Heritable transcriptional defects from aberrations of nuclear architecture.

Transcriptional heterogeneity due to plasticity of the epigenetic state of chromatin contributes to tumour evolution, metastasis and drug resistance1-3. However, the mechanisms that cause this epigenetic variation are incompletely understood. Here we identify micronuclei and chromosome bridges, aberrations in the nucleus common in cancer4,5, as sources of heritable transcriptional suppression. Using a combination of approaches, including long-term live-cell imaging and same-cell single-cell RNA sequencing (Look-Seq2), we identified reductions in gene expression in chromosomes from micronuclei. With heterogeneous penetrance, these changes in gene expression can be heritable even after the chromosome from the micronucleus has been re-incorporated into a normal daughter cell nucleus. Concomitantly, micronuclear chromosomes acquire aberrant epigenetic chromatin marks. These defects may persist as variably reduced chromatin accessibility and reduced gene expression after clonal expansion from single cells. Persistent transcriptional repression is strongly associated with, and may be explained by, markedly long-lived DNA damage. Epigenetic alterations in transcription may therefore be inherently coupled to chromosomal instability and aberrations in nuclear architecture.

Efficient exosome subpopulation isolation and proteomic profiling using a Sub-ExoProfile chip towards cancer diagnosis and treatment.

Exosomes have been extensively studied as liquid biopsy biomarkers in the past decade. However, the origin and molecular heterogeneity of exosomes hinder the research development moving from proof-of-concept to clinical applications. Herein, we report an integrated microfluidic platform termed Sub-ExoProfile chip, to achieve the selective isolation and subsequent proteomic profiling of multiplex exosome subpopulations simultaneously. The Sub-ExoProfile chip comprises three cylindrical self-assembled nanopillars, on which specific exosome capture antibodies (CD81, EpCAM, HER2) were immobilized to capture and sort different exosome subpopulations. It is worth noting that the 3D porous nanopillars afford enhanced interface binding efficiency; thus, a tumor-specific exosome subpopulation with lowly-expressed surface marker was still isolated with satisfactory capture efficiency. Moreover, the amphiphilic mesoporous silica nanoparticle self-assembled nanopillars also served as a nanoreactor for the enrichment and in situ digestion of exosomal proteins, providing improved performance for the mass-spectrometry based molecular characterization of exosome subpopulations. The Sub-ExoProfile chip was investigated on standard exosome samples from different breast cancer cell lines. The isolation and quantitative detection of exosome subpopulations were in line with the molecular subtype of breast cancer cell lines, and the molecular makeup was confirmed using classic microplate ELISA. Clinical samples from HER2-positive and triple-negative breast cancer patients were also examined using the Sub-ExoProfile chip. The quantitative results of three exosome subpopulations distinguished the three subtypes of breast cancer significantly. Most importantly, the molecular characterization of three exosome subpopulations revealed that the distinct exosome subpopulation participated in a different signaling pathway and performed distinct biological functions. It is envisioned that the analysis of the exosome subpopulation on the Sub-ExoProfile chip will facilitate the screening of tumor-specific exosomal biomarkers and open a new avenue for exosome-based liquid biopsy.

Identification of microRNAs for the early diagnosis of Parkinson's disease and multiple system atrophy.

MicroRNAs are reportedly involved in the pathogenesis of neurodegenerative diseases, including Parkinson's disease and multiple system atrophy. We previously identified 7 differentially expressed microRNAs in Parkinson's disease patients and control sera (miR-30c, miR-31, miR-141, miR-146b-5p, miR-181c, miR-214, and miR-193a-3p). To investigate the expression levels of the 7 serum microRNAs in Parkinson's disease and multiple system atrophy, 23 early Parkinson's disease patients (who did not take any anti- Parkinson's disease drugs), 23 multiple system atrophy patients, and 24 normal controls were recruited at outpatient visits in this study. The expression levels of the 7 microRNAs in serum were detected using quantitative real-time polymerase chain reaction. A receiver operating characteristic curve was used to evaluate whether microRNAs can differentially diagnose Parkinson's disease and multiple system atrophy. Clinical scales were used to analyze the correlations between serum microRNAs and clinical features. The results indicated that miR-214 could distinguish Parkinson's disease from the controls, and another 3 microRNAs could differentiate multiple system atrophy from the controls (miR-141, miR-193a-3p, and miR-30c). The expression of miR-31, miR-141, miR-181c, miR-193a-3p, and miR-214 were lower in multiple system atrophy than in Parkinson's disease (all P < 0.05). Combinations of microRNAs accurately discriminated Parkinson's disease from multiple system atrophy (area under the receiver operating characteristic curve = 0.951). For the correlation analysis, negative correlations were discovered between the expression of miR-214 and the Hamilton Anxiety Scale and Parkinson's Disease Non-Motor Symptom scores (all P < 0.05). Our results demonstrate that the distinctive characteristics of microRNAs differentiate Parkinson's disease and multiple system atrophy patients from healthy controls and may be used for the early diagnosis of Parkinson's disease and multiple system atrophy.

