--- name: target-validation-ladder description: > Grade the human-genetic validation of a drug target on a causality-ranked evidence ladder (Mendelian/rare-variant > coding GWAS+colocalization > Mendelian randomization > non-coding GWAS), scoring direction-of-effect concordance, tractability, and on-target safety read-across. Produces a 0-13 composite tier from Open Targets, the Genetic Priority Score, gnomAD constraint, and a cis-MR/PheWAS scan. Activate when assessing whether a target hypothesis is genetically supported, before mechanism-risk or PoS modeling, when screening an early-discovery asset, or when learning what separates a PCSK9-class target from a hopeful GWAS hit. metadata: author: nirav version: "1.0" parent: modality-trajectory compatibility: Designed for Claude Code allowed-tools: Read --- # Target Validation Ladder — Grading the Human-Genetics Prior Target choice is the highest-leverage decision in drug development: roughly 90% of clinical programs fail, and the largest share of Phase II/III failures is lack of efficacy — the *target hypothesis was wrong*, not the molecule. Human genetics is the only widely-validated tool that shifts the prior on efficacy *before* any clinical data exist, because a genetic variant is a natural, lifelong, randomized perturbation of the target in humans. Targets with genetic support have ~2.6x higher relative success across the pipeline (Minikel, Painter, Dong & Nelson, *Nature* 629:624, 2024), refining the original ~2x estimate (Nelson et al., *Nature Genetics* 2015). The headline 2.6x is an average that hides the structure. The multiplier concentrates where two things hold: (1) the **causal gene** at the locus is unambiguous, and (2) the **genetic direction of effect** matches the drug's intended direction. Predictive power is *flat* across genetic effect size, minor allele frequency, and year of discovery (Minikel 2024) — so a clean common-variant signal can be as informative as a rare large-effect one, provided causality is established. A program citing "GWAS support" without naming the causal gene and stating a concordant direction is claiming far less than it sounds. This skill turns that into a gradeable rubric. It is the **earliest-stage** validation check in the suite — it asks "does the human evidence say this target matters, in the right direction, with confidence in the gene?" before any clinical asset exists, then hands the graded prior forward to `probability-of-success/mechanism-risk-adjuster`, which converts it into a phase-weighted PoS multiplier. The #1 failure mode it exists to prevent: **crediting the wrong gene at a locus** (~90% of GWAS hits are non-coding; the nearest gene is often not causal). ## How to Run ### Input | Parameter | Source | Required? | |---|---|---| | Target gene (HGNC symbol) | User | Yes | | Indication / disease | User | Yes | | Intended mechanism direction (inhibit / degrade / agonize / replace) | User | Recommended | | Intended modality (small molecule / antibody / PROTAC / oligo / gene therapy) | User | Recommended (default: score all) | | Ancestry / cohort caveats | User | Optional | ### Steps > **Grading corpus:** Grade a candidate by its nearest analog in `references/validated-target-library.md` — 9+ primary-sourced targets (PCSK9, HMGCR, NPC1L1, ASGR1, Lp(a), TYK2, TL1A, TREM2, LRRK2…) with evidence type, effect direction, drug outcome, and tier, plus the ladder-calibration multipliers (Nelson 2× → Minikel 2.6×, OMIM RS 3.7, Open Targets dose-response) and a genetics-vs-clinical divergence watch. #### Step 1 — Pull the genetics-only association and the pre-computed rank Establish the prior before grading by hand: - **Open Targets Platform** (platform.opentargets.org / Open Targets MCP): pull the target-disease association. Use the 2025 "Associations on the Fly" weighting to **zero out non-genetic data sources** and read a *genetics-only* score — non-genetic evidence (literature, pathways) inflates the headline and is not what predicts approval. - **Genetic Priority Score** (Mount Sinai / Do lab portal): look up the GPS and GPS-with-direction for the gene × indication (19,365 genes × 399 indications). Anchor: the **top 0.28% of GPS conferred ~9.9x odds** of being a valid indication and were **1.7 / 3.7 / 8.8x** more likely to advance Phase I→II / III / IV (Duffy/Do, *Nature Genetics* 56:51, 2024). These two reads give a fast prior. The rest of the workflow confirms *why* the score is what it is — never trust the number without auditing the causal gene and direction. #### Step 2 — Place the evidence on the causality ladder (Axis 1) The ladder is ordered by **causal-gene confidence**, not statistical significance. Climb to the highest tier the evidence supports: ``` EVIDENCE LADDER (highest causal confidence → lowest) Tier A Mendelian / rare-variant burden → OMIM, ClinVar, gene-collapsing