Proteomics Links Ubiquitin Chain Topology Change to Transcription Factor Activation.

A surprising complexity of ubiquitin signaling has emerged with identification of different ubiquitin chain topologies. However, mechanisms of how the diverse ubiquitin codes control biological processes remain poorly understood. Here, we use quantitative whole-proteome mass spectrometry to identify yeast proteins that are regulated by lysine 11 (K11)-linked ubiquitin chains. The entire Met4 pathway, which links cell proliferation with sulfur amino acid metabolism, was significantly affected by K11 chains and selected for mechanistic studies. Previously, we demonstrated that a K48-linked ubiquitin chain represses the transcription factor Met4. Here, we show that efficient Met4 activation requires a K11-linked topology. Mechanistically, our results propose that the K48 chain binds to a topology-selective tandem ubiquitin binding region in Met4 and competes with binding of the basal transcription machinery to the same region. The change to K11-enriched chain architecture releases this competition and permits binding of the basal transcription complex to activate transcription.

Mass-Spectrometry-Based Near-Complete Draft of the Saccharomyces cerevisiae Proteome.

Proteomics approaches designed to catalogue all open reading frames (ORFs) under a defined set of growth conditions of an organism have flourished in recent years. However, no proteome has been sequenced completely so far. Here, we generate the largest yeast proteome data set, including 5610 identified proteins, using a strategy based on optimized sample preparation and high-resolution mass spectrometry. Among the 5610 identified proteins, 94.1% are core proteins, which achieves near-complete coverage of the yeast ORFs. Comprehensive analysis of missing proteins showed that proteins are missed mainly due to physical properties. A review of protein abundance shows that our proteome encompasses a uniquely broad dynamic range. Additionally, these values highly correlate with mRNA abundance, implying a high level of accuracy, sensitivity, and precision. We present examples of how the data could be used, including reannotating gene localization, providing expression evidence of pseudogenes. Our near-complete yeast proteome data set will be a useful and important resource for further systematic studies.

Accurate and rapid screening model for potential diabetes mellitus.

BACKGROUND: Prediction or early diagnosis of diabetes is crucial for populations with high risk of diabetes. METHODS: In this study, we assessed the ability of five popular classifiers (J48, AdaboostM1, SMO, Bayes Net, and Naïve Bayes) to identify individuals with diabetes based on nine non-invasive and easily obtained clinical features, including age, gender, body mass index (BMI), hypertension, history of cardiovascular disease or stroke, family history of diabetes, physical activity, work stress, and salty food preference. A total of 4205 data entries were obtained from annual physical examination reports for adults in the Shengjing Hospital of China Medical University during January-April 2017. Weka data mining software was used to identify the best algorithm for diabetes classification. RESULTS: The results indicate that decision tree classifier J48 has the best performance (accuracy = 0.9503, precision = 0.950, recall = 0.950, F-measure = 0.948, and AUC = 0.964). The decision tree structure shows that age is the most significant feature, followed by family history of diabetes, work stress, BMI, salty food preference, physical activity, hypertension, gender, and history of cardiovascular disease or stroke. CONCLUSIONS: Our study shows that decision tree analyses can be applied to screen individuals for early diabetes risk without the need for invasive tests. This procedure will be particularly useful in developing regions with high epidemiological risk and poor socioeconomic status, and enable clinical practitioners to rapidly screen patients for increased risk of diabetes. The key features in the tree structure could further facilitate diabetes prevention through targeted community interventions, which can potentially improve early diabetes diagnosis and reduce burdens on the healthcare system.

Enhanced Purification of Ubiquitinated Proteins by Engineered Tandem Hybrid Ubiquitin-binding Domains (ThUBDs).

Ubiquitination is one of the most common post-translational modifications, regulating protein stability and function. However, the proteome-wide profiling of ubiquitinated proteins remains challenging due to their low abundance in cells. In this study, we systematically evaluated the affinity of ubiquitin-binding domains (UBDs) to different types of ubiquitin chains. By selecting UBDs with high affinity and evaluating various UBD combinations with different lengths and types, we constructed two artificial tandem hybrid UBDs (ThUBDs), including four UBDs made of DSK2p-derived ubiquitin-associated (UBA) and ubiquilin 2-derived UBA (ThUDQ2) and of DSK2p-derived UBA and RABGEF1-derived A20-ZnF (ThUDA20). ThUBD binds to ubiquitinated proteins, with markedly higher affinity than naturally occurring UBDs. Furthermore, it displays almost unbiased high affinity to all seven lysine-linked chains. Using ThUBD-based profiling with mass spectrometry, we identified 1092 and 7487 putative ubiquitinated proteins from yeast and mammalian cells, respectively, of which 362 and 1125 proteins had ubiquitin-modified sites. These results demonstrate that ThUBD is a refined and promising approach for enriching the ubiquitinated proteome while circumventing the need to overexpress tagged ubiquitin variants and use antibodies to recognize ubiquitin remnants, thus providing a readily accessible tool for the protein ubiquitination research community.

