PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Databases, Genetic”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources
PubMed1998

Comorbid migraine with aura, anxiety, and depression is associated with dopamine D2 receptor (DRD2) NcoI alleles.

BACKGROUND: Unrelated individuals (n = 242) were interviewed directly for the presence of migraine, anxiety disorders, and major depression. MATERIALS AND METHODS: The data described in this study are derived from a clinical genetic relational database that was developed initially for the genetic analysis of migraine. Genotyping of the DRD2 NcoI C to T polymorphism located in exon 6 (His313His) was performed using previously described primers. RESULTS: A significantly increased incidence of migraine with aura (MWA), major depression, generalized anxiety disorder (GAD), panic attacks, and phobia was observed in individuals with the DRD2 NcoI C/C genotype compared with individuals with an DRD2 NcoI T allele. Specifically, 69% (91/131) of DRD2 NcoI C/C individuals in the present study met criteria for at least one of these neuropsychiatric disorders versus only 22% (4/18) of the DRD2 NcoI T/T individuals (Chi-square = 15.29; p < 0.00005). The DRD2 NcoI C allele frequency is significantly higher (Chi-square = 17.13; p < 0.00002) in individuals with MWA, anxiety disorders, and/or major depression (C allele frequency = 0.80) than in individuals who have none of these disorders (C allele frequency = 0.67). CONCLUSIONS: These data indicate that MWA, anxiety disorders, and major depression can be components of a distinct clinical syndrome associated with allelic variations within the DRD2 gene. Clinical recognition of this genetically based syndrome has significant diagnostic and therapeutic implications.

Alleles↗
PubMed2001

A web-based tool to retrieve human genome polymorphisms from public databases.

Single Nucleotide Polymorphisms (SNPs) are the most important source of variation in our genome, and an invaluable tool in the hands of researchers who investigate genetic diseases. Databases of SNPs are growing at a very fast rate, and the ability to perform large-scale, high-resolution association studies is quickly becoming a reality. In this paper we describe SNPper, a web-based tool to search for SNPs in public databases. The system allows searching for all SNPs in a given set of genes (for candidate gene studies) or in a specified region of a chromosome. The information displayed for each gene or each SNP is fully annotated and linked to the leading bioinformatics web sites. The first release of SNPper is available on the web, and has received positive feedback from the genetic and bioinformatics community.

Databases, Genetic↗
PubMed1999

Histone Sequence Database: sequences, structures, post-translational modifications and genetic loci.

The Histone Sequence Database is an annotated and searchable collection of all available histone and histone fold sequences and structures. Particular emphasis has been placed on documenting conflicts between similar sequence entries from a number of source databases, conflicts that are not necessarily documented in the source databases themselves. New additions to the database include compilations of post-translational modifications for each of the core and linker histones, as well as genomic information in the form of map loci for the human histone gene complement, with the genetic loci linked to Online Mendelian Inheritance in Man (OMIM). The database is freely accessible through the World Wide Web at either http://genome.nhgri.nih.gov/histones/ or http://www.ncbi.nlm.nih. gov/Baxevani/HISTONES

Animals↗
PubMed2025

Frequency of variants in Mendelian Alzheimer's disease genes within the Alzheimer's Disease Sequencing Project.

