Loss of the m6A methyltransferase METTL3 in monocyte-derived macrophages ameliorates Alzheimer's disease pathology in mice.

Alzheimer's disease (AD) is a heterogeneous disease with complex clinicopathological characteristics. To date, the role of m6A RNA methylation in monocyte-derived macrophages involved in the progression of AD is unknown. In our study, we found that methyltransferase-like 3 (METTL3) deficiency in monocyte-derived macrophages improved cognitive function in an amyloid beta (Aß)-induced AD mouse model. The mechanistic study showed that that METTL3 ablation attenuated the m6A modification in DNA methyltransferase 3A (Dnmt3a) mRNAs and consequently impaired YTH N6-methyladenosine RNA binding protein 1 (YTHDF1)-mediated translation of DNMT3A. We identified that DNMT3A bound to the promoter region of alpha-tubulin acetyltransferase 1 (Atat1) and maintained its expression. METTL3 depletion resulted in the down-regulation of ATAT1, reduced acetylation of α-tubulin and subsequently enhanced migration of monocyte-derived macrophages and Aß clearance, which led to the alleviated symptoms of AD. Collectively, our findings demonstrate that m6A methylation could be a promising target for the treatment of AD in the future.

GGC repeat expansion in NOTCH2NLC induces dysfunction in ribosome biogenesis and translation.

GGC repeat expansion in the 5' untranslated region (UTR) of NOTCH2NLC is associated with a broad spectrum of neurological disorders, especially neuronal intranuclear inclusion disease (NIID). Studies have found that GGC repeat expansion in NOTCH2NLC induces the formation of polyglycine (polyG)-containing protein, which is involved in the formation of neuronal intranuclear inclusions. However, the mechanism of neurotoxicity induced by NOTCH2NLC GGC repeats is unclear. Here, we used NIID patient-specific induced pluripotent stem cell (iPSC)-derived 3D cerebral organoids (3DCOs) and cellular models to investigate the pathophysiological mechanisms of NOTCH2NLC GGC repeat expansion. IPSC-derived 3DCOs and cellular models showed the deposition of polyG-containing intranuclear inclusions. The NOTCH2NLC GGC repeats could induce the upregulation of autophagic flux, enhance integrated stress response and activate EIF2α phosphorylation. Bulk RNA sequencing for iPSC-derived neurons and single-cell RNA sequencing (scRNA-seq) for iPSC-derived 3DCOs revealed that NOTCH2NLC GGC repeats may be associated with dysfunctions in ribosome biogenesis and translation. Moreover, NOTCH2NLC GGC repeats could induce the NPM1 nucleoplasm translocation, increase nucleolar stress, impair ribosome biogenesis and induce ribosomal RNA sequestration, suggesting dysfunction of membraneless organelles in the NIID cellular model. Dysfunctions in ribosome biogenesis and phosphorylated EIF2α and the resulting increase in the formation of G3BP1-positive stress granules may together lead to whole-cell translational inhibition, which may eventually cause cell death. Interestingly, scRNA-seq revealed that NOTCH2NLC GGC repeats may be associated with a significantly decreased proportion of immature neurons while 3DCOs were developing. Together, our results underscore the value of patient-specific iPSC-derived 3DCOs in investigating the mechanisms of polyG diseases, especially those caused by repeats in human-specific genes.

Clinical Efficacy of Neoadjuvant Chemotherapy plus Modified Radical Mastectomy for Stage II-III Breast Cancer Patients and Its Influence on Serum Tumor Markers.

