Biology subjects

Liu, L.

Publications and source records attributed to Liu, L..

At least 793 records · Page 44Linked to original sources

bioRxiv2020

A novel single-cell based method for breast cancer prognosis

Breast cancer prognosis is challenging due to the heterogeneity of the disease. Various computational methods using bulk RNA-seq data have been proposed for breast cancer prognosis. However, these methods suffer from limited performances or ambiguous biological relevance, as a result of the neglect of intra-tumor heterogeneity. Recently, single cell RNA-sequencing (scRNA-seq) has emerged for studying tumor heterogeneity at cellular levels. In this paper, we propose a novel method, scPrognosis, to improve breast cancer prognosis with scRNA-seq data. scPrognosis uses the scRNA-seq data of the biological process Epithelial-to-Mesenchymal Transition (EMT). It firstly infers the EMT pseudotime and a dynamic gene co-expression network, then uses an integrative model to select genes important in EMT based on their expression variation and differentiation in different stages of EMT, and their roles in the dynamic gene co-expression network. To validate and apply the selected signatures to breast cancer prognosis, we use them as the features to build a prediction model with bulk RNA-seq data. The experimental results show that scPrognosis outperforms other benchmark breast cancer prognosis methods that use bulk RNA-seq data. Moreover, the dynamic changes in the expression of the selected signature genes in EMT may provide clues to the link between EMT and clinical outcomes of breast cancer. scPrognosis will also be useful when applied to scRNA-seq datasets of different biological processes other than EMT. Author summaryVarious computational methods have been developed for breast cancer prognosis. However, those methods mainly use the gene expression data generated by the bulk RNA sequencing techniques, which average the expression level of a gene across different cell types. As breast cancer is a heterogenous disease, the bulk gene expression may not be the ideal resource for cancer prognosis. In this study, we propose a novel method to improve breast cancer prognosis using scRNA-seq data. The proposed method has been applied to the EMT scRNA-seq dataset for identifying breast cancer signatures for prognosis. In comparison with existing bulk expression data based methods in breast cancer prognosis, our method shows a better performance. Our single-cell-based signatures provide clues to the relation between EMT and clinical outcomes of breast cancer. In addition, the proposed method can also be useful when applied to scRNA-seq datasets of different biological processes other than EMT.

bioinformatics↗

bioRxiv2020

DriverGroup: A novel method for identifying drivergene groups

MotivationIdentifying cancer driver genes is a key task in cancer informatics. Most exisiting methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesise that there are driver gene groups that work in concert to regulate cancer and we develop a novel computational method to detect those driver gene groups. ResultsWe develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (1) Constructing the gene network, (2) Discovering critical nodes of the constructed network, and (3) Identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify coding and non-coding driver groups for breast cancer. The identified driver groups are promising as several group members are confirmed to be related to cancer in literature. We further use the predicted driver groups in survival analysis and the results show that the survival curves of patient subpopulations classified using the predicted driver groups are significantly differentiated, indicating the usefulness of DriverGroup. Availability and implementationDriverGroup is available at https://github.com/pvvhoang/DriverGroup ContactThuc.Le@unisa.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2020

pDriver: A novel method for unravelling personalised coding and miRNA cancer drivers

MotivationUnravelling cancer driver genes is important in cancer research. Although computational methods have been developed to identify cancer drivers, most of them detect cancer drivers at population level. However, two patients who have the same cancer type and receive the same treatment may have different outcomes because each patient has a different genome and their disease might be driven by different driver genes. Therefore new methods are being developed for discovering cancer drivers at individual level, but existing personalised methods only focus on coding drivers while microRNAs (miRNAs) have been shown to drive cancer progression as well. Thus, novel methods are required to discover both coding and miRNA cancer drivers at individual level. ResultsWe propose the novel method, pDriver, to discover personalised cancer drivers. pDriver includes two stages: (1) Constructing gene networks for each cancer patient and (2) Discovering cancer drivers for each patient based on the constructed gene networks. To demonstrate the effectiveness of pDriver, we have applied it to five TCGA cancer datasets and compared it with the state-of-the-art methods. The result indicates that pDriver is more effective than other methods. Furthermore, pDriver can also detect miRNA cancer drivers and most of them have been confirmed to be associated with cancer by literature. We further analyse the predicted personalised drivers for breast cancer patients and the result shows that they are significantly enriched in many GO processes and KEGG pathways involved in breast cancer. Availability and implementationpDriver is available at https://github.com/pvvhoang/pDriver ContactThuc.Le@unisa.edu.au Supplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2020

