amygdala, visual and entorhinal cortex, and cerebellum, but there was faster decline with age. Interestingly white matter tracts were largely spared in females during aging. We used vertex screening to find associations between connectome and traits such as age and sex, and sparse multiple canonical correlation analysis to integrate our analyses over connectomes, traits, and RNA-seq. Brain subgraphs favored in males included the secondary motor cortex and superior cerebellar peduncle, while those for females included hippocampus and primary somatosensory cortex. Age related connectivity loss affected the hippocampus and primary somatosensory cortex. We validated these subgraphs using neural networks, showing increased accuracy for sex prediction from 81.9% when using the whole connectome as a predictor, to 94.28% when using the subgraphs estimated through vertex screening. Transcriptomic analyses revealed the largest fold change (FC) for age related genes was for Cpt1c (log2FC = 7.1), involved in transport of long-chain fatty acids into mitochondria and neuronal oxidative metabolism. Arg1, a critical regulator of innate and adaptive immune responses (log2FC = 4.9) also showed age specific changes. Amongst the sex related genes, the largest FC were observed for Maoa (log2FC = 4.9) involved in the degradation of the neurotransmitters serotonin, epinephrine, norepinephrine, and dopamine, and implicated in response to stress. Four genes were common for age and sex related vulnerability: Myo1e (log2FC = -1.5), Creld2 (log2FC = 1.4), Ptprt (log2FC = 2.9), and Pex1 (log2FC = 3.6). We tested whether blood gene expression help track phenotype changes with age and sex. Genes with the highest weight after connectome filtering included Ankzfp1 with a role in maintaining mitochondrial integrity under stress, as well as Pex1, Cep250, Nat14, Arg1, and Rangrf. Connectome filtered genes pointed to pathways relate to stress response, transport, and metabolic processes. Our modeling approaches using sparse canonical correlation analysis help relate quantitative traits to vulnerable brain networks, and blood markers for biological processes. Our study shows the APOE2 impact on neurocognition, brain networks, and biological pathways during a critical middle to old age transition in an animal model of resilience. Identifying changes in vulnerable brain and gene networks and markers of resilience may help reveal targets for therapies that support successful aging.

neuroscience↗

bioRxiv2022

Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics

Functional magnetic resonance imaging (fMRI) with optogenetic neural manipulation is a powerful tool that enables brain-wide mapping of effective functional networks. To achieve flexible manipulation of neural excitation throughout the mouse cortex, we incorporated spatiotemporal programmable optogenetic stimuli generated by a digital micromirror device into an MR scanner via an optical fiber bundle for the first time. This approach offered versatility in space and time in planning the photostimulation pattern, combined with in situ optical imaging and cell-type or circuit-specific genetic targeting in individual mice. Brain-wide effective connectivity obtained by fMRI with optogenetic stimulation of atlas-based cortical regions is generally congruent with anatomically defined axonal tracing data but is affected by the types of anesthetics that act selectively on specific connections. fMRI combined with flexible optogenetics opens a new path to investigate dynamic changes in functional brain states in the same animal through high-throughput brain-wide effective connectivity mapping.

neuroscience↗

bioRxiv2022

Vulnerable Brain Networks Associated with Risk for Alzheimer's Disease

Brain connectomes provide untapped potential for identifying individuals at risk for Alzheimers disease (AD), and can help provide novel targets based on selective circuit vulnerability. Age, APOE4 genotype, and female sex are thought to contribute to the selective vulnerability of brain networks in Alzheimers disease, in a manner that differentiates pathological versus normal aging. These brain networks may predict pathology otherwise hard to detect, decades before overt disease manifestation and cognitive decline. Uncovering network based biomarkers at prodromal, asymptomatic stages may offer new windows of opportunity for interventions, either therapeutic or preventive. We used a sample of 72 people across the age span to model the relationship between Alzheimers disease risk and vulnerable brain networks. Sparse Canonical Correlation analysis (SCCA) revealed relationships between brain subgraphs and AD risk, with bootstrap based confidence intervals. When constructing a composite AD risk factor based on sex, age, genotype, the highest weight was associated with genotype. Next, we mapped networks associated with auditory, visual, and olfactory memory, and identified networks extending beyond the main nodes known to be involved in these functions. The inclusion of cognitive metrics in a composite risk factor pointed to vulnerable networks, and associated with the specific memory tests. These regions with the highest cumulative degree of connectivity in our studies were the pericalcarine, insula, banks of the superior sulcus and cerebellum. To help scale up our approach, we extended Tensor Network Principal Component Analysis (TNPCA) to evaluate AD risk related subgraphs, introducing CCA components and sparsity. When constructing a composite AD risk factor based on sex, age, and genotype, and family risk factor the most significant risk was associated with age. Our sparse regression based predictive models revealed vulnerable networks associated with known risk factors. The prediction error was 17% for genotype, 24% for family risk factor, and 5 years for age. Age prediction in groups including MCI and AD subjects involved several regions that were not prominent for age prediction otherwise. These regions included the middle and transverse temporal, paracentral and superior banks of temporal sulcus, as well as the amygdala and parahippocampal gyrus. The joint estimation of AD risk and connectome based mappings involved the cuneus, temporal, and cingulate cortices known to be associated with AD, and add new candidates, such as the cerebellum, whose role in AD is to be understood. Our predictive modeling approaches for AD risk factors represent a stepping stone towards single subject prediction, based on distances from normative graphs.

neuroscience↗

bioRxiv2021

High-dose drug heat map based on organoid array chip for drug selection with high safety and efficacy

An organoid array chip was developed by adopting a micropillar and microwell structure to test safety and efficacy of drugs using high dose drug heat map. In the chip, we encapsulated patient-derived cells in alginate and grow them to maturity for more than 7 days to form cancer organoids. When screening drug compounds in a high-density organoid array due to lack of number of patient-derived cells, changing media without damage of organoids is a very tedious and difficult process. Organoids grown in conventional well plates needed too many cells and were also easily damaged due to multiple pipetting during maintenance culture or during experimental procedures. To solve those problem, we applied a micropillar and microwell structure to the organoid array. We used patient-derived cells from patients with Glioblastoma multiforme (GBM), the most common and lethal form of central nervous system cancer, to validate the array chip performance. After forming more than 100{micro}m-diameter organoids in 12 x 36 pillar array chip (25mm x 75mm), we tested 70 drug compounds (6 replicates) with high high-dose to find out high safety and efficacy drug candidates. Comparing the drug response of organoids derived from normal cells and cancer cells, we identified four compounds (Dacomitinib, Cediranib, Ly2835219, BGJ398) as drug candidates without toxicity to GBM cells.

cancer biology↗