Tissue-Based Proteogenomics Reveals that Human Testis Endows Plentiful Missing Proteins.

Investigations of missing proteins (MPs) are being endorsed by many bioanalytical strategies. We proposed that proteogenomics of testis tissue was a feasible approach to identify more MPs because testis tissues have higher gene expression levels. Here we combined proteomics and transcriptomics to survey gene expression in human testis tissues from three post-mortem individuals. Proteins were extracted and separated with glycine- and tricine-SDS-PAGE. A total of 9597 protein groups were identified; of these, 166 protein groups were listed as MPs, including 138 groups (83.1%) with transcriptional evidence. A total of 2948 proteins are designated as MPs, and 5.6% of these were identified in this study. The high incidence of MPs in testis tissue indicates that this is a rich resource for MPs. Functional category analysis revealed that the biological processes that testis MPs are mainly involved in are sexual reproduction and spermatogenesis. Some of the MPs are potentially involved in tumorgenesis in other tissues. Therefore, this proteogenomics analysis of individual testis tissues provides convincing evidence of the discovery of MPs. All mass spectrometry data from this study have been deposited in the ProteomeXchange (data set identifier PXD002179).

Special Enrichment Strategies Greatly Increase the Efficiency of Missing Proteins Identification from Regular Proteome Samples.

As part of the Chromosome-Centric Human Proteome Project (C-HPP) mission, laboratories all over the world have tried to map the entire missing proteins (MPs) since 2012. On the basis of the first and second Chinese Chromosome Proteome Database (CCPD 1.0 and 2.0) studies, we developed systematic enrichment strategies to identify MPs that fell into four classes: (1) low molecular weight (LMW) proteins, (2) membrane proteins, (3) proteins that contained various post-translational modifications (PTMs), and (4) nucleic acid-associated proteins. Of 8845 proteins identified in 7 data sets, 79 proteins were classified as MPs. Among data sets derived from different enrichment strategies, data sets for LMW and PTM yielded the most novel MPs. In addition, we found that some MPs were identified in multiple-data sets, which implied that tandem enrichments methods might improve the ability to identify MPs. Moreover, low expression at the transcription level was the major cause of the "missing" of these MPs; however, MPs with higher expression level also evaded identification, most likely due to other characteristics such as LMW, high hydrophobicity and PTM. By combining a stringent manual check of the MS2 spectra with peptides synthesis verification, we confirmed 30 MPs (neXtProt PE2 ∼ PE4) and 6 potential MPs (neXtProt PE5) with authentic MS evidence. By integrating our large-scale data sets of CCPD 2.0, the number of identified proteins has increased considerably beyond simulation saturation. Here, we show that special enrichment strategies can break through the data saturation bottleneck, which could increase the efficiency of MP identification in future C-HPP studies. All 7 data sets have been uploaded to ProteomeXchange with the identifier PXD002255.

Influence of local application of glaucoma medications-travoprost eye drops on patients' tear film function.

This study discussed about the influence of local application of glaucoma medications -- travoprost eye drops to patients' tear film function. We selected 24 patients, 45 eyes with primary open-angle glaucoma or intraocular hypertension. All of the patients topically used the travoprost eye drops for one time every night. After and before the pharmacy, we proceeded 1, 2, 3 mo lines symptom score and Schirmer's test (St), corneal fluorescein staining (FL), breakup time of tear film (BUT). Average value of symptom score and FL of all the patients before pharmacy were 1.32 ± 1. 55, 0.42 ± 0.68, and 1, 2, 3mo after pharmacy were respectively 2.68 ± 1.59, 0.96 ± 0.81; 4.97 ± 1.62, 1.46 ± 0.62; 6.21 ± 1.33, 1.88 ± 0.44. Symptom score and FL of 1, 2, 3 mo patients after pharmacy were all prominent higher than it before pharmacy (P=0.00), and it gradually increased. The average value of patients symptom BUT and St before pharmacy were (7.71 ± 0.87s), (8.32 ± 2.63mm /5min) and 1, 2, 3 mo after pharmacy were respectively (6.93 ± 1.17s), (7.69 ± 3. 33mm /5min); (5.48 ± 1.29s), (6.79 ± 2.94mm /5min); (4.33 ± 1.83s), (5.98 ± 3.11mm/5min). BUT and St value after pharmacy were prominent all lower than the level before pharmacy (P=0.00). And it gradually reduced. Short-term use of travoprost eye drops would aggravate the corneal irritation of patients, and decrease the tear film stability and tear secretion.

