Identification and verification of a novel signature that combines cuproptosis-related genes with ferroptosis-related genes in osteoarthritis using bioinformatics analysis and experimental validation.

BACKGROUND: Exploring the pathogenesis of osteoarthritis (OA) is important for its prevention, diagnosis, and treatment. Therefore, we aimed to construct novel signature genes (c-FRGs) combining cuproptosis-related genes (CRGs) with ferroptosis-related genes (FRGs) to explore the pathogenesis of OA and aid in its treatment. MATERIALS AND METHODS: Differentially expressed c-FRGs (c-FDEGs) were obtained using R software. Enrichment analysis was performed and a protein-protein interaction (PPI) network was constructed based on these c-FDEGs. Then, seven hub genes were screened. Three machine learning methods and verification experiments were used to identify four signature biomarkers from c-FDEGs, after which gene set enrichment analysis, gene set variation analysis, single-sample gene set enrichment analysis, immune function analysis, drug prediction, and ceRNA network analysis were performed based on these signature biomarkers. Subsequently, a disease model of OA was constructed using these biomarkers and validated on the GSE82107 dataset. Finally, we analyzed the distribution of the expression of these c-FDEGs in various cell populations. RESULTS: A total of 63 FRGs were found to be closely associated with 11 CRGs, and 40 c-FDEGs were identified. Bioenrichment analysis showed that they were mainly associated with inflammation, external cellular stimulation, and autophagy. CDKN1A, FZD7, GABARAPL2, and SLC39A14 were identified as OA signature biomarkers, and their corresponding miRNAs and lncRNAs were predicted. Finally, scRNA-seq data analysis showed that the differentially expressed c-FRGs had significantly different expression distributions across the cell populations. CONCLUSION: Four genes, namely CDKN1A, FZD7, GABARAPL2, and SLC39A14, are excellent biomarkers and prospective therapeutic targets for OA.

PELI1 overexpression contributes to pancreatic cancer progression through upregulating ubiquitination-mediated INPP5J degradation.

Inositol Polyphosphate-5-Phosphatase J (INPP5J), a 5-phosphatase, has been identified as a tumor suppressor in several types of cancer. However, its role in pancreatic cancer (PC) is unknown. We found that the INPP5J expression was markedly lower in PC tissues (n = 50) compared to paired adjacent non-tumor tissues, and the lower INPP5J expression was relevant to a worse prognosis of PC patients. We thus proposed that INPP5J might inhibit PC progression and conducted gain-of- and loss-of-function experiments to test our hypothesis. Our results showed that overexpression of INPP5J inhibited cell proliferation, invasion, migration, and xenografted tumor of PC cells. INPP5J silencing showed the opposite effect. Pellino E3 Ubiquitin Protein Ligase 1 (PELI1) is one of the ubiquitin ligases known to promote ubiquitination of its downstream targets. We found that PELI1 could interact with INPP5J and promote the ubiquitination and degradation of INPP5J. PELI1 overexpression enhanced malignant behaviors of PC cells. However, INPP5J overexpression restored the alterations caused by PELI1 overexpression. In conclusion, the results suggest that the decreased INPP5J expression, caused by PELI1 through ubiquitination, may promote PC progression. The PELI1-INPP5J axis represents a potential therapeutic targetable node for PC.

The deep learning framework iCanTCR enables early cancer detection using the T cell receptor repertoire in peripheral blood.

T cells recognize tumor antigens and initiate an anti-cancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stages. Here, we developed the deep learning framework iCanTCR to identify cancer patients based on the TCR repertoire. The iCanTCR framework uses TCRß sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2000 publicly available TCR repertoires from eleven types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish cancer patients from non-cancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an area under the curve (AUC) of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for non-invasive cancer diagnosis.

FDG PET/CT in a Case of Primary Lymphoma of the Ureter.

ABSTRACT: Primary lymphoma of the ureter is extremely rare. We describe the contrast-enhanced CT and FDG PET/CT findings in a case of diffuse large B-cell lymphoma transformed from mucosa-associated lymphoid tissue lymphoma limited to the left ureter. Contrast-enhanced CT showed 2 short-segment circumferential thickening and enhancement of the left pelvic and intramural ureteral wall. The thickened ureteral wall showed significantly increased FDG uptake mimicking urothelial carcinoma.

