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angaGEDUCI: Anopheles gambiae gene expression database with integrated comparative algorithms for identifying conserved DNA motifs in promoter sequences.

BACKGROUND: The completed sequence of the Anopheles gambiae genome has enabled genome-wide analyses of gene expression and regulation in this principal vector of human malaria. These investigations have created a demand for efficient methods of cataloguing and analyzing the large quantities of data that have been produced. The organization of genome-wide data into one unified database makes possible the efficient identification of spatial and temporal patterns of gene expression, and by pairing these findings with comparative algorithms, may offer a tool to gain insight into the molecular mechanisms that regulate these expression patterns. DESCRIPTION: We provide a publicly-accessible database and integrated data-mining tool, angaGEDUCI, that unifies 1) stage- and tissue-specific microarray analyses of gene expression in An. gambiae at different developmental stages and temporal separations following a bloodmeal, 2) functional gene annotation, 3) genomic sequence data, and 4) promoter sequence comparison algorithms. The database can be used to study genes expressed in particular stages, tissues, and patterns of interest, and to identify conserved promoter sequence motifs that may play a role in the regulation of such expression. The database is accessible from the address http://www.angaged.bio.uci.edu. CONCLUSION: By combining gene expression, function, and sequence data with integrated sequence comparison algorithms, angaGEDUCI streamlines spatial and temporal pattern-finding and produces a straightforward means of developing predictions and designing experiments to assess how gene expression may be controlled at the molecular level.

Algorithms↗

Conventional and Shared Genetic Association Analysis Between Diabetes Mellitus and Sensorineural Hearing Loss.

PURPOSE: This study aims to investigate the epidemiological and genetic associations between diabetes mellitus (DM) and sensorineural hearing loss (SNHL) across different subtypes. METHODS: We analyzed 502,490 participants from the UK Biobank using multivariate logistic regression to examine the association between DM and SNHL, considering gender, age, and HbA1c levels. Genetic correlations and causality were examined by linkage disequilibrium score regression and bidirectional Mendelian randomization. Cross-trait meta-analyses identified shared loci between DM and SNHL, followed by gene annotation, functional analysis, and drug candidate exploration for the shared traits. RESULTS: Observational analysis revealed significant associations between DM and SNHL, consistent in subgroups based on age, sex, and certain HbA1c levels. A positive genetic correlation was found between type 2 diabetes mellitus (T2D) and SNHL (Rg = 0.0982, p = 0.0095) between T2D and SNHL, and four loci were identified, with ARHGEF28 and TCF7L2 prioritized as credible pleiotropic genes. Enrichment was indicated in glucose metabolism and organogenesis, with shared heritability in metabolic tissues and outer hair cells. Metformin was identified as potential drug candidates for the T2D-SNHL comorbidity. CONCLUSION: These findings progress our understanding of the epidemiological association, shared genetic basis, and potential therapeutic targets between T2D and SNHL, which might contribute to the management of their comorbidity.

Humans↗

A mixture model with random-effects components for clustering correlated gene-expression profiles.

MOTIVATION: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. RESULTS: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation)and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too. AVAILABILITY: A Fortran program blue called EMMIX-WIRE (EM-based MIXture analysis WIth Random Effects) is available on request from the corresponding author.

Algorithms↗

Duplicated genes evolve slower than singletons despite the initial rate increase.

