Biology subjects

Luo, C.

Publications and source records attributed to Luo, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Systematic Benchmarking of High-Throughput Subcellular Spatial Transcriptomics Platforms

Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. To address this, we collected clinical samples from three cancer types - colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer - and generated serial tissue sections for systematic evaluation. Using these uniformly processed samples, we generated spatial transcriptomics data across five high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, Visium HD FF, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profiled proteins from adjacent tissue sections corresponding to all five platforms using CODEX and performed single-cell RNA sequencing on the same samples. Leveraging manual cell segmentation and detailed annotations, we systematically assessed each platforms performance across key metrics, including capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and transcript-protein alignment with adjacent CODEX. The uniformly generated, processed, and annotated multi-omics dataset is valuable for advancing computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download (http://spatch.pku-genomics.org/).

genomics↗

bioRxiv2024

RNAi-mediated HBV antigen shutdown enhances the antiviral immune effects of PEGIFNalpha via altering T and B cell crosstalk

PEGylated interferon- (PEGIFN) demonstrates promising therapeutic outcomes against chronic hepatitis B (CHB), whereas patient response to PEGIFN therapy remains unsatisfied. Shutdown of hepatitis B virus (HBV) antigens by RNA interference (RNAi) could enhance PEGIFN efficacy in CHB patients, whereas the underlying immunological mechanisms remain obscure. We performed studies by utilizing our newly established extracellular humanized IFNAR (IFNAR-hEC) mice. An in-house constructed small interfering RNAs (GalNac-siHBV) was administrated to mice either alone or in combination with PEGIFN. The phenotypic and functional characteristics of peripheral and organ-specific immune cells were assessed by flow cytometry, ELISpot, RNA sequencing (RNA-seq), and single-cell RNA-seq (scRNA-seq) analysis. Our results demonstrated that combined treatment with PEGIFN and RNAi exerted a synergistic and prolonged inhibition of HBsAg ([~]4log10 IU/mL, vs PBS) and induced a higher incidence of HBsAg seroconversion ([~]30%), comparing with either monotreatment. Mechanistically, combined therapy improved the functionality of global T and B cells, triggered increased anti-HBs producing B cells, and enhanced IFN{gamma}-producing T cells. scRNA-seq analysis revealed that the combined therapy reduced inhibitory B cell-B cell interaction, enhanced MHC-I signaling mediated T cell-T cell communication, and improved T cell-B cell crosstalk, thus improving the functionality of T and B cells. Enhanced MHC-II signaling networks across B cells and hepatocytes/Cd8+ T cells further promoted HBsAg seroconversion in the combined treatment groups. These results together provided scientific rationale and lessons for the combination of the two towards better therapeutic efficacy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/626539v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@84785aorg.highwire.dtl.DTLVardef@f984fborg.highwire.dtl.DTLVardef@189a966org.highwire.dtl.DTLVardef@d081f9_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIShutting down HBsAg through RNA interference augmented the antiviral immune effects of PEGIFN in chronic HBV-carrier IFNAR-hEC mice. C_LIO_LICombined RNAi plus PEGIFN augmented the functionality of T cells, promoted B cell activation and class switch, but also exerted some suppressive effects on B cells. C_LIO_LIReduced inhibitory B cell-B cell interaction, enhanced MHC-I signaling between T cells and T cells, and improved T cell-B cell crosstalk, improved the functionality of T cells and B cells. C_LIO_LIEnhanced MHC-II signaling networks across B cells and hepatocytes/ Cd8+ T cells further promoted HBsAg seroconversion in RNAi plus PEGIFN combined treatment groups. C_LI

microbiology↗

bioRxiv2024

FocalSV: target region-based structural variant assembly and refinement using single-molecule long read sequencing data

Structural variants (SVs) play a critical role in shaping the diversity of the human genome and their detection holds significant potential for advancing precision medicine. Despite notable progress in single-molecule long-read sequencing technologies, accurately identifying SV breakpoints and resolving their sequence remains a major challenge. Current alignment-based tools often struggle with precise breakpoint detection and sequence characterization, while whole genome assembly-based methods are computationally demanding and less practical for targeted analyses. Neither approach is ideally suited for scenarios where regions of interest are predefined and require precise SV characterization. To address this gap, we introduce FocalSV, a target region assembly-based SV detection tool that combines the precision of assembly-based methods with the efficiency of region-specific approaches. FocalSV was evaluated on nine germline datasets and two paired normal-tumor cancer datasets, demonstrating superior performance in both precision and efficiency.

