Biology subjects

Fang, M.

Publications and source records attributed to Fang, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Cyclin A/B RxL Macrocyclic Inhibitors to Treat Cancers with High E2F Activity

Cancer cell proliferation requires precise control of E2F1 activity; excess activity promotes apoptosis. Here, we developed cell-permeable and bioavailable macrocycles that selectively kill small cell lung cancer (SCLC) cells with inherent high E2F1 activity by blocking RxL-mediated interactions of cyclin A and cyclin B with select substrates. Genome-wide CRISPR/Cas9 knockout and random mutagenesis screens found that cyclin A/B RxL macrocyclic inhibitors (cyclin A/Bi) induced apoptosis paradoxically by cyclin B- and Cdk2-dependent spindle assembly checkpoint activation (SAC). Mechanistically, cyclin A/Bi hyperactivate E2F1 and cyclin B by blocking their RxL-interactions with cyclin A and Myt1, respectively, ultimately leading to SAC activation and mitotic cell death. Base editor screens identified cyclin B variants that confer cyclin A/Bi resistance including several variants that disrupted cyclin B:Cdk interactions. Unexpectedly but consistent with our base editor and knockout screens, cyclin A/Bi induced the formation of neo-morphic Cdk2-cyclin B complexes that promote SAC activation and apoptosis. Finally, orally-bioavailable cyclin A/Bi robustly inhibited tumor growth in chemotherapy-resistant patient-derived xenograft models of SCLC. This work uncovers gain-of-function mechanisms by which cyclin A/Bi induce apoptosis in cancers with high E2F activity, and suggests cyclin A/Bi as a therapeutic strategy for SCLC and other cancers driven by high E2F activity.

cancer biology↗

bioRxiv2024

Engineering probiotic Escherichia coli Nissle 1917 to block transfer of multiple antibiotic resistance genes by exploiting a type I CRISPR-Cas system

Many multidrug-resistant (MDR) bacteria evolved through accumulation of antibiotic-resistance genes (ARGs). Although the potential risk of probiotics as reservoirs of ARGs has been recognized, strategies for blocking transfer of ARGs while using probiotics have rarely been explored. The probiotic Escherichia coli Nissle 1917 (EcN) has long been used for treating intestinal diseases. Here, we showed frequent transfer of ARGs into EcN both in vitro and in vivo, raising its potential risk of accumulating antibiotic resistance. Given that no CRISPR-Cas system is found in natural EcN, we integrated the endogenous type I-E CRISPR-Cas system derived from E. coli BW25113 into EcN, and showed that the engineered EcN was able to efficiently cleave multiple ARGs (i.e., mcr-1, blaNDM-1 and tet(X)). By co-incubation of EcN expressing Cas3-Cascade and that expressing Cas9, we showed that the growth of the former strain outcompeted the latter strain, demonstrating better clinical application prospect of EcN expressing the type I-E CRISPR-Cas system. Finally, the engineered EcN exhibited immunity against transfer of targeted ARGs in the intestine of a model animal (i.e. zebrafish). Our work provides a new strategy for restricting transfer of ARGs in EcN, paving the way for safe use of this probiotic and development of probiotics as living therapeutics.

microbiology↗

bioRxiv2024

Genes in Humans and Mice: Insights from Deep learning of 777K Bulk Transcriptomes

Mice are widely used as animal models in biomedical research, favored for their small size, ease of breeding, and anatomical and physiological similarities to humans1,2. However, discrepancies between mouse gene experimental results and the actual behavior of human genes are not uncommon, despite their shared DNA sequence similarity3-8. This suggests that DNA sequence similarity does not always reliably predict functional similarity. On the other hand, RNA-level gene expression could offer additional information about gene function9,10. In this study, we undertook characterization and inter-species comparison of human and mouse genes by applying innovative deep learning methodologies to a large dataset of 410K human and 366K mouse bulk RNA-seq samples. This was achieved by using gene representations from our Transformer-based GeneRAIN model11,12. These gene representations aggregate information from large gene expression datasets, and provide insights beyond DNA sequence similarity. We identified 2,407 human-mouse homologous genes with high DNA similarity but distinct RNA characteristics, and showed that these genes are more likely to have differing disease/phenotype associations between the two species. Additionally, we found 3,070 homologous genes with low similarity at both the DNA and RNA levels, suggesting the highest risk of discrepancies in study results between the two species. We propose that this approach will support future decision making around whether the mouse will be an appropriate model for studying specific human genes, and whether the results of specific mouse gene studies are likely to be recapitulated in humans. Our methodological innovations offer valuable lessons for future deep learning applications in cross-species omics data. The interspecies gene relationship findings from our study also contribute valuable insights into the gene biology and evolution of the two species.

