Tooluniverse Structural Variant Analysis

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Structural Variant Analysis Workflow

Systematic analysis of structural variants (deletions, duplications, inversions, translocations, complex rearrangements) for clinical genomics interpretation using ACMG-adapted criteria.

LOOK UP DON'T GUESS - Always retrieve ClinGen HI/TS scores, gnomAD frequencies, and ClinVar evidence from tools. Do not infer dosage sensitivity from gene function alone.

KEY PRINCIPLES: 1. Report-first approach - Create SV_analysis_report.md FIRST, then populate progressively 2. ACMG-style classification - Pathogenic/Likely Pathogenic/VUS/Likely Benign/Benign with explicit evidence 3. Evidence grading - Grade all findings by confidence level (High/Moderate/Limited) 4. Dosage sensitivity critical - Gene dosage effects drive SV pathogenicity 5. Breakpoint precision matters - Exact gene disruption vs dosage-only effects 6. Population context essential - gnomAD SVs for frequency assessment 7. English-first queries - Always use English terms in tool calls. Respond in the user's language

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Triggers

Use this skill when users:

• Ask about structural variant interpretation
• Have CNV data from array or sequencing
• Ask "is this deletion/duplication pathogenic?"
• Need ACMG classification for SVs
• Want to assess gene dosage effects
• Ask about chromosomal rearrangements
• Have large-scale genomic alterations requiring interpretation

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SV Pathogenicity Reasoning (Start Here)

Before any tool call, apply this reasoning to frame the analysis:

SV pathogenicity depends on what the SV disrupts. A deletion removing an entire gene is likely pathogenic if the gene is haploinsufficient. A duplication is pathogenic if the gene is dosage-sensitive. An inversion is pathogenic only if it disrupts a coding region or regulatory element at the breakpoint.

Work through these questions in order:

1. What type is the SV, and what disruption mechanism does it cause?

• Deletion: loss of one copy. Pathogenic if any contained gene is haploinsufficient (ClinGen HI score 3, pLI >= 0.9). A deletion of a dosage-insensitive gene in a gene-dense region may be benign even if large.
• Duplication: gain of one copy. Pathogenic if any contained gene is dosage-sensitive (ClinGen TS score 3). Duplications can also disrupt gene regulation if tandem (disrupts reading frame at junction) or if they separate a gene from its enhancer.
• Inversion: no copy number change. Pathogenic only at the breakpoints: if one breakpoint falls within an exon (truncation) or separates a gene from its regulatory element. Inversions entirely within gene-poor, regulatory-poor regions are often benign.
• Translocation: pathogenic if a breakpoint disrupts a coding region or creates a pathogenic fusion gene. Balanced translocations in parents of affected children warrant special scrutiny.
• Complex rearrangements: assess each segment and each breakpoint independently.

2. Is the disrupted gene dosage-sensitive?

• ClinGen HI score 3 = definitive haploinsufficiency (deletion of this gene is pathogenic)
• ClinGen HI score 2 = likely haploinsufficient
• pLI >= 0.9 = strong LoF intolerance (supporting haploinsufficiency)
• ClinGen TS score 3 = definitive triplosensitivity (duplication is pathogenic)
• If no ClinGen data: use OMIM inheritance (autosomal dominant = often dosage-sensitive) as weaker evidence

3. Does the population frequency contextualize the SV?

• >=1% frequency in gnomAD SV = BA1 (likely benign unless phenotype is extreme)
• <0.01% = supports pathogenicity (PM2)
• Present in unaffected parents = weak evidence against pathogenicity, but not conclusive

4. Is there clinical precedent?

• Identical SV in ClinVar as Pathogenic/Likely Pathogenic = strong evidence (PS1)
• De novo occurrence = strong evidence for pathogenicity (PS2)
• Phenotype match to known gene-disease association = supporting evidence (PP4)

Document this reasoning before computing the final score.

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Workflow Overview

Phase 1: SV IDENTITY & CLASSIFICATION
  Normalize coordinates (hg19/hg38), determine type (DEL/DUP/INV/TRA/CPX),
  calculate size, assess breakpoint precision

Phase 2: GENE CONTENT ANALYSIS
  Identify fully contained genes, partially disrupted genes (breakpoint within),
  flanking genes (within 1 Mb), annotate function and disease associations

Phase 3: DOSAGE SENSITIVITY ASSESSMENT
  ClinGen HI/TS scores, pLI scores, OMIM inheritance patterns,
  gene-disease validity levels

Phase 4: POPULATION FREQUENCY CONTEXT
  gnomAD SV database, ClinVar known SVs, DECIPHER patient cases,
  reciprocal overlap calculation (>=70% = same SV)

Phase 5: PATHOGENICITY SCORING
  Quantitative 0-10 scale: gene content (40%), dosage sensitivity (30%),
  population frequency (20%), clinical evidence (10%)

Phase 6: LITERATURE & CLINICAL EVIDENCE
  PubMed searches, DECIPHER cohort analysis, functional evidence

Phase 7: ACMG-ADAPTED CLASSIFICATION
  Apply SV-specific evidence codes, calculate final classification,
  generate clinical recommendations

---

Phase 1: SV Identity & Classification

Goal: Standardize SV notation and classify type.

Capture: chromosome(s), coordinates (start/end in hg19/hg38), SV size, SV type (DEL/DUP/INV/TRA/CPX), breakpoint precision, inheritance pattern (de novo/inherited/unknown).

For SV type definitions, scoring tables, and ACMG code details, see CLASSIFICATION_GUIDE.md.

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Phase 2: Gene Content Analysis

Goal: Annotate all genes affected by the SV.

Tools:

• ensembl_lookup_gene - gene structure, coordinates, exons
• NCBIGene_search - official symbol, aliases, description
• GO_get_term_details - biological process, molecular function
• OMIM_search, OMIM_get_entry - disease associations, inheritance
• DisGeNET_search_gene - gene-disease association scores

Classify genes as: fully contained (entire gene in SV), partially disrupted (breakpoint within gene), or flanking (within 1 Mb of breakpoints).

For implementation pseudocode, see ANALYSIS_PROCEDURES.md Phase 2.

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Phase 3: Dosage Sensitivity Assessment

Goal: Determine if affected genes are dosage-sensitive.

Tools:

• ClinGen_search_dosage_sensitivity - HI/TS scores (0-3, gold standard)
• ClinGen_search_gene_validity - gene-disease validity level
• gnomad_search_variants - pLI scores for LoF intolerance
• OMIM_get_entry - inheritance pattern (AD suggests dosage sensitivity)

Interpret scores using the reasoning above. ClinGen HI/TS score 3 = definitive; score 2 = likely; score 1 = little evidence; score 0 = no evidence. Do not equate AD inheritance with haploinsufficiency without ClinGen support.

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Phase 4: Population Frequency Context

Goal: Determine if SV is common (likely benign) or rare (supports pathogenicity).

Tools:

• gnomad_search_variants - population SV frequencies
• ClinVar_search_variants - known pathogenic/benign SVs
• ClinGen_search_dosage_sensitivity - patient SVs with phenotypes

Use >=70% reciprocal overlap to define "same" SV for comparison. A frequency >=1% triggers BA1 unless there is very strong clinical evidence to override.

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Phase 5: Pathogenicity Scoring

Goal: Quantitative pathogenicity assessment on 0-10 scale.

Four components weighted: gene content (40%), dosage sensitivity (30%), population frequency (20%), clinical evidence (10%).

Score mapping: 9-10 = Pathogenic, 7-8 = Likely Pathogenic, 4-6 = VUS, 2-3 = Likely Benign, 0-1 = Benign.

For detailed scoring breakdowns and implementation, see CLASSIFICATION_GUIDE.md and ANALYSIS_PROCEDURES.md Phase 5.

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Phase 6: Literature & Clinical Evidence

Goal: Find case reports, functional studies, and clinical validation.

Tools:

• PubMed_search_articles - peer-reviewed literature
• EuropePMC_search_articles - additional coverage
• ClinGen_search_dosage_sensitivity - patient case database

Search strategies: gene-specific dosage sensitivity papers, SV-specific case reports, phenotype-gene associations. See ANALYSIS_PROCEDURES.md Phase 6.

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Phase 7: ACMG-Adapted Classification

Goal: Apply ACMG/ClinGen criteria adapted for SVs and generate a final classification with explicit evidence summary.

The LLM knows the ACMG criteria codes and combination rules. Apply them to the evidence gathered in Phases 1-6. Key points to verify with tool data:

• PVS1 applies to deletions of genes with ClinGen HI score >= 2 or pLI >= 0.9
• PS2 requires confirmed de novo status (check parental genotypes if available)
• PM2 requires absence from population databases at >=70% reciprocal overlap

For complete evidence code tables and classification algorithm, see CLASSIFICATION_GUIDE.md.

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Output

Create report using the template in REPORT_TEMPLATE.md. Name files as:

SV_analysis_[TYPE]_chr[CHR]_[START]_[END]_[GENES].md

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Required Tools Reference

• ClinGen_search_dosage_sensitivity - HI/TS scores (required for all deletions/duplications)
• ClinGen_search_gene_validity - gene-disease validity (required)
• ClinVar_search_variants - known pathogenic/benign SVs (required)
• ensembl_lookup_gene - gene coordinates, structure (required)
• OMIM_search, OMIM_get_entry - gene-disease associations (required)
• gnomad_search_variants - population frequency and pLI (required)
• DisGeNET_search_gene - additional disease associations (recommended)
• PubMed_search_articles - literature evidence (recommended)
• GO_get_term_details - gene function (supporting)

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When NOT to Use This Skill

• Single nucleotide variants (SNVs) - Use tooluniverse-variant-interpretation
• Small indels (<50 bp) - Use variant interpretation skill
• Somatic variants in cancer - Different framework needed
• Mitochondrial variants - Specialized interpretation required
• Repeat expansions - Different mechanism

Use this skill for structural variants >=50 bp requiring dosage sensitivity assessment and ACMG-adapted classification.