bioinformatics↗

bioRxiv2024

Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue

Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.

genomics↗

bioRxiv2024

Large Serine Integrase Off-target Discovery and Validation for Therapeutic Genome Editing

While numerous technologies for the characterization of potential off-target editing by CRISPR/Cas9 have been described, the development of new technologies and analytical methods for off-target recombination by Large Serine Integrases (LSIs) are required to advance the application of LSIs for therapeutic gene integration. Here we describe a suite of off-target recombination discovery technologies and a hybrid capture validation approach as a comprehensive framework for off-target characterization of LSIs. HIDE- Seq (High-throughput Integrase-mediated DNA Event Sequencing) is a PCR-free unbiased genome-wide biochemical assay capable of discovering sites with LSI- mediated free DNA ends (FDEs) and off-target recombination events. Cryptic-Seq is a PCR-based unbiased genome-wide biochemical or cellular-based assay that is more sensitive than HIDE-Seq but is limited to the discovery of sites with off-target recombination. HIDE-Seq and Cryptic-Seq discovered 38 and 44,311 potential off-target sites respectively. 2,455 sites were prioritized for validation by hybrid capture NGS in LSI- edited K562 cells and off-target integration was detected at 52 of the sites. We benchmarked the sensitivity of our LSI off-target characterization framework against unbiased whole genome sequencing (WGS) on LSI-edited samples, and off-target integration was detected at 5 sites with an average genome coverage of 40x. This reflects a greater than 10-fold increase in sensitivity for off-target detection compared to WGS, however only 4 of the 5 sites detected by WGS were also validated by hybrid capture NGS. The dissemination of these technologies will help advance the application of LSIs in therapeutic genome editing by establishing methods and benchmarks for the sensitivity of off-target detection.

genomics↗

bioRxiv2024

Human transcription factor combinations mapped by genome-wide footprinting with deaminase

An individuals somatic cells have the same genome but exhibit cell-type-specific transcriptome regulated by a combination of transcription factors (TFs) for each gene. Mapping of TF sites on the human genome is critically important for understanding functional genomics. Here we report a novel technique to measure human TFs binding sites genome-wide with single-base resolution by footprinting with deaminase (FOODIE). Single-molecule sequencing reads from thousands of cells after in situ deamination yielded site-specific TF binding fractions and the cooperativity among adjacent TFs. In a human lymphoblastoid cell line, we found that genes in a correlated gene module (CGM) share TF(s) in their cis-regulatory elements to participate a particular biological function. Finally, single-cell resolved experiments (scFOODIE) allow cell-type-specific TF footprinting in heterogeneous brain tissues.

genomics↗

bioRxiv2024

Spatial Single-cell Analysis Decodes Cortical Layer and Area Specification

The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas1,2. The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization3,4. While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation5,6,7,8. Here, we utilized multiplexed error-robust fluorescence in situ hybridization (MERFISH)9, augmented with deep-learning-based cell segmentation, to examine the molecular, cellular, and cytoarchitectural development of human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing 16 million single cells, spans eight cortical areas across four time points in the second and third trimesters. We uncovered an early establishment of the six-layer structure, identifiable in the laminar distribution of excitatory neuronal subtypes by mid-gestation, long before the emergence of cytoarchitectural layers. Notably, while anterior-posterior gradients of neuronal subtypes were generally observed in most cortical areas, a striking exception was the sharp molecular border between primary (V1) and secondary visual cortices (V2) at gestational week 20. Here we discovered an abrupt binary shift in neuronal subtype specification at the earliest stages, challenging the notion that continuous morphogen gradients dictate mid-gestation cortical arealization6,10. Moreover, integrating single-nuclei RNA-sequencing and in situ whole transcriptomics revealed an early upregulation of synaptogenesis in V1-specific Layer 4 neurons, suggesting a role of synaptogenesis in this discrete border formation. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This work not only provides a valuable resource for the field, but also establishes a spatially resolved single-cell analysis paradigm that paves the way for a comprehensive developmental atlas of the human brain.

neuroscience↗

bioRxiv2024

msCNVS: medium throughput single cell copy number variation sequencing with barcoded library construction free of preamplification toward clinical implementation