Objective: This research aims to assess the clinical efficacy of neoadjuvant chemotherapy (NACT) in combination with modified radical mastectomy (MRM) for stage II-III breast cancer (BC) patients and its impact on serum tumor markers (STMs). Methods: The study included 119 stage II-III BC patients treated between June 2018 and June 2021. Among them, 55 cases underwent MRM (reference group), while 64 cases received NACT followed by MRM (research group). We compared intraoperative parameters (blood loss, operation time, hospital stay), clinical outcomes, the incidence of postoperative adverse events (AEs), changes in STMs (CA125, CA153, CEA), and one-year postoperative quality of life (QOL). Results: In comparison to the reference group, the research group exhibited significantly lower intraoperative blood loss, shorter operation times, reduced hospital stays, and higher rates of disease remission. Notably, the research group experienced a lower overall incidence of AEs, including skin flap necrosis, subscalp effusion, infection, and upper limb lymphedema. Postoperatively, all STMs in the research group exhibited statistically significant reductions and were lower than those in the reference group. Additionally, all QOL subscales demonstrated improvements and higher scores in the research group. Conclusions: NACT followed by MRM represents an effective approach for enhancing surgical outcomes and clinical efficacy in stage II-III BC patients. This combination therapy also reduces the risk of postoperative AEs and leads to favorable changes in STMs and postoperative QOL levels.

GIPC1 CGG Repeat Expansion Is Associated with Movement Disorders.

OBJECTIVE: CGG/GGC repeat expansion in FMR1 and NOTCH2NLC is reportedly associated with movement disorders; therefore, we hypothesized that the CGG repeat expansion in LRP12, NUTM2B-AS1, and GIPC1, which was previously identified in myopathy, might also be associated with movement-disorder phenotypes. Here, we investigated whether CGG repeat expansion in LRP12, NUTM2B-AS1, and GIPC1 presents in a cohort of patients with movement disorders. METHODS: We screened for the CGG repeat expansion in LRP12, NUTM2B-AS1, and GIPC1 in 1,346 movement-disorder patients and 1,451 matched healthy controls. RESULTS: No patients or controls harbored expanded CGG repeats in LRP12 or NUTM2B-AS1, whereas 16 patients harbored >40 CGG repeats in GIPC1, with 11 of these patients harboring >60 CGG repeats. One control individual harbored an expanded GIPC1 allele (83 CGG units), suggesting that approximately 1% of patients affected by movement disorders in our population might harbor GIPC1 CGG repeat expansion, with this likely extremely rare in healthy controls (<0.001). The clinical phenotypes of the GIPC1 CGG repeat-positive patients strongly resembled those in patients displaying NOTCH2NLC GGC repeat-positive movement disorders. Additionally, the GIPC1 CGG repeat-positive patients presented white-matter hyperintensities but without typical NOTCH2NLC-related high-intensity signals in the corticomedullary junction. Furthermore, 44% of the GIPC1 CGG repeat-positive patients showed a cognitive deficit, and skin biopsies in 2 patients revealed deposition of intranuclear inclusions. INTERPRETATION: The CGG repeat expansion in GIPC1 might be associated with movement-disorder phenotypes and lead to diseases related to intranuclear inclusions. ANN NEUROL 2022;91:704-715.

Identifying causal genes for migraine by integrating the proteome and transcriptome.

BACKGROUND: While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. METHODS: We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. RESULTS: We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. CONCLUSIONS: Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.

Easy-to-operate calibration method for structured light systems.

Traditional calibration methods of structured light measurement systems are expensive and difficult to operate. In this paper, an accurate, low-cost, and easy-to-operate calibration method is proposed, where each projector pixel is considered as a line-of-sight in space, and an off-the-shelf LCD monitor is used to display the calibration pattern. Experimental results verify the accuracy and validity of the proposed method.

Triple-negative breast cancer survival prediction: population-based research using the SEER database and an external validation cohort.