Fused in sarcoma regulates DNA replication timing and progression

Fused in sarcoma (FUS) encodes a low complexity RNA-binding protein with diverse roles in transcriptional activation and RNA processing. While oncogenic fusions of FUS and transcription factor DNA-binding domains are associated with soft tissue sarcomas, dominant mutations in FUS cause amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). FUS has also been implicated in DNA double-strand break repair (DSBR) and genome maintenance. However, the underlying mechanisms are unknown. Here we employed quantitative proteomics, transcriptomics, and DNA copy number analysis (Sort-Seq), in conjunction with FUS-/- cells to ascertain roles of FUS in genome protection. FUS-/- cells exhibited alterations in the recruitment and retention of DSBR factors BRCA1 and 53BP1 but were not overtly sensitive to genotoxins. By contrast, FUS-deficient cells had reduced proliferative potential that correlated with reduced replication fork speed, diminished loading of pre-replication complexes, and attenuated expression of S-phase associated genes. FUS interacted with lagging strand DNA synthesis factors and other replisome components, but did not translocate with active replication forks. Using a Sort-Seq workflow, we show that FUS contributes to genome-wide control of DNA replication timing and is essential for the early replication of transcriptionally active DNA. These findings illuminate new roles for FUS in DNA replication initiation and timing that may contribute to genome instability and functional defects in cells harboring disease-associated FUS fusions.

genomics↗

bioRxiv2020

Flow cytometric analysis and purification of airway epithelial cell subsets

The human airway epithelium is essential in homeostasis, and epithelial dysfunction contributes to chronic airway disease. Development of flow cytometric methods to characterize subsets of airway epithelial cells will enable further dissection of airway epithelial biology. Leveraging single cell RNA-sequencing (scRNA-seq) data in combination with known cell type-specific markers, we developed panels of antibodies to characterize and isolate the major airway epithelial subsets (basal, ciliated, and secretory cells) from human bronchial epithelial cell cultures. We also identified molecularly distinct subpopulations of secretory cells and demonstrated cell subset-specific expression of low abundance transcripts and micro-RNAs that are challenging to analyze with current scRNA-seq methods. These new tools will be valuable for analyzing and separating airway epithelial subsets and interrogating airway epithelial biology.

cell biology↗

bioRxiv2020

Employing NaChBac for cryo-EM analysis of toxin action on voltage-gated Na+ channels in nanodisc

NaChBac, the first bacterial voltage-gated Na+ (Nav) channel to be characterized, has been the prokaryotic prototype for studying the structure-function relationship of Nav channels. Discovered nearly two decades ago, the structure of NaChBac has not been determined. Here we present the cryo-EM analysis of NaChBac in both detergent micelles and nanodiscs. Under both conditions, the conformation of NaChBac is nearly identical to that of the potentially inactivated NavAb. Determining the structure of NaChBac in nanodiscs enabled us to examine gating modifier toxins (GMTs) of Nav channels in lipid bilayers. To study GMTs in mammalian Navs, we generated a chimera in which the extracellular fragment of the S3 and S4 segments in the second voltage-sensing domain from Nav1.7 replaces the corresponding sequence in NaChBac. Cryo-EM structures of the nanodisc-embedded chimera alone and in complex with HuwenToxin IV (HWTX-IV) were determined to 3.5 [A] and 3.2 [A] resolutions, respectively. Compared to the structure of HWTX-IV-bound human Nav1.7, which was obtained at an overall resolution of 3.2 [A], the local resolution of the toxin has been improved from ~ 6 [A] to ~ 4 [A]. This resolution enabled visualization of toxin docking. NaChBac can thus serve as a convenient surrogate for structural studies of the interactions between GMTs and Nav channels in a membrane environment.

biophysics↗

bioRxiv2020

Tissue tropisms of avian influenza A viruses affect their spillovers from wild birds to pigs