Far-field super-focusing by a feedback-based wavefront shaping method.

Abbe diffraction limit has always been an important subject in conventional far-field focusing and imaging systems, where the resolution of an image is usually limited to 0.5λ/NA. Recently, the studies of the optical super-oscillation lens (SOL) enable us to break the limitation in both theory and practice successfully. Here a genetic algorithm was introduced to design the SOL phase more controllably and precisely obtain much better focusing such as the focal spot with 0.105λ/NA (or 79.0% minification) in the simulation and 65.5% minification in the experimental demonstration. This technique is of great significance in advanced optical lithography or biology microscopy, because it promises non-invasive unlabelled imaging from the far field.

Highly efficient and selective enrichment of glycopeptides using easily synthesized magG/PDA/Au/l-Cys composites.

Highly selective and efficient enrichment of glycopeptides from complex biological samples is necessary. In this study, novel zwitterionic hydrophilic polydopamine-coated magnetic graphene composites (magG/PDA/Au/l-Cys) were synthesized and applied to the enrichment of glycopeptides. The size, morphology, and composition of magG/PDA/Au/l-Cys composites were investigated by transmission electron microscopy, scanning electron microscopy, FT-infrared spectroscopy, and X-ray diffraction. The composites possessed a number of desirable characteristics, including good biocompatibility easy separation property and excellent hydrophilicity. By virtue of the features contributed by different ingredients, the prepared composites demonstrated superior performance for glycopeptide enrichment with high sensitivity (0.1 fmol), efficiency, selectivity (1:100), and repeatability (at least ten times). In addition, the composites were successfully applied to the enrichment of glycopeptides from human serum and 40 unique N-glycosylation peptides from 31 different N-linked glycoproteins were identified. The superior hydrophilic material is of great potential for the analysis of glycoproteins.

Laser-assisted proteolysis for accelerating and enhancing protein N-termini analysis.

RATIONALE: Targeted analysis of protein N-termini contributes to elucidating the starting sites and post-translational modifications of mature protein N-termini. Tryptic digestion is important in protein N-termini analysis, as well as in conventional bottom-up proteomics strategies. It is essential to explore a new proteolysis method for the enhancement of protein N-termini analysis. METHODS: Laser-assisted proteolysis was compared with conventional overnight proteolysis. Four standard proteins were studied as models and analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. 100 pg of synthesized peptide was used as internal standard for comparison of N-terminus intensity. Laser-assisted proteolysis was demonstrated to accelerate and enhance N-termini analysis. A complex mouse liver proteome sample was used to validate the effect of laser-assisted proteolysis. RESULTS: According to online database search, the number of matched peptides of four model proteins and the sequence coverage were comparable between the two proteolysis methods. Laser exposure time (40 s) could enhance the release of the N-terminus in model proteins. The number of identified N-termini in mouse liver was improved by 28.3% in the laser-assisted digest, compared to the conventional overnight digest. The time cost for digestion was shortened from overnight to 40 s. CONCLUSIONS: Laser-assisted proteolysis was demonstrated to accelerate proteolysis and enhance N-termini analysis. If laser-assisted proteolysis was integrated into protein N-termini targeted methods, the performance of those methods should be improved. Copyright © 2016 John Wiley & Sons, Ltd.

A high-throughput method for measurement of glycohemoglobin in blood samples utilizing laser-accelerated proteolysis and MALDI-TOF MS.