Introduction: Triple-negative breast cancer (TNBC) is linked to a poorer outlook, heightened aggressiveness relative to other breast cancer variants, and limited treatment choices. The absence of conventional treatment methods makes TNBC patients susceptible to metastasis. The objective of this research was to assess the clinical and pathological traits of TNBC patients, predict the influence of risk elements on their outlook, and create a prediction model to assist doctors in treating TNBC patients and enhancing their prognosis. Methods: We included 23,394 individuals with complete baseline clinical data and survival information who were diagnosed with primary TNBC between 2010 and 2015 based on the SEER database. External validation utilised a group from The Affiliated Lihuili Hospital of Ningbo University. Independent risk factors linked to TNBC prognosis were identified through univariate, multivariate, and least absolute shrinkage and selection operator regression methods. These characteristics were chosen as parameters to develop 3- and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) nomogram models. Model accuracy was assessed using calibration curves, consistency indices (C-indices), receiver operating characteristic curves (ROCs), and decision curve analyses (DCAs). Finally, TNBC patients were divided into groups of high, medium, and low risk, employing the nomogram model for conducting a Kaplan-Meier survival analysis. Results: In the training cohort, variables such as age at diagnosis, marital status, grade, T stage, N stage, M stage, surgery, radiation, and chemotherapy were linked to OS and BCSS. For the nomogram, the C-indices stood at 0.762, 0.747, and 0.764 in forecasting OS across the training, internal validation, and external validation groups, respectively. Additionally, the C-index values for the training, internal validation, and external validation groups in BCSS prediction stood at 0.793, 0.755, and 0.811, in that order. The findings revealed that the calibration of our nomogram model was successful, and the time-variant ROC curves highlighted its effectiveness in clinical settings. Ultimately, the clinical DCA showcased the prospective clinical advantages of the suggested model. Furthermore, the online version was simple to use, and nomogram classification may enhance the differentiation of TNBC prognosis and distinguish risk groups more accurately. Conclusion: These nomograms are precise tools for assessing risk in patients with TNBC and forecasting survival. They can help doctors identify prognostic markers and create more effective treatment plans for patients with TNBC, providing more accurate assessments of their 3- and 5-year OS and BCSS.

Naples Prognostic Score: A Novel Predictor of Survival in Patients with Triple-Negative Breast Cancer.

Purpose: This study investigated the correlation between the Naples prognostic score (NPS), clinicopathological traits, and the postoperative prognoses of patients with triple-negative breast cancer (TNBC). Based on NPS, a predictive nomogram was developed to estimate the long-term survival probabilities of patients with TNBC post-surgery. Patients and Methods: We retrospectively examined the clinical records of 223 women with TNBC treated at Ningbo Medical Center, Lihuili Hospital between January 1, 2016 and December 31, 2020. Blood tests and biochemical analyses were conducted before surgery. The prognostic nutritional index (PNI), controlling nutritional status (CONUT), neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and NPS were determined based on blood-related markers. A Kaplan-Meier survival analysis assessed the association between NPS, PNI, CONUT score, overall survival (OS), and breast cancer-specific survival (BCSS). Predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUC) and C index. The patients were randomly divided into the training and the validation group (6:4 ratio). A nomogram prediction model was developed and evaluated using the R Software for Statistical Computing (RMS) package. Results: NPS outperformed other scores in predicting inflammation outcomes. Patients with an elevated NPS had a poorer prognosis (P<0.001). Lymph node ratio (LNR), surgical method, postoperative chemotherapy, and NPS independently predicted OS, whereas M stage, LNR, and NPS independently predicted BCSS outcome. The OS and BCSS predicted by the nomogram model aligned well with the actual OS and BCSS. The decision curve analysis showed significant clinical utility for the nomogram model. Conclusion: In this study, NPS was an important prognostic indicator for patients with TNBC. The nomogram prognostic model based on NPS outperformed other prognostic scores for predicting patient prognosis. The model demonstrated a clear stratification ability for patient prognosis, which emphasized the potential benefits of early intervention for high-risk patients.

In this study, we aimed to understand how the Naples prognostic score (NPS) scoring system could predict the prognosis for patients with triple-negative breast cancer (TNBC). TNBC is a type of breast cancer that can be difficult to treat. Medical records of 223 women with TNBC were retrospectively analyzed. These women had their blood tested before surgery to check for certain markers related to nutrition and inflammation. NPS was used along with other scores to determine their accuracy in predicting survival. NPS was better at predicting outcomes than the other scores. The patients with higher NPS scores tended to have poorer outcomes. We also created a visual tool called a nomogram to help doctors predict patient outcomes based on the NPS scores. NPS can be a valuable tool for doctors treating patients with TNBC because it can help them predict how well a patient might do after surgery. This information could be used to tailor treatment plans for these patients. The nomogram provides a user-friendly way for doctors to use NPS in their practice. Overall, this study showed that NPS is a powerful tool for predicting outcomes for patients with TNBC, which could lead to better treatment decisions and improved outcomes for these patients.

