Biology subjects

Xing, H.

Publications and source records attributed to Xing, H..

18 recordsLinked to original sources

bioRxiv2026

Repetitive transcranial magnetic stimulation targeting motor cortical region induces cell-type-specific transcriptional reprogramming and behavioral recovery in non-human primate model of Rett syndrome

Rett syndrome (RTT), a severe neurodevelopmental disorder caused by mutations in the MECP2 gene, currently lacks effective treatments. The motor cortex is a pivotal hub in RTT and autism spectrum disorders, and its impairments contribute to motor, social, and cognitive deficits. Here we examined the effects of repetitive transcranial magnetic stimulation (rTMS) targeting motor area in non-human primate of RTT (MECP2-mutant monkey) and investigated neuromolecular basis underlying therapeutic effects. We identified a new treatment target, ventral premotor cortex (PMv), for RTT and found that following a 20-day rTMS course, several behavioral and functional connectivity measures showed directional changes. Neuroimaging analyses confirmed that rTMS induced reorganization of large-scale functional connectivity with enhanced functional integration between the somatomotor and the salience networks and normalized coupling between the motor cortex and both the thalamus and the anterior cingulate cortex. Notably, single-nucleus RNA sequencing revealed that rTMS triggered cell-type-specific transcriptional reprogramming: it rescued pathological hyperactivity of excitatory neurons by restoring the expression and regulatory networks of immediate early genes (e.g., FOS, EGR1) and corrected dysregulated intercellular signaling (e.g., NRG, WNT). These findings indicate that targeting motor cortical areas with brain stimulation may treat RTT, which warrants further clinical validation.

neuroscience↗

bioRxiv2026

Deep learning based behavioral analysis in a neonatal rat model of hypoxic ischemic brain injury

Hypoxic-ischemic (HI) brain injury in neonates is one of the leading causes of lifelong neurological disability. Behavioral tests in preclinical rodent models are widely used to assess motor and cognitive outcomes after HI injury; however, these assays usually depend on subjective and labor-intensive manual scoring. Recent advances in markerless pose estimation offer new opportunities for automated and reproducible behavioral quantification in animal and infant recordings, but their use in neonatal HI preclinical studies remains limited. Wistar rat pups underwent HI injury using the Rice-Vannucci model at postnatal day 7 (P7). Three developmental behavioral tests included righting reflex (P8), negative geotaxis (P14), and wire hang (P16), were recorded and analyzed by both a human rater and an automated pipeline using DeepLabCut (DLC), an open source markerless pose estimation framework. Automated measurements were compared with manual scores using Intraclass Correlation Coefficients (ICC), Bland-Altman analysis, and Pearson correlation. DLC-derived measurements demonstrated strong agreement with manual scoring across all assays. ICC values were 0.929 (95% CI 0.648-0.971) for righting reflex, 0.965 (0.888-0.989) for negative geotaxis, and 0.958 (0.876-0.985) for wire hang. An automated behavioral analysis framework integrating DLC-based pose estimation with rule based quantification and supervised machine learning offers a reliable and objective alternative to manual scoring in neonatal HI models, enabling more efficient and reproducible behavioral assessment.

neuroscience↗

bioRxiv2026

How the TREX-2 complex associates with the nuclear pore

Nuclear pore complexes (NPCs) control nucleocytoplasmic transport in eukaryotes, yet their architecture remains incompletely understood. Here we report a substantially extended structure of the human NPC, obtained by combining cryo-electron tomography, crosslinking mass spectrometry, and AI-assisted integrative modeling. We resolve the molecular arrangement of TPR, NUP153, NUP50 and ZC3HC1, and reveal that five additional proteins -- TMEM209, SMPD4, GANP, Centrin-2 and ENY2 -- are incorporated into the NPC. Unexpectedly, GANP, Centrin-2 and ENY2, core members of the TREX-2 mRNA export complex, are built into the nuclear ring. This finding establishes TREX-2 not as a transiently associated factor, but as an integral NPC module, positioning it opposite of the cytoplasmic NUP214 mRNA export platform. Together, our results redefine the molecular composition of the inner ring, nuclear ring and nuclear basket. They suggest a direct structural basis that couples TREX-2-mediated mRNP remodeling to NPC-facilitated transport.

cell biology↗

bioRxiv2026

Molecular atlas of key food odorants reveals structured aroma organization and enables generative aroma design