Aberrant expression of PELI1 caused by Jagged1 accelerates the malignant phenotype of pancreatic cancer.

Pancreatic cancer is one of the most aggressive cancers. PELI1 has been reported to promote cell survival and proliferation in multiple cancers. As of now, the role of PELI1 in pancreatic cancer is largely unknown. Here, we found that the PELI1 mRNA was higher expressed in pancreatic tumor tissues than in adjacent normal tissues, and the high PELI1 level in pancreatic cancer patients had a short survival time compared with the low level. Moreover, the results showed that PELI1 promoted cell proliferation, migration, and invasion, and inhibited apoptosis in vitro. Xenograft tumor experiments were used to determine the biological function of PELI1, and the results showed that PELI1 promoted tumor growth in vivo. Additionally, we found that Jagged1 activated PELI1 transcription in pancreatic cancer cells. To sum up, our results show that PELI1 affects the malignant phenotype of pancreatic cancer.

LC-NeRF: Local Controllable Face Generation in Neural Radiance Field.

3D face generation has achieved high visual quality and 3D consistency thanks to the development of neural radiance fields (NeRF). However, these methods model the whole face as a neural radiance field, which limits the controllability of the local regions. In other words, previous methods struggle to independently control local regions, such as the mouth, nose, and hair. To improve local controllability in NeRF-based face generation, we propose LC-NeRF, which is composed of a Local Region Generators Module (LRGM) and a Spatial-Aware Fusion Module (SAFM), allowing for geometry and texture control of local facial regions. The LRGM models different facial regions as independent neural radiance fields and the SAFM is responsible for merging multiple independent neural radiance fields into a complete representation. Finally, LC-NeRF enables the modification of the latent code associated with each individual generator, thereby allowing precise control over the corresponding local region. Qualitative and quantitative evaluations show that our method provides better local controllability than state-of-the-art 3D-aware face generation methods. A perception study reveals that our method outperforms existing state-of-the-art methods in terms of image quality, face consistency, and editing effects. Furthermore, our method exhibits favorable performance in downstream tasks, including real image editing and text-driven facial image editing.

N-glycosylation by N-acetylglucosaminyltransferase IVa enhances the interaction of integrin ß1 with vimentin and promotes hepatocellular carcinoma cell motility.

N-glycosylation has been revealed to be tightly associated with cancer metastasis. As a key transferase that catalyzes the formation of ß1,4 N-acetylglucosamine (ß1,4GlcNAc) branches on the mannose core of N-glycans, N-acetylglucosaminyltransferase IVa (GnT-IVa) has been reported to be involved in hepatocellular carcinoma (HCC) metastasis by forming N-glycans; however, the underlying mechanisms are largely unknown. In the current study, we found that GnT-IVa was upregulated in HCC tissues and positively correlated with worse outcomes in HCC patients. We found that GnT-IVa could promote tumor growth in mice; notably, this effect was attenuated after mutating the enzymatic site (D445A) of GnT-IVa, suggesting that GnT-IVa regulated HCC progression by forming ß1,4GlcNAc branches. To mechanistically investigate the role of GnT-IVa in HCC, we conducted GSEA and GO functional analysis as well as in vitro experiments. The results showed that GnT-IVa could enhance HCC cell migration, invasion and adhesion ability and increase ß1,4GlcNAc branch glycans on integrin ß1 (ITGB1), a tumor-associated glycoprotein that is closely involved in cell motility by interacting with vimentin. Interruption of ß1,4GlcNAc branch glycan modification on ITGB1 could suppress the interaction of ITGB1 with vimentin and inhibit cell motility. These results revealed that GnT-IVa could promote HCC cell motility by affecting the biological functions of ITGB1 through N-glycosylation. In summary, our results revealed that GnT-IVa is highly expressed in HCC and can form ß1,4GlcNAc branches on ITGB1, which are essential for interactions with vimentin to promote HCC cell motility. These findings not only proposed a novel mechanism for GnT-IVa in HCC progression but also revealed the significance of N-glycosylation on ITGB1 during the process, which may provide a novel target for future HCC therapy.

Fiber-specific white matter alterations in Parkinson's disease patients with freezing of gait.