BACKGROUND: Gene duplication is an important mechanism that can lead to the emergence of new functions during evolution. The impact of duplication on the mode of gene evolution has been the subject of several theoretical and empirical comparative-genomic studies. It has been shown that, shortly after the duplication, genes seem to experience a considerable relaxation of purifying selection. RESULTS: Here we demonstrate two opposite effects of gene duplication on evolutionary rates. Sequence comparisons between paralogs show that, in accord with previous observations, a substantial acceleration in the evolution of paralogs occurs after duplication, presumably due to relaxation of purifying selection. The effect of gene duplication on evolutionary rate was also assessed by sequence comparison between orthologs that have paralogs (duplicates) and those that do not (singletons). It is shown that, in eukaryotes, duplicates, on average, evolve significantly slower than singletons. Eukaryotic ortholog evolutionary rates for duplicates are also negatively correlated with the number of paralogs per gene and the strength of selection between paralogs. A tally of annotated gene functions shows that duplicates tend to be enriched for proteins with known functions, particularly those involved in signaling and related cellular processes; by contrast, singletons include an over-abundance of poorly characterized proteins. CONCLUSIONS: These results suggest that whether or not a gene duplicate is retained by selection depends critically on the pre-existing functional utility of the protein encoded by the ancestral singleton. Duplicates of genes of a higher biological import, which are subject to strong functional constraints on the sequence, are retained relatively more often. Thus, the evolutionary trajectory of duplicated genes appears to be determined by two opposing trends, namely, the post-duplication rate acceleration and the generally slow evolutionary rate owing to the high level of functional constraints.

Animals↗

Transcriptomic insights into the coordinated regulation of signaling, apoptosis, immunity, and metabolism during Sinonovacula constricta larval metamorphosis.

Metamorphosis is a critical ontogenetic transition for marine bivalves, marking the shift from planktonic to benthic lifestyles, where successful transformation dictates survival. The razor clam Sinonovacula constricta is economically important; however, low larval metamorphosis rates remain a major bottleneck in seedling production. To elucidate the mechanisms governing this process, we performed a comparative transcriptome analysis of S. constricta larvae at pre- and post-metamorphosis stages using Illumina sequencing. A total of 3701 differentially expressed genes (DEGs) were identified, including 3254 up-regulated and 447 down-regulated genes. Functional annotation of the respective top 20 significantly up-regulated and down-regulated DEGs indicated their potential pivotal roles in signal transduction (e.g., up-regulated: CAV1, CHRNA2; down-regulated: APP, NOTCH1), cellular proliferation and differentiation (e.g., up-regulated: TUBA, EGF1; down-regulated: KIF23, TTC25), transcriptional and epigenetic regulation (e.g., up-regulated: NFIL3; down-regulated: OVO, HMX1), substance transport (e.g., up-regulated: LRP2, LRP1B; down-regulated: SLC51A, Slc33a1), substance metabolism (e.g., up-regulated: CPK3, CYP26A1; down-regulated: RDMT1, ADAC), immunomodulation (e.g., up-regulated: CPN2, CRISP2), and protein homeostasis (e.g., up-regulated: HSP27, NAS-27). Functional enrichment analysis further revealed that DEGs were significantly enriched in pathways related to signal transduction and developmental regulation (e.g., Ras, TNF), cell death and homeostasis (e.g., apoptosis), immune responses (e.g., Toll-like receptor), energy metabolism (e.g., lipid), cardiovascular related (e.g., Fluid shear stress), cell junction and architecture (e.g., Tight junction), and infectious disease (e.g., measles). These results suggest a synergistic interplay between signaling, apoptosis, immunity, and metabolism during S. constricta metamorphosis. This study advances our understanding of marine bivalve metamorphosis and offers candidate genes for further mechanistic studies.

Animals↗

Profiling and functional annotation of mRNA gene expression in pediatric rhabdomyosarcoma and Ewing's sarcoma.