BackgroundPrior studies examined variants within presenilin-2 (PSEN2), presenilin-1 (PSEN1), and amyloid precursor protein (APP) genes. However, previously-reported clinically-relevant variants and other predicted damaging missense (DM) variants have not been characterized in a newer release of the Alzheimer's Disease Sequencing Project (ADSP).ObjectiveTo characterize previously-reported clinically-relevant variants and DM variants in PSEN2, PSEN1, APP within the participants from the ADSP.MethodsWe identified rare variants (MAF&#x2009;<&#x2009;1%) in PSEN2, PSEN1, and APP in 14,641 individuals with whole genome sequencing and 16,849 individuals with whole exome sequencing available (Ntotal&#x2009;=&#x2009;31,490). We additionally curated variants from ClinVar, OMIM, and Alzforum and report carriers of variants in clinical databases as well as predicted DM variants in these genes.ResultsWe detected 31 previously-reported clinically-relevant variants with alternate alleles observed within the ADSP: 4 variants in PSEN2, 25 in PSEN1, and 2 in APP. The overall variant carrier rate for the 31 clinically-relevant variants in the ADSP was 0.3%. We observed that 79.5% of the variant carriers were cases compared to 3.9% were controls. In those with AD, the mean age of onset of AD among carriers of these clinically-relevant variants was 19.6&#x2009;&#xb1;&#x2009;1.4 years earlier compared with noncarriers (p&#x2009;=&#x2009;7.8&#x2009;&#xd7;&#x2009;10-57). Additionally, we identified 197 rare variants (MAF&#x2009;<&#x2009;1%) within ADSP participants not reported in known clinical databases.ConclusionsA small proportion of individuals in the ADSP are carriers of a previously-reported clinically-relevant variant allele for AD and these participants have significantly earlier age of AD onset compared to noncarriers.

Humans↗
PubMed2025

Characterizing trends in clinical genetic testing: A single-center analysis of EHR data from 1.8 million patients over two decades.

A lack of structural data in electronic health records (EHRs) makes assessing the impact of genetic testing on clinical practice challenging. We extracted clinical genetic tests from the EHRs of more than 1.8 million patients seen at Vanderbilt University Medical Center from 2002 to 2022. With these data, we quantified the use of clinical genetic testing in healthcare and described how testing patterns and results changed over time. We assessed trends in types of genetic tests, tracked usage across medical specialties, and introduced a new measure, the genetically attributable fraction (GAF), to quantify the proportion of observed phenotypes attributable to a genetic diagnosis over time. We identified 104,392 tests and 19,032 molecularly confirmed diagnoses. The proportion of patients with genetic testing in their EHRs increased from 1.0% in 2002 to 6.1% in 2022, and testing became more comprehensive with the growing use of multi-gene panels. The number of unique diseases diagnosed with genetic testing increased from 51 in 2002 to 509 in 2022, and there was a rise in the number of variants of uncertain significance. The phenome-wide GAF for 6,505,620 diagnoses made in 2022 was 0.46%, and the GAF was greater than 5% for 74 phenotypes, including pancreatic insufficiency (67%), chorea (64%), atrial septal defect (24%), microcephaly (17%), paraganglioma (17%), and ovarian cancer (6.8%). Our study provides a comprehensive quantification of the increasing role of genetic testing at a major academic medical institution and demonstrates its growing utility in explaining the observed medical phenome.

Humans↗
PubMed2026

Comprehensive evaluation of ACMG/AMP-based variant classification tools.

MOTIVATION: The American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines represent the gold standard for clinical variant interpretation. Despite the widespread adoption of ACMG/AMP guidelines, a comprehensive comparison of the software tools designed to implement them has been lacking. This represents a significant gap, as clinicians require evidence-based guidance on which tools to use in their practice. RESULTS: We benchmarked four ACMG/AMP-based tools (Franklin, InterVar, TAPES, Genebe) selected from 22 tools, and compared their performance with LIRICAL, a top-performing phenotype-driven tool, using 151 expert-curated datasets from Mendelian disorders. Selection criteria included free availability, VCF compatibility, operational reliability, and not being disease-specific. Our evaluation framework assessed top-N accuracy (N&#x2009;=&#x2009;1, 5, 10, 20, 50), retention rates, precision, recall, F1 scores, and area under the curve (AUC). Statistical validation employed bootstrap confidence intervals (n&#x2009;=&#x2009;1000) and Friedman tests. LIRICAL (68.21%) and Franklin (61.59%) demonstrated superior top-10 variant prioritization accuracy in Mendelian disorders, significantly outperforming other tools (P&#x2009;=&#x2009;.0000). Results demonstrate that tools with advanced phenotypic integration significantly outperform those relying primarily on genomic features. AVAILABILITY AND IMPLEMENTATION: All data and source code required to reproduce the findings of this study are openly available in the Code Ocean repository at https://doi.org/10.24433/CO.6562438.v1.