Wild aquatic birds maintain a large genetically diverse pool of influenza A viruses (IAVs), which can be transmitted to lower mammals and ultimately humans. Through phenotypic analyses, only a small set of avian IAVs replicated well in the epithelial cells of swine upper respiratory tracts, and these viruses were shown to infect and cause virus shedding in pigs. Such a phenotypic trait appears to emerge randomly and are distributed among IAVs across multiple avian species, geographic and temporal orders, and is determined not by receptor binding preference but other markers across genomic segments, such as those in the ribonucleoprotein complex. This study demonstrates that phenotypic variants exist among avian IAVs, only a few of which may result in viral shedding in pigs upon infection, providing opportunities for these viruses to become pig adapted, thus posing a higher potential risk for creating novel variants or detrimental reassortants within pig populations. Author SummaryHaving both avian-like receptors and human-like 2,6-linked sialic acid receptors, swine serve as a "mixing vessel" for generating human influenza pandemic strains. All HA subtypes of IAVs can infect swine; however, only sporadic cases of avian IAVs are reported in domestic swine. The molecular mechanisms affecting avian IAVs ability to infect swine are still not fully understood. Through phenotypic analyses, this study suggested that tissue tropisms (i.e., in swine upper respiratory tracts) of avian IAVs affect their spillovers from wild birds to pigs, and this phenotype was determined not by receptor binding preference but by other markers across genomic segments, such as those in the ribonucleoprotein complex. In addition, our results showed that such a phenotypic trait was sporadically and randomly distributed among IAVs across multiple avian species, geographic and temporal orders. This study suggested an efficient way for risk assessment of avian IAVs, such as in evaluating their potentials to be transmitted from avian to pigs.

microbiology↗

bioRxiv2020

Quantify the requirements to achieve grain Zn biofortification of high-yield wheat on calcareous soils

The solution to address global human Zn deficiency is Zn biofortification of staple food crops, aimed at high grain Zn concentration as well as high yield. However, the desired high grain Zn concentration above 40 mg kg-1 is rarely observed for high-yield wheat on worldwide calcareous soils, due to inadequate Zn uptake or Zn distribution to grain. The present study aims to investigate how much Zn uptake or distribution is adequate to achieve the Zn.t of high-yield wheat on calcareous soils with low available Zn ([~] 0.5 mg kg-1). Of the 123 cultivars tested in a three-year field experiment, 19 high-yield cultivars were identified with similar yields around 7.0 t ha-1 and various grain Zn concentrations from 9.3 to 26.7 mg kg-1. The adequate Zn distribution to grain was defined from the view of Zn biofortification, as the situation where the Zn distribution to grain (Zn harvest index) increased to the observed maximum of [~] 91.0% and the Zn concentration of vegetative parts (straw Zn concentration) decreased to the observed minimum of [~] 1.5 mg kg-1 (Zn.m). Under the assumed condition of adequate Zn distribution to grain ([~] 91.0%), all the extra Zn above Zn.m was remobilized from straw to grain and the grain Zn concentration would be increased to its highest attainable level, which was 14.5 [~] 31.3 mg kg-1 for the 19 high-yield cultivars but still lower than 40 mg kg-1. Thus, even with the adequate Zn distribution to grain, the current Zn uptake is still not adequate and needs to be increased to 308 g ha-1 or higher to achieve Zn.t for high-yield wheat (7.0 t ha-1) on low-Zn calcareous soils. Besides, the established method here can also provide the priority measures and quantitative guidelines to achieve Zn biofortification in other wheat production regions.

plant biology↗

bioRxiv2020

Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19

Stopping COVID-19 is a priority worldwide. Understanding which cell types are targeted by SARS-CoV-2 virus, whether interspecies differences exist, and how variations in cell state influence viral entry is fundamental for accelerating therapeutic and preventative approaches. In this endeavor, we profiled the transcriptome of nine tissues from a Macaca fascicularis monkey at single-cell resolution. The distribution of SARS-CoV-2 facilitators, ACE2 and TMRPSS2, in different cell subtypes showed substantial heterogeneity across lung, kidney, and liver. Through co-expression analysis, we identified immunomodulatory proteins such as IDO2 and ANPEP as potential SARS-CoV-2 targets responsible for immune cell exhaustion. Furthermore, single-cell chromatin accessibility analysis of the kidney unveiled a plausible link between IL6-mediated innate immune responses aiming to protect tissue and enhanced ACE2 expression that could promote viral entry. Our work constitutes a unique resource for understanding the physiology and pathophysiology of two phylogenetically close species, which might guide in the development of therapeutic approaches in humans. Bullet pointsO_LIWe generated a single-cell transcriptome atlas of 9 monkey tissues to study COVID-19. C_LIO_LIACE2+TMPRSS2+ epithelial cells of lung, kidney and liver are targets for SARS-CoV-2. C_LIO_LIACE2 correlation analysis shows IDO2 and ANPEP as potential therapeutic opportunities. C_LIO_LIWe unveil a link between IL6, STAT transcription factors and boosted SARS-CoV-2 entry. C_LI