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Reference Files

• EXAMPLES.md - Sample SV interpretations with worked examples
• CLASSIFICATION_GUIDE.md - ACMG criteria, scoring system, evidence codes, special scenarios, clinical recommendations
• REPORT_TEMPLATE.md - Full report template with section structure and file naming
• ANALYSIS_PROCEDURES.md - Detailed implementation pseudocode for each phase

External References

• ClinGen Dosage Sensitivity Map: https://www.ncbi.nlm.nih.gov/projects/dbvar/clingen/
• ACMG SV Guidelines: Riggs et al., Genet Med 2020 (PMID: 31690835)
• tooluniverse-variant-interpretation - For SNVs and small indels

SV Analysis Procedures

Detailed implementation guidance for each phase of the structural variant analysis workflow. These are pseudocode examples showing how to use ToolUniverse tools for SV interpretation.

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Phase 2: Gene Content Analysis

Gene Categories

1. Fully contained genes - Entire gene within SV boundaries

• Deletion: Complete loss of one copy (haploinsufficiency)
• Duplication: Extra copy (triplosensitivity)

2. Partially disrupted genes - Breakpoint within gene

• Likely loss-of-function for affected allele
• Check if critical domains disrupted

3. Flanking genes - Within 1 Mb of breakpoints

• May be affected by position effects
• Regulatory disruption possible

Implementation

def analyze_gene_content(tu, chrom, sv_start, sv_end, sv_type):
    """
    Identify and annotate all genes within SV region.
    """
    genes = {
        'fully_contained': [],
        'partially_disrupted': [],
        'flanking': []
    }

    for gene in genes_in_region:
        gene_start = gene['start']
        gene_end = gene['end']

        if gene_start >= sv_start and gene_end <= sv_end:
            gene_info = annotate_gene(tu, gene['symbol'])
            genes['fully_contained'].append(gene_info)
        elif (gene_start < sv_start < gene_end) or (gene_start < sv_end < gene_end):
            gene_info = annotate_gene(tu, gene['symbol'])
            genes['partially_disrupted'].append(gene_info)
        elif abs(gene_start - sv_end) < 1000000 or abs(gene_end - sv_start) < 1000000:
            gene_info = annotate_gene(tu, gene['symbol'])
            genes['flanking'].append(gene_info)

    return genes

def annotate_gene(tu, gene_symbol):
    """Comprehensive gene annotation."""
    omim = tu.tools.OMIM_search(operation="search", query=gene_symbol, limit=5)
    disgenet = tu.tools.DisGeNET_search_gene(operation="search_gene", gene=gene_symbol, limit=10)
    ncbi = tu.tools.NCBIGene_search(term=gene_symbol, organism="human")
    return {'symbol': gene_symbol, 'omim': omim, 'disgenet': disgenet, 'ncbi': ncbi}

---

Phase 3: Dosage Sensitivity Assessment

Implementation

def assess_dosage_sensitivity(tu, gene_list):
    """Assess dosage sensitivity for all genes in SV."""
    dosage_data = []

    for gene_symbol in gene_list:
        # ClinGen dosage sensitivity (gold standard)
        clingen = tu.tools.ClinGen_search_dosage_sensitivity(gene=gene_symbol)
        hi_score, ts_score = None, None
        if clingen.get('data'):
            for entry in clingen['data']:
                hi_score = entry.get('Haploinsufficiency Score')
                ts_score = entry.get('Triplosensitivity Score')
                break

        # ClinGen gene validity
        validity = tu.tools.ClinGen_search_gene_validity(gene=gene_symbol)
        validity_level = None
        if validity.get('data'):
            for entry in validity['data']:
                validity_level = entry.get('Classification')
                break

        # OMIM inheritance pattern
        omim = tu.tools.OMIM_search(operation="search", query=gene_symbol, limit=3)

        dosage_data.append({
            'gene': gene_symbol,
            'hi_score': hi_score,
            'ts_score': ts_score,
            'validity_level': validity_level,
            'is_dosage_sensitive': (hi_score == '3' or ts_score == '3'),
        })

    return dosage_data

---

Phase 4: Population Frequency Assessment

Implementation

def assess_population_frequency(tu, chrom, sv_start, sv_end, sv_type):
    """Check population databases for overlapping SVs."""
    # ClinVar for known pathogenic/benign SVs
    clinvar = tu.tools.ClinVar_search_variants(
        chromosome=str(chrom), start=sv_start, stop=sv_end, variant_type=sv_type.upper()
    )

    known_svs = []
    if clinvar.get('data'):
        for variant in clinvar['data']:
            known_svs.append({
                'database': 'ClinVar',
                'classification': variant.get('clinical_significance'),
                'review_status': variant.get('review_status'),
            })

    # DECIPHER for similar patient cases
    decipher_search = tu.tools.DECIPHER_search(
        query=f"chr{chrom}:{sv_start}-{sv_end}", search_type="region"
    )

    return {
        'clinvar_matches': known_svs,
        'decipher_cases': decipher_search.get('data', []),
        'frequency_interpretation': interpret_frequency(known_svs)
    }

def interpret_frequency(known_svs):
    """Interpret frequency based on ClinVar matches."""
    if any(sv['classification'] == 'Benign' for sv in known_svs):
        return {'acmg_code': 'BA1 or BS1', 'interpretation': 'Likely benign'}
    elif any(sv['classification'] == 'Pathogenic' for sv in known_svs):
        return {'acmg_code': 'PS1', 'interpretation': 'Pathogenic match found'}
    else:
        return {'acmg_code': 'PM2', 'interpretation': 'Rare, not in databases'}

---

Phase 5: Pathogenicity Scoring

Implementation

def calculate_pathogenicity_score(gene_content, dosage_data, frequency_data, clinical_data):
    """Calculate comprehensive pathogenicity score (0-10 scale)."""
    breakdown = {}

    # Gene content scoring (max 40 pts -> scaled to 4)
    gene_score = 0
    for gene in gene_content['fully_contained'] + gene_content['partially_disrupted']:
        dosage_info = next((d for d in dosage_data if d['gene'] == gene['symbol']), None)
        if dosage_info:
            if dosage_info['hi_score'] == '3': gene_score += 10
            elif dosage_info['hi_score'] == '2': gene_score += 5
            elif gene.get('omim_disease'): gene_score += 2
    breakdown['gene_content'] = min(gene_score, 40) / 40 * 4

    # Dosage sensitivity scoring (max 30 pts -> scaled to 3)
    definitive = sum(1 for d in dosage_data if d['hi_score'] == '3')
    if definitive >= 2: dosage_score = 30
    elif definitive == 1: dosage_score = 20
    else: dosage_score = sum(1 for d in dosage_data if d['hi_score'] == '2') * 5
    breakdown['dosage_sensitivity'] = min(dosage_score, 30) / 30 * 3

    # Population frequency scoring (max 20 pts -> scaled to 2)
    freq = frequency_data.get('frequency')
    if freq is None: freq_score = 20
    elif freq < 0.0001: freq_score = 10
    elif freq > 0.01: freq_score = -20
    else: freq_score = 0
    breakdown['population_frequency'] = freq_score / 20 * 2

    # Clinical evidence scoring (max 10 pts -> scaled to 1)
    if clinical_data.get('clinvar_pathogenic'): clinical_score = 10
    elif clinical_data.get('decipher_matching_phenotype'): clinical_score = 8
    elif clinical_data.get('literature_support'): clinical_score = 5
    else: clinical_score = 0
    breakdown['clinical_evidence'] = min(clinical_score, 10) / 10

    total = sum(breakdown.values())
    total = max(0, min(10, total))
    return {'total_score': round(total, 1), 'breakdown': breakdown}

---

Phase 6: Literature Search

Search Strategies

def comprehensive_literature_search(tu, genes, sv_type, phenotype):
    """Search literature for SV evidence."""
    literature = []
    for gene in genes:
        dosage_papers = tu.tools.PubMed_search_articles(
            query=f'"{gene}" AND (haploinsufficiency OR dosage sensitivity OR deletion syndrome)',
            max_results=20
        )
        case_papers = tu.tools.PubMed_search_articles(
            query=f'"{gene}" AND deletion AND {phenotype}', max_results=15
        )
        literature.append({'gene': gene, 'dosage_papers': dosage_papers, 'case_reports': case_papers})

    # DECIPHER cases
    decipher_cases = [tu.tools.DECIPHER_search(query=gene, search_type="gene") for gene in genes]

    return {'gene_literature': literature, 'decipher_cases': decipher_cases}

---

Phase 7: ACMG Classification

Implementation

def apply_acmg_criteria(gene_content, dosage_data, frequency_data, clinical_data, inheritance):
    """Apply ACMG SV criteria and calculate classification."""
    evidence = {'pathogenic': [], 'benign': []}

    # PVS1: Complete deletion of HI gene
    hi_genes = [d for d in dosage_data if d['hi_score'] == '3']
    if hi_genes and gene_content['fully_contained']:
        evidence['pathogenic'].append({'code': 'PVS1', 'strength': 'Very Strong',
            'rationale': f"Complete deletion of HI gene(s): {', '.join(g['gene'] for g in hi_genes)}"})

    # PS1: Same as known pathogenic SV
    if clinical_data.get('clinvar_pathogenic_match'):
        evidence['pathogenic'].append({'code': 'PS1', 'strength': 'Strong',
            'rationale': f">=70% overlap with ClinVar pathogenic SV"})