Qualitative and quantitative analysis of the adult Drosophila melanogaster proteome.

Drosophila melanogaster is one of the most widely used model organisms in life sciences. Mapping its proteome is of great significance for understanding the biological characteristics and tissue functions of this species. However, the comprehensive coverage of its proteome remains a challenge. Here, we describe a high-coverage analysis of whole fly through a 1D gel electrophoresis and LC-MS/MS approach. By combining the datasets of two types of SDS-PAGE and two kinds of tagmata, the high-coverage analysis resulted in the identification of 5262 genes, which correspond to 38.23% of the entire coding genes. Moreover, we found that the fly head and body have different molecular weight distributions of their proteomes when the proteins were resolved with SDS-PAGE and image analysis of the stained gel. This phenomenon was further confirmed by both label-free and isobaric tags for relative and absolute quantitation-based quantitative approaches. The consistent results of the two different quantitation methods also demonstrated the stability and accuracy of the LC-MS/MS platform. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD000454 and PXD000455 (http://proteomecentral.proteomexchange.org/dataset/PXD000454; (http://proteomecentral.proteomexchange.org/dataset/PXD000455).

Discovery of novel genes and gene isoforms by integrating transcriptomic and proteomic profiling from mouse liver.

Comprehensively identifying gene expression in both transcriptomic and proteomic levels of one tissue is a prerequisite for a deeper understanding of its biological functions. Alternative splicing and RNA editing, two main forms of transcriptional processing, play important roles in transcriptome and proteome diversity and result in multiple isoforms for one gene, which are hard to identify by mass spectrometry (MS)-based proteomics approach due to the relative lack of isoform information in standard protein databases. In our study, we employed MS and RNA-Seq in parallel into mouse liver tissue and captured a considerable catalogue of both transcripts and proteins that, respectively, covered 60 and 34% of protein-coding genes in Ensembl. We then developed a bioinformatics workflow for building a customized protein database that for the first time included new splicing-derived peptides and RNA-editing-caused peptide variants, allowing us to more completely identify protein isoforms. Using this experimentally determined database, we totally identified 150 peptides not present in standard biological databases at false discovery rate of <1%, corresponding to 72 novel splicing isoforms, 43 new genetic regions, and 15 RNA-editing sites. Of these, 11 randomly selected novel events passed experimental verification by PCR and Sanger sequencing. New discoveries of gene products with high confidence in two omics levels demonstrated the robustness and effectiveness of our approach and its potential application into improve genome annotation. All the MS data have been deposited to the iProx ( http://ww.iprox.org ) with the identifier IPX00003601.

A proteomics strategy for the identification of FAT10-modified sites by mass spectrometry.

The ubiquitin-like protein FAT10 (HLA-F adjacent transcript 10) is uniquely expressed in mammals. The fat10 gene is encoded in the MHC class I locus in the human genome and is related to some specific processes, such as apoptosis, immune response, and cancer. However, biological knowledge of FAT10 is limited, owing to the lack of identification of its conjugates. FAT10 covalently modifies proteins in eukaryotes, but only a few substrates of FAT10 have been reported until now, and no FATylated sites have been identified. Here, we report the proteome-scale identification of FATylated proteins by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We identified 175 proteins with high confidence as FATylated candidates. A total of 13 modified sites were identified for the first time by a modified search of the raw MS data. The modified sites were highly enriched with hydrophilic amino acids. Furthermore, the FATylation processes of hnRNP C2, PCNA, and PDIA3 were verified by a coimmunoprecipitation assay. We confirmed that most of the substrates were covalently attached to a FAT10 monomer. The functional distribution of the FAT10 targets suggests that FAT10 participates in various biological processes, such as translation, protein folding, RNA processing, and macromolecular complex assembly. These results should be very useful for investigating the biological functions of FAT10.

Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines.