bioinformatics↗

bioRxiv2024

Multifaceted Representation of Genes via Deep Learning of Gene Expression Networks

Accurate predictive modeling of human gene relationships would fundamentally transform our ability to uncover the molecular mechanisms that underpin key biological and disease processes. Recent studies have employed advanced AI techniques to model the complexities of gene networks using large gene expression datasets1-11. However, the extent and nature of the biological information these models can learn is not fully understood. Furthermore, the potential for improving model performance by using alternative data types, model architectures, and methodologies remains underexplored. Here, we developed GeneRAIN models by training on a large dataset of 410K human bulk RNA-seq samples, rather than single-cell RNA-seq datasets used by most previous studies. We showed that although the models were trained only on gene expression data, they learned a wide range of biological information well beyond gene expression. We introduced GeneRAIN-vec, a state-of-the-art, multifaceted vectorized representation of genes. Further, we demonstrated the capabilities and broad applicability of this approach by making 4,797 biological attribute predictions for each of 13,030 long non-coding RNAs (62.5 million predictions in total). These achievements stem from various methodological innovations, including experimenting with multiple model architectures and a new Binning-By-Gene normalization method. Comprehensive evaluation of our models clearly demonstrated that they significantly outperformed current state-of-the-art models3,12. This study improves our understanding of the capabilities of Transformer and self-supervised deep learning when applied to extensive expression data. Our methodological advancements offer crucial insights into refining these techniques. These innovations are set to significantly advance our understanding and exploration of biology.

bioinformatics↗

bioRxiv2024

Alterations in Lysosomal, Glial and Neurodegenerative Biomarkers in Patients with Sporadic and Genetic Forms of Frontotemporal Dementia

BackgroundFrontotemporal dementia (FTD) is the most common cause of early-onset dementia with 10-20% of cases caused by mutations in one of three genes: GRN, C9orf72, or MAPT. To effectively develop therapeutics for FTD, the identification and characterization of biomarkers to understand disease pathogenesis and evaluate the impact of specific therapeutic strategies on the target biology as well as the underlying disease pathology are essential. Moreover, tracking the longitudinal changes of these biomarkers throughout disease progression is crucial to discern their correlation with clinical manifestations for potential prognostic usage. MethodsWe conducted a comprehensive investigation of biomarkers indicative of lysosomal biology, glial cell activation, synaptic and neuronal health in cerebrospinal fluid (CSF) and plasma from non-carrier controls, sporadic FTD (symptomatic non-carriers) and symptomatic carriers of mutations in GRN, C9orf72, or MAPT, as well as asymptomatic GRN mutation carriers. We also assessed the longitudinal changes of biomarkers in GRN mutation carriers. Furthermore, we examined biomarker levels in disease impacted brain regions including middle temporal gyrus (MTG) and superior frontal gyrus (SFG) and disease-unaffected inferior occipital gyrus (IOG) from sporadic FTD and symptomatic GRN carriers. ResultsWe confirmed glucosylsphingosine (GlcSph), a lysosomal biomarker regulated by progranulin, was elevated in the plasma from GRN mutation carriers, both symptomatic and asymptomatic. GlcSph and other lysosomal biomarkers such as ganglioside GM2 and globoside GB3 were increased in the disease affected SFG and MTG regions from sporadic FTD and symptomatic GRN mutation carriers, but not in the IOG, compared to the same brain regions from controls. The glial biomarkers GFAP in plasma and YKL40 in CSF were elevated in asymptomatic GRN carriers, and all symptomatic groups, except the symptomatic C9orf72 mutation group. YKL40 was also increased in SFG and MTG regions from sporadic FTD and symptomatic GRN mutation carriers. Neuronal injury and degeneration biomarkers NfL in CSF and plasma, and UCHL1 in CSF were elevated in patients with all forms of FTD. Synaptic biomarkers NPTXR, NPTX1/2, and VGF were reduced in CSF from patients with all forms of FTD, with the most pronounced reductions observed in symptomatic MAPT mutation carriers. Furthermore, we demonstrated plasma NfL was significantly positively correlated with disease severity as measured by CDR+NACC FTLD{square}SB in genetic forms of FTD and CSF NPTXR was significantly negatively correlated with CDR+NACC FTLD{square}SB in symptomatic GRN and MAPT mutation carriers. ConclusionsIn conclusion, our comprehensive investigation replicated alterations in biofluid biomarkers indicative of lysosomal function, glial activation, synaptic and neuronal health across sporadic and genetic forms of FTD and unveiled novel insights into the dysregulation of these biomarkers within brain tissues from patients with GRN mutations. The observed correlations between biomarkers and disease severity open promising avenues for prognostic applications and for indicators of drug efficacy in clinical trials. Our data also implicated a complicated relationship between biofluid and tissue biomarker changes and future investigations should delve into the mechanistic underpinnings of these biomarkers, which will serve as a foundation for the development of targeted therapeutics for FTD.