Glycosylated hemoglobin A1c (HbA1c) is a useful marker for the diagnosis of diabetes mellitus. Commercial column separation methods for HbA1c measurement were lacking throughput and sometimes interfered with hemoglobin variants. In this work, we developed a high-throughput and specific method for HbA1c by quantitative measurement of N-terminal peptides (NT method). Two thousand specimens could be measured in 8 h. The high-throughput was achieved by using a fast analysis of matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) and an efficient proteolysis accelerated by laser irradiation. An intensity ratio of glycosylated to non-glycosylated hemoglobin N-terminal peptides was used to calculate the HbA1c level in blood. Interference from Hb variants of N-terminal peptides could be excluded by a highly accurate mass selection. The coefficient of variation (CV) of intra-assay precision was 9.8 and 9.9%, respectively. The CVs of inter-assay precision over 20 days were 9.1 and 8.4%, respectively. Measurement results were well correlated with the commercially available column method (r = 0.995). The NT method is promising for large-scale screening for diabetes mellitus among people.

A novel method to isolate protein N-terminal peptides from proteome samples using sulfydryl tagging and gold-nanoparticle-based depletion.

A novel method to isolate global N-termini using sulfydryl tagging and gold-nanoparticle-based depletion (STagAu method) is presented. The N-terminal and lysine amino groups were first completely dimethylated at the protein level, after which the proteins were digested. The newly generated internal peptides were tagged with sulfydryl by Traut's reagent through digested N-terminal amines in yields of 96%. The resulting sulfydryl peptides were depleted through binding onto nano gold composite materials. The Au-S bond is stable and widely used in materials science. Nano gold composite materials showed nearly complete depletion of sulfydryl peptides. A set of the acetylated and dimethylated N-terminal peptides were analyzed by liquid chromatography-tandem mass spectrometry. This method was demonstrated to be an efficient N-terminus enrichment method because of the use of an effective derivatization reaction, in combination with robust and relative easy to implement Au-S coupling. We identified 632 N-terminal peptides from 386 proteins in a mouse liver sample. The STagAu approach presented is therefore a facile and efficient method for mass-spectrometry-based analysis of proteome N-termini or protease-generated cleavage products.

Association between dietary intake of saturated fatty acid subgroups and breast cancer risk.

The impact of dietary saturated fatty acids (SFAs) on breast cancer risk may vary depending on their carbon chain lengths, attributable to the discrepancy in their dietary sources and biological activities. The associations between SFA subgroups classified by chain length and breast cancer risk remain controversial. In this case-control study, we aimed to investigate the association between the dietary intake of SFA subgroups, classified by chain lengths, and odds of breast cancer in China. This study included 1661 cases of breast cancer (confirmed as primary and histologically) and 1674 frequency-matched controls. Face-to-face interviews were used to collect basic information, while dietary intake information was obtained by a food frequency questionnaire. The unconditional logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (95% CIs). All SFA subgroups were inversely associated with odds of breast cancer. The adjusted ORs (95% CIs) were 0.78 (0.61-0.99) for medium-chain SFAs, 0.50 (0.31-0.83) for long even-chain SFAs, 0.69 (0.54-0.88) for long odd-chain, and 0.67 (0.48-0.95) for very long-chain SFAs, respectively. In the restricted cubic spline (RCS) models, a non-linear M-shaped association was observed between long odd-chain SFAs and odds of breast cancer (Pnon-linearity = 0.007). However, the associations of medium-chain SFAs, long even-chain SFAs, and very long-chain SFAs did not reach statistical significance (Pnon-linearity > 0.05). No significant interactions were observed between all these four subgroups of SFAs and menopausal status or BMI. Our findings emphasize the significance of elucidating the associations of dietary SFAs according to chain lengths, providing insights into the etiology as well as the potential benefits of SFA-rich food intake in reducing the risk of breast cancer. Further prospective cohort studies and intervention studies are warranted to confirm these findings and identify the underlying mechanisms of the association between dietary SFAs and breast cancer.

Clinical efficacy of combination therapy of FuXi-Tiandi-Wuxing Decoction and anti-viral drugs in the treatment of novel coronavirus pneumonia: A prospective interventional study.