    # PS2: De novo with phenotype match
    if inheritance == 'de_novo' and clinical_data.get('phenotype_match'):
        evidence['pathogenic'].append({'code': 'PS2', 'strength': 'Strong',
            'rationale': "De novo with consistent phenotype"})

    # PM2: Absent from controls
    if frequency_data.get('frequency') is None or frequency_data.get('frequency') == 0:
        evidence['pathogenic'].append({'code': 'PM2', 'strength': 'Moderate',
            'rationale': "Absent from gnomAD SV and DGV"})

    # PP4: Phenotype consistent
    if clinical_data.get('phenotype_consistent'):
        evidence['pathogenic'].append({'code': 'PP4', 'strength': 'Supporting',
            'rationale': "Patient phenotype consistent with gene-disease association"})

    # BA1/BS1: Common variant
    freq = frequency_data.get('frequency', 0)
    if freq > 0.05:
        evidence['benign'].append({'code': 'BA1', 'strength': 'Stand-Alone',
            'rationale': f"Frequency {freq:.3f} too high"})
    elif freq > 0.01:
        evidence['benign'].append({'code': 'BS1', 'strength': 'Strong',
            'rationale': f"Frequency {freq:.3f} exceeds expected"})

    return {'evidence': evidence, 'classification': determine_classification(evidence)}

def determine_classification(evidence):
    """Apply ACMG classification rules."""
    path = evidence['pathogenic']
    ben = evidence['benign']

    vs = len([e for e in path if e['strength'] == 'Very Strong'])
    s_p = len([e for e in path if e['strength'] == 'Strong'])
    m_p = len([e for e in path if e['strength'] == 'Moderate'])
    sup_p = len([e for e in path if e['strength'] == 'Supporting'])
    sa_b = len([e for e in ben if e['strength'] == 'Stand-Alone'])
    s_b = len([e for e in ben if e['strength'] == 'Strong'])
    sup_b = len([e for e in ben if e['strength'] == 'Supporting'])

    if sa_b >= 1: return 'Benign'
    if s_b >= 2: return 'Benign'
    if s_b >= 1 and sup_b >= 1: return 'Likely Benign'
    if sup_b >= 2: return 'Likely Benign'
    if vs >= 1 and s_p >= 1: return 'Pathogenic'
    if s_p >= 2: return 'Pathogenic'
    if vs >= 1 and m_p >= 1: return 'Likely Pathogenic'
    if s_p >= 1 and m_p >= 2: return 'Likely Pathogenic'
    if s_p >= 1 and m_p >= 1 and sup_p >= 1: return 'Likely Pathogenic'
    if m_p >= 3: return 'Likely Pathogenic'
    return 'VUS'

SV Classification Guide: ACMG-Adapted Criteria

Reference material for structural variant pathogenicity classification using ACMG-adapted criteria.

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SV Types

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ClinGen Dosage Sensitivity Scores

pLI Score Interpretation (gnomAD)

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Population Frequency Interpretation

Reciprocal Overlap Calculation

For proper comparison, calculate reciprocal overlap between query SV and population SV:

Reciprocal Overlap = min(overlap_with_A, overlap_with_B)
where:
  overlap_with_A = (overlap length) / (SV_A length)
  overlap_with_B = (overlap length) / (SV_B length)

Threshold: >=70% reciprocal overlap = "same" SV

---

Pathogenicity Scoring (0-10 Scale)

Scoring Components

1. Gene Content (40 points max / scaled to 4):

• 10 points per dosage-sensitive gene (HI/TS score 3)
• 5 points per likely dosage-sensitive gene (score 2)
• 2 points per gene with disease association
• Cap at 40 points

2. Dosage Sensitivity Evidence (30 points max / scaled to 3):

• 30 points: Multiple genes with definitive HI/TS (score 3)
• 20 points: One gene with definitive HI/TS
• 10 points: Genes with emerging evidence (score 2)
• 5 points: Predicted haploinsufficiency (pLI >0.9)

3. Population Frequency (20 points max / scaled to 2):

• 20 points: Absent from gnomAD, DGV
• 10 points: Rare (<0.01%)
• 0 points: Common (>0.1%)
• -20 points: Very common (>1%) - likely benign

4. Clinical Evidence (10 points max / scaled to 1):

• 10 points: Matching ClinVar pathogenic SV
• 8 points: DECIPHER cases with matching phenotype
• 5 points: Literature support for gene dosage effects
• 3 points: Phenotype consistent with genes

Score to Classification Mapping

---

ACMG Evidence Codes

Pathogenic Evidence

Benign Evidence

Classification Rules

---

Evidence Grading System

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Special Scenarios

Recurrent Microdeletion Syndrome

• Check for recurrence mechanism (LCRs, NAHR)
• Look for founder effects
• Population-specific frequencies
• Incomplete penetrance and variable expressivity
• Examples: 22q11.2 deletion, 17q21.31 deletion (Koolen-De Vries)

Balanced Translocation (No Gene Disruption)

• If no genes disrupted: Likely benign (in most cases)
• Check for cryptic imbalances
• Consider position effects (rare)
• Reproductive risk (unbalanced offspring)
• Classification: Usually VUS or Likely Benign unless offspring affected

Complex Rearrangement

• Break down into component SVs
• Assess each breakpoint independently
• Look for chromothripsis pattern
• Consider cumulative gene dosage effects
• Check for DNA repair defects

Small In-Frame Deletion/Duplication

• May not cause haploinsufficiency
• Check if critical domain affected
• Look for similar variants in ClinVar
• Consider protein structural impact
• May need functional studies

---

Clinical Recommendations Framework

For Pathogenic/Likely Pathogenic SVs

For VUS

For Benign/Likely Benign

Structural Variant Analysis - Examples

Example 1: Large Deletion Disrupting Tumor Suppressor (NF1)

User Query

"Interpret this deletion: chr17:31094927-31377677 (GRCh38), 283 kb deletion including NF1 gene. Patient has café-au-lait spots and neurofibromas."

Expected Output

# Structural Variant Analysis Report: NF1 Deletion

**Generated**: 2026-02-09 | **Analyst**: ToolUniverse SV Interpreter

---

## Executive Summary

| Field | Value |
|-------|-------|
| **SV Type** | Deletion (heterozygous) |
| **Coordinates** | chr17:31094927-31377677 (GRCh38) |
| **Size** | 283 kb |
| **Gene Content** | 1 gene fully contained (NF1), 0 partially disrupted |
| **Classification** | **PATHOGENIC** ★★★ |
| **Pathogenicity Score** | 9.5 / 10 |
| **Confidence** | High (multiple lines of strong evidence) |
| **Key Finding** | Complete deletion of NF1, established haploinsufficient tumor suppressor |

**Clinical Action Required**: Genetic counseling, cascade family testing, neurofibromatosis type 1 surveillance protocol

---

## 1. SV Identity & Classification

| Property | Value |
|----------|-------|
| **SV Type** | Deletion (loss) |
| **Chromosome** | 17 |
| **Start** | 31,094,927 |
| **End** | 31,377,677 |
| **Size** | 282,750 bp (283 kb) |
| **Build** | GRCh38/hg38 |
| **Breakpoint Precision** | ±5 kb (array CGH resolution) |
| **Inheritance** | Unknown (testing recommended for parents) |
| **Detection Method** | Chromosomal microarray |

**SV Notation**: arr[GRCh38] 17q11.2(31094927_31377677)x1

*Coordinates validated against GRCh38*

---

## 2. Gene Content Analysis

### 2.1 Fully Contained Genes (Complete Dosage Effect)

| Gene | Start | End | Size | Function | Disease Association |
|------|-------|-----|------|----------|---------------------|
| **NF1** | 31,094,927 | 31,377,677 | 283 kb | RAS GTPase-activating protein | Neurofibromatosis type 1 (AD) |

**Gene Details - NF1**:
- **Full Name**: Neurofibromin 1
- **Function**: Negative regulator of RAS signaling pathway; tumor suppressor
- **Critical Domains**:
  - GTPase-activating protein (GAP) domain
  - Sec14p domain
  - Pleckstrin homology domain
- **Expression**: Ubiquitous; highest in nervous system, adrenal gland
- **OMIM Gene**: #613113
- **OMIM Disease**: Neurofibromatosis type 1 (#162200)

**Molecular Consequence**: Complete deletion of NF1 gene → haploinsufficiency → loss of RAS-GAP activity → RAS pathway hyperactivation → tumor predisposition

*Sources: `ensembl_lookup_gene`, `NCBIGene_search`, `OMIM_get_entry`*

### 2.2 Partially Disrupted Genes

**None** - Deletion breakpoints do not disrupt additional genes

### 2.3 Flanking Genes (Within 1 Mb)

| Gene | Distance | Direction | Regulatory Risk |
|------|----------|-----------|-----------------|
| SUZ12 | 800 kb | Centromeric | Low |
| ATAD5 | 650 kb | Telomeric | Low |

**Assessment**: No high-risk position effects expected. NF1 deletion fully explains phenotype.

---

## 3. Dosage Sensitivity Assessment

### 3.1 Haploinsufficient Genes (Critical for Deletions)

| Gene | ClinGen HI Score | pLI (gnomAD) | Inheritance | Disease Mechanism | Evidence |
|------|-----------------|--------------|-------------|-------------------|----------|
| **NF1** | **3 (Sufficient)** | 1.00 | Autosomal Dominant | Haploinsufficiency | ★★★ |

**ClinGen Dosage Sensitivity Details - NF1**:
- **Haploinsufficiency Score**: 3 (Sufficient evidence)
- **Evidence**:
  - Numerous whole-gene deletions reported in NF1 patients
  - Loss-of-function variants cause neurofibromatosis type 1
  - Tumor suppressor gene - one functional copy insufficient
- **Curation Date**: 2023-06-15
- **ISCA ID**: ISCA-37448

**pLI Score**: 1.00 (highest intolerance to loss-of-function)
- Indicates extreme constraint against heterozygous LoF
- Only 1.3 expected LoF variants in gnomAD vs 0 observed
- Confirms haploinsufficiency mechanism

**Gene-Disease Validity (ClinGen)**:
| Disease | Classification | MOI | Evidence |
|---------|----------------|-----|----------|
| Neurofibromatosis type 1 | **Definitive** | AD | ★★★ |

**Interpretation**: NF1 has the highest level of evidence for haploinsufficiency. Deletion of one copy is sufficient to cause neurofibromatosis type 1 with high penetrance (>95%).

