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Chapter 8: Step 6 — Clinical & Population Repositories: gnomAD, ClinVar, COSMIC & OMIM

Tested Stacks: GATK 4.6.1 Samtools 1.21 Nextflow 24.10 Seurat v5.1 Python 3.12
Prerequisites: Basic Linux CLI & Sequencing Formats
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Chapter 8: Step 6 — Clinical & Population Repositories: gnomAD, ClinVar, COSMIC & OMIM

Even with precise molecular consequence and in silico scores, a variant cannot be diagnosed in a clinical vacuum. Step 6 of the clinical pipeline interrogates four foundational biomedical databases to establish population frequency, archived clinical consensus, somatic cancer recurrence, and Mendelian inheritance patterns.

Step 6 Technical Specifications
  • Core Repositories: gnomAD (Population Controls) • ClinVar (Archived Submissions) • COSMIC (Somatic Hotspots) • OMIM (Gene-Disease Phenotypes).
  • Contributed Pipeline Evidence: Control allele frequencies ($AF$), ClinVar review status star tiers, somatic recurrence counts, and disease inheritance modes.
  • Clinical Utility: High population control frequency definitively proves a variant is benign, while ClinVar consensus and OMIM validation provide the legal and medical basis for clinical reporting.

The 4 Essential Repositories Master Matrix

Database NamePrimary Clinical RoleScale & CoverageContributed Pipeline EvidenceACMG Evidence Triggers
gnomADPopulation Control Frequency>800,000 diverse human exomes & genomesDetermines whether a variant is common or extremely rare in healthy individuals. High frequency (>1% or >5%) proves a variant is benign.BA1 (>5%), BS1 (>expected), PM2 (absent / ultra-rare ≤0.001%)
ClinVarArchived Clinical Assertions>3 million clinical variant records from diagnostic labsPublic registry of variants mapped to clinical disease classifications submitted by accredited diagnostic labs (Invitae, GeneDx, Ambry).PP5 (Reputable pathogenic), BP6 (Reputable benign), Star curation
COSMICSomatic Cancer Catalogue>37 million coding mutations across 1.5M tumor samplesTracks mutation frequencies in tumor tissue specimens to highlight recurrent cancer driver hotspots and therapeutic targets.Somatic Actionability Tiers (AMP/ASCO/CAP), Hotspot validation
OMIMGene-Disease Inheritance>26,000 curated Mendelian entriesAuthoritative compendium linking target genes to specific clinical syndromes and inheritance patterns (Autosomal Dominant/Recessive).Verifies gene-disease validity, establishes inheritance criteria (dominant vs recessive)

1. gnomAD: Evaluating Population Control Allele Frequencies

The fundamental rule of Mendelian medical genetics is that a variant cannot be more common in the general population than the disease it is claimed to cause. If a genetic disease has a prevalence of 1 in 10,000 individuals, any variant present at 2% in gnomAD is mathematically impossible to be a fully penetrant causal allele.

  • Stand-Alone Benign Threshold (BA1): Allele frequency $> 5\%$ in gnomAD across any major continental subpopulation (e.g. European, African, East Asian, South Asian, Latino).
  • Rarity for Pathogenic Consideration (PM2_Supporting): Absent from gnomAD, or allele frequency $< 0.001\%$ ($1 imes 10^{-5}$) for dominant diseases.

2. ClinVar: Navigating the 4-Star Review Status Hierarchy

Not all ClinVar records carry equal diagnostic weight. When curating clinical variants, pathologists must verify the submission's review status:

  • 0 Stars (No assertion criteria provided): Single laboratory submission without formal scoring documentation. Low evidentiary weight.
  • 1 Star (Criteria provided, single submitter OR conflicting interpretations): Multiple submitters disagree (e.g. 2 labs call it VUS, 1 calls it Likely Pathogenic). Requires independent curation.
  • 2 Stars (Criteria provided, multiple submitters, no conflicts): Consistent consensus reached across independent accredited diagnostic laboratories. Strong clinical benchmark.
  • 3 Stars (Reviewed by an expert panel): Curation performed by a recognized ClinGen Variant Curation Expert Panel (VCEP) (e.g. ClinGen PTEN, CDH1, or Hearing Loss VCEPs). Overrides all 1-star and 2-star records.
  • 4 Stars (Practice guideline): Formal ACMG or professional society consensus recommendation.
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Common Pitfalls & Troubleshooting Checklist

  • Java Heap Exhaustion (GATK / Picard): If processes terminate with java.lang.OutOfMemoryError, set your environment variable explicitly: export _JAVA_OPTIONS="-Xmx16g -Djava.io.tmpdir=/tmp".
  • Index Timestamp Mismatch: If tools complain that a BAM index is missing or out of date, regenerate with samtools index -@ 4 sample.bam.
  • Conda Channel Conflicts: Avoid ABI incompatibilities between bioconda and conda-forge by setting strict priority: conda config --set channel_priority strict.
  • Chromosome Naming Contamination: Always verify whether reference FASTA headers use chr1 or 1; divergent naming causes silent alignment drops.
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