Food aromas arise from complex combinations of odorants, yet how these combinations are organized across foods to define aroma identity remains unclear. Decoding this "aroma code" could help bridge the sensory gap between traditional foods and sustainable alternatives, which often struggle with off-notes or to replicate consumer-expected flavor profiles. Here we present KFO-Atlas, a molecular atlas of 896 key food odorants curated from 2,282 food aroma formulations. Analysis shows that food aromas are built from sparse and structured sets of odorants. Plant-derived foods span a broad and diverse aroma space, whereas animal-derived foods tend to exhibit more similar odorant sets. In specific cases, distinct plant- and animal-based foods converge on similar odorant compositions through shared reaction pathways. Building on these insights, we develop a generative AI model that produces category-targeted aroma formulations and validate its outputs by blinded human sensory evaluation. As a proof of principle, the model reconstructs meat-like aromas using exclusively plant-derived odorants, demonstrating a data-driven route to address sensory bottlenecks in sustainable food products.

systems biology↗

bioRxiv2025

MIND: Multimodal Integration with Neighbourhood-aware Distributions

Multi-omics profiling has become a powerful tool for biomedical applications such as cancer patient stratification and clustering. However, the characterisation and integration of multi-omics data remain challenging because of missingness and inherent heterogeneity. Methods such as imputation and sample exclusion often rely on strong assumptions that could potentially lead to information loss or distortion. To address these limitations, we propose a multi-omics integration framework that learns patient-specific embeddings from incomplete multiomics data based on a multimodal Variational Autoencoder with a data-driven prior. Specifically, we inject neighbourhood structure of the observed dataset encoded as affinity matrices into the prior of embeddings through exponential tilting, and use this prior to penalise the configuration of the latent embeddings based on the discrepancy between the neighbourhood structures in the data spaces and in the latent space. Our proposed method handles high missing rate and unbalanced missingness pattern well, and is robust in the presence of data with a low signal-to-noise ratio. Compared with existing data integration methods, the proposed method achieves better performance on a range of supervised and unsupervised downstreaming tasks on both synthetic and real data.

bioinformatics↗

bioRxiv2025

BioMedTools: a language model-powered community for biomedical computational tools

A large number of biomedical computational tools have spawned several tool registries. However, in the face of the rapid growth in the number of tools, existing tool registries, which are manually curated or community-driven, are difficult to keep up to date, resulting in inadequate tool repository data. In this paper, we show that language models (LMs) can aid in building a community of tools. We introduce BioMedTools (https://biomed.tools), a community of biomedical computational tools that mainly implements LM-based tool identification and a chat assistant. Compared with existing tool registries, BioMedTools achieves excellence in terms of the number of tools, frequency of data updates, and functionality. Meanwhile, the Model Context Protocol (MCP) servers hub in BioMedTools may promote the building of agents in the biomedical field. BioMedTools enables the efficient collection of tools and enhances their findability and accessibility.

bioinformatics↗

bioRxiv2025

Allosteric modulation of dimeric GPR3 by ligands in the dimerization interface

Class C G-protein coupled receptors (GPCRs) are widely recognized to function as a dimer, whereas the existence, molecular mechanisms and functional importance of dimerization in class A GPCRs remain poorly explored. GPR3, GPR6 and GPR12 are closely related to cannabinoid receptors, and are associated with neurogenerative diseases such as Parkinsons and Alzheimers diseases. Here, we determined cryo-EM structures of GPR3-Gs complex in the active state and GPR3 alone in the inactive state. We observe that GPR3 forms symmetric dimers in both states, with the dimerization interface primarily involving TM5 and TM6. Upon activation, GPR3 undergoes an outward movement of TM6 and an inward movement of TM7, alongside stabilization of helix 8, which is disordered in the inactive state. Functionally, GPR3 dimerization attenuates Gs signaling. Furthermore, we identify AF64394 as a negative allosteric modulator that targets the GPR3 dimerization interface and allosterically shifts the -helical structure of ICL2 into a random coil structure, thereby impairing Gs coupling. Our findings provide structural and mechanistic insights into class A GPCR dimerization, offering potential therapeutic strategies targeting the dimerization interface of these receptors.