Single cell copy number variation sequencing (scCNV-seq) is valuable for genomic analysis of a variety of health and disease systems, yet the available methods either depend on either preamplification of the whole genome of each cell, special devices or untracable, which hinder scCNV-seq practice in clinics. Here we provide scalable multiplex scCNV-seq (msCNVS) that allows direct medium-throughput library construction for single cells, which are barcoded individually with Tn5 transposome in a microplate and immediately pooled for downstream processes, elevating the efficiency by orders of magnitude. An algorithm is developed on the distribution of segmented normalized read count density to identify the major peaks associating with integer copy numbers, further improving the accuracy for objective CNV calling. Here msCNVS faithfully distinguishes the unique CNV patterns of 5 cell lines. The individual msCNVS profiles of 70 individual K562 cells highly correlate with the profile of K562 bulk cells (R=0.90-0.98), and the triplicates of HeLa3 bulk cells correlated nearly perfect (R=0.99). The msCNVS CNV profiles of primary cell cultures of amniotic fluid are confirmed by G-banding karyotype analysis and chromosomal microarray analysis. Additionally, the coverage uniformity of msCNVS is superior to that of MDA and MALBAC and approaches what eMDA and DOP-PCR achieves. Furthermore, msCNVS detects CNV deletions in 2 stunted, abnormal blastocysts, one with CNV mosaicism, and uncovered variants of CNVs in circulated tumor cells, cancerous pleural effusion cells, and patient-derived xenograft nuclei. Thus, msCNVS promises a robust, reliable and highly efficient approach to genomic testing of precious and rare cells like those typically obtained in reproductive and cancer clinics. One-Sentence SummaryBy early pooling of multiple single cells individually barcoded with Tn5 transposome, msCNVS enables efficient CNV profiling of rare clinic samples

genomics↗

bioRxiv2024

Benchmarking clustering, alignment, and integration methods for spatial transcriptomics

Spatial transcriptomics (ST) is advancing our understanding of complex tissues and organisms. However, building a robust clustering algorithm to define spatially coherent regions in a single tissue slice, and aligning or integrating multiple tissue slices originating from diverse sources for essential downstream analyses remain challenging. Numerous clustering, alignment, and integration methods have been specifically designed for ST data by leveraging its spatial information. The absence of benchmark studies complicates the selection of methods and future method development. Here we systematically benchmark a variety of state-of-the-art algorithms with a wide range of real and simulated datasets of varying sizes, technologies, species, and complexity. Different experimental metrics and analyses, like adjusted rand index (ARI), uniform manifold approximation and projection (UMAP) visualization, layer-wise and spot-to-spot alignment accuracy, spatial coherence score (SCS), and 3D reconstruction, are meticulously designed to assess method performance as well as data quality. We analyze the strengths and weaknesses of each method using diverse quantitative and qualitative metrics. This analysis leads to a comprehensive recommendation that covers multiple aspects for users. The code used for evaluation is available on GitHub. Additionally, we provide jupyter notebook tutorials and documentation to facilitate the reproduction of all benchmarking results and to support the study of new methods and new datasets (https://benchmarkst-reproducibility.readthedocs.io/en/latest/).

bioinformatics↗

bioRxiv2024

Cortical traveling waves link visual and frontal cortex during working memory-guided behavior

Cortical traveling waves, or global patterns of activity that extend over several centimeters of the cortical surface, are a key mechanism for guiding the spatial propagation of neural activity and computational processes across the brain. Recent studies have implicated cortical traveling waves in successful short- and long-term memory encoding, storage, and retrieval. However, human memory systems are fundamentally-action oriented: eventually, the contents of memory must be utilized to produce appropriate behaviors. Cortical traveling waves could contribute to the production and control of memory-guided behaviors by flexibly routing information between brain areas responsible for storing memory content and brain areas responsible for planning and executing actions. Here, using short-term memory as a test case, we report evidence supporting this possibility. By applying image-based analyses to published human EEG studies, we show that the initiation of a memory-guided behavior is accompanied by a low-frequency (2-6 Hz) feedforward (occipital to frontal) traveling wave that predicts intra- and inter-individual differences in response onset, while the termination of a memory-guided behavior is followed by a higher frequency (14-32 Hz) feedback (frontal-to-occipital) traveling wave. Control analyses established that neither waveform could be explained by nuisance factors (e.g., propagation of visually-evoked potentials, eye movements, or passive volume conduction). Moreover, both waveforms required an overt behavior: when participants selected task-relevant memory content and prepared but did not yet execute an action based on this content, neither waveform was observed. Our findings suggest a role for traveling waves in the generation and control of memory-guided behaviors by flexibly organizing the timing and direction of interactions between brain regions involved in memory storage and action.