Cancer genomics unveils many cancer-related mutations, including some chromosome 20 (Chr.20) genes. The mutated messages have been found in the corresponding mRNAs; however, whether they could be translated to proteins still requires more evidence. Herein, we proposed a transomics strategy to profile the expression status of human Chr.20 genes (555 in Ensembl v72). The data of transcriptome and translatome (the mRNAs bound with ribosome, translating mRNAs) revealed that ∼80% of the coding genes on Chr.20 were detected with mRNA signals in three liver cancer cell lines, whereas of the proteome identified, only ∼45% of the Chr.20 coding genes were detected. The high amount of overlapping of identified genes in mRNA and RNC-mRNA (ribosome nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent distribution of the abundance averages of mRNA and RNC-mRNA along the Chr.20 subregions in three liver cancer cell lines indicate that the mRNA information is efficiently transmitted from transcriptional to translational stage, qualitatively and quantitatively. Of the 457 genes identified in mRNAs and RNC-mRNA, 136 were found to contain SNVs with 213 sites, and >40% of these SNVs existed only in metastatic cell lines, suggesting them as the metastasis-related SNVs. Proteomics analysis showed that 16 genes with 20 SNV sites were detected with reliable MS/MS signals, and some SNVs were further validated by the MRM approach. With the integration of the omics data at the three expression phases, therefore, we are able to achieve the overall view of the gene expression of Chr.20, which is constructive in understanding the potential trend of encoding genes in a cell line and exploration of a new type of markers related to cancers.

Chromosome-8-coded proteome of Chinese Chromosome Proteome Data set (CCPD) 2.0 with partial immunohistochemical verifications.

We upgraded the preliminary CCPD 1.0 to CCPD 2.0 using the latest deep-profiling proteome (CCPD 2013) of three hepatocellular carcinoma (HCC) cell lines, namely, Hep3B, MHCC97H, and HCCLM3 (ProteomeXchange identifiers: PXD000529, PXD000533, and PXD000535). CCPD 2.0 totally covered 63.6% (438/689) of Chr. 8-coded proteins and 62.6% (439/701) of Chr. 8-coded protein-coding genes. Interestingly, we found that the missing proteins exhibited a tendency to form a cluster region in chromosomes, such as two ß-defensins clusters in Chr. 8, caused perhaps by their inflammation-related features. For the 41 Chr. 8-coded proteins being weakly or barely identified previously, we have performed an immunohistochemical (IHC) verification in 30 pairs of carcinoma/para-carcinoma HCC and 20 noncancerous liver tissues and confirmed their expressional evidence and occurrence proportions in tissue samples. We also verified 13 Chr. 8-coded HCC tumorigenesis-associated depleting or deficient proteins reported in CCPD 1.0 using IHC and screened 16 positive and 24 negative HCC metastatic potential-correlated proteins from large-scale label-free proteome quantitation data of CCPD 2013. Our results suggest that the selection of proper samples and the methodology to look for targeted missing proteins should be carefully considered in further verifications for the remaining Chr. 8-coded proteins.

Systematic analyses of the transcriptome, translatome, and proteome provide a global view and potential strategy for the C-HPP.

To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.

Systematic analysis of missing proteins provides clues to help define all of the protein-coding genes on human chromosome 1.

Our first proteomic exploration of human chromosome 1 began in 2012 (CCPD 1.0), and the genome-wide characterization of the human proteome through public resources revealed that 32-39% of proteins on chromosome 1 remain unidentified. To characterize all of the missing proteins, we applied an OMICS-integrated analysis of three human liver cell lines (Hep3B, MHCC97H, and HCCLM3) using mRNA and ribosome nascent-chain complex-bound mRNA deep sequencing and proteome profiling, contributing mass spectrometric evidence of 60 additional chromosome 1 gene products. Integration of the annotation information from public databases revealed that 84.6% of genes on chromosome 1 had high-confidence protein evidence. Hierarchical analysis demonstrated that the remaining 320 missing genes were either experimentally or biologically explainable; 128 genes were found to be tissue-specific or rarely expressed in some tissues, whereas 91 proteins were uncharacterized mainly due to database annotation diversity, 89 were genes with low mRNA abundance or unsuitable protein properties, and 12 genes were identifiable theoretically because of a high abundance of mRNAs/RNC-mRNAs and the existence of proteotypic peptides. The relatively large contribution made by the identification of enriched transcription factors suggested specific enrichment of low-abundance protein classes, and SRM/MRM could capture high-priority missing proteins. Detailed analyses of the differentially expressed genes indicated that several gene families located on chromosome 1 may play critical roles in mediating hepatocellular carcinoma invasion and metastasis. All mass spectrometry proteomics data corresponding to our study were deposited in the ProteomeXchange under the identifiers PXD000529, PXD000533, and PXD000535.