Using Affymetrix oligonucleotide microarrays, we analyzed mRNA gene expression patterns of 12 primary pediatric rhabdomyosarcomas (RMS) and 11 Ewing's sarcomas (EWS), which belong to the small round blue cell tumors (SRBCTs). Diagnostic classification of these cancers is frequently complicated by the highly similar appearance in routine histology, and additional molecular markers could significantly improve tumor classification. A combination of three independent statistical approaches (t-test, SAM, k-nearest neighborhood analysis) resulted in 101 highly significant probe sets that clearly discriminate between EWS and RMS. We identified novel marker transcripts that have not been previously associated with either RMS or EWS yet, including CITED2, glypican 3 (GPC3), and cyclin D1 (CCND1). Expression levels for selected candidate genes were validated by quantitative real-time reverse-transcription PCR. Furthermore, to identify biologically meaningful trends, functional annotations were assigned to 946 genes differentially expressed between EWS and RMS (t-test). Genes involved in protein biosynthesis (n = 28) and complex assembly (n = 9), lipid metabolism (n = 23), energy generation (n = 22), and mRNA processing (n = 11) were expressed significantly higher in EWS. Thus, functional annotation of tumor-specific genes reveals detailed insights into tumor biology and differentiation-specific expression patterns and gives important clues related to the possible cellular origin of these pediatric tumors. Supplementary material for this article is available at the International Journal of Cancer website at http://www.interscience.wiley.com/jpages/0020-7136/suppmat/index.html.

Biomarkers, Tumor↗

Gene targeting of ErbB3 using a Cre-mediated unidirectional DNA inversion strategy.

Recombinase-mediated unidirectional DNA inversion and transcriptional arrest is a promising strategy for high throughput conditional mutagenesis in the mouse. Banks of mouse embryonic stem cells with defined, transcriptionally silent insertions that can be activated by Cre recombinase would take advantage of existing transgenic Cre lines to rapidly produce hundreds of lineage specific and temporally controlled knockout mice for each gene, thereby introducing significant parallelism to functional gene annotation. However, the extent to which this strategy results in effective gene knockout has not been established. To test the feasibility of this strategy we targeted ErbB3, a member of the ErbB family of tyrosine kinase receptors, using this strategy. Insertion of a reversed "flipflox" vector consisting of a gene inactivation cassette (GI) and an internal ribosome entry site (IRES)-GFP reporter into intron 1 of ErbB3 was transcriptionally silent and did not affect ErbB3 expression. Crosses with ubiquitous and lineage specific Cre recombinase expressing lines permanently inverted the inserted GI cassette and blocked ErbB3 expression. Unidirectional DNA inversion by in vivo recombination is an effective strategy for targeted or ubiquitous gene knockout.

Animals↗

Shared genetic architecture and therapeutic targets across paediatric immune-mediated diseases.

OBJECTIVES: Paediatric-onset immune-mediated inflammatory diseases (IMIDs), including juvenile idiopathic arthritis and related rheumatic diseases, remain genetically undercharacterised. We aimed to define shared and category-specific genetic architecture across paediatric IMIDs, compare signals with adult IMIDs, and identify therapeutic opportunities. METHODS: We analysed 24 paediatric IMIDs classified as autoimmune, polygenic-autoinflammatory, mixed-pattern, or allergic. Genome-wide association analyses included 18,086 cases and 131,019 controls of European ancestry. We estimated single nucleotide polymorphism (SNP)-based heritability, genetic correlations, and polygenic overlap; performed subset-based meta-analysis; and conducted functional annotation, gene prioritisation, pathway and protein network analyses, adult-IMID comparison, and drug-target prioritisation. RESULTS: SNP-based heritability ranged from 28.9% for allergic IMIDs to 61.9% for autoimmune IMIDs. Genetic correlation and polygenic modelling supported partial sharing across categories with category-specific components. Meta-analysis identified 39 genome-wide significant loci outside the Major Histocompatibility Complex (MHC) region, including 15 previously unreported loci; 19 loci were shared between categories. Gene-prioritisation and protein interaction analyses identified a core MHC-centred antigen-presentation network, with category-enriched modules involving complement, innate/barrier pathways, epithelial biology, and type 2 immunity. Enriched pathways included nuclear factor κB signalling, T helper 17 related pathways, Janus kinase-signal transducer and activator of transcription signalling, programmed cell death protein 1/programmed death‑ligand 1, cytotoxic T‑lymphocyte associated protein 4 regulation, and osteoclast differentiation, several of which are relevant to rheumatic diseases. Paediatric IMIDs shared broad polygenic architecture with adult IMIDs, whereas top-ranked genes converged strongly with adult rheumatic diseases. Priority Index analysis identified 178 high-scoring genes, including 43 approved or investigational IMID drug targets. CONCLUSIONS: Paediatric-onset IMIDs share core pathways with adult forms but exhibit distinct genetic architecture shaped by age-specific immune and neurodevelopmental biology. These findings provide a genomic framework for paediatric precision medicine, guiding classification, risk prediction, and therapeutic development.

