# Bio Causal Genomics Proteome Mr Drug Target

> Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenome-wide on-target adverse-effect scans, cross-platform Olink/SomaScan replication, and PAV (protein-altering variant) sensitivity. Use when nominating or de-risking a drug target from plasma-proteome G…

- **Type:** Skill
- **Install:** `agentstack add skill-gptomics-bioskills-proteome-mr-drug-target`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [GPTomics](https://agentstack.voostack.com/s/gptomics)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [GPTomics](https://github.com/GPTomics)
- **Source:** https://github.com/GPTomics/bioSkills/tree/main/causal-genomics/proteome-mr-drug-target

## Install

```sh
agentstack add skill-gptomics-bioskills-proteome-mr-drug-target
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

## Version Compatibility

Reference examples tested with: TwoSampleMR 0.5.11+, MendelianRandomization 0.10+, MR-PRESSO 1.0+, coloc 5.2.3+, susieR 0.12.35+, ieugwasr 1.0+, plink2 2.00a5+, R 4.4+.

Before using code patterns, verify installed versions match. If versions differ:
- R: `packageVersion('')` then `?function_name` to verify parameters
- CLI: `plink2 --version`; VEP `vep --help`

If code throws OAuth or rate-limit errors from OpenGWAS, or a missing `dataset$N` from coloc, introspect the installed API and adapt the example rather than retrying. UKB-PPP, deCODE, and Fenland summary statistics changed file layouts between 2023 and 2025; verify column headers before passing into `format_data()`.

# Proteome-Wide Drug-Target Mendelian Randomization

**"Does genetically lowering plasma protein X cause a change in disease Y, mimicking a drug?"** -> Use cis-pQTLs in the gene window for protein X as instruments under the Schmidt 2020 framework (Nat Commun 11:3255), restrict the exclusion-restriction violation to the geometric neighbourhood of the encoding gene, triangulate with colocalization (3-tier PP.H4 ladder below) and cross-platform replication (Olink vs SomaScan), and flag protein-altering-variant (PAV) confounding. A single significant cis-MR estimate is necessary but not sufficient for a drug-target claim; the operational bar is MR + coloc + cross-platform agreement + PAV-excluded sensitivity.

### PP.H4 Three-Tier Threshold Ladder

| Tier | PP.H4 | Use case |
|------|-------|----------|
| Suggestive | >= 0.7 | Open Targets / exploratory; consistent with shared-causal |
| Standard publication | >= 0.8 | Wallace 2020 PLoS Genet 16:e1008720; most peer-reviewed pubs |
| Industry / clinical | >= 0.95 | Drug-claim grade; pharma internal target-validation standard |

Operational rule: drug-target nomination requires PP.H4 >= 0.8 minimum; industry-grade clinical claim requires PP.H4 >= 0.95 plus the full triangulation panel.

- R (canonical): `TwoSampleMR::mr()` orchestrates the cis-IVW + Egger + median + Wald-ratio panel
- R (correlated cis-pQTLs in a window): `MendelianRandomization::mr_ivw(model='default', correl=TRUE, correl.x=ld_matrix)`
- R (triangulation): `coloc::coloc.abf()` or `coloc::coloc.susie()` on the same cis-window
- pheWAS: `ieugwasr::associations()` against the OpenGWAS catalogue, looped over outcomes
- VEP CLI: annotate every cis-pQTL with `vep --species homo_sapiens --canonical --check_existing` for PAV flagging

## Data Source Taxonomy

| pQTL dataset | Platform | N | Proteins | Reference | Fails when |
|--------------|----------|---|----------|-----------|------------|
| UKB-PPP | Olink Explore 3072 (antibody PEA) | 54,219 | 2923 (54k primary cis-pQTLs across studies; 14,287 primary pQTLs across cis+trans) | Sun 2023 Nature 622:329 | Target not on Olink panel; ancestry mostly EUR; antibody epitope may miss isoforms |
| deCODE | SomaScan v4 (aptamer SOMAmer) | 35,559 | 4907 | Ferkingstad 2021 Nat Genet 53:1712 | Population isolate; LD differs from outbred EUR; aptamers can be PAV-confounded |
| Fenland | SomaScan v4 | 10,708 | 4775 | Pietzner 2021 Science 374:eabj1541 | UK Fenland-specific ascertainment; SomaScan caveats |
| INTERVAL | SomaScan v3 (older) | 3301 | 3622 | Sun 2018 Nature 558:73 | Smaller N; older SomaScan version; useful only as replication |
| ARIC | SomaScan v4 | ~7000 (multi-ancestry sub-cohorts) | 4877 | Zhang 2022 Nat Genet 54:593 | Stratify by ancestry; do not pool |
| FinnGen-PPP | Olink Explore | ~12,000 | ~3000 | FinnGen DF12 (2024 release) | Finnish-specific allele frequencies; not always meta-analyse with UKB |
| AGES-Reykjavik | SomaScan v4 | ~5400 | 4782 | Emilsson 2018 Science 361:769 | Elderly Icelandic cohort; ascertainment bias |
| Olink Explore 1536 disease-specific cohorts (CARDIoGRAMplusC4D, etc) | Olink Explore subset | varies | varies | per-study | Lower N per cohort; use as replication |

Methodology evolves; check the UKB-PPP portal (ukb-ppp.gwas.eu), deCODE Genetics summary-stat releases, and the eQTL Catalogue / GTEx Portal for the current data version. UKB-PPP was substantially re-released in 2024 (extended ancestry meta-analyses); pin a download date in the methods.

### Platform and Cohort Versioning (2024-2026)

- **UKB-PPP Phase 2 (2024)** -- cross-ancestry meta-analyses; ~54k EUR plus multi-ancestry expansion; file layouts differ from Phase 1 (per-protein parquet vs flat TSV); the 14,287 primary pQTL count from Phase 1 shifts in Phase 2 results. Verify the freeze used.
- **FinnGen-PPP** -- Olink Explore platform; DF12 (2024) release is current; Finnish-specific allele frequencies require ancestry-aware downstream analysis.
- **AoU pQTL (2024)** -- All-of-Us proteomics; pre-symptomatic-cohort design strength for reverse-causation control and longitudinal follow-up.
- **SomaScan v4 vs v5** -- v5 expands to ~11k SOMAmers (vs ~5k in v4); binding consistency for shared SOMAmers documented in deCODE / SomaLogic technical notes but not guaranteed; pin platform version.
- **Olink Explore HT** -- ~5,400 proteins (vs ~3,072 in Explore Expansion, ~1,536 in Explore 1536); UKB-PPP Phase 1 used Explore 3072 -- do not assume Explore HT coverage when reading Phase 1 papers.