biochemistry↗

bioRxiv2025

GPerturb: Gaussian process modelling of single-cell perturbation data

Single-cell RNA sequencing and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening facilitate the high-throughput study of genetic perturbations at a single-cell level. Characterising combinatorial perturbation effects, such as the subset of genes affected by a specific perturbation, is crucial yet computationally challenging in the analysis of single-cell CRISPR screening datasets due to the sparse and complex structure of unknown biological mechanisms. We propose Gaussian process based sparse perturbation regression (GPerturb) to identify and estimate interpretable gene-level perturbation effects for such data. GPerturb uses an additive structure to disentangle perturbation-induced variation from background noise, and can learn sparse, gene-level perturbation-specific effects from either discrete or continuous responses of perturbed samples. Crucially, GPerturb provides uncertainty estimates for both the presence and magnitude of perturbation effects on individual genes. We validate the efficacy of GPerturb on both simulated and real-world datasets, demonstrating that its prediction and generalisation performance is competitive with existing state-of-the-art methods. Using real-world datasets, we also show that the model reveals interesting gene-perturbation interactions and identifies perturbation effects consistent with known biological mechanisms. Our findings confirm the utility of GPerturb in revealing new insights into the complex dependency structure between gene expressions and perturbations.

bioinformatics↗

bioRxiv2024

Alteration of skin fibroblast steady state contributes to healing outcomes

Fibroblasts display complex functions associated with distinct gene expression profiles that influence matrix production and cell communications and the autonomy of tissue development and repair. Thrombospondin-2 (TSP-2), produced by fibroblasts, is a potent angiogenesis inhibitor and negatively associated with tissue repair. Single-cell (sc) sequencing analysis on WT and TSP2KO skin fibroblasts demonstrate distinct cell heterogeneity. Specifically, we found an enrichment of Sox10+ multipotent progenitor cells, identified as Schwann precursor cells, in TSP2KO fibroblasts, while fibrosis-related subpopulations decreased. Immunostaining of tissue and cells validated the increase of this Sox10+ population in KO fibroblasts. Furthermore, in silico analysis suggested enhanced pro-survival signaling, including WNT, TGF-{beta}, and PDGF-{beta}, alongside a reduced BMP4 response. Additionally, the creation of two TSP2KO NIH3T3 cell lines using the CRISPR/Cas9 technique allowed functional and signaling validation in a less complex system. Moreover, KO 3T3 cells exhibited enhanced migration and proliferation, with elevated levels of pro-regenerative molecules including TGF-{beta}3 and Wnt4, and enrichment of nuclear {beta}-catenin. These functional and molecular alterations likely contribute to improved healing and increased neurogenesis in TSP2-deficient wounds. Overall, our findings describe the heterogeneity of dermal fibroblasts and identify pro-regenerative features of TSP2KO fibroblasts.

pathology↗

bioRxiv2024

Selective Enhancement of the Interneuron Network and Gamma-Band Power via GluN2C/GluN2D NMDA Receptor Potentiation

N-methyl-D-aspartate receptors (NMDARs) comprise a family of ligand-gated ionotropic glutamate receptors that mediate a slow, calcium-permeable component to excitatory neurotransmission. The GluN2D subunit is enriched in GABAergic inhibitory interneurons in cortical tissue. Diminished levels of GABAergic inhibition contribute to multiple neuropsychiatric conditions, suggesting that enhancing inhibition may have therapeutic utility, thus making GluN2D modulation an attractive drug target. Here, we describe the actions of a GluN2C/GluN2D-selective positive allosteric modulator (PAM), (+)-EU1180-453, which has improved drug-like properties such as increased aqueous solubility compared to the first-in-class GluN2C/GluN2D-selective prototypical PAM (+)-CIQ. (+)-EU1180-453 doubles the NMDAR response at lower concentrations (< 10 {micro}M) compared to (+)-CIQ, and produces a greater degree of maximal potentiation at 30 {micro}M. Using in vitro electrophysiological recordings, we show that (+)-EU1180-453 potentiates triheteromeric NMDARs containing at least one GluN2C or GluN2D subunit, and is active at both exon5-lacking and exon5-containing GluN1 splice variants. (+)-EU1180-453 increases glutamate efficacy for GluN2C/GluN2D-containing NMDARs by both prolonging the deactivation time and potentiating the peak response amplitude. We show that (+)-EU1180-453 selectively increases synaptic NMDAR-mediated charge transfer onto P11-15 CA1 stratum radiatum hippocampal interneurons, but is without effect on CA1 pyramidal cells. This increased charge transfer enhances inhibitory output from GABAergic interneurons onto CA1 pyramidal cells in a GluN2D-dependent manner. (+)-EU1180-453 also shifts excitatory-to-inhibitory coupling towards increased inhibition and produces enhanced gamma band power from carbachol-induced field potential oscillations in hippocampal slices. Thus, (+)-EU1180-453 can enhance overall circuit inhibition, which could prove therapeutically useful for the treatment of anxiety, depression, schizophrenia, and other neuropsychiatric disorders. Significance StatementInterneuron dysfunction and diminished GABAergic inhibition in neocortical and hippocampal circuits remains a prominent molecular hypothesis for neuropsychiatric diseases including anxiety, depression, and schizophrenia. Pharmacological agents that boost GABA receptor function have shown utility in various forms of depression and treating symptoms of schizophrenia. Cortical GABAergic interneurons, unlike their excitatory pyramidal cell counterparts, are enriched for the GluN2D subunit of the NMDA receptor. Thus, GluN2D subunit-selective modulation could be a useful therapeutic tool to enhance local inhibition, improving the prognosis for neuropsychiatric diseases for which interneuron dysfunction is prominent and causal to circuit aberration.