Introduction: The National Administration of Traditional Chinese Medicine of the People's Republic of China (NATCM) and the State Administration of Traditional Chinese medicine (TCM) advocated a combination therapy of TCM and anti-viral drugs for novel coronavirus pneumonia (NCP) to improve the efficacy of clinical treatment. Methods: Forty-six patients diagnosed with NCP were sequentially divided into intent-to-treat population: the experimental group (combination of FuXi-Tiandi-Wuxing Decoction and anti-viral drugs; n = 23) and the control group (anti-viral drugs only) (n = 23). The two groups were compared in terms of duration of fever, cough symptom score, fatigue, appetite, dyspnea, out-of-bed activities, chest computer tomography (CT) recovery, virological clearance, average length of hospital stay, and clinical effective rate of drug. After 6 days of observation, patients from the control group were divided into as-treated population: experimental subgroup (n = 14) to obtain clinical benefit and control subgroup (n = 9). Results: There was a significant improvement in the duration of fever (1.087 ± 0.288 vs 4.304 ± 2.490), cough (0.437 ± 0.589 vs 2.435 ± 0.662; P < 0.05), chest CT evaluation (82.6% vs 43.4%; P < 0.05), and virological clearance (60.8% vs 8.7%; P < 0.05) in patients of the experimental group compared with patients in the control group. Further observation in as-treated population reported that cough (0.742 ± 0.463 vs 1.862 ± 0.347; P < 0.05) and fatigue (78.5% vs 33.3%; P < 0.05) were significantly relieved after adding FuXi-Tiandi-Wuxing Decoction to the existing treatment. Conclusion: An early treatment with combination therapy of FuXi-Tiandi-Wuxing Decoction and anti-viral drugs significantly relieves the clinical symptoms of NCP, shows improvement in chest CT scan, improves virological clearance, shortens average length of hospital stay, and reduces the risk of severe illness. The effect of FuXi-Tiandi-Wuxing Decoction in NCP may be clinically important and require further consideration.

Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis.

PURPOSE: Finding the biomarkers associated with autism spectrum disorder (ASD) is helpful for understanding the underlying roots of the disorder and can lead to earlier diagnosis and more targeted treatments. In essence, we are faced with two challenges (i) how to learn a node representation and a clean graph structure from original graph data with high dimensionality and (ii) how to jointly model the procedure of node representation learning, structure learning and graph classification. METHODS: We propose FSL-BrainNet, an interpretable graph convolution network (GCN) model for jointly Learning of node Features and clean Structures in brain networks for automatic brain network classification and interpretation. We formulate an end-to-end trainable and interpretable framework for graph classification and biomarkers (salient brain regions and potential subnetworks) identification. RESULTS: The experimental results on the ABIDE dataset show that our proposed methods not only achieve improved prediction performance compared with the state-of-the-art methods, but also find a compact set of highly suggestive biomarkers including relevant brain regions and subnetworks to ASD. CONCLUSION: Through node feature learning and structure learning, our model can simultaneously select important brain regions and identify subnetworks.

Meta-optics empowered vector visual cryptography for high security and rapid decryption.

Optical encryption is a promising approach to protecting secret information owing to the advantages of low-power consumption, parallel, high-speed, and multi-dimensional processing capabilities. Nevertheless, conventional strategies generally suffer from bulky system volume, relatively low security level, redundant measurement, and/or requirement of digital decryption algorithms. Here, we propose a general optical security strategy dubbed meta-optics-empowered vector visual cryptography, which fully exploits the abundant degrees of freedom of light as well as the spatial dislocation as key parameters, significantly upgrading the security level. We also demonstrate a decryption meta-camera that can implement the reversal coding procedure for real-time imaging display of hidden information, avoiding redundant measurement and digital post-processing. Our strategy features the merits of a compact footprint, high security, and rapid decryption, which may open an avenue for optical information security and anti-counterfeiting.

Modeling global and local label correlation with graph convolutional networks for multi-label chest X-ray image classification.

The diagnosis of chest diseases is a challenging task for assessing thousands of radiology subjects. Their diagnosis decisions heavily rely on the expert radiologists' manual annotations. It is important to develop automated analysis methods for the computer-aided diagnosis of chest diseases on chest radiography. To explore the label relationship and improve the diagnosis performance, we present an end-to-end multi-label learning framework for jointly modeling the global and local label correlation, called GL-MLL that (1) explores the label correlation from a globally static view and a locally adaptive view, (2) considers the imbalanced class distribution, and (3) focuses on capturing label-specific features in image-level representation. We validate the performance of the proposed framework on the CheXpert dataset. The results demonstrate that the proposed GL-MLL outperforms state-of-the-art approaches. The code is available at https://github.com/llt1836/GL-MLL.