- Pin specific platform version + release date in the methods section of every cis-MR drug-target manuscript.

## Cis-MR Methodological Taxonomy

| Method | Cis-window assumption | Min cis-pQTLs | Strength | Fails when |
|--------|------------------------|----------------|----------|------------|
| Single cis-pQTL Wald ratio | Single sentinel SNP within +/-500 kb | 1 | Simplest, transparent point estimate `beta_Y/beta_X` and ratio SE | Confounded by LD-linked eQTL/pQTL of neighbour gene; no heterogeneity test |
| Cis-IVW (clumped r2  0.1 inflates SE under independence assumption |
| Cis-IVW with correlation `correl=TRUE` | Cis-pQTLs in moderate LD; supply LD matrix | 2 | Correct SE under correlated instruments (Burgess, Zuber, Valdes-Marquez, Sun, Hopewell 2017 Genet Epidemiol 41:714-725) | LD matrix mismatched to summary-stat ancestry |
| Cis-MR-Egger | Directional pleiotropy across cis-pQTLs | 3+ (>=10 for power) | Sensitivity for in-window directional pleiotropy | Underpowered 50% invalid cis-pQTLs |
| MR-PRESSO in cis-window | Outlier cis-pQTLs from LD-confounded neighbours | 4+ | Removes neighbour-eQTL-tagged cis-pQTLs; distortion test (Verbanck 2018) |  T2D) |
| On-target adverse-effect scan (already-marketed drug) | pheWAS cis-MR vs all FinnGen / OpenGWAS phenotypes | Bonferroni + coloc + clinical-event registry | Re-derives known and novel on-target effects |
| Cross-platform replication required for clinical claim | Run independently on UKB-PPP (Olink) AND deCODE (SomaScan) | Direction agreement + magnitude within 2x | Single platform never sufficient for therapeutic decision |
| Trans-pQTL "wants" to be an instrument | Refuse | -- | Trans = horizontal pleiotropy by definition; use only as confirmatory |
| Target gene not on Olink panel | deCODE / Fenland SomaScan only | Cross-replicate across two SomaScan cohorts | Olink panel is gated; do not infer "untested" as null |
| Target in cis-region with strong neighbour eQTL | coloc.susie + coloc to non-target gene's pQTL/eQTL | Drop cis-pQTLs that coloc with non-target | Mandatory: must rule out neighbour-gene mediation |
| Sample overlap (UKB-PPP exposure + UKB phenotype outcome) | MR-RAPS with one-sample-equivalent correction OR independent outcome (FinnGen, BBJ) | Repeat in non-overlapping cohort | Pretending overlap is two-sample inflates effect estimates |

## Per-Method Failure Modes

### Olink vs SomaScan platform discordance

**Trigger:** A cis-pQTL effect size or even direction differs between UKB-PPP (Olink antibody) and deCODE/Fenland (SomaScan aptamer) for the same protein.

**Mechanism:** Olink uses paired antibody proximity-extension assay (PEA) binding distinct epitopes; SomaScan uses single-aptamer SOMAmer binding a folded epitope. A missense SNP that alters one epitope produces an apparent pQTL on that platform only (a pseudo-PAVQTL / aptamer-affinity QTL, AAVQTL). Splice/isoform differences also produce platform-specific signal. Pietzner 2021 and Sun 2023 reported ~15-30% protein-level discordance.

**Symptom:** Cis-MR significant on one platform, null on the other; or significant on both but opposite direction.

**Fix:** Replicate every cis-MR claim on at least one alternate platform; annotate cis-pQTLs with VEP and flag missense / nonsense / splice variants in the gene; consult Olink and SomaScan documentation for the protein's antibody / aptamer binding region; perform a PAV-excluded sensitivity analysis and report both estimates. If platforms disagree irreconcilably, report the protein as platform-discordant and do NOT advance for clinical claim.

**Olink panel coverage pre-check:** Olink Explore 3072 covers ~3,000 proteins; Explore Expansion ~3,000; Explore HT ~5,400. Always confirm the target is on the panel BEFORE running cis-MR: `grep -i  olink_panel_proteins.tsv` (panel manifest from olink.com). Sun 2023 Nature supplementary Table S1 lists every UKB-PPP-covered protein explicitly; absence from Table S1 means the target was not measured in Phase 1 (regardless of biology) and the analysis must use SomaScan.

### LD-based pleiotropy in the cis-window

**Trigger:** A cis-pQTL for target gene X is also a strong eQTL or pQTL for a neighbouring gene within +/-500 kb.

**Mechanism:** The instrument's effect on outcome may be mediated by the neighbour gene's protein, not by target X. Cis-window proximity does NOT guarantee specificity.

**Symptom:** Colocalization with the non-target gene's pQTL or eQTL returns PP.H4 >= 0.7; cis-MR using only "clean" cis-pQTLs (those not coloc'd with neighbours) gives a substantially different estimate.

**Fix:** For every cis-pQTL, run colocalization against all eQTL/pQTL signals within +/-500 kb in the relevant tissue; drop cis-pQTLs that coloc (PP.H4 >= 0.5) with any non-target gene; coloc.susie is preferred when multiple credible sets exist in the window. Reports must list which cis-pQTLs were retained and the rationale.

### Reverse causation from disease state on plasma protein

**Trigger:** The outcome trait elevates the protein as a downstream consequence (e.g. CRP elevated in coronary disease patients; TNF in autoimmune disease).

**Mechanism:** Plasma proteomes measured in observational cohorts (including UKB-PPP) include people who have or will develop the outcome; the observed protein-disease association may be downstream not upstream.

**Symptom:** Observational protein-disease association is large; cis-MR estimate is much smaller, null, or in the opposite direction.

**Fix:** Apply Steiger filtering on each cis-pQTL (`steiger_filtering()`); restrict to pre-symptomatic samples where possible (pediatric or early-adult cohorts); replicate in longitudinal cohorts measuring protein years before disease onset. Note: Steiger has its own caveat under unmeasured confounding (Hemani Tilling 2022 Wellcome Open Res 7:14); cross-validate via bidirectional cis-MR.