neuroscience↗

bioRxiv2023

Performance of Large Language Models on Pharmacy Exam: A Comparative Assessment Using the NAPLEX

BackgroundThere has been considerable recent effort in integrating Large Language Models (LLMs) across different fields, including healthcare. However, the possibility of applying LLMs in pharmacy-related sciences is under-explored. ObjectivesThis study aims to evaluate the capabilities and limitations of six LLMs-GPT-3.5, GPT-4, Llama-2-7B, Llama-2-13B, Llama-2-70B, and Mistral-7B, in the field of pharmacy by assessing their reasoning abilities on a sample of the North American Pharmacist Licensure Examination (NAPLEX). Additionally, we explore the potential impacts of LLMs on pharmacy education and practice. MethodsTo evaluate the LLMs, we utilized the sample of the NAPLEX exam comprising 225 multiple-choice questions sourced from the APhA Complete Review for Pharmacy, 13th Edition | Pharmacy Library. These questions were presented to the Large Language Models through either local deployment or the Application programming interface (API), and the answers generated by the LLMs were subsequently compared with the answer key. ResultsThere is a notable disparity in the performance of the LLMs. GPT-4 emerged as the top performer, accurately answering 87.1% of the questions. Among the six LLMs evaluated, GPT-4 was the only model capable of passing the NAPLEX exam. ConclusionWe examined the performance of Large Language Models based on their model size, training methods, and fine-tuning algorithms. Given the continuous evolution of LLMs, it is reasonable to anticipate that future models will effortlessly excel in exams such as the NAPLEX. This highlights the significant potential of LLMs to influence the field of pharmacy. Hence, we must evaluate both the positive and negative implications associated with the integration of LLMs in pharmacy education and practice.

bioinformatics↗

bioRxiv2023

Translation dynamics in human cells visualized at high-resolution reveal cancer drug action

Ribosomes catalyze protein synthesis by cycling through various functional states. These states have been extensively characterized in vitro, yet their distribution in actively translating human cells remains elusive. Here, we optimized a cryo-electron tomography-based approach and resolved ribosome structures inside human cells with a local resolution of up to 2.5 angstroms. These structures revealed the distribution of functional states of the elongation cycle, a Z tRNA binding site and the dynamics of ribosome expansion segments. In addition, we visualized structures of Homoharringtonine, a drug for chronic myeloid leukemia treatment, within the active site of the ribosome and found that its binding reshaped the landscape of translation. Overall, our work demonstrates that structural dynamics and drug effects can be assessed at near-atomic detail within human cells. One-Sentence SummarySnapshots of ribosome dynamics at near-atomic resolution within native and drug-treated human cells are revealed.

cell biology↗

bioRxiv2022

Cooperatively Designed Aptamer-PROTACs for Spatioselective Degradation of Nucleocytoplasmic Shuttling Protein for Enhanced Combinational Therapy