Genetic Analysis of Patients With Early-Onset Parkinson's Disease in Eastern China.

Background: Genetic factors play an important role in the pathogenesis of early-onset Parkinson's disease (EOPD). To date, more than 20 pathogenic genes associated with Parkinson's disease (PD) have been identified. This study aims to explore the mutation spectrum of EOPD and the clinical characteristics of mutation carriers in eastern China. Methods: We recruited 155 unrelated EOPD patients, including 8 familial and 147 sporadic EOPD (age at onset ≤ 50 years). Overall, 24 known PD-associated genes were detected by whole exome sequencing and multiplex ligation-dependent probe amplification (MLPA) from patient samples. The genetic and clinical characteristics of pathogenic/likely pathogenic (P/LP) loci in this cohort were analyzed. Results: Overall, 14 (9.03%) patients were detected with P/LP variants distributed in seven genes. The most frequent mutation occurred in PRKN (7/155, 4.52%), followed by LRRK2 (2/155, 1.29%), SNCA, CHCHD2, TMEM230, DNAJC13 and PLA2G6 (1/155, 0.64%, respectively). Exon rearrangement mutations accounted for 57.9% (11/19) of all mutations in PRKN. Four novel variants were detected: c.14T > C (p.M5T) in SNCA, c.297C > A (p.Y99X) in CHCHD2, c.2578C > T (p.R860C) in DNAJC13 and c.4C > T (p.Q2X) in TMEM230. We found the first case of LRRK2 c.6055G > A (p.G2019S) mutation in Chinese population. The median onset age of patients with P/LP mutations in autosomal recessive genes (PRKN and PLA2G6) was about 18.0 years earlier than patients without mutation. The proportion of patients with mutations were 63.64%, 27.03% and 9.68% when patients were stratified according to the age of onset at ≤ 30, ≤ 40 and ≤ 50 years, respectively. Conclusion: Early-onset Parkinson's disease patients from eastern China present a regional specific mutation spectrum. Analysis of larger patient cohorts is required to support these findings, and mechanistic studies of the four novel missense/non-sense mutations will clarify their role in the pathogenicity of EOPD.

TE-HI-GCN: An Ensemble of Transfer Hierarchical Graph Convolutional Networks for Disorder Diagnosis.

Accurate diagnosis of psychiatric disorders plays a critical role in improving the quality of life for patients and potentially supports the development of new treatments. Graph convolutional networks (GCNs) are shown to be successful in modeling applications with graph structures. However, training an accurate GCNs model for brain networks faces several challenges, including high dimensional and noisy correlation in the brain networks, limited labeled training data, and depth limitation of GCN learning. Generalization and interpretability are important in developing predictive models for clinical diagnosis. To address these challenges, we proposed an ensemble framework involving hierarchical GCN and transfer learning for sparse brain networks, which allows GCN to capture the intrinsic correlation among the subjects and domains, to improve the network embedding learning for disease diagnosis. Extensive experiments on two real medical clinical applications: diagnosis of Autism spectrum disorder (ASD) and diagnosis of Alzheimer's disease (AD) on both the ADNI and ABIDE databases, showing the effectiveness of the proposed framework. We achieved state-of-the-art accuracy and AUC for AD/MCI and ASD/NC (Normal control) classification in comparison with studies that used functional connectivity as features or GCN models. The proposed TE-HI-GCN model achieves the best classification performance, leading to about 27.93% (31.38%) improvement for ASD and 16.86% (44.50%) for AD in terms of accuracy and AUC compared with the traditional GCN model. Moreover, the obtained clustering results show high correspondence with the previous neuroimaging derived evidence of within and between-networks biomarkers for ASD. The discovered subnetworks are used as evidence for the proposed TE-HI-GCN model. Furthermore, this work is the first attempt of transfer learning on the two related disorder domains to uncover the correlation among the two diseases with a transfer learning scheme.