*Sources: `ClinGen_search_dosage_sensitivity`, `ClinGen_search_gene_validity`, gnomAD*

### 3.2 Triplosensitive Genes

**Not applicable** - This is a deletion, not duplication. NF1 triplosensitivity is not established.

---

## 4. Population Frequency Context

### 4.1 ClinVar Matches (Known Pathogenic/Benign SVs)

**Search Strategy**: Queried ClinVar for overlapping deletions in chr17:31094927-31377677

| VCV ID | Classification | Size | Overlap | Genes | Review Status | Condition |
|--------|----------------|------|---------|-------|---------------|-----------|
| VCV000001621 | Pathogenic | 1.4 Mb | NF1 contained | NF1 + adjacent | ★★★★ Expert panel | Neurofibromatosis type 1 |
| VCV000145678 | Pathogenic | 350 kb | 100% NF1 | NF1 only | ★★★ Criteria provided | NF1 |
| VCV000234891 | Pathogenic | 180 kb | Exons 1-10 | NF1 partial | ★★ Single submitter | NF1 |

**Key Finding**: Multiple pathogenic NF1 deletions in ClinVar, ranging from partial gene deletions to larger microdeletions encompassing adjacent genes. All classified as pathogenic.

**ACMG Code**: **PS1** (Strong) - Multiple established pathogenic deletions encompass NF1

*Source: `ClinVar_search_variants`*

### 4.2 gnomAD SV Database

**Search Result**: No NF1 loss-of-function deletions found in gnomAD v4.0 (76,156 genomes)

**Interpretation**:
- Complete absence from large population database supports pathogenicity
- NF1 LoF variants extremely rare in general population (constraint score = 1.00)
- Consistent with high disease penetrance

**ACMG Code**: **PM2** (Moderate) - Absent from population databases

*Note: gnomAD queried via browser; NF1 LoF count = 0 in 152,312 alleles*

### 4.3 DECIPHER Patient Cases

**Query**: NF1 deletion cases in DECIPHER database

**Results**: 87 patients with NF1 deletions/disruptions

**Phenotype Frequency in DECIPHER NF1 Cohort (n=87)**:

| HPO Term | Phenotype | Frequency | Patient Match |
|----------|-----------|-----------|---------------|
| HP:0007565 | Multiple café-au-lait spots | 78/87 (90%) | ✓ **Yes** |
| HP:0009732 | Plexiform neurofibroma | 45/87 (52%) | ✓ **Yes** |
| HP:0009737 | Lisch nodules (iris hamartomas) | 56/87 (64%) | Not assessed |
| HP:0000252 | Microcephaly | 23/87 (26%) | Unknown |
| HP:0001250 | Seizures | 8/87 (9%) | No |
| HP:0001263 | Developmental delay | 34/87 (39%) | Unknown |

**Phenotype Match Analysis**:
- Patient presents with café-au-lait spots (90% in DECIPHER cohort) ✓
- Patient has neurofibromas (52% in cohort) ✓
- 2/2 assessed features match NF1 phenotype

**ACMG Code**: **PP4** (Supporting) - Patient phenotype highly specific for NF1-related disorder

*Source: `ClinGen_search_dosage_sensitivity` (accessed 2026-02-09)*

---

## 5. Pathogenicity Scoring

### 5.1 Quantitative Assessment (0-10 Scale)

| Component | Points Earned | Max Points | Weight | Rationale |
|-----------|--------------|------------|--------|-----------|
| **Gene Content** | 4.0 | 4 | 40% | Complete deletion of definitive HI gene (NF1) |
| **Dosage Sensitivity** | 3.0 | 3 | 30% | ClinGen HI score 3, pLI = 1.00, definitive gene-disease |
| **Population Frequency** | 2.0 | 2 | 20% | Absent from gnomAD, extremely constrained |
| **Clinical Evidence** | 0.5 | 1 | 10% | ClinVar pathogenic matches, phenotype consistent |

**Total Pathogenicity Score**: **9.5 / 10**

**Classification**: **Pathogenic** (★★★ High Confidence)

### 5.2 Score Breakdown Visualization

Gene Content: ████████████████████████████████████████ 4.0/4 Dosage Sensitivity: ████████████████████████████████████████ 3.0/3 Population Freq: ████████████████████████████████████████ 2.0/2 Clinical Evidence: ████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0.5/1 ───────────────────────────────────────── Total Score: ████████████████████████████████████████ 9.5/10

Classification: PATHOGENIC ★★★

### 5.3 Key Drivers of Pathogenicity

1. **Complete deletion of NF1** - Established haploinsufficient tumor suppressor
2. **ClinGen definitive evidence** - HI score 3, gene-disease validity definitive
3. **Extreme LoF constraint** - pLI = 1.00, no LoF variants in 76k genomes
4. **Phenotype match** - Café-au-lait spots and neurofibromas diagnostic for NF1
5. **Population absence** - Not found in gnomAD or DGV

**Confidence Factors**:
- ✓ Gold-standard gene-disease curation (ClinGen definitive)
- ✓ Well-characterized molecular mechanism (RAS-GAP loss)
- ✓ >95% penetrance for NF1 features
- ✓ Phenotype present in patient

---

## 6. Literature & Clinical Evidence

### 6.1 Key Publications on NF1 Deletions

| Study | Design | Key Finding | PMID |
|-------|--------|-------------|------|
| Kehrer-Sawatzki et al., 2017 | Review (n=1,300) | Type-1 NF1 deletions (1.4 Mb) in 5-10% of NF1 patients | 28301757 |
| Pasmant et al., 2010 | Cohort (n=65) | Whole-gene NF1 deletions → more severe phenotype | 19862833 |
| Mautner et al., 2010 | Clinical series | NF1 microdeletions associated with earlier onset, more neurofibromas | 20513137 |
| Upadhyaya et al., 1998 | Molecular study | Identified recurrent deletion breakpoints (NF1-REP repeats) | 9806547 |

**Key Findings from Literature**:
- NF1 deletions account for 5-11% of all NF1 cases
- Type-1 deletions (1.4 Mb) mediated by nonallelic homologous recombination (NAHR) between NF1-REP repeats
- Patients with large deletions often have more severe phenotypes (earlier onset, more tumors)
- 100% penetrance for NF1 diagnostic criteria by adulthood

**ACMG Code**: **PS3_Supporting** - Well-established in literature that NF1 deletions cause NF1

*Source: `PubMed_search_articles` - query: "NF1 deletion neurofibromatosis"*

### 6.2 NF1 Molecular Mechanism (Functional Evidence)

**RAS-GAP Activity Loss**:
- NF1 encodes neurofibromin, which acts as a GTPase-activating protein (GAP) for RAS
- Neurofibromin converts active RAS-GTP → inactive RAS-GDP
- Loss of one NF1 copy → reduced RAS-GAP activity → RAS pathway hyperactivation
- Consequence: Increased cell proliferation, tumor formation, learning deficits

**Evidence Strength**: ★★★ (Definitive) - Molecular mechanism fully characterized

### 6.3 Genotype-Phenotype Correlation

**Whole-Gene Deletions vs Point Mutations**:
| Feature | Large Deletions | Point Mutations | Difference |
|---------|----------------|-----------------|------------|
| Café-au-lait spots | 95% | 99% | Similar |
| Neurofibromas | 100% | 85% | More frequent |
| Facial dysmorphism | 40% | 10% | More common in deletions |
| Cognitive impairment | 50% | 30% | Increased risk |

**Patient Implications**: Deletion patients may have more severe manifestations compared to point mutation carriers.

---

## 7. ACMG-Adapted Classification

### 7.1 Evidence Codes Applied

**Pathogenic Evidence**:

| Code | Strength | Rationale |
|------|----------|-----------|
| **PVS1** | Very Strong | Complete deletion of established haploinsufficient gene (NF1) causing loss of function |
| **PS1** | Strong | Same region as multiple known pathogenic NF1 deletions in ClinVar |
| **PM2** | Moderate | Absent from gnomAD (76,156 genomes) and DGV; extreme LoF constraint (pLI=1.0) |
| **PP4** | Supporting | Patient's phenotype (café-au-lait spots, neurofibromas) highly specific for NF1 |

**Benign Evidence**: None

### 7.2 Evidence Summary

| Category | Evidence Codes | Count |
|----------|----------------|-------|
| **Pathogenic** | PVS1, PS1, PM2, PP4 | 4 codes |
| Very Strong | PVS1 | 1 |
| Strong | PS1 | 1 |
| Moderate | PM2 | 1 |
| Supporting | PP4 | 1 |
| **Benign** | None | 0 |

### 7.3 Classification: **PATHOGENIC** ★★★

**ACMG Criteria Met**:
- 1 Very Strong (PVS1) + 1 Strong (PS1) + 1 Moderate (PM2) + 1 Supporting (PP4)
- Meets criteria: "1 Very Strong + 1 Strong" = **Pathogenic**

**Rationale**:
Complete deletion of NF1, an established haploinsufficient tumor suppressor with definitive gene-disease validity. Multiple independent lines of strong evidence support pathogenic classification. Patient phenotype consistent with neurofibromatosis type 1.

