Bridges Lab Protocols - Recent changes [en]

Mendelian Randomization

Davebrid1 — Fri, 31 Jul 2026 21:02:03 GMT

5. Decision Matrix: Which Results to Report: Updated decision tree

@@ Line 90: / Line 90: @@
 print(paste("I^2_GX =", round(i2gx_value, 3)))
 </syntaxhighlight>
 == 4 Selection and Collider Bias (Survival / Ascertainment) ==
@@ Line 163: / Line 204: @@
 == 5. Decision Matrix: Which Results to Report ==
-Use the following adjudication criteria to synthesize the results from the models above.
 {| class="wikitable"
 ! Scenario !! Data Presentation !! Adjudicated Result to Report
 |-
-| '''1. Clean Signal'''
+| '''1. Clean Signal''' || F > 10. Cochran's Q p > 0.05. Egger Intercept p > 0.05. CAUSE Causal Model p < 0.05. || "IVW (Fixed Effects). All assumptions are met."
 |-
-| '''2. Balanced Pleiotropy'''
+| '''2. Balanced Pleiotropy''' || F > 10. Cochran's Q p < 0.05 '''or''' one/few outlier SNPs visible in the scatter/funnel (§3.5). Egger Intercept p > 0.05. || "MR-PRESSO (Outlier Corrected) or IVW (Random Effects). Support with Weighted Median."
 |-
-| '''3. Weak Instruments'''
+| '''3. Weak Instruments''' || Mean F < 10 OR Relaxed criteria (p < 5e-6) used. || "MR-RAPS. Baseline IVW is vulnerable to weak instrument bias."
 |-
-| '''4. Directional Pleiotropy'''
+| '''4. Directional Pleiotropy''' || Egger Intercept p < 0.05 '''or''' clear funnel asymmetry (§3.5). || "Weighted Mode (if I2GX < 0.90) OR MR-Egger Slope (if I2GX >= 0.90). IVW is discarded."
 |-
-| '''5. Correlated Pleiotropy'''
+| '''5. Correlated Pleiotropy''' || CAUSE model comparison p > 0.05 (Sharing Model wins). || "Null Result (Discard Causality). The traits are correlated due to shared genetics, not a direct causal pathway."
 |-
-| '''6. Inconclusive'''
+| '''6. Inconclusive''' || MR-PRESSO removes >30% of SNPs causing power loss, OR Median and Mode significantly contradict each other. || "Unresolved / Inconclusive. State that genetic evidence is too pleiotropic to reliably disentangle."
 |-
-| '''7. Selection/collider bias''' || Both arms present AND predicted bias same sign as observed
+| '''7. Selection/collider bias''' || Both arms present AND predicted bias same sign as observed AND predicted ≈ observed magnitude. || "Report as selection-bias-consistent, not causal. Give uncorrected + corrected estimates."
 |}

Talk:Mendelian Randomization

Davebrid1 — Sat, 18 Jul 2026 18:20:07 GMT

Fixed formatting

← Older revision		Revision as of 18:20, 18 July 2026
Line 1:		Line 1:
			== MR SOP — outstanding items (selection/collider bias work, 2026-07-18) ==

	~~## A~~. MR SOP ~~— outstanding items~~		Context: §4 "Selection and Collider Bias" was added to the [https://bridgeslab.sph.umich.edu/protocols/index.php/Mendelian_Randomization MR SOP] after the smoking→AD project found its headline result was most plausibly a survival-collider artefact.

	~~###~~ Sections still missing ~~(all~~ cheap, all bit us on smoking→AD)		=== Sections still missing ===
	~~1. Steiger directionality / reverse causation — absent entirely. One line~~		All three are cheap, and all three bit us on smoking→AD.
	~~(`TwoSampleMR::directionality_test()`). Important for the disease→AD portfolio, where~~
	~~reverse causation is plausible.~~
	~~2. Sample overlap — absent. Two-sample MR assumes independent samples; UK Biobank is in~~
	~~nearly every GWAS we use (it was in both our exposure and outcome). Tool: MRlap~~
	~~(needs full genome-wide sumstats + LD scores).~~
	~~3. Dataset provenance verification — absent. We caught **two mislabelled OpenGWAS~~
	~~accessions**: `ieu-a-1001` labelled "parental lifespan" is actually Okbay EA;~~
	~~`ieu-b-5067` labelled "Wightman" is Woolf 2022 with 954 cases. Rule: verify N,~~
	~~case/control split and cohort composition via `gwasinfo()` before use; never trust the label~~.