```r
library(TwoSampleMR)
dat = 0.8** between cis-pQTL and outcome GWAS at the gene locus -- standard publication tier; >= 0.95 for industry-grade claim (cross-reference causal-genomics/colocalization-analysis)
3. **Cross-platform replication** -- significant on both Olink (UKB-PPP) AND SomaScan (deCODE or Fenland); direction agreement is mandatory, magnitude within 2x is acceptable
4. **Cross-cohort replication** (ideal but not strictly required) -- UKB-PPP -> deCODE -> FinnGen-PPP step-up
5. **PAV-excluded sensitivity** -- the cis-MR survives when missense / nonsense / splice / aptamer-binding-region SNPs are dropped
6. **No neighbour-gene coloc** -- no cis-pQTL in the instrument set coloc-shares a causal variant with any non-target gene's eQTL or pQTL within +/-500 kb
7. **Open Targets L2G concordance** -- Open Targets Platform locus-to-gene score for the target gene >= 0.5 at the disease GWAS lead (cross-reference causal-genomics/effector-gene-prioritization)

Operational claim ladder: cis-MR significant alone = exploratory; +coloc PP.H4 >= 0.7 = consistent with shared-causal; +cross-platform = consistent across detection chemistries; +PAV-excluded + neighbour-clear = publication-grade target nomination; +cohort replication + Open Targets L2G >= 0.5 = clinical-pharmacology-grade. Clinical-pharmacology claims require ALL 6 original criteria PLUS L2G concordance.