cell biology↗

bioRxiv2020

Tocilizumab treatment in severe COVID-19 patients attenuates the inflammatory storm incited by monocyte centric immune interactions revealed by single-cell analysis

ABSTRACTDespite the current devastation of the COVID-19 pandemic, several recent studies have suggested that the immunosuppressive drug Tocilizumab can powerfully treating inflammatory responses that occur in this disease. Here, by employing single-cell analysis of the immune cell composition of severe-stage COVID-19 patients and these same patients in post Tocilizumab-treatment remission, we have identified a monocyte subpopulation specific to severe disease that contributes to inflammatory storms in COVID-19 patients. Although Tocilizumab treatment attenuated the strong inflammatory immune response, we found that immune cells including plasma B cells and CD8+ T cells still exhibited an intense humoral and cell-mediated anti-virus immune response in COVID-19 patients after Tocilizumab treatment. Thus, in addition to providing a rich, very high-resolution data resource about the immune cell distribution at multiple stages of the COVID-19 disease, our work both helps explain Tocilizumab’s powerful therapeutic effects and defines a large number of potential new drug targets related to inflammatory storms.Competing Interest StatementJingwen Fang is the executive officer of HanGen BiotechView Full Text

genomics↗

bioRxiv2020

Disease stage-specific pathogenicity of CD138 (syndecan 1)-expressing T cells in systemic lupus erythematosus

ObjectiveTo identify and characterize CD138 (syndecan 1)-expressing T cells in SLE-prone mice. MethodsWe characterized CD138-expressing T cells in MRL/Lpr mice by flow cytometry assay and by gene analysis. Functional properties of TCR{beta}+CD138+ cells were assessed either by activating through TCR or by co-incubating with purified B cells in the presence of auto-antigens. Purified TCR{beta}+CD138+ cells were adoptively transferred into MRL/Lpr mice and lupus disease was assessed by measuring serum auto-antibodies, proteinuria and by histopathological evaluation of kidney. ResultsWe found that the frequency of TCR{beta}+CD138+ cells was significantly higher in MRL/Lpr mice than in wild-type MRL mice (p < 0.01), and the increase in their numbers correlated with disease severity. Majority of the TCR{beta}+CD138+ cells were CD4 and CD8 double-negative and 20% were CD4. Compared to TCR{beta}+CD138- cells, TCR{beta}+CD138+ cells exhibited central memory phenotype with reduced ability to proliferate, and produce the cytokines IFN{gamma} and IL-17. When co-cultured with B cells, the ability of TCR{beta}+CD138+ cells to promote plasma cell formation and autoreactive antibody production was dependent on the presence of auto-antigens and CD4 co-receptor expression. Surprisingly, adoptively transferred TCR{beta}+CD138+ cells slowed down the disease progression in young MRL/Lpr mice but had the opposite effect when DNA was co-administered or when TCR{beta}+CD138+ cells were transferred into older MRL/Lpr mice with established disease. ConclusionHere, we provided evidence for the pathogenic role of CD138-expressing T cells when auto-antigens are exposed to immune system. Thus, monitoring the changes in TCR{beta}+CD138+ cell-frequency may serve as a tool to assess SLE severity. Moreover, CD138-expressing T cells may be targeted to alleviate lupus progression.