Nucleocytoplasmic shuttling proteins (NSPs) has emerged as a promising class of therapeutic targets for many diseases including cancer. However, most reported NSPs-based therapies largely rely on small molecule inhibitors with limited efficacy and off-target effects. Proteolysis targeting chimera (PROTAC) represents a revolutionary inhibitory modality for targeted protein degradation with many advantages, including substoichiometric catalytic activity, improved selectivity, and high efficacy. However, the majority of reported PROTACs so far are still limited to the degradation of cytoplasmic proteins and lack of tumor-specific targeting. To realize the full potential of the PROTAC technology and broaden its applications for the degradation of NSPs, we herein report a conceptual approach for the design of a new archetype of PROTAC (denoted as PS-ApTCs) by introducing phosphorothioate-modified AS1411 aptamer to a ligand of the CRBN E3 ligase, realizing tumor-targeting and spatioselective degradation with improved efficacy. We have demonstrated that PS-ApTCs is capable of effectively degrading nucleolin in target cell membrane and cytoplasm but not in the nucleus, in a CRBN- and proteasome-dependent manner. In addition, PS-ApTCs exhibits superior antiproliferation, pro-apoptotic, and cell cycle arrest potencies. Importantly, we demonstrate for the first time that combination of PS-ApTCs-mediated nucleolin degradation with aptamer-drug conjugates-based chemotherapy can enable an AND-gated synergistic effect on tumor inhibition. Collectively, our results suggest that PS-ApTCs possess the ability to expand the PROTACs toolbox to even wider range of targets in subcellular localization and accelerate the discovery of new combinational therapeutic approaches. For Table of Contents Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/514682v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@ed8331org.highwire.dtl.DTLVardef@1400b91org.highwire.dtl.DTLVardef@1b795a6org.highwire.dtl.DTLVardef@1c1f141_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2022

Optimized phylogenetic clustering of HIV-1 sequence data for public health applications

Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14,221 sequences) from four sites in USA (Tennessee, Seattle), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.

bioinformatics↗

bioRxiv2020

A distant pathway-cross regulation designed with transcription factors and JAZ repressors downregulates the biosynthesis of tobacco alkaloids and specific nitrosamines

IntroductionTranscription factors (TFs) and cis-regulatory elements (CREs) control gene transcripts involved in various biological processes. We hypothesize that TFs and CREs can be effective molecular tools for De Novo regulation designs to engineer plants. ObjectivesWe selected two Arabidopsis TF types and two tobacco CRE types to design a De Novo regulation and evaluated its effectiveness in plant engineering. MethodsG-box and MYB recognition elements (MREs) were identified in four Nicotiana tabacum JAZs (NtJAZs) promoters. MRE-like and G-box like elements were identified in one nicotine pathway gene promoter. TF screening led to select Arabidopsis Production of Anthocyanin Pigment 1 (PAP1/MYB) and Transparent Testa 8 (TT8/bHLH). Two NtJAZ and two nicotine pathway gene promoters were cloned from commercial Narrow Leaf Madole (NL) and KY171 (KY) tobacco cultivars. Electrophoretic mobility shift assay (EMSA), cross-linked chromatin immunoprecipitation (ChIP), and dual luciferase assays were performed to test the promoter binding and activation by PAP1 (P), TT8 (T), PAP1/TT8 together, and the PAP1/TT8/Transparent Testa Glabra 1 (TTG1) complex. A DNA cassette was designed and then synthesized for stacking and expressing PAP1 and TT8 together. Three years of field trials were performed by following industrial and GMO protocols. Gene expression and metabolic profiling were completed to characterize plant secondary metabolism. ResultsPAP1, TT8, PAP1/TT8, and the PAP1/TT8/TTG1 complex bound to and activated NtJAZ promoters but did not bind to nicotine pathway gene promoters. The engineered red P+T plants significantly upregulated four NtJAZs but downregulated the tobacco alkaloid biosynthesis. Field trials showed significant reduction of five tobacco alkaloids and four carcinogenic tobacco specific nitrosamines in most or all cured leaves of engineered P+T and PAP1 genotypes. ConclusionG-boxes, MREs, and two TF types are appropriate molecular tools for a De Novo regulation design to create a novel distant-pathway cross regulation for altering plant secondary metabolism.

bioengineering↗

bioRxiv2019

The microRNA476a/RFL module regulates adventitious root formation through a mitochondria-dependent pathway in Populus

Adventitious root (AR) formation at the base of stem cuttings determines the efficiency of clonal propagation for woody plants. Many endogenous and environmental factors influence AR formation. However, our knowledge about the regulation of AR development by mitochondrial metabolism in plants is very limited. Here we identified Populus-specific miR476a as a novel regulator of wound-induced adventitious rooting via orchestrating mitochondrial homeostasis in poplar. MiR476a exhibited inducible expression during AR formation and directly targets several Restorer of Fertility like (RFL) genes encoding mitochondrion-localized pentatricopeptide repeat proteins. Genetic modification of miR476-RFL expression revealed the miR476/RFL-mediated dynamic regulation of mitochondrial homeostasis on AR formation in transgenic poplar. Furthermore, mitochondrial perturbation via exogenous chemical inhibitor validated that the miR476a/RFL-directed AR formation depended on mitochondrial regulation though modulating the auxin pathway. Our results established a miRNA-directed mitochondrion-auxin signaling cascade required for AR development, providing novel insights into the understanding of mitochondrial regulation on plant developmental plasticity.