	##~~# MR~~-~~PRESSO /~~ MR-~~Egger imbalance (raised, not yet drafted~~)		# '''Steiger directionality / reverse causation''' — absent entirely. One line (<code>TwoSampleMR::directionality_test()</code>). Important for the disease→AD portfolio, where reverse causation is plausible.
	~~Observation~~: ~~we report MR~~-~~PRESSO outlier~~-~~corrected far more than MR~~-~~Egger~~. ~~This is~~		# '''Sample overlap''' — absent. Two-sample MR assumes independent samples; UK Biobank is in nearly every GWAS we use (it was in ''both'' our exposure and outcome). Tool: MRlap (needs full genome-wide sumstats + LD scores).
	~~structural~~, ~~not accidental — Egger intercept tests are underpowered so Scenario 4 rarely~~		# '''Dataset provenance verification''' — absent. We caught '''two mislabelled OpenGWAS accessions''': <code>ieu-a-1001</code> labelled "parental lifespan" is actually Okbay EA; <code>ieu-b-5067</code> labelled "Wightman" is Woolf 2022 with 954 cases. Rule: verify N, case/control split and cohort composition via <code>gwasinfo()</code> before use; never trust the label.
	~~fires, while Cochran's Q is almost always significant so Scenario 2 fires constantly~~.

	~~Why it matters — our own Layer 0: IVW b~~=~~−0.065 p~~=~~0.296 →~~ MR-PRESSO b=~~−0.112 p~~=~~0.0015.~~		=== MR-PRESSO / MR-Egger imbalance (raised, not yet drafted) ===
	~~Outlier removal manufactured the significant result later shown to be collider~~-~~driven~~. It		Observation: we report MR-PRESSO outlier-corrected far more often than MR-Egger. This is '''structural''', not accidental — Egger intercept tests are underpowered so Scenario 4 rarely fires, while Cochran's Q is almost always significant so Scenario 2 fires constantly.
	~~removed only 2/22 SNPs (9%)~~, so ~~the existing ">30% removed" tripwire never fired~~.

	Proposed amendments (Scenario 2 currently has no conclusion-change tripwire):		Why it matters — our own Layer 0: IVW b=−0.065 '''p=0.296''' → MR-PRESSO b=−0.112 '''p=0.0015'''. Outlier removal ''manufactured'' the significant result later shown to be collider-driven. It removed only 2/22 SNPs (9%), so the existing ">30% removed" tripwire never fired.
	- Add a conclusion-change tripwire to Scenario 2: if outlier removal moves the estimate
	outside the original IVW 95% CI or flips significance → report corrected + uncorrected,		Proposed amendments (Scenario 2 currently has '''no''' conclusion-change tripwire):
	corrected as sensitivity only. (Key on effect on conclusion, not SNP count.)		* Add a '''conclusion-change tripwire''' to Scenario 2: if outlier removal moves the estimate outside the original IVW 95% CI or flips significance → report corrected + uncorrected, with the corrected value as sensitivity only. Key on ''effect on the conclusion'', not SNP count.
	- Stop treating Egger intercept p>0.05 as evidence of no directional pleiotropy — it's an		* Stop treating '''Egger intercept p>0.05''' as evidence of no directional pleiotropy — it is an underpowered null, the same error pattern we rejected in §4.2. Report the intercept estimate with CI.
	underpowered null, the same error pattern we rejected in §4.2. Report intercept + CI.		* Elevate '''Weighted Median''' to co-primary (better power ''and'' robustness than MR-Egger; currently only "support" in Scenario 2).
	- Elevate ~~weighted median~~ to co-primary (better power and robustness than Egger; currently		* Report the '''full estimator panel with a concordance flag''' — our estimates spanned −0.065 to −0.208 with p from 0.0015 to 0.647; single-winner adjudication hides that spread.
	only "support" in Scenario 2).
	- Report the full estimator panel with a concordance flag — our estimates spanned
	−0.065 to −0.208 with p from 0.0015 to 0.647; single-winner adjudication hides that.