neuroscience↗

bioRxiv2024

Trajectory inference from single-cell genomics data with a process time model

Single-cell transcriptomics experiments provide gene expression snapshots of heterogeneous cell populations across cell states. These snapshots have been used to infer trajectories and dynamic information even without intensive, time-series data by ordering cells according to gene expression similarity. However, while single-cell snapshots sometimes offer valuable insights into dynamic processes, current methods for ordering cells are limited by descriptive notions of "pseudotime" that lack intrinsic physical meaning. Instead of pseudotime, we propose inference of "process time" via a principled modeling approach to formulating trajectories and inferring latent variables corresponding to timing of cells subject to a biophysical process. Our implementation of this approach, called Chronocell, provides a biophysical formulation of trajectories built on cell state transitions. The Chronocell model is identifiable, making parameter inference meaningful. Furthermore, Chronocell can interpolate between trajectory inference, when cell states lie on a continuum, and clustering, when cells cluster into discrete states. By using a variety of datasets ranging from cluster-like to continuous, we show that Chronocell enables us to assess the suitability of datasets and reveals distinct cellular distributions along process time that are consistent with biological process times. We also compare our parameter estimates of degradation rates to those derived from metabolic labeling datasets, thereby showcasing the biophysical utility of Chronocell. Nevertheless, based on performance characterization on simulations, we find that process time inference can be challenging, highlighting the importance of dataset quality and careful model assessment.

bioinformatics↗

bioRxiv2023

Identification of functional genes underlining growth in large yellow croaker

Large yellow croaker (Larimichthys crocea) is the largest cultured marine fish in China, although its economic benefits are significant, its growth cycle is long and it takes 2 years to market. Identification of genomic variations and genes affecting the growth of L. crocea is of great significance for breeding fast-growing strains by molecular means. We utilized whole genome resequencing to identify a highly effective GWAS locus on chromosome 6 of the genome, and identified some candidate genes that affect growth. This study provides a theoretical basis for analyzing the genetic mechanism of growth traits of L. crocea and cultivating fast-growing varieties.

genetics↗

bioRxiv2023

LrhA promotes CRISPR-Cas immunity by promoting reciprocal interplay between interference and primed adaptation in Escherichia coli

The CRISPR-based defense system protects prokaryotes against foreign genetic elements. Previous studies indicated that the activity of the CRISPR-Cas system is the outcome of the combined effect of adaptation and interference. However, it remains unclear how coordination of the two processes is regulated to optimize the efficacy of adaptive immunity. Here, we identify the LysR-type transcriptional regulator LrhA as a new CRISPR-Cas activator which plays an important role in coordinating adaptation and interference. Through directly binding to the promoter of the cas operon, LrhA enhances the CRISPR-Cas adaptive immunity against bacteriophage infection by stimulating the transcription of cas genes. Moderate activation of cas genes by LrhA efficiently promoted the clearance of horizontally transferred CRISPR-targeted plasmid via increasing the acquisition of new spacers by interference-driven adaptation in Escherichia coli. Our results indicate that intermediate level of transcription of cas genes achieved optimal outcomes of the adaptive immunity through triggering positive feedback between adaptation and interference, highlighting the importance of fine-tuning expression of CRISPR-Cas system.

microbiology↗

bioRxiv2023

Rapid and accurate multi-phenotype imputation for millions of individuals

Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains extremely challenging. In the present study, we developed a novel multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms. We demonstrate that PIXANT runtime is faster and computer memory usage is less than that of other state-of-the-art methods when applied to the UK Biobank (UKB) data, suggesting that PIXANT is scalable to cohorts with millions of individuals. Our simulations with hundreds of individuals showed that PIXANT accuracy was superior to or comparable to the accuracy of the most advanced methods available. PIXANT was used to impute 425 phenotypes for the UKB data of 277,301 unrelated White British citizens. When GWAS was subsequently performed on the imputed phenotypes, 18.4% more GWAS loci were identified than before imputation (8,710 vs 7,355). The increased statistical power of GWAS identified novel positional candidate genes affecting heart rate, such as RNF220, SCN10A, and RGS6, suggesting that the use of imputed phenotype data from a large cohort may lead to the discovery of novel genes for complex traits.