**Confidence**: ★★★ (High)
- ClinGen definitive gene-disease curation
- Well-established molecular mechanism
- Phenotype matches expected
- No conflicting evidence

### 7.4 Classification Certainty Factors

**Strengths**:
- ✓ Gold-standard curation (ClinGen HI score 3, Definitive validity)
- ✓ Complete gene deletion (unambiguous loss of function)
- ✓ Well-characterized disease (>5,000 NF1 patients documented)
- ✓ Phenotype present and specific
- ✓ No tolerance for LoF in population (pLI = 1.00)

**Limitations**:
- Breakpoint precision limited to ±5 kb (array resolution)
- Inheritance unknown (recommend parental testing)
- Penetrance incomplete for some features (e.g., optic glioma ~15%)

**Certainty**: Very high - no significant limitations affecting classification

---

## 8. Clinical Recommendations

### 8.1 For Affected Individual

| Category | Recommendation | Urgency |
|----------|----------------|---------|
| **Diagnosis Confirmation** | Molecular diagnosis confirmed; no additional testing needed | N/A |
| **Genetic Counseling** | Comprehensive genetic counseling regarding NF1, inheritance, management | **Immediate** |
| **Surveillance Protocol** | Initiate NF1 surveillance per NIH criteria (annual exams) | **Immediate** |
| **Ophthalmology** | Annual eye exams (risk of optic glioma, especially in children) | **Immediate** |
| **Neurology** | Assess for learning disabilities, ADHD; MRI if neurological symptoms | Within 3 months |
| **Dermatology** | Monitor café-au-lait spots and neurofibromas; document baseline | Within 3 months |
| **Cardiovascular** | Blood pressure monitoring (risk of renovascular hypertension) | Annual |
| **Oncology Referral** | Low-threshold imaging for any masses; risk of malignant peripheral nerve sheath tumors (MPNST) | As needed |

**NIH Diagnostic Criteria for NF1** (≥2 required):
1. ≥6 café-au-lait macules (>5mm prepubertal, >15mm postpubertal) ✓
2. ≥2 neurofibromas or 1 plexiform neurofibroma ✓
3. Freckling in axillary or inguinal regions
4. Optic glioma
5. ≥2 Lisch nodules (iris hamartomas)
6. Distinctive osseous lesion (sphenoid dysplasia, tibial pseudarthrosis)
7. First-degree relative with NF1

**Patient Status**: Meets 2/7 criteria (café-au-lait spots, neurofibromas); molecular diagnosis confirms NF1.

### 8.2 For Family Members

| Relationship | Recommendation | Priority |
|--------------|----------------|----------|
| **Parents** | Test for NF1 deletion to determine if de novo or inherited | **High** |
| **Siblings** | If parent positive, offer predictive testing; if de novo, low risk | Medium |
| **Children (current/future)** | 50% risk if inherited; 50% if patient is parent; prenatal/preimplantation testing available | High |

**Inheritance Pattern**:
- Autosomal dominant
- 50% risk to offspring if patient has children
- 50% of cases are de novo (new mutation)
- Recommend parental testing to determine if inherited or de novo

**Recurrence Risk**:
- If de novo: Low recurrence risk for siblings (<1% due to germline mosaicism)
- If inherited from parent: 50% for each sibling

### 8.3 Reproductive Considerations

| Option | Details |
|--------|---------|
| **Prenatal Testing** | Available via amniocentesis or CVS (microarray or targeted testing) |
| **Preimplantation Genetic Testing (PGT)** | Available via IVF with PGT-M for at-risk embryo selection |
| **Genetic Counseling** | Discuss reproductive options, natural history, variable expressivity |

**Key Points**:
- Variable expressivity: Some NF1 patients mildly affected, others severely
- Anticipation does NOT occur (severity not increased in next generation)
- Prenatal ultrasound cannot reliably detect NF1

---

## 9. Limitations & Uncertainties

### 9.1 Technical Limitations

| Factor | Impact | Mitigation |
|--------|--------|------------|
| **Breakpoint Precision** | ±5 kb uncertainty in exact breakpoint location | Not clinically significant; NF1 fully deleted |
| **Array Resolution** | Cannot detect balanced rearrangements or inversions | Unlikely given clear deletion; confirmatory FISH/MLPA if needed |
| **Mosaicism** | Cannot rule out low-level mosaicism | If clinical features mild, consider tissue-specific testing |

### 9.2 Clinical Uncertainties

| Factor | Uncertainty | Plan |
|--------|-------------|------|
| **Phenotype Severity** | Cannot predict exact severity (variable expressivity) | Close surveillance; manage symptoms as they arise |
| **Malignancy Risk** | 8-13% lifetime risk of malignant peripheral nerve sheath tumor (MPNST) | Low-threshold imaging for rapidly growing or painful neurofibromas |
| **Cognitive Impact** | 30-50% have learning disabilities; cannot predict for individual | Neuropsychological testing; early educational interventions |
| **Inheritance** | Unknown if de novo or inherited until parents tested | Parental testing to inform recurrence risk |

### 9.3 Knowledge Gaps

- **Genotype-phenotype correlation**: Deletion size does not perfectly predict severity
- **Modifier genes**: Other genetic factors may influence phenotype
- **Environmental factors**: Unknown modifiers of disease expression

### 9.4 Classification Certainty

**Overall Certainty**: Very High ★★★

No significant uncertainties affect the Pathogenic classification. NF1 haploinsufficiency is definitive, mechanism well-understood, and patient phenotype consistent.

---

## 10. Data Sources & Tool Usage

### 10.1 Genomic Databases

| Database | Tool | Query | Result |
|----------|------|-------|--------|
| Ensembl | `ensembl_lookup_gene` | NF1 gene coordinates | chr17:31094927-31377677 confirmed |
| NCBI Gene | `NCBIGene_search` | NF1 function | GeneID: 4763, RAS-GAP function confirmed |
| ClinVar | `ClinVar_search_variants` | chr17:31094927-31377677 DEL | 3 pathogenic matches found |
| gnomAD | Browser query | NF1 LoF variants | 0 LoF in 152,312 alleles; pLI=1.00 |

### 10.2 Clinical Databases

| Database | Tool | Query | Result |
|----------|------|-------|--------|
| ClinGen | `ClinGen_search_dosage_sensitivity` | NF1 | HI score 3 (Sufficient evidence) |
| ClinGen | `ClinGen_search_gene_validity` | NF1 - Neurofibromatosis 1 | Definitive |
| OMIM | `OMIM_search` | NF1 | Gene #613113, Disease #162200 |
| OMIM | `OMIM_get_entry` | 162200 | Neurofibromatosis type 1 details |
| DECIPHER | `ClinGen_search_dosage_sensitivity` | NF1 deletions | 87 patients, phenotype frequencies |
| DisGeNET | `DisGeNET_search_gene` | NF1 | Score 0.8 for neurofibromatosis |

### 10.3 Literature

| Database | Tool | Query | Results |
|----------|------|-------|---------|
| PubMed | `PubMed_search_articles` | "NF1 deletion neurofibromatosis" | 245 articles, top 20 reviewed |
| PubMed | `PubMed_search_articles` | "NF1 haploinsufficiency mechanism" | 78 articles |

### 10.4 Quality Control

- ✓ All genes in SV region annotated
- ✓ ClinGen dosage scores retrieved
- ✓ Population frequency assessed (gnomAD, ClinVar)
- ✓ Literature search completed (PubMed, DECIPHER)
- ✓ All ACMG codes applied with rationale
- ✓ Evidence grading assigned
- ✓ Clinical recommendations provided

---

**Report Completed**: 2026-02-09
**Analyst**: ToolUniverse Structural Variant Analysis Skill
**Classification**: PATHOGENIC ★★★
**Clinical Action**: Immediate genetic counseling and NF1 surveillance protocol

---

Example 2: Duplication of Dosage-Sensitive Gene (MECP2)

User Query

"Analyze this duplication: chrX:154021599-154137217 (GRCh38), 115 kb duplication including MECP2. Male patient with intellectual disability, seizures, and regression."

Expected Output (Key Sections)

# SV Analysis Report: MECP2 Duplication

## Executive Summary

| Field | Value |
|-------|-------|
| **SV Type** | Duplication (hemizygous in male) |
| **Coordinates** | chrX:154021599-154137217 (GRCh38) |
| **Size** | 115 kb |
| **Gene Content** | MECP2, IRAK1 (fully contained) |
| **Classification** | **PATHOGENIC** ★★★ |
| **Pathogenicity Score** | 9.0 / 10 |
| **Key Finding** | MECP2 duplication syndrome in hemizygous male |

---

## 3. Dosage Sensitivity Assessment

### 3.1 Triplosensitive Genes (Critical for Duplications)

| Gene | ClinGen TS Score | pLI | Disease | Mechanism | Evidence |
|------|-----------------|-----|---------|-----------|----------|
| **MECP2** | **3 (Sufficient)** | 0.96 | MECP2 duplication syndrome | Triplosensitivity | ★★★ |
| IRAK1 | 0 (No evidence) | 0.31 | None established | N/A | ★☆☆ |

**MECP2 Dosage Sensitivity**:
- **Triplosensitivity Score**: 3 (Definitive evidence)
- **Mechanism**: MECP2 encodes methyl-CpG-binding protein 2, critical for neuronal function
- **Dosage Effect**: Extra copy in males → overexpression → severe neurodevelopmental disorder
- **Gene-Disease Validity**: Definitive (ClinGen)

**Why Triplosensitivity Matters**:
- MECP2 expression is tightly regulated; dosage-critical
- Loss of function → Rett syndrome (females)
- Gain of function → MECP2 duplication syndrome (males)
- Goldilocks gene: "just right" dosage required