neuroscience↗

bioRxiv2024

CNVeil enables accurate and robust tumor subclone identification and copy number estimation from single-cell DNA sequencing data

Single-cell DNA sequencing (scDNA-seq) has significantly advanced cancer research by enabling precise detection of chromosomal aberrations, such as copy number variations (CNVs), at a single-cell level. These variations are crucial for understanding tumor progression and heterogeneity among tumor subclones. However, accurate CNV inference in scDNA-seq has been constrained by several factors, including low coverage, sequencing errors, and data variability. To address these challenges, we introduce CNVeil, a robust quantitative algorithm designed to accurately reveal CNV profiles while overcoming the inherent noise and bias in scDNA-seq data. CNVeil incorporates a unique bias correction method using normal cell profiles identified by a PCA-based Gini coefficient, effectively mitigating sequencing bias. Subsequently, a multi-level hierarchical clustering, based on selected highly variable bins, is employed to initially identify coarse subclones for robust ploidy estimation and further identify fine subclones for segmentation. To infer the CNV segmentation landscape, a novel change rate-based across-cell breakpoint identification approach is specifically designed to diminish the effects of low coverage and data variability on a per-cell basis. Finally, a consensus segmentation is utilized to further standardize read depth for the inference of the final CNV profile. In comprehensive benchmarking experiments, where we compared CNVeil with seven state-of-the-art CNV detection tools, CNVeil exhibited exceptional performance across a diverse set of simulated and real scDNA-seq data in cancer genomics. CNVeil excelled in subclone identification, segmentation, and CNV profiling. In light of these results, we anticipate that CNVeil will significantly contribute to single-cell CNV analysis, offering enhanced insights into chromosomal aberrations and genomic complexity.

bioinformatics↗

bioRxiv2024

scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.

genomics↗

bioRxiv2024

Complementation testing identifies causal genes at quantitative trait loci underlying fear related behavior

Knowing the genes involved in quantitative traits provides a critical entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. Here we address a key step towards that goal by deploying a test that directly queries whether a gene mediates the effect of a quantitative trait locus (QTL). To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six QTLs, and identified six genes. Four genes, Lsamp, Ptprd, Nptx2 and Sh3gl, have known roles in synapse function; the fifth gene, Psip1, is a transcriptional co-activator not previously implicated in behavior; the sixth is a long non-coding RNA 4933413L06Rik with no known function. Single nucleus transcriptomic and epigenetic analyses implicated excitatory neurons as likely mediating the genetic effects. Surprisingly, variation in transcriptome and epigenetic modalities between inbred strains occurred preferentially in excitatory neurons, suggesting that genetic variation is more permissible in excitatory than inhibitory neuronal circuits. Our results open a bottleneck in using genetic mapping of QTLs to find novel biology underlying behavior and prompt a reconsideration of expected relationships between genetic and functional variation.

genetics↗

bioRxiv2023

Community-based peptidomic clustering reveals pathogen-specific proteolytic signatures in wounds

Recent advances in mass spectrometry-based peptidomics has catalyzed the identification and quantification of thousands endogenous peptides across diverse biological systems. However, the large theoretical peptidomic landscape and high proportion of missing values poses several challenges for downstream analyses and limits the comparability of clinical samples. Here, we present a generalizable computational workflow that clusters peptides with overlapping sequences to reduce the dimensionality of peptidomic data, improve the definition of protease cut-sites, enhance inter-sample comparability, and enable the implementation of reliable and large-scale data analysis methods akin to those employed in other omics fields. We showcase the algorithm by performing large-scale quantitative analysis of wound fluid peptidomes of highly defined porcine wounds and human clinical non-healing wounds. The analysis revealed signature phenotype-specific peptide regions reflecting pathogen-specific proteolytic activity at the earliest stages of colonization, resulting in novel class of potential peptide cluster-based biomarkers.

bioinformatics↗

bioRxiv2023

Not dasycladalean alga, but an Odyssey of the earliest Phanerozoic animal reef-builders