Knowledge mapping and current trends of m6A methylation in the field of cancer.

Background: Cancer is a serious threat to people's lives and health, killing millions of people every year. Here, we performed a bibliometric analysis of tumor N6-methyladenosine methylation data between 2001 and 2022 to understand research trends and potential future directions. Methods: A total of 890 papers published in the Web of Science core collection database between January 1, 2001 and December 31, 2022 were analyzed. Bibliometric analysis was performed using VOSviewer software to explore citations, co-authorship, co-citations, and co-occurrence. Results: Although few papers were published before 2018, there was a rapid increase in publications after 2018. The People's Republic of China published 810 papers with 16,957 citations, both ranking first in the word. Sun Yat Sen University had the highest number of citations and published articles (67 published papers and 2702 citations), indicative of its active collaborative research status. Wang Xiao was the most co-cited author with 546 co-citations. Huang Yufei and Meng Jia ranked first with a link strength of 22, making them the most active collaborative authors. Frontiers in Oncology and Nature were the most active and co-cited journals, with 57 papers and 1953 co-citations, respectively. Studies of tumor N6-methyladenosine methylation can be divided into three categories: "tumor metabolism", "tumor bioinformatics and immunity", and "tumor progression". Conclusions: This study systematically summarized the research on tumor N6-methyladenosine methylation during the past 20 years and suggested potential ways to explore its biomarkers and immunotherapy in the future.

Proteome atlas of human chromosome 8 and its multiple 8p deficiencies in tumorigenesis of the stomach, colon, and liver.

Chromosome 8, a medium-length euchromatic unit in humans that has an extraordinarily high mutation rate, can be detected not only in evolution but also in multiple mutant diseases, such as tumorigenesis, and further invasion/metastasis. The Chromosome-Centric Human Proteome Project of China systematically profiles the proteomes of three digestive organs (i.e., stomach, colon, and liver) and their corresponding carcinoma tissues/cell lines according to a chromosome organizational roadmap. By rigorous standards, we have identified 271 (38.7%), 330 (47.1%), and 325 (46.4%) of 701 chromosome 8-coded proteins from stomach, colon, and liver samples, respectively, in Swiss-Prot and observed a total coverage rate of up to 58.9% by 413 identified proteins. Using large-scale label-free proteome quantitation, we also found some 8p deficiencies, such as the presence of 8p21-p23 in tumorigenesis of the above-described digestive organs, which is in good agreement with previous reports. To our best knowledge, this is the first study to have verified these 8p deficiencies at the proteome level, complementing genome and transcriptome data.

First proteomic exploration of protein-encoding genes on chromosome 1 in human liver, stomach, and colon.

The launch of the Chromosome-Centric Human Proteome Project provides an opportunity to gain insight into the human proteome. The Chinese Human Chromosome Proteome Consortium has initiated proteomic exploration of protein-encoding genes on human chromosomes 1, 8, and 20. Collaboration within the consortium has generated a comprehensive proteome data set using normal and carcinomatous tissues from human liver, stomach, and colon and 13 cell lines originating in these organs. We identified 12,101 proteins (59.8% coverage against Swiss-Prot human entries) with a protein false discovery rate of less than 1%. On chromosome 1, 1,252 proteins mapping to 1,227 genes, representing 60.9% of Swiss-Prot entries, were identified; however, 805 proteins remain unidentified, suggesting that analysis of more diverse samples using more advanced proteomic technologies is required. Genes encoding the unidentified proteins were concentrated in seven blocks, located at p36, q12-21, and q42-44, partly consistent with correlation of these blocks with cancers of the liver, stomach, and colon. Combined transcriptome, proteome, and cofunctionality analyses confirmed 23 coexpression clusters containing 165 genes. Biological information, including chromosome structure, GC content, and protein coexpression pattern was analyzed using multilayered, circular visualization and tabular visualization. Details of data analysis and updates are available in the Chinese Chromosome-Centric Human Proteome Database ( http://proteomeview.hupo.org.cn/chromosome/ ).

Qualitative and quantitative expression status of the human chromosome 20 genes in cancer tissues and the representative cell lines.