*Sources: `ClinGen_search_dosage_sensitivity`, `ClinGen_search_gene_validity`*

---

## 5. Pathogenicity Scoring

**Total Score**: 9.0 / 10

| Component | Points | Rationale |
|-----------|--------|-----------|
| Gene Content | 4.0/4 | MECP2 TS score 3 (definitive triplosensitive) |
| Dosage Sensitivity | 3.0/3 | Established triplosensitivity with clear mechanism |
| Population Frequency | 2.0/2 | Absent from gnomAD; not found in healthy males |
| Clinical Evidence | 0.0/1 | Phenotype consistent (pending detailed assessment) |

**Classification**: PATHOGENIC (★★★)

---

## 7. ACMG Classification

**Pathogenic Evidence**:
| Code | Strength | Rationale |
|------|----------|-----------|
| **PVS1** | Very Strong | Complete duplication of triplosensitive gene (MECP2) in hemizygous male |
| **PS1** | Strong | Multiple pathogenic MECP2 duplications in ClinVar |
| **PM2** | Moderate | Absent from male population in gnomAD |
| **PP4** | Supporting | Male with ID, seizures, regression typical for MECP2 duplication syndrome |

**Classification**: **PATHOGENIC** (PVS1 + PS1 meets criteria)

**Sex-Specific Considerations**:
- Males hemizygous (one X chromosome) → more severe phenotype
- Females heterozygous → may be asymptomatic or mildly affected (X-inactivation)
- This patient is male → full MECP2 duplication syndrome expected

---

## 8. Clinical Recommendations

**For Patient** (Male with MECP2 duplication):
- Diagnosis: MECP2 duplication syndrome confirmed
- Neurology: Manage seizures aggressively (often drug-resistant)
- Pulmonology: Monitor for respiratory infections (high risk)
- Gastroenterology: Assess for constipation, GERD
- Infectious disease: Increased susceptibility to infections
- Physical therapy: Address hypotonia, motor delays
- Special education: Severe-to-profound intellectual disability expected

**For Family**:
- Mother: MUST be tested - likely carrier (90% inherited maternally)
- If mother is carrier: 50% risk to male offspring, variable risk to females
- If mother is NOT carrier: De novo in patient; low recurrence risk
- Future pregnancies: Prenatal testing available

**Prognosis**:
- Life expectancy: Often reduced (median survival unclear; serious infections common)
- Developmental: Severe ID, most non-verbal
- Medical complexity: High (seizures, infections, GI issues)

---

Example 3: Balanced Translocation (No Gene Disruption)

User Query

"Interpret balanced translocation t(2;11)(p16.3;q23.3) in healthy adult with recurrent miscarriages. Breakpoints: chr2:50,234,567 and chr11:118,345,234. No genes disrupted."

Expected Output (Key Sections)

# SV Analysis Report: Balanced Translocation t(2;11)

## Executive Summary

| Field | Value |
|-------|-------|
| **SV Type** | Balanced reciprocal translocation |
| **Breakpoints** | chr2:50,234,567; chr11:118,345,234 |
| **Size** | N/A (balanced rearrangement) |
| **Gene Content** | 0 genes disrupted |
| **Classification** | **LIKELY BENIGN** ★★☆ (for carrier health) |
| **Reproductive Risk** | High (unbalanced offspring) |
| **Key Finding** | Balanced translocation, no dosage imbalance, explains recurrent pregnancy loss |

---

## 2. Gene Content Analysis

### 2.1 Breakpoint Analysis

**Chromosome 2 Breakpoint** (2p16.3 - 50,234,567):
- **Location**: Intergenic region
- **Nearest genes**:
  - NRXN1 (500 kb downstream) - neurexin gene
  - Regulatory desert region
- **No gene disruption**

**Chromosome 11 Breakpoint** (11q23.3 - 118,345,234):
- **Location**: Intergenic region
- **Nearest genes**:
  - LARGE1 (350 kb upstream) - glycosyltransferase
  - No coding genes within 1 Mb
- **No gene disruption**

**Critical Finding**: Both breakpoints fall in gene-desert regions. No protein-coding genes are disrupted.

---

## 3. Dosage Sensitivity Assessment

**N/A** - Balanced translocation maintains normal gene dosage (2 copies of all genes).

---

## 5. Pathogenicity Scoring

**Total Score**: 2.0 / 10 (Likely Benign range)

| Component | Points | Rationale |
|-----------|--------|-----------|
| Gene Content | 0.0/4 | No genes disrupted or affected by dosage |
| Dosage Sensitivity | 0.0/3 | Balanced rearrangement; normal copy number |
| Population Frequency | 1.0/2 | Balanced translocations occur in ~1/500 population |
| Clinical Evidence | 1.0/1 | Carrier is healthy; no phenotype |

**Classification for Carrier Health**: **LIKELY BENIGN** (★★☆)

**Note**: Although benign for the carrier, this translocation poses HIGH REPRODUCTIVE RISK due to unbalanced segregation in offspring.

---

## 7. ACMG Classification

**For Carrier Phenotype**:

**Benign Evidence**:
| Code | Strength | Rationale |
|------|----------|-----------|
| **BP5** | Supporting | Carrier is healthy adult with no features of genetic disorder |
| **BP4** | Supporting | No genes disrupted; no predicted haploinsufficiency |

**Classification**: **LIKELY BENIGN** for carrier health ★★☆

**However - Reproductive Risk Assessment**:
- Balanced translocation carriers are typically healthy
- Risk for UNBALANCED offspring with duplications/deletions: 5-30%
- Explains recurrent miscarriages (likely due to unbalanced conceptions)

---

## 8. Clinical Recommendations

### 8.1 For Carrier (Patient)

| Category | Recommendation |
|----------|----------------|
| **Carrier Health** | No medical surveillance needed; translocation benign for carrier |
| **Genetic Counseling** | Comprehensive reproductive counseling **ESSENTIAL** |
| **Pregnancy Management** | Prenatal diagnosis (amniocentesis/CVS) recommended for ALL pregnancies |
| **Family Planning** | Consider preimplantation genetic testing (PGT-SR) via IVF |

### 8.2 Reproductive Risk Assessment

**Segregation Outcomes** (theoretical):
1. **Balanced (normal or translocation carrier)**: 50% - Healthy
2. **Unbalanced (partial trisomy/monosomy)**: 50% - Usually nonviable or severe

**Empiric Risks**:
- Miscarriage risk: 25-50% (higher than general population)
- Unbalanced live birth: 5-10% (varies by breakpoint locations)
- Balanced carrier offspring: ~25% (healthy like parent)
- Normal (non-carrier) offspring: ~25%

**Recommendations**:
1. **Prenatal Diagnosis**: Amniocentesis or CVS with karyotype + microarray
2. **Preimplantation Genetic Testing (PGT-SR)**: IVF with embryo testing
   - Test embryos for balanced vs unbalanced translocations
   - Transfer only balanced/normal embryos
   - Success rate: 40-60% per cycle
3. **Partner Testing**: Partner should have normal karyotype (already confirmed)

### 8.3 For Family Members

| Relationship | Recommendation |
|--------------|----------------|
| **Parents** | Karyotype testing to determine if inherited or de novo |
| **Siblings** | If parent positive → 50% risk; offer testing if planning pregnancy |
| **Children** | If patient has balanced carrier children → test before they reproduce |

**Inheritance Pattern**:
- If inherited: 50% of siblings may also be carriers
- If de novo: Low risk to siblings

---

## 9. Explanation of Recurrent Miscarriages

**Mechanism**:

During meiosis (egg/sperm formation), chromosomes pair up. With balanced translocation:
- Normal pairing disrupted
- Multiple segregation outcomes possible
- ~50% of gametes carry unbalanced chromosome complement

**Unbalanced Conceptions**:
- Partial trisomy 2p + monosomy 11q
- Partial trisomy 11q + monosomy 2p
- Other imbalances
- Most result in early miscarriage (embryonic lethality)
- Rarely, live birth with severe congenital anomalies

**Patient's Miscarriages**:
- Likely due to unbalanced conceptions
- Not due to other maternal factors
- Recurrence risk remains high (~25-50% per pregnancy) without intervention

**Recommendations**:
- PGT-SR (preimplantation genetic testing) offers best chance for healthy baby
- Prenatal diagnosis in natural pregnancies
- Genetic counseling for informed decision-making

---

Example 4: Complex Rearrangement (Multiple SVs)

User Query

"Patient has complex rearrangement on chromosome 17: deletion 17q12 (1.4 Mb), inversion 17q21.31 (500 kb), duplication 17q23.3 (200 kb). How do I interpret this?"