The compacted macrofossil Protomelission? sp. from the early Cambrian Xiaoshiba Lagerstatte was recently ascribed to early dasycladalean green algae and used to disprove the bryozoan affinity of coeval phosphatized microfossils, which made the puzzling question whether the bryozoans originated in early Cambrian pending again. Our new analyses of multiple specimens which are conspecific with Protomelission? from the Chengjiang Lagerstatte indicate that they are not dasycladaleans but one of the three groups of archaeocyath-like sponges that atypically inhabited siliciclastic substrates. All the archaeocyath-like fossils share the same preservation mode and exhibit archaeocyath-type external skeletal features. Particularly, the Protomellision?-like fossils preserve structures indicative of archaeocyath aquiferous system and ontogeny. They represent the first recognized one-walled archaeocyath sponges in South China and evidence the niche expansion of archaeocyaths on their way of global radiation from Siberia, 518 million years ago. The origin of the bryozoans remains a mystery.

paleontology↗

bioRxiv2023

Cell type-specific effects of age and sex on human cortical neurons

Excitatory and inhibitory neurons establish specialized identities early in life through cell type-specific patterns of epigenetic regulation and gene expression. Although cell types are largely stable throughout the lifespan, altered transcriptional and epigenetic regulation may contribute to cognitive changes with advanced age. Using single-nucleus multiomic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex samples from young adult and aged donors, we found widespread age- and sex-related variability in specific neuronal cell types. The proportion of GABAergic inhibitory cells, including SST and VIP expressing cells, was reduced in aged donors. On the other hand, excitatory neurons had more profound age-related changes in their gene expression and DNA methylation compared with inhibitory cells. Hundreds of genes involved in synaptic activity were downregulated, while genes located in subtelomeric regions were upregulated with age and anti-correlated with telomere length. We further mapped sex differences in autosomal gene expression and escape from X-inactivation in specific neuron types. Multiomic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

neuroscience↗

bioRxiv2023

A peptide-centric local stability assay to unveil protein targets of diverse ligands

While tremendous progress has been made in chemical proteomics for identifying protein-ligand interactions, it remains challenging for proteome-wide identification of ligand-binding regions without modifying the ligands. Here, we discovered that "disruptive trypsinization" amplifies the readout of ligand-induced protein local stability shifts, and explored this notion in developing "peptide-centric local stability assay" (PELSA), a modification-free approach which achieves unprecedented sensitivity in proteome-wide target identification and binding-region determination. We demonstrate the versatility of PELSA by investigating the interactions across various biological contexts including drug-target interactions, metabolism, epitope mapping, metal proteomics, and post-translational modification recognition. A PELSA study of the oncometabolite R2HG revealed functional insights about its targets and pathogenic processes in both cancer and immune cells. Thus, beyond offering users unprecedented sensitivity for characterizing diverse target-ligand interactions, PELSA supports informative screening and hypothesis generation studies throughout life science.

biochemistry↗

bioRxiv2023

Epigenome erosion in Alzheimer's disease brain cells and induced neurons

Late-onset Alzheimers disease (LOAD) is typically sporadic, correlated only to advanced age, and has no clear genetic risk factors. The sporadic nature of LOAD presents a challenge to understanding its pathogenesis and mechanisms. Here, we comprehensively investigated the epigenome of LOAD primary entorhinal cortex brain tissues via single-cell multi-omics technologies, simultaneously capturing DNA methylation and 3D chromatin conformation. We identified AD-specific DNA methylation signatures and found they interact with bivalent promoters of AD differentially expressed genes. In addition, we discovered global chromosomal epigenome erosion of 3D genome structure within and across brain cell types. Furthermore, to evaluate whether these age- and disease-dependent molecular signatures could be detected in the in vitro cellular models, we derived induced neurons (iNs) converted directly from AD patients fibroblasts and found a set of conserved methylation signatures and shared molecular processes. We developed a machine-learning algorithm to identify robust and consistent methylation signatures of LOAD in vivo primary brain tissues and in vitro fibroblast-derived iNs. The results recapitulate the age- and disease-related epigenetic features in iNs and highlight the power of epigenome and chromatin conformation for identifying molecular mechanisms of neuronal aging and generating biomarkers for LOAD. HIGHLIGHTO_LIAD-specific DNA methylation signatures are identified in entorhinal cortex brain cell types C_LIO_LIThe AD differentially expressed genes linked with differentially methylated regions via loop interactions are enriched in a bivalent chromatin state C_LIO_LIChromosomal epigenome erosion of 3D genome structures occurs in LOAD brain cell types. C_LIO_LIShared and reliable methylation signatures are observed in both in vitro cellular iN models and primary brain tissues. C_LIO_LIMachine learning models identify robust and reliable methylation loci as AD biomarkers across cell types. C_LI

genomics↗