Under the guidance of the Chromosome-centric Human Proteome Project (C-HPP), (1, 2) we conducted a systematic survey of the expression status of genes located at human chromosome 20 (Chr.20) in three cancer tissues, gastric, colon, and liver carcinoma, and their representative cell lines. We have globally profiled proteomes in these samples with combined technology of LC-MS/MS and acquired the corresponding mRNA information upon RNA-seq and RNAchip. In total, 323 unique proteins were identified, covering 60% of the coding genes (323/547) in Chr.20. With regards to qualitative information of proteomics, we overall evaluated the correlation of the identified Chr.20 proteins with target genes of transcription factors or of microRNA, conserved genes and cancer-related genes. As for quantitative information, the expression abundances of Chr.20 genes were found to be almost consistent in both tissues and cell lines of mRNA in all individual chromosome regions, whereas those of Chr.20 proteins in cells are different from tissues, especially in the region of 20q13.33. Furthermore, the abundances of Chr.20 proteins were hierarchically evaluated according to tissue- or cancer-related distribution. The analysis revealed several cancer-related proteins in Chr.20 are tissue- or cell-type dependent. With integration of all the acquired data, for the first time we established a solid database of the Chr.20 proteome.

PepDistiller: A quality control tool to improve the sensitivity and accuracy of peptide identifications in shotgun proteomics.

In this study, we presented a quality control tool named PepDistiller to facilitate the validation of MASCOT search results. By including the number of tryptic termini, and integrating a refined false discovery rate (FDR) calculation method, we demonstrated the improved sensitivity of peptide identifications obtained from semitryptic search results. Based on the analysis of a complex data set, approximately 7% more peptide identifications were obtained using PepDistiller than using MASCOT Percolator. Moreover, the refined method generated lower FDR estimations than the percentage of incorrect target (PIT) fixed method applied in Percolator. Using a standard data set, we further demonstrated the increased accuracy of the refined FDR estimations relative to the PIT-fixed FDR estimations. PepDistiller is fast and convenient to use, and is freely available for academic access. The software can be downloaded from http://www.bprc.ac.cn/pepdistiller.

Association of Peripheral Blood Cell Profile With Alzheimer's Disease: A Meta-Analysis.

Background: Inflammation and immune dysfunction play significant roles in the pathogenesis of Alzheimer's disease (AD)-related dementia. Changes in peripheral blood cell profiles are a common manifestation of inflammation and immune dysfunction and have been reported in patients with AD or mild cognitive impairment (MCI). We systematically evaluated the association of peripheral blood cell counts and indices with AD or MCI through a meta-analysis. Methods: We electronically searched sources to identify all case-control trials comparing peripheral blood cell counts and/or lymphocyte subsets between patients with AD or MCI and healthy controls (HCs). Meta-analyses were used to estimate the between-group standardized mean difference (SMD) and 95% confidence interval (CI). Results: A total of 36 studies involving 2,339 AD patients, 608 MCI patients, and 8,352 HCs were included. AD patients had significantly decreased lymphocyte counts (SMD -0.345, 95% CI [-0.545, -0.146], P = 0.001) and significantly increased leukocyte counts (0.140 [0.039, 0.241], P = 0.006), neutrophil counts (0.309 [0.185, 0.434], P = 0.01), and neutrophil-lymphocyte ratio (NLR) (0.644 [0.310, 0.978], P < 0.001) compared to HCs. Similarly, significantly increased leukocyte counts (0.392 [0.206, 0.579], P < 0.001), NLR (0.579 [0.310, 0.847], P < 0.001), and neutrophil counts (0.248 [0.121, 0.376], P < 0.001) were found in MCI patients compared with HCs. A significantly decreased percentage of B lymphocytes (-1.511 [-2.775, -0.248], P = 0.019) and CD8+ T cells (-0.760 [-1.460, -0.061], P = 0.033) and a significantly increased CD4/CD8 ratio (0.615 [0.074, 1.156], P = 0.026) were observed in AD patients compared to HCs. Furthermore, significant changes in hemoglobin level and platelet distribution width were found in patients with AD or MCI compared with HCs. However, no significant difference was found between AD or MCI patients and HCs in terms of platelet counts, mean corpuscular volume, red cell distribution width, mean platelet volume, and CD4+ T, CD3+ T, or natural killer cell counts. Conclusion: Changes in peripheral blood cell profiles, particularly involving leukocyte, lymphocyte, neutrophil, and CD8+ T cell counts, as well as the NLR and the CD4/CD8 ratio, are closely associated with AD. The diagnostic relevance of these profiles should be investigated in future.