immunology↗

bioRxiv2020

Potent human neutralizing antibodies elicited by SARS-CoV-2 infection

The pandemic caused by emerging coronavirus SARS-CoV-2 presents a serious global public health emergency in urgent need of prophylactic and therapeutic interventions. SARS-CoV-2 cellular entry depends on binding between the viral Spike protein receptor-binding domain (RBD) and the angiotensin converting enzyme 2 (ACE2) target cell receptor. Here, we report on the isolation and characterization of 206 RBD-specific monoclonal antibodies (mAbs) derived from single B cells of eight SARS-CoV-2 infected individuals. These mAbs come from diverse families of antibody heavy and light chains without apparent enrichment for particular families in the repertoire. In samples from one patient selected for further analyses, we found coexistence of germline and germline divergent clones. Both clone types demonstrated impressive binding and neutralizing activity against pseudovirus and live SARS-CoV-2. However, the antibody neutralizing potency is determined by competition with ACE2 receptor for RBD binding. Surprisingly, none of the SARS-CoV-2 antibodies nor the infected plasma cross-reacted with RBDs from either SARS-CoV or MERS-CoV although substantial plasma cross-reactivity to the trimeric Spike proteins from SARS-CoV and MERS-CoV was found. These results suggest that antibody response to RBDs is viral species-specific while that cross-recognition target regions outside the RBD. The specificity and neutralizing characteristics of this plasma cross-reactivity requires further investigation. Nevertheless, the diverse and potent neutralizing antibodies identified here are promising candidates for prophylactic and therapeutic SARS-CoV-2 interventions.

immunology↗

bioRxiv2020

Evolution of an enzyme conformational ensemble guides design of an efficient biocatalyst

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we used room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 160 M-1s-1). We observed that catalytic residues were increasingly rigidified, the active site became better pre-organized, and its entrance was widened. Based on these observations, we engineered HG4, an efficient biocatalyst (kcat/KM 120,000 M-1s-1) containing active-site mutations found during evolution but not distal ones. HG4 structures revealed that its active site was pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

biophysics↗

bioRxiv2020

Simulation of Ca2+ oscillations in astrocytes mediated by amyloid beta in Alzheimer's disease

Disruptions of astrocyte Ca2+ signaling is important in Alzheimers disease (AD) with the unclear mechanism of amyloid beta peptide (A{beta}). We have modified our previous computational model of spontaneous Ca2+ oscillations in astrocytes to investigate the effects of A{beta} on intracellular Ca2+ dynamics. The simulation results have shown consistence with the previous experiments. A{beta} can increase the resting concentration of intracellular Ca2+ and change the regime of Ca2+ oscillations by activating L-type voltage-gated calcium channels and the metabolic glutamate receptors, or by increasing ryanodine receptors sensitivity and Ca2+ leakage, respectively. This work have provided a toolkit to study the influence of A{beta} on intracellular Ca2+ dynamics in AD. It is helpful for understanding the toxic role of A{beta} during the progression of AD. Statement of SignificanceAlzheimers disease (AD) is the most common neurodegenerative disease with the unclear mechanism of amyloid beta peptide (A{beta}). This work have implemented a computational model to address the Ca2+ dynamics of astrocyte mediated by A{beta} with the four different pathways: voltage-gated calcium channels, metabotropic glutamate receptors 5, ryanodine receptor channels and membrane leak. The Ca2+ oscillations and bifurcation diagram indicate that astrocytes exhibit ionic excitability mediated by A{beta} and become the potential targets of A{beta} neurotoxicity. We expect this shared computational model would advance the understanding of AD.

biophysics↗

bioRxiv2020

Temporal coordination of collective migration and lumen formation by antagonism between two nuclear receptors

During development, cells often undergo multiple, distinct morphogenetic processes to form a tissue or organ, but how their temporal order and time interval are determined remain poorly understood. Here we show that the nuclear receptors E75 and DHR3 regulate the temporal order and time interval between the collective migration and lumen formation of a coherent group of about 8 cells called border cells during Drosophila oogenesis. In wild type egg chambers, border cells need to first collectively migrate to the anterior border of oocyte before undergoing lumen formation to form micropyle, the structure that is essential for sperm entry into the oocyte. We show that E75 is required for border cell migration and it antagonizes the activity of DHR3, which is necessary and sufficient for the subsequent lumen formation during micropyle formation. Furthermore, E75s loss of function or DHR3 overexpression each leads to precocious lumen formation before collective migration, an incorrect temporal order for the two morphogenetic processes. Interestingly, both E75 and DHR3s levels are simultaneously elevated in response to signaling from the EcR, a steroid hormone receptor that initiates border cell migration. Subsequently, the decrease of E75 levels in response to decreased EcR signaling leads to the de-repression of DHR3s activity and hence switch-on of lumen formation, contributing to the regulation of time interval between collective migration and micropyle formation.