Comparison of Net Clinical Benefit Between Clopidogrel and Ticagrelor Following Percutaneous Coronary Intervention in Patients in China With Acute Coronary Syndrome.

INTRODUCTION: The objective of the present study was to evaluate the difference in net clinical benefit of clopidogrel plus aspirin compared with ticagrelor plus aspirin after 12 months in patients in mainland China with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) with newer-generation drug-eluting stents (DESs). METHODS: In this multicenter, retrospective, real-world study, the data were sourced from three databases: BRIC-ACS(I) study, COSTIC study, and 301 Hospital PCI patient database from January 2014 to October 2017. The primary endpoint of the study was net adverse clinical and cerebral events (NACCE) comprised of all-cause death, non-fatal myocardial infarction (MI), non-fatal stroke or Bleeding Academic Research Consortium (BARC) type ≥ 2 (excluding BARC type = 4) bleeding, whereas the secondary end point was evaluation of major adverse cardiovascular events (MACE) and BARC type ≥ 2 bleeding events. RESULTS: A total of 7862 ACS patients were included in the final analysis, of whom propensity score matching (PSM) analysis yielded 2165 patients in each cohort. After PSM analysis, cumulative incidence of NACCE was significantly lower with clopidogrel and aspirin than with ticagrelor and aspirin [117 (5.4%) vs. 180 (8.3%), P < 0.001] at 12 months. Effect estimates showed reduced risk of NACCE occurrence in patients treated with clopidogrel and aspirin [adjusted hazard ratio (aHR): 0.61, 95% CI 0.48-0.77, P < 0.001]. Incidence of bleeding was significantly lower in the clopidogrel cohort than in the ticagrelor cohort (aHR: 0.48, 95% CI 0.35-0.66, P < 0.001). Clopidogrel and aspirin therapy was comparable to ticagrelor and aspirin in reducing the incidence of MACE after PSM analysis. CONCLUSION: In Chinese ACS patients who underwent PCI with second-generation DESs, outpatient use of clopidogrel dual antiplatelet therapy (DAPT) was associated with reduction in NACCE and bleeding.

Factors predicting the occurrence of net adverse clinical and cerebral events in patients with acute coronary syndrome treated with clopidogrel or ticagrelor in combination with aspirin: a real-world study.

Background: This study aimed to establish the factors influencing the clinical benefits of ticagrelor and clopidogrel for acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) surgery. Methods: A multicenter, retrospective, real-world study was conducted on patients with ACS whose data were sourced from 3 databases, namely the BRIC-ACS(I) study, COSTIC study, and 301 Hospital PCI patient database from January 2014 to October 2017. The primary endpoint was net adverse clinical and cerebral events (NACCE). Results: A total of 7,236 ACS patients were included, of which 4,444 patients (61.4%) and 2,792 patients (38.6%) were in the clopidogrel dual antiplatelet therapy (DAPT) group and ticagrelor DAPT group, respectively. The hazard ratio (HR) for NACCE was significantly higher in patients aged ≥65 years than those aged ≤65 years in the clopidogrel DAPT group (HR: 2.15, 95% CI: 1.68-2.76) and ticagrelor DAPT group (HR: 1.75, 95% CI: 1.34-2.29). In patients treated with clopidogrel DAPT, patients with unstable angina had a significantly lower HR for NACCE than patients with ST-elevation myocardial infarction. Use of beta blockers (HR: 0.77, 95% CI: 0.60-0.99) was an influencing factor in patients treated with clopidogrel DAPT, whereas in patients treated with ticagrelor DAPT, only smoking status (HR: 0.75, 95% CI: 0.57-0.99) was a significant influencing factor. Conclusions: Age, hypertension status, and presence or absence of unstable angina were factors influencing the composite outcome of NACCE. The selection of patients to be treated with either clopidogrel DAPT or ticagrelor DAPT depending on the presence or absence of factors influencing treatment outcome may improve therapeutic management.

Altered Neural Network Connectivity Predicts Depression in de novo Parkinson's Disease.