Freezing of gait (FOG) is a gait disorder that usually occurs in advanced stages of Parkinson's disease (PD). Understanding the underlying mechanism of FOG is important for treatment and prevention. Previous studies have investigated white matter (WM) structure to explore the pathology of FOG. However, the pathology is still unclear, possibly due to the methodological limitation in identifying specific fiber tracts. This study aimed to investigate tract-specific WM structural changes in FOG patients and their relationships with clinical characteristics. We enrolled 19 PD patients with FOG (PD-FOG), 19 without FOG (PD-woFOG) and 21 controls. Fixel-based analysis is a novel framework to avoid the effect of crossing fibers, which provides the metrics to assess WM morphology. By combining a method for segmenting fibers, we identified abnormalities in the specific fiber tracts. Compared to PD-woFOG, PD-FOG showed significant increased fiber-bundle cross-section (FC) in the corpus callosum (CC), fornix (FX), inferior longitudinal fasciculus (ILF), striato-premotor (ST_PREM), superior thalamic radiation (STR), thalamo-premotor (T_PREM), increased fiber density and cross-section (FDC) in the STR, and decreased fiber density (FD) in the CC and ILF. Additionally, the ILF was correlated with motor, cognition and memory, the CC was correlated with anxiety, and the T_PREM was also correlated with cognition. In conclusion, in addition to impairments of WM found in PD-FOG, we found enhancements in WM, which may imply compensatory mechanisms. Furthermore, multiple fiber tracts were correlated with clinical characteristics, especially the ILF, validating the involvement of transmission circuits of multiple distinct information in mechanisms of FOG.

Character recognition competition for street view shop signs.

This paper presents the inaugural character recognition competition for street view shop signs, including the associated tasks, datasets, participating teams, the winning team's solution, and justification for the award.

An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation.

Single-cell RNA sequencing (scRNA-seq) detects whole transcriptome signals for large amounts of individual cells and is powerful for determining cell-to-cell differences and investigating the functional characteristics of various cell types. scRNA-seq datasets are usually sparse and highly noisy. Many steps in the scRNA-seq analysis workflow, including reasonable gene selection, cell clustering and annotation, as well as discovering the underlying biological mechanisms from such datasets, are difficult. In this study, we proposed an scRNA-seq analysis method based on the latent Dirichlet allocation (LDA) model. The LDA model estimates a series of latent variables, i.e. putative functions (PFs), from the input raw cell-gene data. Thus, we incorporated the 'cell-function-gene' three-layer framework into scRNA-seq analysis, as this framework is capable of discovering latent and complex gene expression patterns via a built-in model approach and obtaining biologically meaningful results through a data-driven functional interpretation process. We compared our method with four classic methods on seven benchmark scRNA-seq datasets. The LDA-based method performed best in the cell clustering test in terms of both accuracy and purity. By analysing three complex public datasets, we demonstrated that our method could distinguish cell types with multiple levels of functional specialization, and precisely reconstruct cell development trajectories. Moreover, the LDA-based method accurately identified the representative PFs and the representative genes for the cell types/cell stages, enabling data-driven cell cluster annotation and functional interpretation. According to the literature, most of the previously reported marker/functionally relevant genes were recognized.

PSMD12 interacts with CDKN3 and facilitates pancreatic cancer progression.

Proteasome 26S subunit, non-ATPase 12 (PSMD12) genes have been implicated in several types of malignancies but the role of PSMD12 in pancreatic cancer (PC) remains elusive. Bioinformatics analysis showed that PSMD12 was highly expressed in PC patients and was associated with shorter overall survival. PSMD12 was also shown to be highly expressed in PC tissues and cell lines. Upregulated PSMD12 showed enhanced cell viability, increased colony formation rate and upregulated levels of PCNA and c-Myc, while the inhibition of PSMD12 abated these levels. PSMD12 knockdown promoted cell apoptosis. The results of xenografts in nude mice confirmed that PSMD12 promoted PC tumor growth in vivo. Protein‒protein interaction network and functional enrichment analyses implied that PSMD12 may have a connection with cyclin-dependent kinase inhibitor 3 (CDKN3). Co­immunoprecipitation and western blot results confirmed that PSMD12 could interact with and abate the ubiquitination level of CDKN3, thus stabilizing the CDKN3 protein. Rescue assays showed that PSMD12 overexpression caused cell proliferation and that knockdown-induced cell apoptosis could be reversed by CDKN3 regulation. This work reveals the essential roles of PSMD12 in the proliferation and apoptosis of PC development. PSMD12 may regulate CDKN3 expression by interacting with and abating the ubiquitination level of CDKN3, thereby participating in the malignant behavior of PC.