Expected Output (Key Sections)

# SV Analysis Report: Complex Chr17 Rearrangement

## Executive Summary

| Field | Value |
|-------|-------|
| **SV Type** | Complex rearrangement (deletion + inversion + duplication) |
| **Chromosome** | 17 |
| **Total Affected** | ~2.1 Mb across 3 regions |
| **Gene Content** | 15 genes affected (7 deleted, 3 inverted, 5 duplicated) |
| **Classification** | **PATHOGENIC** ★★★ |
| **Pathogenicity Score** | 8.5 / 10 |
| **Key Finding** | Deletion includes HNF1B (17q12 deletion syndrome); additional complexity worsens prognosis |

---

## 1. SV Identity & Classification

**Component SVs**:

| SV# | Type | Region | Coordinates | Size | Genes Affected |
|-----|------|--------|-------------|------|----------------|
| SV1 | Deletion | 17q12 | chr17:36,000,000-37,400,000 | 1.4 Mb | HNF1B, LHX1, ACACA, + 4 others (7 genes) |
| SV2 | Inversion | 17q21.31 | chr17:43,500,000-44,000,000 | 500 kb | MAPT, KANSL1, + 1 other (3 genes) |
| SV3 | Duplication | 17q23.3 | chr17:61,000,000-61,200,000 | 200 kb | BRCA1 partial, + 4 others (5 genes) |

**Classification**: **Complex genomic rearrangement** - likely chromothripsis or multiple-event rearrangement

---

## 2. Gene Content Analysis (Aggregated)

### 2.1 Deleted Genes (SV1 - 17q12 deletion)

| Gene | Function | Dosage Sensitivity | Disease Association |
|------|----------|-------------------|---------------------|
| **HNF1B** | Transcription factor | HI score 3 | RCAD syndrome (renal cysts, diabetes) |
| **LHX1** | Transcription factor | HI score 2 | Developmental defects |
| ACACA | Fatty acid synthesis | Low | Obesity (rare) |

**Primary Pathogenic Driver**: HNF1B deletion → 17q12 deletion syndrome

### 2.2 Inverted Genes (SV2 - 17q21.31 inversion)

| Gene | Disruption Status | Effect |
|------|------------------|--------|
| MAPT | Breakpoint in intron 3 | Likely loss-of-function |
| KANSL1 | Intact (inverted orientation) | Position effect possible |

**Effect**: MAPT disrupted (but MAPT haploinsufficiency not established); KANSL1 orientation change (uncertain effect)

### 2.3 Duplicated Genes (SV3 - 17q23.3 duplication)

| Gene | Duplication Extent | TS Evidence | Effect |
|------|-------------------|-------------|--------|
| BRCA1 | Exons 1-8 only | No TS | Partial duplication; unclear effect |
| Other genes | Full duplication | No TS for any | Unknown significance |

**Effect**: Uncertain - no established triplosensitivity for these genes

---

## 5. Pathogenicity Scoring

**Total Score**: 8.5 / 10

| Component | Points | Rationale |
|-----------|--------|-----------|
| Gene Content | 3.5/4 | HNF1B deletion (HI score 3); MAPT disruption (unclear significance) |
| Dosage Sensitivity | 2.5/3 | One definitive HI gene; others uncertain |
| Population Frequency | 2.0/2 | Complex rearrangement extremely rare; not in gnomAD |
| Clinical Evidence | 0.5/1 | 17q12 deletion known pathogenic; rest uncertain |

**Classification**: **PATHOGENIC** - driven primarily by 17q12 deletion (HNF1B)

---

## 7. ACMG Classification

**Evidence Codes**:

| Code | Strength | Rationale |
|------|----------|-----------|
| **PVS1** | Very Strong | Complete deletion of HNF1B (HI score 3) |
| **PM2** | Moderate | Complex rearrangement not in population databases |
| **PP3** | Supporting | Multiple gene disruptions compound pathogenicity |

**Classification**: **PATHOGENIC** (PVS1 sufficient for reclassification with supporting evidence)

**Additional Complexity**:
- Inversion and duplication add uncertainty
- May contribute to more severe or atypical phenotype
- Reclassification may be needed as patient phenotype evolves

---

## 8. Clinical Recommendations

**For Patient**:

**Primary Diagnosis**: 17q12 deletion syndrome (due to HNF1B deletion)

**Expected Features**:
1. **Renal**: Cysts, malformations (80-90% of cases)
2. **Diabetes**: MODY5 (maturity-onset diabetes of the young) - onset teens to 30s
3. **Developmental**: Mild ID or learning disabilities (30%)
4. **Other**: Genital anomalies, pancreatic hypoplasia

**Additional Considerations** (due to complex rearrangement):
- Phenotype may be atypical or more severe
- MAPT disruption: Monitor for neurological symptoms (though MAPT haploinsufficiency rare)
- BRCA1 partial duplication: Uncertain effect; not expected to affect cancer risk

**Recommended Surveillance**:
1. **Renal ultrasound** - baseline and periodic monitoring
2. **Glucose monitoring** - screen for diabetes starting age 10
3. **Developmental assessment** - neuropsychological testing
4. **Genetic counseling** - discuss complex rearrangement, recurrence risk

**Recurrence Risk**:
- Likely de novo (complex rearrangements usually sporadic)
- Low recurrence risk for parents' future pregnancies (<1%)
- 50% risk to patient's offspring (if complex rearrangement transmissible)
- Parental testing recommended

---

## 9. Interpretation Challenges

**Challenges with Complex Rearrangements**:
1. **Mechanism unclear**: Chromothripsis? Multiple events? Timing?
2. **Additive effects**: Do multiple SVs compound pathogenicity?
3. **Inversion significance**: Position effects hard to predict
4. **Partial duplication**: BRCA1 exons 1-8 only - gain or loss of function?

**Approach**:
- Prioritize known pathogenic SV (17q12 deletion)
- Consider other SVs as modifiers of phenotype
- Phenotype-first interpretation (let clinical features guide)
- Reclassify as more data emerges

**Recommendation**: Consider research enrollment to characterize this rare complex rearrangement.

---

Example 5: Common Benign CNV (15q11.2 BP1-BP2 Microdeletion)

User Query

"My patient has a 500 kb deletion at 15q11.2 (BP1-BP2 region) including NIPA1 and CYFIP1. Is this pathogenic?"

Expected Output (Key Sections)

# SV Analysis Report: 15q11.2 BP1-BP2 Microdeletion

## Executive Summary

| Field | Value |
|-------|-------|
| **SV Type** | Deletion |
| **Coordinates** | chr15:22,770,421-23,282,798 (GRCh38) |
| **Size** | 512 kb |
| **Region** | 15q11.2 BP1-BP2 |
| **Gene Content** | NIPA1, NIPA2, CYFIP1, TUBGCP5 |
| **Classification** | **VUS** ★☆☆ |
| **Pathogenicity Score** | 5.0 / 10 (Uncertain range) |
| **Key Finding** | Recurrent microdeletion with unclear pathogenicity; seen in 1% of population but enriched in neurodevelopmental disorders |

---

## 2. Gene Content Analysis

| Gene | Function | Dosage Sensitivity | Disease Association |
|------|----------|-------------------|---------------------|
| CYFIP1 | Cytoskeleton regulation, FMRP interactor | HI score 1 (Little evidence) | Autism, ID (uncertain) |
| NIPA1 | Magnesium transporter | HI score 0 | Spastic paraplegia (AR, not deletion) |
| NIPA2 | Magnesium transporter | HI score 0 | None established |
| TUBGCP5 | Microtubule complex | HI score 0 | None established |

**Key Gene: CYFIP1**
- Interacts with fragile X mental retardation protein (FMRP)
- Haploinsufficiency proposed but NOT definitive
- ClinGen HI score: 1 (Little evidence)

---

## 4. Population Frequency Context

### 4.1 gnomAD SV Database

**Frequency**: ~1% (1 in 100 individuals)
- Found in 750+ individuals in gnomAD v4.0 (76,156 genomes)
- Present in healthy controls without neurodevelopmental disorders

**ACMG Code**: Does NOT meet BA1 (>5%) but frequency is high

### 4.2 ClinVar Matches

| VCV ID | Classification | Review Status |
|--------|----------------|---------------|
| VCV000004267 | **VUS** | ★★ Criteria provided, multiple submitters |
| VCV000145982 | **Uncertain significance** | ★★ |

**No consensus pathogenic classification** in ClinVar.

### 4.3 Clinical Literature

**Key Studies**:
1. **Burnside et al., 2011 (PMID: 21841781)**:
   - 15q11.2 deletion found in 1.27% of cases vs 0.72% of controls
   - Odds ratio: 1.77 (modest enrichment)
   - Associated with variable neurodevelopmental phenotypes

2. **Cox & Butler, 2015 (PMID: 25849863)**:
   - Phenotype highly variable: 20-30% with developmental delay
   - But also found in 1% of healthy individuals
   - Incomplete penetrance and variable expressivity

**Interpretation**:
- Modest enrichment in neurodevelopmental disorders
- BUT also common in healthy population
- Suggests susceptibility locus, not Mendelian pathogenic variant

---

## 5. Pathogenicity Scoring

**Total Score**: 5.0 / 10 (VUS range)

| Component | Points | Rationale |
|-----------|--------|-----------|
| Gene Content | 1.5/4 | CYFIP1 haploinsufficiency uncertain; no definitive HI genes |
| Dosage Sensitivity | 0.5/3 | ClinGen HI scores all 0-1; limited evidence |
| Population Frequency | -1.0/2 | Found in 1% of population (too common for high penetrance) |
| Clinical Evidence | 1.0/1 | If patient has neurodevelopmental features, modest support |

**Classification**: **VUS** (Variant of Uncertain Significance)

---

## 7. ACMG Classification

**Pathogenic Evidence**:
| Code | Strength | Rationale |
|------|----------|-----------|
| **PM2** | Moderate → Downgraded to Supporting | Present but rare (1%); not definitive rarity |
| **PP3** | NOT applied | No strong computational predictions for haploinsufficiency |

**Benign Evidence**:
| Code | Strength | Rationale |
|------|----------|-----------|
| **BS1** | NOT applied | 1% is high but not >5% (BA1 threshold) |
| **BP2** | Supporting | Seen in healthy individuals in gnomAD |

**Evidence Summary**:
- 1 Supporting pathogenic (downgraded PM2)
- 1 Supporting benign (BP2)
- **Conflicting / Insufficient evidence**

**Classification**: **VUS** (Variant of Uncertain Significance) ★☆☆

**Rationale**:
- Insufficient evidence for Likely Pathogenic (would need gene-disease definitive curation + rarity)
- Insufficient evidence for Likely Benign (found in neurodevelopmental cases at higher rate than controls)
- High population frequency (1%) argues against high-penetrance pathogenic variant
- Variable phenotype and incomplete penetrance consistent with susceptibility factor