Pathology steered stratification network for subtype identification in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by three neurobiological factors beta-amyloid, pathologic tau, and neurodegeneration. There are no effective treatments for AD at a late stage, urging for early detection and prevention. However, existing statistical inference approaches in neuroimaging studies of AD subtype identification do not take into account the pathological domain knowledge, which could lead to ill-posed results that are sometimes inconsistent with the essential neurological principles. PURPOSE: Integrating systems biology modeling with machine learning, the study aims to assist clinical AD prognosis by providing a subpopulation classification in accordance with essential biological principles, neurological patterns, and cognitive symptoms. METHODS: We propose a novel pathology steered stratification network (PSSN) that incorporates established domain knowledge in AD pathology through a reaction-diffusion model, where we consider non-linear interactions between major biomarkers and diffusion along the brain structural network. Trained on longitudinal multimodal neuroimaging data, the biological model predicts long-term evolution trajectories that capture individual characteristic progression pattern, filling in the gaps between sparse imaging data available. A deep predictive neural network is then built to exploit spatiotemporal dynamics, link neurological examinations with clinical profiles, and generate subtype assignment probability on an individual basis. We further identify an evolutionary disease graph to quantify subtype transition probabilities through extensive simulations. RESULTS: Our stratification achieves superior performance in both inter-cluster heterogeneity and intra-cluster homogeneity of various clinical scores. Applying our approach to enriched samples of aging populations, we identify six subtypes spanning AD spectrum, where each subtype exhibits a distinctive biomarker pattern that is consistent with its clinical outcome. CONCLUSIONS: The proposed PSSN (i) reduces neuroimage data to low-dimensional feature vectors, (ii) combines AT[N]-Net based on real pathological pathways, (iii) predicts long-term biomarker trajectories, and (iv) stratifies subjects into fine-grained subtypes with distinct neurological underpinnings. PSSN provides insights into pre-symptomatic diagnosis and practical guidance on clinical treatments, which may be further generalized to other neurodegenerative diseases.

Carbon Dot-Based Photo-Cross-Linked Gelatin Methacryloyl Hydrogel Enables Dental Pulp Regeneration: A Preliminary Study.

An essential factor in tooth nutritional deficits and aberrant root growth is pulp necrosis. Removing inflammatory or necrotic pulp tissue and replacing it with an inert material are the most widely used therapeutic concepts of endodontic treatment. However, pulp loss can lead to discoloration, increased fracture risk, and the reinfection of the damaged tooth. It is now anticipated that the pulp-dentin complex will regenerate through a variety of application methods based on human dental pulp stem cells (hDPSC). In order to create a photo-cross-linked gelatinized methacrylate hydrogel, GelMA/EUO-CDs-E (ECE), that is biodegradable and injectable for application, we created a novel nanoassembly of ECE based on eucommia carbon dots (EUO-CDs) and epigallocatechin gallate (EGCG). We then loaded it onto gelatin methacryloyl (GelMA) hydrogel. We have evaluated the material and examined its in vivo and in vitro angiogenesis-promoting potential as well as its dentin differentiation-enabling characteristics. The outcomes of the experiment demonstrated that GelMA/ECE was favorable to cell proliferation and enhanced hDPSC's capacity for angiogenesis and dentin differentiation. The regeneration of vascular-rich pulp-like tissues was found to occur in vivo when hDPSC-containing GelMA/ECE was injected into cleaned human root segments (RS) for subcutaneous implantation in nude mice. This suggests that the injectable bioscaffold is appropriate for clinical use in pulp regenerative medicine.

Recent Advances in Whiskers: Properties and Clinical Applications in Dentistry.