Single-cell transcriptomics reveals the interaction between peripheral CD4+ CTLs and mesencephalic endothelial cells mediated by IFNG in Parkinson's disease.

Parkinson's disease (PD) is characterized by dopaminergic neurons degeneration in the substantia nigra pars compacta. Increasing evidence indicates that peripheral CD4+ T cells, a vital pathological component of PD, have been implicated in systemic inflammation activation, blood-brain barrier (BBB) dysfunction, central nervous system infiltration, and consequent neurons degeneration. However, there is no consensus on CD4+ T cell types' exact phenotypic characteristics in systemic inflammation and the mechanism of CD4+ T cells traffic into the BBB in patients with PD. In this study, we employed single-cell RNA sequencing (scRNA-seq) to elucidate the potential mechanism of T cells on the breakdown of BBB. The PD-associated Cytotoxic CD4+ T cells (CD4+ CTLs) were characterized by a significant increase in proportion as well as enhancement of interferon-gamma (IFNG) response and cell adhesion. Meanwhile, TBX21, IRF1 and NFATC2, identified as the key transcription factors in effector CD4+ T cells differentiation, induced overexpression of target genes-IFNG in CD4+ CTLs. Interestingly, endothelial cells (ECs) in PD patients were discovered to be more responsive to IFNG than other cell types of midbrain. Furthermore, the cell-cell communication analysis between CD4+ T cells and midbrain cells identified IFNG/IFNGR1 and SPP1/ITGB1 as the ligand-receptor pairs to mediate CD4+ CTLs' infiltration into the central nervous system (CNS) through the weakened ECs' tight junction. Together, these results suggested that PD-specific peripheral CD4+ CTLs might influence BBB function by migrating to mesencephalic endothelial cells (ECs) and activating the IFNG response in ECs.

Local white matter abnormalities in Parkinson's disease with mild cognitive impairment: Assessed with neurite orientation dispersion and density imaging.

Mild cognitive impairment is a nonmotor complication in Parkinson's disease (PD) that have a high risk of developing dementia. White matter is associated with cognitive function in PD and the alterations may occur before the symptoms of the disease. Previous diffusion tensor imaging (DTI) studies lacked specificity to characterize the concrete contributions of distinct white matter tissue properties. This may lead to inconsistent conclusions about the alteration of white matter microstructure. Here, we used neurite orientation dispersion and density imaging (NODDI) and white matter fiber clustering method to uncover local white matter microstructures in PD with mild cognitive impairment (PD-MCI). This study included 23 PD-MCI and 20 PD with normal cognition (PD-NC) and 21 healthy controls (HC). To probe specific and fine-grained differences, metrics of NODDI and DTI in white matter fiber clusters were evaluated using along-tract analysis. Our results showed that PD-MCI patients had significantly lower neurite density index (NDI) and orientation dispersion index (ODI) in white matter fiber clusters in the prefrontal region. Correlation analysis and receiver operating characteristic (ROC) analysis revealed that the diagnostic performance of NODDI-derived metrics in cingulum bundle (2 clusters) and thalamo-frontal (2 clusters) were superior to DTI metrics. Our study provides a more specific insight to uncover local white matter abnormalities in PD-MCI, which benefit understanding the underlying mechanism of cognitive decline in PD and predicting the disease in advance.

GID2 Interacts With CDKN3 and Regulates Pancreatic Cancer Growth and Apoptosis.

