Exploration of the shared genetic biomarkers in Alzheimer's disease and chronic kidney disease using integrated bioinformatics analysis.

In order to investigate the potential link between Alzheimer's disease (AD) and chronic kidney disease (CKD), we conducted a comprehensive analysis using a bioinformatics approach. We downloaded AD and CKD datasets from the Gene Expression Omnibus database and analyzed differentially expressed genes and weighted gene co-expression networks to identify candidate genes for AD and CKD. We used a combination of the least absolute shrinkage and selection operator and random forest algorithms to select the shared genes. Subsequently, we shared genes and performed an immune infiltration analysis to investigate the association between different immune cell types and shared genes. Finally, we elucidated the relationship between the expression levels of the shared genes in disease samples and cells using single-cell analysis. Our analysis identified 150 candidate genes that may be primarily involved in immune inflammatory responses and energy metabolism pathways. We found that JunD Proto-Oncogene, ALF transcription elongation factor 1, and ZFP36 Ring Finger Protein Like 1 were the best co-diagnostic markers for AD and CKD based on the results of Least Absolute Shrinkage Selection Operator analysis and the random forest algorithm. Based on the results of immune infiltration analysis, macrophages and T-cells play a significant role in the progression of AD and CKD. Our scRNA-sequencing data showed that the 3 shared genes in AD were significantly expressed in astrocytes, excitatory neurons, oligodendrocytes, and MAIT cells. The 3 shared genes in CKD were significantly expressed in oligodendrocytes, neutrophils, fibroblasts, astrocytes, and T-cells. JunD Proto-Oncogene, ALF transcription elongation factor 1, and ZFP36 Ring Finger Protein Like 1 genes are the best diagnostic markers for AD and CKD.

Scientometric analysis of post-stroke depression research based on CiteSpace.

Post-stroke depression (PSD) has served as a severe and common complication leading to a higher level of mortality. Though various studies have been focused on PSD, limited research endeavor has been dedicated to bibliometric analysis in the past. In view of this, the current analysis serves to elucidate the latest status of global research and pinpoint the emerging area of interest for PSD, in order to support further investigation of the field. Publications related to PSD were retrieved from the Web of Science Core Collection database on September 24, 2022, and included in the bibliometric analysis. VOSviewer and CiteSpace software were used to visually analyze publication outputs, scientific cooperation, highly-cited references, and keywords to identify the current status and future trends in PSD research. A total of 533 publications were retrieved. The annual number of publications showed an increasing trend from 1999 to 2022. In terms of country and academic institution, the USA and Duke University have topped the list of PSD research respectively. Meanwhile, Robinson RG and Alexopoulos GS have been the most representative investigators of the field. In the past, researchers focused on the risk factors of PSD, late-life depression, and Alzheimer disease. In recent years, further research effort has been placed on meta-analysis, ischemic stroke, predictor, inflammation, mechanism, and mortality. In conclusion, in the past 20 years, PSD research has been progressing and gaining more attention. The bibliometric analysis successfully unveiled the field's major contributing countries, institutions, and investigators. Furthermore, current hot spots and future trends in the field of PSD were identified, which included meta-analysis, ischemic stroke, predictor, inflammation, mechanism, and mortality.

Global and regional prevalence and burden for premenstrual syndrome and premenstrual dysphoric disorder: A study protocol for systematic review and meta-analysis.