bioinformatics↗

bioRxiv2023

Automatic Auditory Streaming Restores Missing Temporal Modulations in Echoic Speech

Human listeners can reliably recognize speech in adverse listening environments, and previous studies have identified that reliable neural encoding of slow temporal modulations in speech is essential for speech recognition. Recent behavioral studies demonstrate that long-delay echoes, which are rare in physical environments but common during online conferencing, can eliminate critical temporal modulations. These echoes, however, barely affect speech intelligibility, and here we investigate the underlying neural mechanisms. MEG experiments demonstrate that cortical activity can effectively track the temporal modulations eliminated by an echo, which cannot be explained by basic neural adaptation mechanisms such as synaptic depression, gain control, and adaptive filtering. Instead, the cortical response to echoic speech is better explained by a model that segregates speech from its echo than a model that encodes echoic speech as a whole. The speech segregation effect is observed even when attention is diverted, but disappears when speech segregation cues in the spectro-temporal fine structure are degraded. Altogether, these results strongly suggest that the auditory system can automatically segregate speech and its echo and encode them as two auditory streams, providing a potential neural basis for reliable speech recognition in echoic environments.

neuroscience↗

bioRxiv2023

Inducible mismatch repair streamlines forward genetic approaches to target identification of cytotoxic small molecules

Orphan cytotoxins are small molecules for which the mechanism of action (MoA) is either unknown or ambiguous. Unveiling the mechanism of these compounds may lead to useful tools for biological investigation and in some cases, new therapeutic leads. In select cases, the DNA mismatch repair-deficient colorectal cancer cell line, HCT116, has been used as a tool in forward genetic screens to identify compound-resistant mutations, which have ultimately led to target identification. To expand the utility of this approach, we engineered cancer cell lines with inducible mismatch repair deficits, thus providing temporal control over mutagenesis. By screening for compound resistance phenotypes in cells with low or high rates of mutagenesis, we increased both the specificity and sensitivity of identifying resistance mutations. Using this inducible mutagenesis system, we implicate targets for multiple orphan cytotoxins, including a natural product and compounds emerging from a high-throughput screen, thus providing a robust tool for future MoA studies.

biochemistry↗

bioRxiv2023

PI3Kδ inhibition potentiates glucocorticoids in B-ALL by decreased receptor phosphorylation and enhanced gene regulation

Glucocorticoids, including dexamethasone and prednisone, are the cornerstone of B-lymphoblastic leukemia (B-ALL) therapy. Because response to glucocorticoids alone predicts overall outcomes for B-ALL, enhancing glucocorticoid potency is a route to improving outcomes. However, systematic toxicities prevent the use of higher dose and more potent glucocorticoids. We therefore took a functional genomic approach to identify targets to enhance glucocorticoid activity specifically in B-ALL cells. Here we show that inhibition of the lymphoid-restricted PI3K{delta}, signaling through the RAS/MAPK pathway, enhances both prednisone and dexamethasone activity in almost all ex vivo B-ALL specimens tested. This potentiation is most synergistic at sub-saturating doses of glucocorticoids, approaching the EC50. Potentiation correlates with global enhancement of glucocorticoid-induced gene regulation, including regulation of effector genes that drive B-ALL cell death. Idelalisib reduces phosphorylation of the glucocorticoid receptor (GR) at MAPK1/ERK2 targets S203 and S226, and ablation of these phospho-acceptor sites enhances glucocorticoid potency. We further show that phosphorylation of S226 reduces the affinity of GR for DNA in vitro, which impairs DNA binding. We therefore propose that PI3K{delta} inhibition improves glucocorticoid efficacy in B-ALL in part by decreasing GR phosphorylation, increasing DNA binding affinity, and enhancing downstream gene regulation. The overall enhancement of GR function suggests that idelalisib will provide benefit to most patients with B-ALL by improving outcomes for patients whose disease is less responsive to glucocorticoid-based therapy, including high-risk disease, and allowing less toxic glucocorticoid-sparing strategies for patients with standard-risk disease.