Whiskers are nanoscale, high-strength fibrous crystals with a wide range of potential applications in dentistry owing to their unique mechanical, thermal, electrical, and biological properties. They possess high strength, a high modulus of elasticity and good biocompatibility. Hence, adding these crystals to dental composites as reinforcement can considerably improve the mechanical properties and durability of restorations. Additionally, whiskers are involved in inducing the value-added differentiation of osteoblasts, odontogenic osteocytes, and pulp stem cells, and promoting the regeneration of alveolar bone, periodontal tissue, and pulp tissue. They can also enhance the mucosal barrier function, inhibit the proliferation of tumor cells, control inflammation, and aid in cancer prevention. This review comprehensively summarizes the classification, properties, growth mechanisms and preparation methods of whiskers and focuses on their application in dentistry. Due to their unique physicochemical properties, excellent biological properties, and nanoscale characteristics, whiskers show great potential for application in bone, periodontal, and pulp tissue regeneration. Additionally, they can be used to prevent and treat oral cancer and improve medical devices, thus making them a promising new material in dentistry.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes.

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

Artificial intelligence in breast cancer: application and future perspectives.

Breast cancer is one of the most common cancers and is one of the leading causes of cancer-related deaths in women worldwide. Early diagnosis and treatment are the key for a favorable prognosis. The application of artificial intelligence technology in the medical field is increasingly extensive, including image analysis, automated diagnosis, intelligent pharmaceutical system, personalized treatment and so on. AI-based breast cancer imaging, pathology and adjuvant therapy technology cannot only reduce the workload of clinicians, but also continuously improve the accuracy and sensitivity of breast cancer diagnosis and treatment. This paper reviews the application of AI in breast cancer, as well as looks ahead and poses challenges to the future development of AI for breast cancer detection and therapeutic, so as to provide ideas for future research.

Causal effects of genetically predicted endometriosis on breast cancer: a two-sample Mendelian randomization study.

This study used a Mendelian randomization (MR) approach to investigate the causal relationship between genetically predicted endometriosis (EMS) and breast cancer risk. A total of 122,977 cases and 105,974 controls were included in the analysis, with gene-level summary data obtained from the Breast Cancer Association Consortium (BCAC). An inverse variance-weighting approach was applied to assess the causal relationship between EMS and breast cancer risk, and weighted median and MR-Egger regression methods were used to evaluate pleiotropy. Results showed a causal relationship between EMS and a decreased risk of overall breast cancer (odds ratio [OR] 0.95; 95% CI 0.90-0.99, p = 0.02). Furthermore, EMS was associated with a lower risk for estrogen receptor (ER)-positive breast cancer in a subgroup analysis based on immunohistochemistry type (OR 0.91; 95% CI 0.86-0.97, p = 0.005). However, there was no causal association between ER-negative breast cancer and survival (OR 1.00; 95% CI 0.94-1.06, p = 0.89). Pleiotropy was not observed. These findings provide evidence of a relationship between EMS and reduced breast cancer risk in invasive breast cancer overall and specific tissue types, and support the results of a previous observational study. Further research is needed to elucidate the mechanisms underlying this association.

NOTCH2NLC expanded GGC repeats in patients with cerebral small vessel disease.

OBJECTIVE: GGC repeat expansions in the human-specific NOTCH2NLC gene have been reported as the cause of neuronal intranuclear inclusion disease (NIID). Given the clinical overlap of cognitive impairment in NIID and cerebral small vessel disease (CSVD), both diseases have white matter hyperintensity on T2-fluid-attenuated inversion recovery sequences of brain MRI, and white matter hyperintensity is a primary neuroimaging marker of CSVD on MRI. Therefore, we hypothesised that the GGC repeat expansions might also contribute to CSVD. To further investigate the relationship between NOTCH2NLC GGC repeat expansions and CSVD, we performed a genetic analysis of 814 patients with the disease. METHODS: We performed a comprehensive GGC repeat expansion screening in NOTCH2NLC from 814 patients with sporadic CSVD. Their Fazekas score was greater than or equal to 3 points. Repeat-primed PCR and fluorescence amplicon length analyses were performed to identify GGC repeat expansions, and whole-exome sequencing was used to detect any pathogenic mutation in previously reported genes associated with CSVD. RESULTS: We identified nine (1.11%) patients with pathogenic GGC repeat expansions ranging from 41 to 98 repeats. The minor allele frequency of expanded GGC repeats in NOTCH2NLC was 0.55%. CONCLUSION: Our findings suggest that intermediate-length and longer-length GGC repeat expansions in NOTCH2NLC are associated with sporadic CSVD. This provides new thinking for studying the pathogenesis of CSVD.