Dysregulation of deubiquitinase or ubiquitinase-mediated protein expression contributes to various diseases, including cancer. In the present study, we identified GID2, a subunit of the glucose-induced degradation-deficient (GID) complex that functions as an E3 ubiquitin ligase, as a potential key candidate gene in pancreatic cancer (PC) progression. The functional role and potential mechanism of GID2 in PC progression were investigated. Integrated bioinformatics analysis was performed to identify differentially expressed genes in PC based on the Gene Expression Profiling Interactive Analysis data sets. We found that GID2 was upregulated in PC tissues and that a high level of GID2 expression in clinical PC samples was positively associated with tumor stage and poor survival. Functional assays elucidated that GID2 expression promoted cell growth in vitro and accelerated tumor growth in vivo. GID2 knockdown effectively attenuated the malignant behaviors of PC cells and tumor formation. Furthermore, the protein network that interacted with the GID2 protein was constructed based on the GeneMANIA website. Cyclin-dependent kinase inhibitor 3 (CDKN3), a cell cycle regulator, was identified as a potential target of the GID2 protein. We revealed that GID2 positively regulated CDKN3 expression and inhibited CDKN3 ubiquitination. Furthermore, CDKN3 downregulation reversed the promoting effects of GID2 on PC progression. Therefore, the present study demonstrated that GID2 might regulate PC progression by maintaining the stability of the CDKN3 protein. These findings highlight the potential roles of the GID2/CDKN3 axis as a potential therapeutic target in PC.

Regional transcriptional vulnerability to basal forebrain functional dysconnectivity in mild cognitive impairment patients.

Nucleus basalis of Meynert (NbM), one of the earliest targets of Alzheimer's disease (AD), may act as a seed for pathological spreading to its connected regions. However, the underlying basis of regional vulnerability to NbM dysconnectivity remains unclear. NbM functional dysconnectivity was assessed using resting-state fMRI data of health controls and mild cognitive impairment (MCI) patients from the Alzheimer's disease Neuroimaging Initiative (ADNI2/GO phase). Transcriptional correlates of NbM dysconnectivity was explored by leveraging public intrinsic and differential post-mortem brain-wide gene expression datasets from Allen Human Brain Atlas (AHBA) and Mount Sinai Brain Bank (MSBB). By constructing an individual-level tissue-specific gene set risk score (TGRS), we evaluated the contribution of NbM dysconnectivity-correlated gene sets to change rate of cerebral spinal fluid (CSF) biomarkers during preclinical stage of AD, as well as to MCI onset age. An independent cohort of health controls and MCI patients from ADNI3 was used to validate our main findings. Between-group comparison revealed significant connectivity reduction between the right NbM and right middle temporal gyrus in MCI. This regional vulnerability to NbM dysconnectivity correlated with intrinsic expression of genes enriched in protein and immune functions, as well as with differential expression of genes enriched in cholinergic receptors, immune, vascular and energy metabolism functions. TGRS of these NbM dysconnectivity-correlated gene sets are associated with longitudinal amyloid-beta change at preclinical stages of AD, and contributed to MCI onset age independent of traditional AD risks. Our findings revealed the transcriptional vulnerability to NbM dysconnectivity and their crucial role in explaining preclinical amyloid-beta change and MCI onset age, which offer new insights into the early AD pathology and encourage more investigation and clinical trials targeting NbM.

Recursive-NeRF: An Efficient and Dynamically Growing NeRF.

View synthesis methods using implicit continuous shape representations learned from a set of images, such as the Neural Radiance Field (NeRF) method, have gained increasing attention due to their high quality imagery and scalability to high resolution. However, the heavy computation required by its volumetric approach prevents NeRF from being useful in practice; minutes are taken to render a single image of a few megapixels. Now, an image of a scene can be rendered in a level-of-detail manner, so we posit that a complicated region of the scene should be represented by a large neural network while a small neural network is capable of encoding a simple region, enabling a balance between efficiency and quality. Recursive-NeRF is our embodiment of this idea, providing an efficient and adaptive rendering and training approach for NeRF. The core of Recursive-NeRF learns uncertainties for query coordinates, representing the quality of the predicted color and volumetric intensity at each level. Only query coordinates with high uncertainties are forwarded to the next level to a bigger neural network with a more powerful representational capability. The final rendered image is a composition of results from neural networks of all levels. Our evaluation on public datasets and a large-scale scene dataset we collected shows that Recursive-NeRF is more efficient than NeRF while providing state-of-the-art quality. The code will be available at https://github.com/Gword/Recursive-NeRF.