cancer biology↗

bioRxiv2022

Different tissues in the maternal-fetal interface harbor distinct microbiomes showing associations related to their anatomical position or function

The human placenta was thought to be sterile in healthy pregnancies which has been challenged by the development of DNA sequence-based techniques, although it is still open to controversy. Nonetheless, little is known whether different parts of fetal appurtenances contain district microbiome profiles. Here, DNA 16S rRNA sequencing was performed of the amniotic fluid cells (AC), amnion membrane (AM), the placenta of fetal surface (remove the amniotic membrane, PL), maternal blood (MB), and umbilical cord blood (UCB) at V3-V4 hypervariable region from participants with cesarean delivery. Then sequence raw data were followed by taxonomic classification at 97% similarity and diversity analysis at the genus level. The differences and associations among the five tissues were analyzed. At the phylum composition level, the most abundant microorganisms were Proteobacteria in all five tissues, and followed by Firmicutes in AC, AM, and MB groups, Actinobacteria in UCB and Bacteroidetes in PL, respectively. As the maternal-fetal barrier, PL and AM had the lower OUT number and weaker co-occurrence network compared with the other three tissues. At the beta diversity clustering level, the microbiota constituents in the MB and UCB were highly similar; the microbiota profiles of PL and AM were also remarkably alike; AC was immensely different from those two clusters. Therefore, the five tissues were distinctly separated into three clusters. Our study reveals that different pregnancy-related anatomical sites harbor unique microbial compositions and show different degrees of correlation with other tissues.

microbiology↗

bioRxiv2022

ExposomeX: Integrative Exposomic Platform Expediates Discovery of "Exposure-Biology-Disease" Nexus

Exposome has become the hotspot of next-generation health studies. To date, there is no available effective platform to standardize the analysis of exposomic data. In this study, we aim to propose one new framework of exposomic analysis and build up one novel integrated platform "ExposomeX" to expediate the discovery of the "Exposure-Biology-Disease" nexus. We have developed 13 standardized modules to accomplish six major functions including statistical learning (E-STAT), exposome database search (E-DB), mass spectrometry data processing (E-MS), meta-analysis (E-META), biological link via pathway integration and protein-protein interaction (E-BIO) and data visualization (E-VIZ). Using ExposomeX, we can effectively analyze the multiple-dimensional exposomics data and investigate the "Exposure-Biology-Disease" nexus by exploring mediation and interaction effects, understanding statistical and biological mechanisms, strengthening prediction performance, and automatically conducting meta-analysis based on well-established literature databases. The performance of ExposomeX has been well validated by re-analyzing two previous multi-omics studies. Additionally, ExposomeX can efficiently help discover new associations, as well as relevant in-depth biological pathways via protein-protein interaction and gene ontology network analysis. In sum, we have proposed a novel framework for standardized exposomic analysis, which can be accessed using both R and online interactive platform (http://www.exposomex.cn/).

bioinformatics↗

bioRxiv2022

Intranasal delivery of NS1-deleted influenza virus vectored COVID-19 vaccine restrains the SARS-CoV-2 inflammatory response

The emergence of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) variants and "anatomical escape" characteristics threaten the effectiveness of current coronavirus disease (COVID-19) vaccines. There is an urgent need to understand the immunological mechanism of broad-spectrum respiratory tract protection to guide broader vaccines development. In this study, we investigated immune responses induced by an NS1-deleted influenza virus vectored intranasal COVID-19 vaccine (dNS1-RBD) which provides broad-spectrum protection against SARS-CoV-2 variants. Intranasal delivery of dNS1-RBD induced innate immunity, trained immunity and tissue-resident memory T cells covering the upper and lower respiratory tract. It restrained the inflammatory response by suppressing early phase viral load post SARS-CoV-2 challenge and attenuating pro-inflammatory cytokine (IL-6, IL-1B, and IFN-{gamma}) levels, thereby reducing excess immune-induced tissue injury compared with the control group. By inducing local cellular immunity and trained immunity, intranasal delivery of NS1-deleted influenza virus vectored vaccine represents a broad-spectrum COVID-19 vaccine strategy to reduce disease burden.