Human blood metabolites and lacunar stroke: A Mendelian randomization study.

BACKGROUND: Lacunar stroke accounts for a quarter of all strokes, but little is known about the underlying pathological mechanisms. Analysis of serum metabolites may allow better understanding of the underlying biological processes. Mendelian randomization (MR) can provide information on the causality of associations. AIMS: To identify causal relationships between serum metabolites and lacunar stroke. METHODS: We applied a two-sample MR analysis to evaluate relationships between 486 serum metabolites and lacunar stroke. The inverse-variance weighted (IVW) method was used to estimate the causal relationship of the exposure on the outcome, while sensitivity analyses were performed using MR-Egger, weighted median, and MR-PRESSO to eliminate the pleiotropy. We also performed a metabolic pathway analysis to identify potential metabolic pathways. RESULTS: We identified 15 known (8 risk and 7 protective) and 14 unknown serum metabolites associated with lacunar stroke. Among the known risk metabolites, two were lipids (1-linoleoylglycerophosphoethanolamine and dihomo-linolenate (20:3n3 or n6)), five amino acids (kynurenine, isobutyrylcarnitine, aspartate, trans-4-hydroxyproline, and 3-methyl-2-oxovalerate), and one peptide (ADSGEGDFXAEGGGVR). The known protective metabolites included four lipids (4-androsten-3beta,17beta-diol disulfate 1, 1-palmitoleoylglycerophosphocholine, adrenate (22:4n6), and glycodeoxycholate), one amino acid (methionine), and two exogenous metabolites (homostachydrine and 2-methoxyacetaminophen sulfate). Metabolic pathway analysis identified several pathways that might be involved in the disease. CONCLUSION: We identified eight risk and seven protective human serum metabolites associated with lacunar stroke. Isobutyrylcarnitine was positively associated with an increased risk of lacunar stroke. In addition, 3-methyl-2-oxovalerate and aspartate may be involved in the disease pathogenesis through metabolic pathways.

Intelligence, education level, and risk of Parkinson's disease in European populations: A Mendelian randomization study.

Background: A high level of education or intelligence (IQ) is reported to be a risk factor for Parkinson's disease (PD). The purpose of this study was to systematically examine the causal relationships between IQ, educational attainment (EA), cognitive performance, and PD. Methods: We used summary statistics from genome-wide association studies on IQ, EA, cognitive performance, and PD. Four genome-wide association study (GWAS) data for PD were used to comprehensively explore the causal relationship, including PD GWAS (regardless of sex), age at onset of PD GWAS, male with PD GWAS, and female with PD GWAS data. We conducted a two sample Mendelian randomization (MR) study using the inverse-variance weighted (IVW), weighted median, simple mode, and weighted mode methods to evaluate the causal association between these factors. MR-Egger and MR-PRESSO were used for sensitivity analysis to test and correct horizontal pleiotropy. Multivariate MR (MVMR) was also used to account for the covariation between IQ, EA, and cognition, as well as to explore potential mediating factors. Results: Genetically predicted higher IQ was associated with an increased risk of PD in the entire population, regardless of gender. In the analyses using the IVW method, the odds ratio was 1.37 (p = 0.0064). Men with a higher IQ, more years of education, or stronger cognitive ability are more likely to develop PD compared to women. MVMR showed that adjusting for education and cognition largely attenuated the association between IQ and PD, suggesting that education and cognition may mediate the effect of IQ on PD. Conclusion: This study provides genetic support for the causal link between higher IQ and an increased risk of PD.

An autophagy-related long non-coding RNA prognostic model and related immune research for female breast cancer.