Humans↗

Computational identification and systematic analysis of the ACR gene family in Oryza sativa.

Based on sequence similarity search and domain detection, nine ACT domain repeat protein-coding genes (the "ACR" genes) in rice were identified, which were mainly distributed on the chromosomes 2, 3, 4, and 8. An InterPro database search indicated that four copies of the ACT domain linearly occupied the entire polypeptide. The first three ACT domains were linked by two different sequences. However, the fourth ACT domain was extremely close to ACT3. Gene structure comparisons showed large differences in exon numbers, from three to eight, among members of the rice ACR gene family. In addition, it appeared that gene duplication might be operative when the compositions of exons and introns were analyzed. Phylogenetic analysis divided the ACR gene family into five distinct groups, and this division was generally according to the expression patterns of the ACR genes. The Arabidopsis and rice ACR proteins were clustered across together, suggesting that these ACR genes might originate from an ancient common ancestor. Notably, the identification of orthologues and paralogues would be useful for rice gene functional annotation.

Chromosome Mapping↗

Mining DNA microarray data using a novel approach based on graph theory.

The recent demonstration that biochemical pathways from diverse organisms are arranged in scale-free, rather than random, systems [Jeong et al., Nature 407 (2000) 651-654], emphasizes the importance of developing methods for the identification of biochemical nexuses--the nodes within biochemical pathways that serve as the major input/output hubs, and therefore represent potentially important targets for modulation. Here we describe a bioinformatics approach that identifies candidate nexuses for biochemical pathways without requiring functional gene annotation; we also provide proof-of-principle experiments to support this technique. This approach, called Nexxus, may lead to the identification of new signal transduction pathways and targets for drug design.

Apoptosis↗

Selection system for genes encoding nuclear-targeted proteins.

Nuclear proteins have essential roles in cell proliferation and differentiation. We have developed a yeast selection system-the nuclear transportation trap (NTT)-to identify genes encoding nuclear transport signals. Both unknown and previously identified nuclear localization signals were identified from a human fetal brain cDNA library. The majority (75%) of the unknown proteins examined were exclusively localized to the nucleus in COS-7 cells. We propose that NTT is an efficient method for isolating cDNAs that encode nuclear targeted proteins that can be applied to the retrieval of novel nuclear proteins and to annotate gene function.

Amino Acid Sequence↗

Delineation of modular proteins: domain boundary prediction from sequence information.

The delineation of domain boundaries of a given sequence in the absence of known 3D structures or detectable sequence homology to known domains benefits many areas in protein science, such as protein engineering, protein 3D structure determination and protein structure prediction. With the exponential growth of newly determined sequences, our ability to predict domain boundaries rapidly and accurately from sequence information alone is both essential and critical from the viewpoint of gene function annotation. Anyone attempting to predict domain boundaries for a single protein sequence is invariably confronted with a plethora of databases that contain boundary information available from the internet and a variety of methods for domain boundary prediction. How are these derived and how well do they work? What definition of 'domain' do they use? We will first clarify the different definitions of protein domains, and then describe the available public databases with domain boundary information. Finally, we will review existing domain boundary prediction methods and discuss their strengths and weaknesses.

Algorithms↗

Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure.