Talk:Mendelian Randomization

Davebrid1 — Sat, 18 Jul 2026 18:18:52 GMT

Added notes on what to add to MR SOP

New page

## A. MR SOP — outstanding items

### Sections still missing (all cheap, all bit us on smoking→AD)
1. **Steiger directionality / reverse causation** — absent entirely. One line
(`TwoSampleMR::directionality_test()`). Important for the disease→AD portfolio, where
reverse causation is plausible.
2. **Sample overlap** — absent. Two-sample MR assumes independent samples; UK Biobank is in
nearly every GWAS we use (it was in *both* our exposure and outcome). Tool: MRlap
(needs full genome-wide sumstats + LD scores).
3. **Dataset provenance verification** — absent. We caught **two mislabelled OpenGWAS
accessions**: `ieu-a-1001` labelled "parental lifespan" is actually Okbay EA;
`ieu-b-5067` labelled "Wightman" is Woolf 2022 with 954 cases. Rule: verify N,
case/control split and cohort composition via `gwasinfo()` before use; never trust the label.

### MR-PRESSO / MR-Egger imbalance (raised, not yet drafted)
Observation: we report MR-PRESSO outlier-corrected far more than MR-Egger. This is
**structural**, not accidental — Egger intercept tests are underpowered so Scenario 4 rarely
fires, while Cochran's Q is almost always significant so Scenario 2 fires constantly.

Why it matters — our own Layer 0: IVW b=−0.065 **p=0.296** → MR-PRESSO b=−0.112 **p=0.0015**.
Outlier removal *manufactured* the significant result later shown to be collider-driven. It
removed only 2/22 SNPs (9%), so the existing ">30% removed" tripwire never fired.

Proposed amendments (Scenario 2 currently has **no** conclusion-change tripwire):
- Add a **conclusion-change tripwire** to Scenario 2: if outlier removal moves the estimate
outside the original IVW 95% CI or flips significance → report corrected + uncorrected,
corrected as sensitivity only. (Key on *effect on conclusion*, not SNP count.)
- Stop treating **Egger intercept p>0.05** as evidence of no directional pleiotropy — it's an
underpowered null, the same error pattern we rejected in §4.2. Report intercept + CI.
- Elevate **weighted median** to co-primary (better power *and* robustness than Egger; currently
only "support" in Scenario 2).
- Report the **full estimator panel with a concordance flag** — our estimates spanned
−0.065 to −0.208 with p from 0.0015 to 0.647; single-winner adjudication hides that.

Mendelian Randomization

Davebrid1 — Sat, 18 Jul 2026 18:11:39 GMT

3.4 Calculating I-squared GX for MR-Egger: Fixed error in I2 calculation

@@ Line 1: / Line 1: @@
 = Mendelian Randomization Standard Operating Procedure (SOP) =
 This SOP outlines the standardized pipeline for conducting two-sample Mendelian Randomization (MR) analyses, from instrument selection through to causal inference adjudication.
@@ Line 79: / Line 80: @@
 calculate_i2gx <- function(dat) {
-   beta_x <- dat$beta.exposure
+   y <- dat$beta.exposure; s <- dat$se.exposure
-  se_x <- dat$se.exposure
+   k <- length(y); w <- 1/s^2
+   mu <- sum(y * w) / sum(w)      # inverse-variance weighted mean
-  # Variance of the exposure estimates
+   Q  <- sum(w * (y - mu)^2)      # Cochran's Q for the exposure effects
-  var_beta_x <- var(beta_x)
+   max(0, (Q - (k - 1)) / Q)
+}
@@ Line 101: / Line 91: @@
 </syntaxhighlight>
-== 4. Decision Matrix: Which Results to Report ==
+== 4 Selection and Collider Bias (Survival / Ascertainment) ==
 Use the following adjudication criteria to synthesize the results from the models above.
@@ Line 131: / Line 192: @@
 | MR-PRESSO removes >30% of SNPs causing power loss, OR Median and Mode significantly contradict each other.
 | '''Unresolved / Inconclusive'''. State that genetic evidence is too pleiotropic to reliably disentangle.
 |}