---

## 8. Clinical Recommendations

### 8.1 For Patient

**DO NOT use this finding to make clinical decisions**

| Category | Recommendation |
|----------|----------------|
| **Diagnosis** | 15q11.2 BP1-BP2 deletion is **VUS**; cannot confirm/rule out genetic diagnosis |
| **Clinical Management** | Manage phenotype based on symptoms, NOT genotype |
| **Additional Testing** | Consider: <br>- Exome sequencing (look for second hit)<br>- Array on parents (determine inheritance) |
| **Genetic Counseling** | Discuss uncertainty, variable expressivity, population frequency |

**Key Points**:
- **Not diagnostic** of specific genetic condition
- May be **susceptibility factor** (modest effect)
- Also found in **healthy individuals** (1%)
- Cannot predict if patient's features caused by deletion or other factors

### 8.2 Interpretation Based on Inheritance

**If Deletion is De Novo**:
- Slightly higher likelihood of contributing to phenotype
- But still found in 0.7% of healthy controls, so not definitive
- Consider: PP1_Supporting (de novo)

**If Deletion is Inherited from Healthy Parent**:
- Argues against high-penetrance pathogenic variant
- More consistent with benign or low-penetrance susceptibility
- Consider: BS2_Supporting (inherited from healthy parent)

**Recommendation**: Test parents to determine inheritance

### 8.3 Family Counseling

- **If inherited from healthy parent**: Low likelihood of pathogenicity; reassure family
- **If de novo**: Slightly higher concern, but still uncertain
- **Recurrence risk**:
  - If inherited: 50% to siblings (but may be asymptomatic)
  - If de novo: Low (<1%) recurrence risk

### 8.4 Reclassification Potential

**This VUS may be reclassified if**:
1. **New evidence**: ClinGen revises CYFIP1 haploinsufficiency score
2. **Large studies**: Meta-analysis definitively associates 15q11.2 with disorder
3. **Functional studies**: CYFIP1 dosage sensitivity proven in models
4. **Phenotype evolution**: Patient develops features strongly linked to 15q11.2

**Recommendation**: Reanalyze in 2-3 years or if phenotype changes

---

## 9. Scientific Controversy: 15q11.2 BP1-BP2 Deletion

**Why is this controversial?**

1. **Population frequency**: 1% is high for a pathogenic variant
2. **Incomplete penetrance**: 70-80% of carriers are healthy
3. **Variable expressivity**: When phenotype present, highly variable
4. **Modest effect size**: OR ~1.8 in case-control studies (weak association)

**Competing Models**:
- **Model 1**: Benign variant (incidental finding, no causation)
- **Model 2**: Susceptibility locus (contributes risk in polygenic model)
- **Model 3**: Pathogenic with low penetrance (20-30%)

**Current Consensus**: VUS pending further evidence

**Implication for Patient**:
- May contribute to phenotype in combination with other factors
- Alone, insufficient to explain clinical features
- Continue phenotype-based diagnostic workup

---

## 10. Comparison: VUS vs Pathogenic SVs

**What makes an SV Pathogenic?** (for contrast)

| Feature | 15q11.2 BP1-BP2 (VUS) | 17q21.31 KANSL1 DEL (Pathogenic) |
|---------|----------------------|----------------------------------|
| **Gene HI Score** | 0-1 (Little evidence) | 3 (Definitive) |
| **Population Freq** | 1% | <0.01% |
| **Penetrance** | 20-30% | >95% |
| **ClinVar** | VUS | Pathogenic (expert panel) |
| **Clinical** | Variable, nonspecific | Specific syndrome |

**Take-Home**: 15q11.2 BP1-BP2 lacks definitive evidence required for Pathogenic classification.

---

**Report Completed**: 2026-02-09
**Classification**: VUS ★☆☆
**Clinical Action**: Manage based on phenotype; do not use deletion for diagnosis
**Reclassification**: Reanalyze in 2-3 years

---

Summary of Examples

Key Principles Illustrated: 1. Dosage sensitivity is critical - HI/TS scores drive classification 2. Population frequency matters - Common CNVs (>1%) unlikely to be highly penetrant pathogenic variants 3. Balanced translocations - Benign for carrier but reproductive risk 4. Complex SVs - Break down into components; identify primary driver 5. VUS requires humility - Don't over-interpret; manage phenotype, not genotype

SV Analysis Report Template

Use this template when generating SV_analysis_report.md files. Create the report first, then populate progressively as each phase completes.

File Naming Convention

SV_analysis_[TYPE]_chr[CHR]_[START]_[END]_[GENES].md

Examples:
SV_analysis_DEL_chr17_44039927_44352659_KANSL1_MAPT.md
SV_analysis_DUP_chr22_17400000_17800000_TBX1.md
SV_analysis_INV_chr11_2100000_2400000_complex.md

---

Report Template

# Structural Variant Analysis Report: [SV_IDENTIFIER]

**Generated**: [Date] | **Analyst**: ToolUniverse SV Interpreter

---

## Executive Summary

| Field | Value |
|-------|-------|
| **SV Type** | Deletion / Duplication / Inversion / Translocation |
| **Coordinates** | chr_:________-________ (GRCh38) |
| **Size** | ___ kb |
| **Gene Content** | X genes fully contained, Y partially disrupted |
| **Classification** | Pathogenic / Likely Pathogenic / VUS / Likely Benign / Benign |
| **Pathogenicity Score** | X.X / 10 |
| **Confidence** | High / Moderate / Limited |
| **Key Finding** | [One-sentence summary] |

**Clinical Action**: [Required / Recommended / None]

---

## 1. SV Identity & Classification

{SV type, coordinates, size, breakpoint precision, inheritance}

---

## 2. Gene Content Analysis

### 2.1 Fully Contained Genes

| Gene | Function | Disease Association | Inheritance | Evidence |
|------|----------|---------------------|-------------|----------|
| | | | | |

**Interpretation**: [Summary of dosage effect for contained genes]

*Sources: OMIM, DisGeNET, Ensembl*

### 2.2 Partially Disrupted Genes

| Gene | Breakpoint Location | Effect | Critical Domains Lost |
|------|-------------------|--------|----------------------|
| | | | |

**Interpretation**: [Impact of breakpoint on gene function]

### 2.3 Flanking Genes (Potential Position Effects)

| Gene | Distance from SV | Regulatory Risk | Evidence |
|------|------------------|-----------------|----------|
| | | | |

---

## 3. Dosage Sensitivity Assessment

### 3.1 Haploinsufficient Genes (Deletions/Disruptions)

| Gene | ClinGen HI Score | pLI | Validity | Disease | Evidence |
|------|-----------------|-----|----------|---------|----------|
| | | | | | |

### 3.2 Triplosensitive Genes (Duplications)

| Gene | ClinGen TS Score | Disease Mechanism | Evidence |
|------|-----------------|-------------------|----------|
| | | | |

### 3.3 Non-Dosage-Sensitive Genes

| Gene | HI Score | TS Score | Interpretation |
|------|----------|----------|----------------|
| | | | |

---

## 4. Population Frequency Context

### 4.1 ClinVar Matches (Overlapping SVs)

| VCV ID | Classification | Size | Overlap | Review Status | Genes |
|--------|----------------|------|---------|---------------|-------|
| | | | | | |

**ACMG Code**: [PS1 / PM2 / BA1 / BS1]

### 4.2 gnomAD SV Database

**Search Result**: [Frequency or absent]

### 4.3 DECIPHER Patient Cases

| Case ID | Phenotype | SV Type | Size | Overlap | Similarity |
|---------|-----------|---------|------|---------|------------|
| | | | | | |

---

## 5. Pathogenicity Scoring

### 5.1 Quantitative Assessment (0-10 Scale)

| Component | Points | Max | Contribution | Rationale |
|-----------|--------|-----|-------------|-----------|
| **Gene Content** | | 4 | 40% | |
| **Dosage Sensitivity** | | 3 | 30% | |
| **Population Frequency** | | 2 | 20% | |
| **Clinical Evidence** | | 1 | 10% | |
| **Total Score** | **X.X** | 10 | 100% | |

**Classification**: [Classification] ([Confidence])

---

## 6. Literature & Clinical Evidence

### 6.1 Key Publications

| Study | Finding | Evidence Type | PMID |
|-------|---------|---------------|------|
| | | | |

### 6.2 DECIPHER Cohort Analysis

| Feature | Frequency | Match to Patient |
|---------|-----------|------------------|
| | | |

### 6.3 Functional Evidence

| Study | Model | Finding | PMID |
|-------|-------|---------|------|
| | | | |

---

## 7. ACMG-Adapted Classification

### 7.1 Evidence Codes Applied

**Pathogenic Evidence**:

| Code | Strength | Rationale |
|------|----------|-----------|
| | | |

**Benign Evidence**:

| Code | Strength | Rationale |
|------|----------|-----------|
| | | |

### 7.2 Evidence Summary

| Pathogenic | Benign |
|------------|--------|
| | |

### 7.3 Classification: **[CLASSIFICATION]** [Confidence]

**Rationale**: [Why this classification was reached]

### 7.4 Certainty Factors

**Strengths**: [What supports the classification]

**Limitations**: [What could change the classification]

---

## 8. Clinical Recommendations

### 8.1 For Affected Individual
{Testing, management, surveillance}

### 8.2 For Family Members
{Cascade testing, genetic counseling}

### 8.3 Reproductive Considerations
{Recurrence risk, prenatal testing}

---

## 9. Limitations & Uncertainties

{Missing data, conflicting evidence, knowledge gaps}

---

## Data Sources

{All tools and databases queried with results}