{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T19:52:19Z","timestamp":1791316339320,"version":"4.3.1"},"reference-count":80,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Bioinform Biotech"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>During the COVID-19 pandemic, large-scale sequencing generated millions of SARS-CoV-2 genomes in public repositories including GenBank and GISAID. However, most records lack detailed patient metadata, including demographic information and clinical outcomes. This lack of host-associated information limits their utility for large-scale pathogen genomics analyses. Although sequence records linked to journal publications may contain relevant metadata, systematically extracting and linking this information requires substantial manual effort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to assess host metadata completeness in GenBank SARS-CoV-2 records and to demonstrate, through an exploratory case study, analytical opportunities enabled by enriched clinical and demographic annotations for genomic epidemiology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The authors searched LitCovid for PubMed Central (PMC) articles published between January 2023 and December 2024 that reported original complete SARS-CoV-2 genome sequences deposited in GenBank with sequence-specific patient metadata from human hosts. Two independent reviewers screened eligible articles and manually extracted metadata on sample collection, demographics, treatments, serology, vaccination status, infection presentation, and clinical outcomes. Enriched metadata were defined as patient information in the publication but absent from GenBank records. Synonymous clinical and demographic terms were standardized using SNOMED CT, and Charlson Comorbidity Index scores were calculated when metadata were available. SARS-CoV-2 genomes were retrieved, assembled, and subjected to quality control using standard bioinformatics tools. To demonstrate enriched metadata\u2019s analytical value, we selected a subset of genomes with longitudinal sequencing, comprising 100 genomes from 34 patients across 4 studies for exploratory analysis of within-host viral evolution and patient outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among 116,600 articles identified through our PMC\/LitCovid screening framework, approximately 0.02% (n=21) reported original complete SARS-CoV-2 genomes deposited in GenBank with accessible sequence-specific metadata. Within this eligible set, GenBank records contained on average 22% completeness for host metadata in our extraction schema. Completeness was confined to sample fields (averaging 81%); host demographic and clinical fields averaged 2%. Manual enrichment increased overall completeness by 30% on average, recovering 56% (14\/25) of metadata types absent from GenBank records. In the longitudinal subset, enriched metadata enabled host-stratified analyses, showing nominal associations between immunocompromised status and higher within-host evolutionary rates (\n                      <jats:italic>P<\/jats:italic>\n                      =.02) and unique amino acid mutations (\n                      <jats:italic>P<\/jats:italic>\n                      =.04). Models with enriched patient and treatment metadata outperformed mutation-only models for mortality, hospitalization, and infection duration.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Enriched host metadata improve the utility of pathogen genomic data by enabling analyses linking viral variation with demographics and clinical outcomes. Despite limited clinical and demographic information in examined GenBank records, manual enrichment facilitated a more comprehensive view of viral evolution and disease dynamics than sequence data alone. The case study\u2019s genotype-phenotype associations are exploratory and require validation in larger, independently collected cohorts. These findings highlight the need for more standardized, structured, and accessible patient metadata deposition with genomic sequences to strengthen pathogen genomics and precision public health research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/92529","type":"journal-article","created":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T16:20:06Z","timestamp":1787070006000},"page":"e92529-e92529","source":"Crossref","is-referenced-by-count":0,"title":["Enriching Public Pathogen Genomic Records With Patient Metadata: Quantitative Study and Exploratory Case Analysis"],"prefix":"10.2196","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8756-7346","authenticated-orcid":false,"given":"Michael 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