immunology↗

bioRxiv2022

Targeted Protein Degradation via Nanoparticles

Strategies that hijack selective proteins of interest (POIs) to the intracellular protein recycling machinery for targeted protein degradation (TPD) have recently emerged as powerful tools for undruggable targets in biomedical research and the pharmaceutical industry. However, targeting any new POI with current TPD tools requires laborious case-by-case design for different diseases and cell types, especially for those extracellular targets. Here, we observed that nanoparticles (NPs) can mediate the receptor-free internalization of hijacked protein and further developed a generic paradigm for both intra- and extracellular POI degradation, by making full use of clinically approved components. The phenomenon is general, as we found nanostructures such as lipid nanoparticle (LNP), liposomes, exosomes, polymeric nanoparticles, inorganic nanoparticles and their hybrid nanoparticles modified with POI-recognizing moiety (antibody, peptides, small molecule drugs) can mediate TPD for a wide range of extracellular/membrane and intracellular targets. The super flexible and feasible-to-synthesize TPD-NPs paradigm may revolutionize the current TPD tools development landscape and it provides fundamental knowledge to receptor mediated drug therapies. HighlightsO_LINanoparticle mediated targeted protein degradation (TPD-NP) can be constructed by "Mix-and-Match" and do not require de novo synthesis or specific internalization design. C_LIO_LITPD-NPs can be equipped with specific cell type targeting capacity, loading and controlled release of therapeutic cargos, as well as biological barrier penetration capacity. C_LIO_LIAssembling components can be clinical-approved or biodegradable for translational medicine. C_LIO_LITPD-NP highly boosted current application platforms of nano-delivery and TPD. C_LI

bioengineering↗

bioRxiv2022

Protective human anti-poxvirus monoclonal antibodies are generated from rare memory B cells isolated by multicolor antigen tetramers

Smallpox, an epidemic disease caused by Orthopoxvirus variola, was eradicated worldwide through immunization. The immunization against smallpox was discontinued in 1980. However, incidences of monkeypox virus infection in humans have occurred sporadically, and there is also great fear that engineered forms of poxvirus could be used as biological weapons. Therefore, monoclonal antibodies against poxvirus are in urgent need for the detection and treatment of poxvirus infection. The vaccinia virus extracellular envelope protein A33 is a potential candidate for subunit vaccine. We used multi-fluorescence-labeled tetrameric A33 antigen to identify rare poxvirus specific memory B cells from PBMC of volunteers with vaccinia virus immunization more than 40 years ago. Despite extremely low frequencies of the poxvirus specific memory B cells, we successfully sorted A33 tetramer-labeled single memory B cells and reconstructed antibodies with single-cell RT-PCR of the B-cell receptor. Among the monoclonal antibodies, one clone H2 exhibited high specificity and affinity with A33. H2 efficiently inhibited viral infection and spread in cells. Passive immunotherapy of H2 in mice protected mice from lethal infection when administered either prophylactically or therapeutically. These results suggest the potential of the anti-A33 human antibody-based detection and therapeutics for poxvirus infection.

immunology↗

bioRxiv2022

Impaired peri-olfactory Cerebrospinal Fluid clearance mediated cognitive decline after dyssomnia

Animal experiments have demonstrated the dependency of CSF clearance function on age and sleep, which partially underlay the cognitive decline in the elderly. However, evidence is lacking in humans mainly due to limited method to assess CSF clearance function. We aimed to image CSF clearance pathways in human brain by dynamic MRI with intrathecal contrast agent as a CSF tracer. We performed T1-weighted and T2-fluid attenuated inversion recovery imaging with equal sequence parameters before and at multiple time points after intrathecal injection of contrast agent to visualize the putative meningeal lymphatic pathway, peri-olfactory nerve pathway and peri-optic nerve pathway. We defined the CSF clearance function as the percentage change in signal unit ratio of critical locations in these pathways from baseline to 39 hours after intrathecal injection. CSF clearance through the putative meningeal lymphatic and peri-neural pathways were clearly visualized in all 85 patients. The CSF clearance function of meningeal lymphatic and peri-neural pathways were reduced with aging (all P < 0.05). The CSF clearance function through peri-olfactory nerve pathway was positive correlated with sleep quality and cognitive function (both P < 0.05). Moreover, the CSF clearance function through peri-olfactory nerve pathway mediated the association of sleep quality with cognitive function (percent change in {beta} [bootstrap 95% confidence interval]: 35% [-0.220, -0.003]). The study shows promise for dynamic MRI with intrathecal injection of contrast agent as a method to assess CSF clearance function through putative peri-neural pathways, and interprets the impaired clearance through putative peri-olfactory nerve pathway may explain the cognitive decline in patients with dyssomnia.

neuroscience↗