## Phenome-Wide Drug-Target MR

**Goal:** For a single drug target (single protein), test causal effect across hundreds of outcomes to discover on-target adverse effects.

**Approach:** Hold cis-pQTL instrument set fixed; loop outcome over OpenGWAS catalogue or FinnGen DF12; multi-test correct over outcomes.

```r
library(TwoSampleMR); library(ieugwasr)

target_pqtl = 50000 & population == 'European')

results  T2D signal (Schmidt 2017 Lancet Diabetes Endocrinol 5:97) was discovered exactly via curated-endpoint pheWAS: cis-MR of LDL-lowering instruments revealed on-target T2D risk before clinical trials confirmed it. Drug-target pheWAS is the canonical use case.

## Cis-MR Standard Workflow

**Goal:** Produce a defensible cis-MR estimate with triangulation, given a target gene and an outcome.

**Approach:** Extract cis-pQTLs in +/-500 kb of the gene -> compute F per instrument from exposure -> clump within window at r2  harmonise with outcome -> run TwoSampleMR -> run coloc.abf on the same window -> PAV-annotate via VEP -> report panel.

```r
library(TwoSampleMR); library(coloc); library(ieugwasr)

cis_window_kb  (gene_start - cis_window_kb * 1000) &
    POS = 10)  # Staiger-Stock 1997 weak-IV floor

exposure_dat  cis_pqtls.vcf
vep --species homo_sapiens --assembly GRCh38 --canonical --check_existing \
    --input_file cis_pqtls.vcf --output_file pqtl_vep.tsv --tab --force_overwrite
```

PAV consequences to flag (drop in sensitivity analysis): `missense_variant`, `stop_gained`, `stop_lost`, `frameshift_variant`, `splice_acceptor_variant`, `splice_donor_variant`, `start_lost`, `protein_altering_variant`. For aptamer panels, additionally consider `synonymous_variant` within the SOMAmer-binding region (rare but documented).

## Cis-Window Width: 500 kb vs 1 Mb Decision

- **Default ±500 kb** (Schmidt 2020 Nat Commun 11:3255 standard) -- balances cis-specificity against power; matches Open Targets Genetics defaults
- **Widen to ±1 Mb** when: (a) target gene has a documented distal regulatory element in ENCODE-rE2G or ABC enhancer-gene maps; (b)  500 kb itself, e.g. DMD, RBFOX1)
- **Narrow to ±250 kb** when high-density cis-eQTL background causes multi-gene pleiotropy concerns (e.g. HLA region; gene-dense pericentromeric loci)

Pre-specify the window in the methods section; window-width sensitivity is a recognized peer-review pushback (see Anticipated Reviewer Pushback below).

## Quantitative Thresholds

| Threshold | Source | Rationale |
|-----------|--------|-----------|
| Bonferroni for cis-MR pheWAS | Standard | `P = 0.7 (suggestive) | Open Targets Genetics; Mountjoy 2021 Nat Genet 53:1527 | Exploratory; consistent with shared-causal |
| Coloc PP.H4 >= 0.8 (publication) | Wallace 2020 PLoS Genet 16:e1008720 | Standard peer-reviewed publication bar |
| Coloc PP.H4 >= 0.95 (industry) | Pharma internal target-validation standard | Drug-claim grade; clinical-pharmacology bar |
| Cis-pQTL F >= 10 | Staiger & Stock 1997; Burgess 2011 | Weak-instrument floor |
| Cis-window +/-500 kb | Schmidt 2020 Nat Commun 11:3255 | Standard cis definition; some pipelines use 1 Mb |
| r2 = 2 pQTL datasets in agreement | Best-practice (UKB-PPP + deCODE) | Cross-platform replication mandatory for clinical claim |
| PAV-excluded sensitivity | Sun 2023 supplementary | Required for clinical claim; Olink/SomaScan vulnerable to PAV artifact |
| Neighbour-gene coloc PP.H4  0.05 (correct direction) | Hemani 2017 PLoS Genet 13:e1007081 | Directionality check; subject to

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [GPTomics](https://github.com/GPTomics)
- **Source:** [GPTomics/bioSkills](https://github.com/GPTomics/bioSkills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-gptomics-bioskills-proteome-mr-drug-target
- Seller: https://agentstack.voostack.com/s/gptomics
- Browse the marketplace: https://agentstack.voostack.com/browse

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