MOTIVATION: Drawing inferences from large, heterogeneous sets of biological data requires a theoretical framework that is capable of representing, e.g. DNA and protein sequences, protein structures, microarray expression data, various types of interaction networks, etc. Recently, a class of algorithms known as kernel methods has emerged as a powerful framework for combining diverse types of data. The support vector machine (SVM) algorithm is the most popular kernel method, due to its theoretical underpinnings and strong empirical performance on a wide variety of classification tasks. Furthermore, several recently described extensions allow the SVM to assign relative weights to various datasets, depending upon their utilities in performing a given classification task. RESULTS: In this work, we empirically investigate the performance of the SVM on the task of inferring gene functional annotations from a combination of protein sequence and structure data. Our results suggest that the SVM is quite robust to noise in the input datasets. Consequently, in the presence of only two types of data, an SVM trained from an unweighted combination of datasets performs as well or better than a more sophisticated algorithm that assigns weights to individual data types. Indeed, for this simple case, we can demonstrate empirically that no solution is significantly better than the naive, unweighted average of the two datasets. On the other hand, when multiple noisy datasets are included in the experiment, then the naive approach fares worse than the weighted approach. Our results suggest that for many applications, a naive unweighted sum of kernels may be sufficient. AVAILABILITY: http://noble.gs.washington.edu/proj/seqstruct

Algorithms↗

Temporal- and dose-dependent hepatic gene expression changes in immature ovariectomized mice following exposure to ethynyl estradiol.

Temporal- and dose-dependent changes in hepatic gene expression were examined in immature ovariectomized C57BL/6 mice gavaged with ethynyl estradiol (EE), an orally active estrogen. For temporal analysis, mice were gavaged every 24 h for 3 days with 100 microg/kg EE or vehicle and liver samples were collected at 2, 4, 8, 12, 24 and 72 h. Gene expression was monitored using custom cDNA microarrays containing 3067 genes/ESTs of which 393 exhibited a change at one or more time points. Functional gene annotation extracted from public databases associated temporal gene expression changes with growth and proliferation, cytoskeletal and extracellular matrix responses, microtubule-based processes, oxidative metabolism and stress, and lipid metabolism and transport. In the dose-response study, hepatic samples were collected 24 h following treatment with 0, 0.1, 1, 10, 100 or 250 microg/kg EE. Thirty-nine of the 79 genes identified as differentially regulated at 24 h in the time course study exhibited a dose-response relationship with an average ED50 value of 47 +/- 3.5 microg/kg. Comparative analysis indicated that many of the identified temporal and dose-dependent hepatic responses are similar to EE-induced uterine responses reported in the literature and in a companion study using the same animals. Results from these studies confirm that the liver is a highly estrogen responsive tissue that exhibits a number of common responses shared with the uterus as well as distinct estrogen-mediated profiles. These data will further aid in the elucidation of the mechanisms of action of estrogens in the liver as well as in other classical and non-classical estrogen responsive tissues.

Animals↗

The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community.

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.

Arabidopsis↗

VicMAG, an open-source tool for visualizing circular metagenome-assembled genomes highlighting bacterial virulence and antimicrobial resistance.

Bacterial pathogens spread in clinical and environmental settings, and mobile genetic elements (MGEs), such as plasmids and phages, mediate the transfer of virulence factor genes (VFGs) and antimicrobial resistance genes (ARGs) among bacterial communities. Metagenomic analysis of environmental and wastewater samples using highly accurate long-read sequencing technologies, such as Pacific Biosciences (PacBio) HiFi sequencing, provides valuable insights into monitoring the regional spread of VFGs and ARGs, including dissemination mediated by MGEs. No visualization tool is currently available for the comprehensive display of numerous resulting circular metagenome-assembled genomes (cMAGs) with functional gene annotations. Here, we developed visualization of circular metagenome-assembled genome (VicMAG), a visualization tool for highly complex cMAGs derived from long-read metagenome assemblies annotated using updated databases of VFGs, ARGs, and MGEs. Using 353 cMAGs from PacBio HiFi sequencing of a wastewater sample, we demonstrated the utility of VicMAG for metagenome visualization. VicMAG provides comprehensive, size-aware visualization of cMAGs representing bacterial chromosomes and plasmids, annotated with VFGs, ARGs, and phages. By simultaneously visualizing all cMAGs in a framework, VicMAG facilitates a holistic understanding of the distribution and genomic context of VFGs and ARGs across complex microbial communities. This tool supports integrated surveillance of bacteria associated with virulence and antimicrobial resistance across clinical, environmental, and One Health contexts.