plant biology↗

bioRxiv2019

Leveraging correlations between polygenic risk score predictors to detect heterogeneity in GWAS cohorts

Evidence from both GWAS and clinical observation has suggested that certain psychiatric, metabolic, and autoimmune diseases are heterogeneous, comprising multiple subtypes with distinct genomic etiologies and Polygenic Risk Scores (PRS). However, the presence of subtypes within many phenotypes is frequently unknown. We present CLiP (Correlated Liability Predictors), a method to detect heterogeneity in single GWAS cohorts. CLiP calculates a weighted sum of correlations between SNPs contributing to a PRS on the case/control liability scale. We demonstrate mathematically and through simulation that among i.i.d. homogeneous cases, significant anti-correlations are expected between otherwise independent predictors due to ascertainment on the hidden liability score. In the presence of heterogeneity from distinct etiologies, confounding by covariates, or mislabeling, these correlation patterns are altered predictably. We further extend our method to two additional association study designs: CLiP-X for quantitative predictors in applications such as transcriptome-wide association, and CLiP-Y for quantitative phenotypes, where there is no clear distinction between cases and controls. Through simulations, we demonstrate that CLiP and its extensions reliably distinguish between homogeneous and heterogeneous cohorts when the PRS explains as low as 5% of variance on the liability scale and cohorts comprise 50, 000 - 100, 000 samples, an increasingly practical size for modern GWAS. We apply CLiP to heterogeneity detection in schizophrenia cohorts totaling > 50, 000 cases and controls collected by the Psychiatric Genomics Consortium. We observe significant heterogeneity in mega-analysis of the combined PGC data (p-value 8.54e-4), as well as in individual cohorts meta-analyzed using Fishers method (p-value 0.03), based on significantly associated variants.

bioinformatics↗

bioRxiv2018

Rapid CD4 cell loss is caused by specific CRF01_AE cluster with V3 signatures favoring CXCR4 usage

HIV-1 evolved into various genetic subtypes and circulating recombinant forms (CRFs) in the global epidemic, with the same subtype or CRF usually having similar phenotype. Being one of the worlds major CRFs, CRF01_AE infection was reported to associate with higher prevalence of CXCR4 (X4) viruses and faster CD4 decline. However, the underlying mechanisms remain unclear. We identified eight phylogenetic clusters of CRF01_AE in China and hypothesized that they may have different phenotypes. In the national HIV molecular epidemiology survey, we discovered that people infected by CRF01_AE cluster 4 had significantly lower CD4 count (391 vs. 470, p < 0.0001) and higher prevalence of predicted X4-using viruses (17.1% vs. 4.4%, p < 0.0001) compared to those infected by cluster 5. In a MSM cohort, X4-using viruses were only isolated from sero-convertors infected by cluster 4, which associated with rapid CD4 loss within the first year of infection (141 vs. 440, p = 0.01). Using co-receptor binding model, we identified unique V3 signatures in cluster 4 that favor CXCR4 usage. We demonstrate for the first time that HIV-1 phenotype and pathogenicity can be determined at the phylogenetic cluster level in a single subtype. Since its initial spread to human from chimpanzee in 1930s, HIV-1 remains undergoing rapid evolution in larger and more diverse population. The divergent phenotype evolution of two major CRF01_AE clusters highlights the importance in monitoring the genetic evolution and phenotypic shift of HIV-1 to provide early warning for the appearance of more pathogenic strains such as CRF01_AE cluster 4.\n\nSignificance StatementPast studies on HIV-1 evolution were mainly at the genetic level. This study provides well-matched genotype and phenotype data and demonstrates disparate pathogenicity of two major CRF01_AE clusters. While both CRF01_AE cluster 4 and cluster 5 are mainly spread through the MSM route, cluster 4 but not cluster 5 causes fast CD4 loss, which is associated with the higher prevalence CXCR4 viruses in cluster 4. The higher CXCR4 use tendency in cluster 4 is derived from its unique V3 loop favoring CXCR4 binding. This study for the first time demonstrates disparate HIV-1 phenotype between different phylogenetic clusters. It is important to monitor HIV-1 evolution at both the genotype and phenotype level to identify and control more pathogenic HIV-1 strains.

microbiology↗