MutCov: A pipeline for evaluating the effect of mutations in spike protein on infectivity and antigenicity of SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing an outbreak of coronavirus disease 2019 (COVID-19), is a major threat to public health worldwide. Previous studies have shown that the spike protein of SARS-CoV-2 determines viral infectivity and major antigenicity. However, the spike protein has been undergoing various mutations, which bring a great challenge to the prevention and treatment of COVID-19. Here we present the MutCov, a pipeline for evaluating the effect of mutations in spike protein on infectivity and antigenicity of SARS-CoV-2 by calculating the binding free energy between spike protein and angiotensin-converting enzyme 2 (ACE2) or neutralizing monoclonal antibody (mAb). The predicted infectivity and antigenicity were highly consistent with biologically experimental results, and demonstrated that the MutCov achieved good prediction performance. In conclusion, the MutCov is of high importance for systematically evaluating the effect of novel mutations and improving the prevention and treatment of COVID-19. The source code and installation instruction of MutCov are freely available at http://jianglab.org.cn/MutCov.

Global Characterization of Peripheral B Cells in Parkinson's Disease by Single-Cell RNA and BCR Sequencing.

Immune system plays important roles in the pathogenesis of Parkinson's disease (PD). However, the role of B cells in this complex disease are still not fully understood. B cells produce antibodies but can also regulate immune responses. In order to decode the relative contribution of peripheral B cell subtypes to the etiology of PD, we performed single cell RNA and BCR sequencing for 10,466 B cells from 8 PD patients and 6 age-matched healthy controls. We observed significant increased memory B cells and significant decreased naïve B cells in PD patients compared to healthy controls. Notably, we also discovered increased IgG and IgA isotypes and more frequent class switch recombination events in PD patients. Moreover, we identified preferential V and J gene segments of B cell receptors in PD patients as the evidence of convergent selection in PD. Finally, we found a marked clonal expanded memory B cell population in PD patients, up-regulating both MHC II genes (HLA-DRB5, HLA-DQA2 and HLA-DPB1) and transcription factor activator protein 1 (AP-1), suggesting that the antigen presentation capacity of B cells was enhanced and B cells were activated in PD patients. Overall, this study conducted a comprehensive analysis of peripheral B cell characteristics of PD patients, which provided novel insights into the humoral immune response in the pathogenesis of PD.

Identification of alternative splicing-derived cancer neoantigens for mRNA vaccine development.

Messenger RNA (mRNA) vaccines have shown great potential for anti-tumor therapy due to the advantages in safety, efficacy and industrial production. However, it remains a challenge to identify suitable cancer neoantigens that can be targeted for mRNA vaccines. Abnormal alternative splicing occurs in a variety of tumors, which may result in the translation of abnormal transcripts into tumor-specific proteins. High-throughput technologies make it possible for systematic characterization of alternative splicing as a source of suitable target neoantigens for mRNA vaccine development. Here, we summarized difficulties and challenges for identifying alternative splicing-derived cancer neoantigens from RNA-seq data and proposed a conceptual framework for designing personalized mRNA vaccines based on alternative splicing-derived cancer neoantigens. In addition, several points were presented to spark further discussion toward improving the identification of alternative splicing-derived cancer neoantigens.

Alterations in white matter fiber in Parkinson disease across different cognitive stages.

Cognitive impairment in Parkinson disease (PD) leads to substantial disability. Unlike external manifestations such as tremor, the decay of cognitive function is often an underlying process, and its neuroanatomic substrates are not yet fully elucidated. Knowledge regarding cognitive-related alterations in white matter (WM) pathways helps us understand the mechanisms of cognitive decline in patients with PD. Previous voxel-based analyses with Diffusion tensor imaging (DTI) metrics, such as fractional anisotropy (FA) and mean diffusivity (MD) have uncovered white matter differences in groupwise, but the conclusions were inconsistent. That was partially due to white matter fibers that are known to affect cognition, such as the corpus callosum (CC) and superior longitudinal fasciculus that cross in voxel, and are hard to interpreted by the abovementioned metrics. Furthermore, cognitive decay is a continuous process, it is difficult to reflect the continuous changes of white matter fibers between groups comparison. In the present work, we chose the constrained spherical deconvolution (CSD) and the fixel model, which avoided the effect of crossing fibers. To compare the white matter fiber in different cognitive stages of patients with PD, the results found that the CC, the cingulum bundle (CB), and the corticospinal tract (CST) showed the same trend in the decline of cognitive function, and this change may lead to the impairment of cognitive function. Our findings can help physicians determine the cognitive stage of PD from the perspective of white matter fiber and provide a reference for clinical trials and predictions.