developmental biology↗

bioRxiv2020

Viral Architecture of SARS-CoV-2 with Post-Fusion Spike Revealed by Cryo-EM

Since December 2019, the outbreak of Coronavirus Disease 2019 (COVID-19) spread from Wuhan, China to the world, it has caused more than 87,000 diagnosed cases and more than 3,000 deaths globally. To fight against COVID-19, we carried out research for the near native SARS-CoV-2 and report here our preliminary results obtained. The pathogen of the COVID-19, the native SARS-CoV-2, was isolated, amplified and purified in a BSL-3 laboratory. The whole viral architecture of SARS-CoV-2 was examined by transmission electron microscopy (both negative staining and cryo-EM). We observed that the virion particles are roughly spherical or moderately pleiomorphic. Spikes have nail-like shape towards outside with a long body embedded in the envelope. The morphology of virion observed in our result indicates that the S protein of SARS-CoV-2 is in post-fusion state, with S1 disassociated. This state revealed by cryo-EM first time could provide an important information for the identification and relevant clinical research of this new coronavirus.

microbiology↗

bioRxiv2020

A transferrable and interpretable multiple instance learning model for microsatellite instability prediction based on histopathology images

BackgroundMicrosatellite instability (MSI) is a negative prognostic factor for colorectal cancer (CRC) and can be used as a predictor of success for immunotherapy in pan-cancer. However, current MSI identification methods are not available for all patients. We propose an ensemble multiple instance learning (MIL)-based deep learning model to predict MSI status directly from histopathology images. DesignTwo cohorts of patients were collected, including 429 from The Cancer Genome Atlas (TCGA-COAD) and 785 from a self-collected Asian data set (Asian-CRC). The initial model was developed and validated in TCGA-COAD, and then generalized in Asian-CRC through transfer learning. The pathological signatures extracted from the model are associated with genotypes for model interpretation. ResultsA model called Ensembled Patch Likelihood Aggregation (EPLA) was developed in the TCGA-COAD training set based on two consecutive stages: patch-level prediction and WSI-level prediction. The EPLA model achieved an area-under-the -curve (AUC) of 0.8848 in the TCGA-COAD test set, which outperformed the state-of-the-art approach, and an AUC of 0.8504 in the Asian-CRC after transfer learning. Furthermore, the five pathological imaging signatures identified using the model are associated with genomic and transcriptomic profiles, which makes the MIL model interpretable. Results show that our model recognizes pathological signatures related to mutation burden, DNA repair pathways, and immunity. ConclusionOur MIL-based deep learning model can effectively predict MSI from histopathology images and are transferable to a new patient cohort. The interpretability of our model by association with genomic and transcriptomic biomarkers lays the foundation for prospective clinical research.

bioengineering↗

bioRxiv2020

Dynamic graph analysis reveals aging effects on motor network communication

Cognitive performance slows down with increasing age. This includes cognitive processes that are essential for the performance of a motor act, such as the slowing down in response to an external stimulus. The objective of this study was to identify aging-associated functional changes in the brain networks that are involved in the transformation of external stimuli into motor action. To investigate this topic, we employed dynamic graphs based on phase-locking of Electroencephalography signals recorded from healthy younger and older subjects while performing a simple visually-cued finger-tapping task. The network analysis yielded specific age-related network structures varying in time in the low frequencies (2-7 Hz), which are closely connected to stimulus processing, movement initiation and execution in both age groups. The networks in older subjects, however, contained several additional, particularly interhemispheric, connections and showed an overall increased coupling density. Cluster analyses revealed reduced variability of the subnetworks in older subjects, particularly during movement preparation. In younger subjects, occipital, parietal, sensorimotor and central regions were - temporally arranged in this order - heavily involved in hub nodes. Whereas in older subjects, a hub in frontal regions preceded the noticeably delayed occurrence of sensorimotor hubs, indicating different neural information processing in older subjects. All observed changes in brain network organization, which are based on neural synchronization in the low frequencies, provide a possible neural mechanism underlying previous fMRI data, which report an overactivation, especially in the prefrontal and pre-motor areas, associated with a loss of hemispheric lateralization in older subjects.

neuroscience↗