Metagenome↗

Temporal and dose-dependent hepatic gene expression patterns in mice provide new insights into TCDD-Mediated hepatotoxicity.

In an effort to further characterize the mechanisms of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-mediated toxicity, comprehensive temporal and dose-response microarray analyses were performed on hepatic tissue from immature ovariectomized C57BL/6 mice treated with TCDD. For temporal analysis, mice were gavaged with 30 microg/kg of TCDD or vehicle and sacrificed after 2, 4, 8, 12, 18, 24, 72, or 168 h. Dose-response mice were gavaged with 0, 0.001, 0.01, 0.1, 1, 10, 100, or 300 microg/kg of TCDD and sacrificed after 24 h. Hepatic gene expression profiles were monitored using custom cDNA microarrays containing 13,362 cDNA clones. Gene expression analysis identified 443 and 315 features which exhibited a significant change at one or more doses or time points, respectively, as determined using an empirical Bayes approach. Functional gene annotation extracted from public databases associated gene expression changes with physiological processes such as oxidative stress and metabolism, differentiation, apoptosis, gluconeogenesis, and fatty acid uptake and metabolism. Complementary histopathology (H&E and Oil Red O stains), clinical chemistry (i.e., alanine aminotransferase [ALT], triglyceride [TG], free fatty acids [FFA], cholesterol) and high-resolution gas chromatography/mass spectrometry assessment of hepatic TCDD levels were also performed in order to phenotypically anchor changes in gene expression to physiological end points. Collectively, the data support a proposed mechanism for TCDD-mediated hepatotoxicity, including fatty liver, which involves mobilization of peripheral fat and inappropriate increases in hepatic uptake of fatty acids.

Alanine Transaminase↗

Genetic Contributors to Postoperative Delirium and Their Implications for Dementia Outcomes.

BACKGROUND: Postoperative delirium (POD) is a perioperative neurocognitive disorder that substantially impairs patient recovery. Unfortunately, its genetic risk profile and relationship with subsequent dementia remain unclear. This study aimed to elucidate genetic contributors to POD identified via Hospital Episode Statistics codes and to examine its association with subsequent dementia. METHODS: The study included 230,179 noncardiac and 21,254 cardiac surgery subjects from the UK Biobank, defining POD using delirium codes from the International Classification of Diseases (10th revision) recorded within the first 7 postoperative days. Genome-wide association studies were performed in the noncardiac and cardiac cohorts and their prespecified subgroups, followed by functional annotation, gene prioritization and drug-target analyses. Associations between POD and subsequent dementia were estimated using Cox models. RESULTS: In the noncardiac cohort, one genome-wide significant locus was identified at the APOE region, with rs429358 as the lead variant ( P = 5.00 × 10 -28 ). Integrative gene prioritization analyses highlighted multiple genes within this locus. Exploratory drug-target analyses suggested potential subgroup-specific drug-target enrichment. In the cardiac cohort, no genome-wide significant signals were detected. POD was associated with all-cause dementia after both noncardiac (hazard ratio, 6.45; 95% CI, 5.45 to 7.63) and cardiac (hazard ratio, 2.95; 95% CI, 1.71 to 5.08) surgeries. CONCLUSIONS: This study demonstrates APOE as a genetic risk locus for International Classification of Diseases-coded POD in the noncardiac surgery setting and confirms an association between POD and subsequent dementia.

Humans↗