Software↗
PubMed2025

PlantPan: A comprehensive multi-species plant pan-genome database.

The pan-genome represents the complete genomic diversity of specific species, serving as a valuable resource for studying species evolution, crop domestication, and guiding crop breeding and improvement. While there are several single-species-specific plant pan-genome databases, the availability of multi-species pan-genome databases is limited. Additionally, variations in methods and data types used for plant pan-genome analysis across different databases hinder the comparison and integration of pan-genome information from various projects at multi-species or single-species levels. To tackle this challenge, we introduce PlantPan, a comprehensive database housing the results of pan-genome analysis for 195 genomes from 11 plant species. PlantPan aims to provide extensive information, including gene-centric and sequence-centric pan-genome information, graph-based pan-genome, pan-genome openness profiles, gene functions and its variation characteristics, homologous genes, and gene clusters across different species. Statistically, PlantPan incorporates 9&#x2009;163&#x2009;011 genes, 694&#x2009;191 gene clusters, 526&#x2009;973&#x2009;370 genome variations, and 1&#x2009;616&#x2009;089 non-redundant genome variation groups at the species level, 33&#x2009;455,098 genome synteny, and 177&#x2009;827 non-redundant genome synteny groups at the species level. Regarding functional genes, PlantPan contains 5&#x2009;222&#x2009;720 genes related to transcription factors, 395&#x2009;247 literature-reported resistance genes, 455&#x2009;748 predicted microbial/disease resistance genes, and 1&#x2009;612&#x2009;112 genes related to molecular pathways. In summary, PlantPan is a vital platform for advancing the application of pan-genomes in molecular breeding for crops and evolutionary research for plants.

Genome, Plant↗
PubMed2001

Microfluidic arrays in genetic analysis.

The goal of genetic analysis is to discover genetic markers that are informative for providing high confidence, positive predictive value in managing phenotypic outcomes. Primary consensus sequence data, genetic polymorphism databases and associated phenotype data are rapidly making genetic analysis more useful. Therefore, genetic analysis applications are gradually becoming more mainstream. The diversity and complexity of genetic analysis currently requires an array of analytical techniques, instrument platforms and software to support all the steps from data acquisition to interpretation. As supporting research technologies mature, they are incorporating increasing levels of automation, system integration and miniaturization. Microfluidic arrays are positioned to play a key role in routine genetic analysis, particularly as they begin to appear in more fully integrated analytical platforms.

Animals↗
PubMed2001

Availability and characterization of transgenic and knockout mice with behavioral manifestations: where to look and what to search for.

Mice altered by transgenesis or gene targeting ("knockouts") have increasingly been employed as alternative effective tools in elucidating the genetic basis of neurophysiology and behavior. Standardization of specific behavioral paradigms and phenotyping strategies will ensure that these behavioral mouse mutants offer robust models for evaluating the efficacy of novel therapeutics in the treatment of hereditary neurological disorders. The Induced Mutant Resource (IMR) at The Jackson Laboratory (Bar Harbor, Maine, USA) imports, cryopreserves, develops, maintains, and distributes to the research community biomedically valuable stocks of transgenic and targeted mutant mice. Information on behavioral and neurological strains-including a phenotypic synopsis, husbandry requirements, strain availability, and genetic typing protocols-is available through the IMR database (http://www.jax.org/resources/documents/imr/). A current catalog of available strains is readily accessible via the JAX Mice Web site at http://jaxmice.jax.org/index.shtml. In addition, The Jackson Laboratory is now home to TBASE (http://tbase.jax.org/), a comprehensive, community database whose primary focus is on mouse knockouts. TBASE accommodates an exhaustive bibliographical resource for transgenic and knockout mice and provides a detailed phenotypic characterization of numerous behavioral knockouts that is primarily extracted from the literature. Concerted efforts to merge the two resources into a new, schematically reformed database are underway.