INTRODUCTION: Premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD) are becoming common mental diseases in women impairing daily functioning. Estimation of the epidemiological burden of PMS/PMDD can serve as scientific basis for prevention and management of premenstrual disorders. Herein, we firstly provide a protocol to perform estimation on the prevalence and risk factors for PMS/PMDD in the general population globally and regionally. METHODS/DESIGN: The PubMed, Web of Science, Chinese National Knowledge Infrastructure, the Cochrane Central Register of Controlled Trials (Cochrane Library), Chinese VIP Information, EMBASE, Wanfang Database, as well as the Chinese Biomedical Literature Database will be queried to find related studies containing information on the prevalence of PMDD (2011-2021). Two independent reviewers will comb the literature and abstract the data characteristics. Disparities will be reconciled via consents. The primary outcome will be the global prevalence. The random-effect model will be employed to pool the assessments. The standard χ2 tests, as well as the I2 statistic will be used to determine heterogeneity. Furthermore, the meta-regression analysis will be employed to estimate the differences in study-level characteristics. All the statistical analyses will be carried out in the software Stata v 15.0 (Stata Corporation, College Station, TX), as well as the R (v R 3.5.1, R Foundation for Statistical Computing, Vienna, Austria) software. DISCUSSION: Based on existing evidence, our study will offer a high-quality synthesis for global and regional prevalence, burden, and risk factors of PMS/PMDD. Effective strategies will be made for prevention and management of epidemiological burden on the PMS/PMDD, even premenstrual disorders. ETHICS AND DISSEMINATION: This study does not involve the specific patients, and all research data comes from publicly available professional literature, so an ethics committee is not required to conduct an ethical review and approval of the study. INPLASY REGISTRATION NUMBER: INPLASY2021120065.

Alzheimer disease effects of different stages on intestinal flora: A protocol for systematic review and meta-analysis.

BACKGROUND: Alzheimer disease (AD) is a common degenerative disease of the central nervous system that can be divided into 3 stages, according to the degree of cognitive impairment. The clinical manifestations are cognitive dysfunction and memory loss, impacting the daily activities of the affected individuals. In recent years, studies have demonstrated a relationship between intestinal flora and AD. However, no meta-analysis has documented the correlation between AD and intestinal flora, to the best of our knowledge. Herein, we sought to assess the correlation between different stages of AD and intestinal flora. A systematic and comprehensive understanding of this relationship is of great significance for developing prevention and treatment strategies against AD. METHODS: A comprehensive search of the medical literature in Chinese and English language was performed in databases, such as PubMed, EBSCO, CNKI, web of science, WanFang, Cochrane Library, and CBM databases. Pre-defined search strategies were used to retrieve clinical studies of Alzheimer disease and gut microbiota. The included studies were independently analyzed by the 2 researchers who extracted the data. The quality of the data was evaluated according to the "Cochrane system evaluator manual." Finally, Endnote and RevMan software were used for systematic regression and meta-analysis of evidence. RESULTS: We documented the intestinal flora changes in the 3 stages of Alzheimer disease, according to currently available clinical evidence, and revealed the correlation between the abundance and diversity of flora and treatment efficacy. These findings are essential for developing new strategies for the prevention and treatment of Alzheimer disease. INPLASY REGISTRATION NUMBER: INPLASY2021100093. ETHICS AND DISSEMINATION: Since all data utilized in this systematic review and meta-analysis are published, ethical approval was not needed.

Trends in Research Related to Premenstrual Syndrome and Premenstrual Dysphoric Disorder From 1945 to 2018: A Bibliometric Analysis.

Background: The global incidence of premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD) is increasing, with increasing suicide reports. However, the bibliometric analysis of global research on PMS and PMDD is rare. We aimed to evaluate the global scientific output of research on PMS and PMDD and to explore their research hotspots and frontiers from 1945 to 2018 using a bibliometric analysis methodology. Methods: Articles with research on PMS and PMDD between 1945 and 2018 were retrieved from the Web of Science Core Collection (WoSCC). We used the bibliometric method, CiteSpace V and VOSviewer to analyze publication years, journals, countries, institutions, authors, research hotspots, and trends. We plotted the reference co-citation network, and we used keywords to analyze the research hotspots and trends. Results: We identified 2,833 publications on PMS and PMDD research from 1945 to 2018, and the annual publication number increased with time, with fluctuations. Psychoneuroendocrinology published the highest number of articles. The USA ranked the highest among the countries with the most publications, and the leading institute was UNIV PENN. Keyword and reference analysis indicated that the menstrual cycle, depression and ovarian hormones were the research hotspots, whereas prevalence, systematic review, anxiety and depression and young women were the research frontiers. Conclusions: We depicted overall research on PMS and PMDD by a bibliometric analysis methodology. Prevalence and impact in young women, systematic review evaluations of risk factors, and the association of anxiety and depression with menstrual cycle phases are the latest research frontiers that will pioneer the direction of research in the next few years.