Introduction: Breast cancer (BRCA) is the most common malignancy among women worldwide. It was widely accepted that autophagy and the tumor immune microenvironment play an important role in the biological process of BRCA. Long non-coding RNAs (lncRNAs), as vital regulatory molecules, are involved in the occurrence and development of BRCA. The aim of this study was to assess the prognosis of BRCA by constructing an autophagy-related lncRNA (ARlncRNA) prognostic model and to provide individualized guidance for the treatment of BRCA. Methods: The clinical data and transcriptome data of patients with BRCA were acquired from the Cancer Genome Atlas database (TCGA), and autophagy-related genes were obtained from the human autophagy database (HADb). ARlncRNAs were identified by conducting co­expression analysis. Univariate and multivariate Cox regression analysis were performed to construct an ARlncRNA prognostic model. The prognostic model was evaluated by Kaplan-Meier survival analysis, plotting risk curve, Independent prognostic analysis, clinical correlation analysis and plotting ROC curves. Finally, the tumor immune microenvironment of the prognostic model was studied. Results: 10 ARlncRNAs(AC090912.1, LINC01871, AL358472.3, AL122010.1, SEMA3B-AS1, BAIAP2-DT, MAPT-AS1, DNAH10OS, AC015819.1, AC090198.1) were included in the model. Kaplan-Meier survival analysis of the prognostic model showed that the overall survival(OS) of the low-risk group was significantly better than that of the high-risk group (p< 0.001). Multivariate Cox regression analyses suggested that the prognostic model was an independent prognostic factor for BRCA (HR = 1.788, CI = 1.534-2.084, p < 0.001). ROCs of 1-, 3- and 5-year survival revealed that the AUC values of the prognostic model were all > 0.7, with values of 0.779, 0.746, and 0.731, respectively. In addition, Gene Set Enrichment Analysis (GSEA) suggested that several tumor-related pathways were enriched in the high-risk group, while several immune­related pathways were enriched in the low-risk group. Patients in the low-risk group had higher immune scores and their immune cells and immune pathways were more active. Patients in the low-risk group had higher PD-1 and CTLA-4 levels and received more benefits from immune checkpoint inhibitors (ICIs) therapy. Discussion: The ARlncRNA prognostic model showed good performance in predicting the prognosis of patients with BRCA and is of great significance to guide the individualized treatment of these patients.

Generation of an induced pluripotent stem cell line (ZZUi036-A) derived from skin fibroblasts of a Neuronal intranuclear inclusion disease patient with GGC repeat expansion in the NOTCH2NLC gene.

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disease characterized by cognitive impairment, extrapyramidal symptoms, white matter lesions and muscle weakness. The cause of NIID is a repeat amplification of a GGC mutation in the 5 ' untranslated region (UTR) of the NOTCH2NLC gene. Using the non-integrating Sendai virus to deliver the Klf4, OCT3/4, SOX2 and C-MYC factors, fibroblasts obtained from a NIID patient were reprogrammed to generate an induced pluripotent stem cell (iPSC) line (ZZUi036-A). Our approach provided a resource for the investigation of the mechanism of the disease, drug research, cell transplantation and gene therapy.

Rare KCND3 Loss-of-Function Mutation Associated With the SCA19/22.

Spinocerebellar ataxia 19/22 (SCA19/22) is a rare neurodegenerative disorder caused by mutations of the KCND3 gene, which encodes the Kv4. 3 protein. Currently, only 22 KCND3 single-nucleotide mutation sites of SCA19/22 have been reported worldwide, and detailed pathogenesis remains unclear. In this study, Sanger sequencing was used to screen 115 probands of cerebellar ataxia families in 67 patients with sporadic cerebellar ataxia and 200 healthy people to identify KCND3 mutations. Mutant gene products showed pathogenicity damage, and the polarity was changed. Next, we established induced pluripotent stem cells (iPSCs) derived from SCA19/22 patients. Using a transcriptome sequencing technique, we found that protein processing in the endoplasmic reticulum was significantly enriched in SCA19/22-iPS-derived neurons and was closely related to endoplasmic reticulum stress (ERS) and apoptosis. In addition, Western blotting of the SCA19/22-iPS-derived neurons showed a reduction in Kv4.3; but, activation of transcription factor 4 (ATF4) and C/EBP homologous protein was increased. Therefore, the c.1130 C>T (p.T377M) mutation of the KCND3 gene may mediate misfold and aggregation of Kv4.3, which activates the ERS and further induces neuron apoptosis involved in SCA19/22.