Animals↗
PubMed1993

Information resources at the National Center for Biotechnology Information.

The National Center for Biotechnology Information (NCBI), part of the National Library of Medicine, was established in 1988 to perform basic research in the field of computational molecular biology as well as build and distribute molecular biology databases. The basic research has led to new algorithms and analysis tools for interpreting genomic data and has been instrumental in the discovery of human disease genes for neurofibromatosis and Kallmann syndrome. The principal database responsibility is the National Institutes of Health (NIH) genetic sequence database, GenBank. NCBI, in collaboration with international partners, builds, distributes, and provides online and CD-ROM access to over 112,000 DNA sequences. Another major program is the integration of multiple sequences databases and related bibliographic information and the development of network-based retrieval systems for Internet access.

Animals↗
PubMed2002

Genetic testing.

Explore the source record for details and available documents.

Abortion, Legal↗
PubMed2026

cfMethDB: A Comprehensive cfDNA Methylation Data Resource for Cancer Biomarkers.

Cancer is a major global health threat, and early detection is crucial for improving patient outcomes. DNA methylation in circulating cell-free DNA (cfDNA) has emerged as a promising biomarker for non-invasive cancer diagnosis. However, the integration and utilization of existing cfDNA methylation data have been limited, hindering comprehensive research efforts, particularly in the discovery of cfDNA methylation biomarkers. To address this challenge, we introduced cfMethDB, a comprehensive database dedicated to cfDNA methylation in cancer that encompasses 4828 publicly available datasets. Through standardized analysis, we identified 1,048,770 differentially methylated cytosines (DMCs) as candidate biomarkers across seven cancer types. With cfMethDB, we not only identified known cfDNA methylation biomarkers, but also discovered several genes, such as ZIC4, that could be novel biomarkers. Moreover, cfMethDB offers a suite of user-friendly tools, including biomarker evaluation, pan-cancer search, and end motif analysis. We hope that cfMethDB will serve as a valuable platform for the discovery of novel cancer cfDNA methylation biomarkers and facilitate cancer research and clinical applications. cfMethDB is publicly available at https://cfmethdb.hzau.edu.cn/home.

Humans↗
PubMed2001

A sequence-based integrated map of chromosome 22.

The near-completion of the sequence for chromosome 22q revolutionizes map integration. We describe a sequence-based integrated map containing 968 loci including 516 known or predicted gene sequences, 317 STSs not included in these sequences, and 135 nonexpressed multinucleotide polymorphisms. The published sequence spans 34.6 Mb, inclusive of gaps estimated to total 1.1 Mb, compared with a top-down estimate of 43 Mb. This discrepancy is discussed, but will not be resolved until more of the genome is analyzed. The radiation hybrid map has 5% error in order and 34% error in location exceeding 1 Mb. The utility of a composite location based on evidence other than sequence is limited to regions not yet sequenced. A genetic map conditional on sequence order was constructed from pairwise lods. Its length of 74.8 cM in males and 80.2 cM in females is slightly less than the previous estimate not constrained by sequence order. Five recombination hot spots are detected, with differences in location between the sexes. Male recombination correlates with repetitive DNA, whereas female recombination does not. It remains to be seen whether this is true for other human chromosomes. An algorithm to improve the fit of cytogenetic bands sequence location reduces the discrepancies in cytogenetic assignment from 61 to 38. This sequence-based integrated map is represented in the genetic location database (LDB2000), which is available at http://cedar.genetics.soton.ac.uk/public_html/LDB2000.html.

Base Sequence↗