Background: Depression, one of the most frequent non-motor symptoms in Parkinson's disease (PD), was proposed to be related to neural network dysfunction in advanced PD patients. However, the underlying mechanisms in the early stage remain unclear. The study was aimed to explore the alterations of large-scale neural networks in de novo PD patients with depression. Methods: We performed independent component analysis (ICA) on the data of resting-state functional magnetic resonance imaging from 21 de novo PD patients with depression (dPD), 34 de novo PD patients without depression (ndPD), and 43 healthy controls (HCs) to extract functional networks. Intranetwork and internetwork connectivity was calculated for comparison between groups, correlation analysis, and predicting the occurrence of depression in PD. Results: We observed an ordered decrease of connectivity among groups within the ventral attention network (VAN) (dPD < ndPD < HCs), mainly located in the left middle temporal cortex. Besides, dPD patients exhibited hypoconnectivity between the auditory network (AUD) and default mode network (DMN) or VAN compared to ndPD patients or healthy controls. Correlation analysis revealed that depression severity was negatively correlated with connectivity value within VAN and positively correlated with the connectivity value of AUD-VAN in dPD patients, respectively. Further analysis showed that the area under the curve (AUC) for dPD prediction was 0.863 when combining the intranetwork connectivity in VAN and internetwork connectivity in AUD-DMN and AUD-VAN. Conclusion: Our results demonstrated that early dPD may be associated with abnormality of attention bias and especially auditory attention processing. Altered neural network connectivity is expected to be a potential neuroimaging biomarker to predict depression in PD.

Characterizing mild cognitive impairment in prodromal Parkinson's disease: A community-based study in China.

OBJECTIVE: The International Parkinson and Movement Disorder Society (MDS) has published research criteria for prodromal Parkinson's disease (pPD), which includes cognitive impairment as a prodromal marker. However, the clinical features of mild cognitive impairment (MCI) in pPD remain unknown. Our study aimed to evaluate the frequency and clinical features of mild cognitive impairment of pPD in the elderly in China. METHODS: The cross-sectional community-based study recruited 2688 participants aged ≥50 years. Subjects were diagnosed with pPD according to the MDS criteria. Overall, 39 pPD and 22 healthy controls underwent comprehensive clinical and neuropsychological assessment. MCI was also diagnosed by the MDS criteria. Next, we investigated the relationship between clinical factors and cognition. RESULTS: Among the 2,663 dementia-free and Parkinson disease (PD)-free participants, 55 met the criteria for pPD (2.1%) and 23 pPD met the criteria for MCI. Memory, attention/working memory, and executive function were the most frequent impaired domains, and amnestic MCI multidomain phenotype was the most frequent MCI subtype (69.57%) in pPD. Additionally, correlation analysis revealed that the global cognitive performance was negatively related to UPDRS-III score (r = -0.456, p = 0.004). CONCLUSION: MCI, specifically impairment in memory, attention/working memory, and executive domain, is present at the prodromal stage of PD. In addition, cognitive performance is correlated with motor symptoms in pPD. Our results reflect that cognitive profile, combined with motor symptoms, can help clinicians to identify individuals with pPD early, as those would be the optimal candidates for neuroprotective therapy.

Differential functional connectivity of insular subdivisions in de novo Parkinson's disease with mild cognitive impairment.

The insula, consisting of functionally diverse subdivisions, plays a significant role in Parkinson's disease (PD)-related cognitive disorders. However, the functional connectivity (FC) patterns of insular subdivisions in PD remain unclear. Our aim is to investigate the changes in FC patterns of insular subdivisions and their relationships with cognitive domains. Three groups of participants were recruited in this study, including PD patients with mild cognitive impairment (PD-MCI, n = 25), PD patients with normal cognition (PD-NC, n = 13), and healthy controls (HCs, n = 17). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in insular subdivisions of the three groups. Moreover, all participants underwent a neuropsychological battery to assess cognition so that the relationship between altered FC and cognitive performance could be elucidated. Compared with the PD-NC group, the PD-MCI group exhibited increased FC between the left dorsal anterior insular (dAI) and the right superior parietal gyrus (SPG), and altered FC was negatively correlated with memory and executive function. Compared with the HC group, the PD-MCI group showed significantly increased FC between the right dAI and the right median cingulate and paracingulate gyri (DCG), and altered FC was positively related to attention/working memory, visuospatial function, and language. Our findings highlighted the different abnormal FC patterns of insular subdivisions in PD patients with different cognitive abilities. Furthermore, dysfunction of the dAI may partly contribute to the decline in executive function and memory in early drug-naïve PD patients.