The variant IS the gene; no ambiguity. (Regeneron/AZ exome, UKB WES + FinnGen 744-endpoint meta, n=653,219) Tier B Coding GWAS hit OR colocalization → Open Targets L2G (0-1, 51 features, (coloc posterior >0.8 / L2G >0.5) 92-tissue QTL coloc, Shapley Pins the causal gene. explanations); coloc/SuSiE; GWAS Catalog Tier C cis-MR, colocalized, pleiotropy-robust → cis-MR (Nat Commun 2024); mimics Direction + causality, method-dependent pharmacological perturbation Tier D Non-coding GWAS, nearest-gene only → weakest; the wrong-gene failure mode ``` Two orthogonal amplifiers sit beside the ladder, not on it: - **Allelic series / dose-response** (Tier D in the brief's lettering, Axis 3 here): a graded null→partial→GoF set with monotonic effect is the *gold standard* — it predicts the shape of the efficacy curve. PCSK9 is the canonical case. - **Human knockouts / LoF tolerance** (Axis 4 safety): healthy homozygous/compound-het LoF carriers prove full inhibition is tolerated. #### Step 3 — Establish direction-of-effect concordance (Axis 2) The single most underweighted variable. Association says the gene matters; **direction** says whether to agonize or antagonize. ``` LoF protective ⇒ inhibit / degrade (PCSK9, ANGPTL3, APOC3, LPA) LoF causes disease ⇒ activate / replace (enzyme replacement, agonism) Direction discordant ⇒ COLLAPSES the genetic premium — hard gate ``` Confirm direction with: allelic series, LoF-vs-GoF contrast, and **Steiger filtering** in MR (orients cause→effect). Demand the direction be *stated* and *concordant* with the intended mechanism. Use the **GPS-with-direction** variant where available. Discordant or unknown direction is the second-most-common reason a "genetically supported" target fails. #### Step 4 — Run the safety read-across (Axis 4) Human genetics predicts harm, not just efficacy: - **gnomAD constraint** (v4 ~807,000; v2 141,456): read **pLI** and **LOEUF** (LOFTEE-based). Highly constrained genes (pLI~1, low LOEUF) flag that strong/complete perturbation may be poorly tolerated — a caution on full inhibition, not a disqualifier (essential genes can be fine inhibitor targets at sub-maximal engagement). - **Human-knockout catalog**: ~3,421 genes (**18%**) have tolerated two-hit pLoF "human-knockout" genotypes in gnomAD (Minikel et al., *Nature* 581:459, 2020) — positive evidence of dispensability for inhibitor/degrader programs. Absence is ambiguous (lethality vs. rarity), not disqualifying. - **Pleiotropy as a side-effect predictor**: a side effect is **~2x more likely** when it resembles a trait genetically associated with the target gene (Duffy/Minikel/Nelson, *PLOS Genetics* 2025). Operationalize by scanning the gene's full phenome (PheWAS / cis-MR across UKB, FinnGen, MVP — >1M combined) for adverse phenotypes *before* first-in-human. #### Step 5 — Grade modality tractability (Axis 5) A Tier-A genetically validated target can be small-molecule-intractable; the right read is "validated, needs an antibody/oligo," not "fail." Grade *per modality* using Open Targets tractability buckets (ChEMBL v34 pipeline): - **Small molecule (8 buckets):** approved SM drug → Phase 2/3 → Phase 1 → co-crystal with ligand → high-quality ligand (PFI ≤7) → DrugEBIlity pocket ≥0.7 → DrugEBIlity 0–0.7 → druggable-genome family (Finan 2017). - **Antibody:** clinical precedence → high-confidence membrane/secreted localization → predicted signal peptide/TM → Human Protein Atlas membrane evidence. - **PROTAC/degrader:** clinical precedence → literature → ubiquitination sites → protein half-life → ChEMBL binder ≤10 µM. - **Oligo / gene therapy (escape hatch):** the modern route for high-genetic-confidence / low-classical-tractability targets (e.g., *LPA* siRNA). #### Step 6 — Subtract the failure modes, then score Before assigning the composite, run the failure-mode checklist (each is a documented reason "genetically supported" targets still fail): ``` FAILURE-MODE AUDIT [ ] Wrong gene at locus → require coding variant or coloc/L2G > threshold [ ] Wrong direction of effect → Steiger filter, allelic series, explicit direction [ ] Horizontal pleiotropy (MR) → cis-only instruments, coloc, MR-Egger/CAUSE [ ] LD / cross-ancestry confound → matched-ancestry coloc [ ] Tissue-discordant QTLs → use disease-relevant tissue [ ] Reverse causation → trait causes molecular phenotype, not vice versa [ ] Indication mismatch → genetic support for trait X, program targets Y [ ] Mechanism mismatch → variant models one isoform/domain only ``` Then score the six axes (full rubric in `references/quick-reference.md`) and apply the hard gates. ### Output ``` TARGET VALIDATION LADDER — [GENE] in [Indication] Date: [assessment date] Intended mechanism: [inhibit/agonize/...] Modality: [...] Prior reads: Open Targets genetics-only score: [0-1] Genetic Priority Score percentile: [%] (top 0.28% ⇒ ~9.9x indication odds) Axis scores: 1. Causal-gene confidence (0-4): [n] — [ladder tier + evidence] 2. Direction concordance (0-2): [n] — [LoF protective ⇒ inhibit, etc.] 3. Allelic series / dose-response (0-2):[n] — [series / partial / single variant] 4. Safety read-across (0-2): [n] — [pLI/LOEUF; KO tolerance; PheWAS pleiotropy] 5. Tractability (0-2, per modality): [n] — [OT bucket] 6. Replication / generalizability (0-1):[n] — [biobanks / ancestries] COMPOSITE: [0-13] → TIER [1-5]: [de-risked / strong / emerging / hypothesis / none] Hard gates applied: [ ] Discordant direction → capped at Tier 3 [ ] Non-coding-only, no coloc → causal confidence capped at 1 [ ] Intractable in all modalities → flag undevelopable Failure-mode flags: [list any tripped] Verdict: [PCSK9-class de-risked / strong with gaps / emerging needs orthogonal work / association-grade hypothesis / no human prior] Hand-forward to mechanism-risk-adjuster: Genetic-support tier: [Tier 1-5] Implied relative-success multiplier: [~2.6x top-bin → ~1.0x for Tier 5] Direction-concordant: [Y/N] On-target safety flag: [clean / caution / adverse] ``` ## Error Handling | Scenario | Response | |---|---| | No human genetic association found | Score Axis 1 = 0, composite Tier 5. State explicitly there is no genetic prior — not a kill, but the 2.6x lift is unavailable; lean on functional genomics (weakest predictor of human success). | | Strong GWAS signal but no coding variant / no colocalization | Cap causal-gene confidence at 1 (hard gate). Do not credit the nearest gene. Flag "wrong gene at locus" risk; recommend L2G + coloc before crediting. | | Direction of effect unknown or discordant | Cap composite at Tier 3 regardless of other axes. Demand allelic series or Steiger-filtered MR before upgrading. | | MR result is the only support, un-colocalized | Treat as Tier C *only if* cis-instruments + colocalization hold; otherwise discount heavily — un-colocalized druggable-genome MR over-claims novel targets (critiqued 2024-25). | | Genetically pristine but no tractable handle in any modality | Flag undevelopable (hard gate); note the oligo/gene-therapy escape hatch before concluding. | | No healthy human knockouts exist | Treat as no-information for safety (could be lethality OR rarity), not as evidence against. Lean on pLI/LOEUF and PheWAS instead. | | Predominantly European cohort, target may not generalize | Note ancestry caveat; downgrade Axis 6 replication; flag for All of Us / MVP re-check. | | GPS / Open Targets disagree with hand-graded ladder | The hand audit (causal gene + direction) overrides the pre-computed score; the score is a prior, not a verdict. | ## Cross-Domain Connections This skill is deliberately **dual-use** — the same rubric serves two readers: - **A clinical scientist learning the field** uses it as a teaching ladder: it makes explicit *why* PCSK9 (Tier A allelic series + healthy human knockout) is a different class of evidence from a non-coding GWAS hit, and *why* direction-of-effect is the variable that separates a real agonist/antagonist call from a coin flip. - **An investor screening early opportunities** uses it as a diligence gate: a weak rung on this stack is a red flag even when the preclinical data are pretty, and the composite tier becomes the genetic-support input to the conviction stack — applied *before* a clinical asset exists, when the cheapest de-risking decision is made. - **probability-of-success/mechanism-risk-adjuster** *(depends_on — primary hand-forward)*: This skill runs *earlier*. It grades the human-genetics prior; the risk-adjuster consumes the graded tier and converts it into the PoS multiplier (genetic target validation ≈ +20-30% / ~2.6x relative success). The clean contract: this skill outputs {genetic-support tier, direction-concordant Y/N, safety flag}; the adjuster turns it into a phase-weighted number. Never let the adjuster apply a genetic premium this skill has not graded. - **probability-of-success/pos-base-rates**: supplies the therapeutic-area / modality base rate that the 2.6x genetic multiplier scales. - **modality-trajectory/modality-lifecycle** *(sibling)*: when a Tier-A target is intractable by small molecule/antibody, the lifecycle map says whether the rescuing modality's delivery unlock has landed (oligo, degrader, gene therapy). - **modality-trajectory/moa-analog-engine** *(sibling)*: a genetics-first target (PCSK9/GPR75 pattern) is one of three arc templates; this skill confirms the "genetics-first" classification with graded evidence. - **frontier-discovery/frontier-conviction-scorer**: the composite tier is the P(biology holds) term in the discovery-stage trajectory score. - **competitive-intelligence/pipeline-mapper**: a high-tier target with thin clinical competition is white space; pipeline crowding around a Tier-A target is mechanism validation.