Personal Genome — Consolidated Health Summary

Sample: SQ8TH633 · 30× WGS (GRCh38, DRAGEN) · genetic ancestry EAS 100% (measured) · male (XY)
Generated: 2026-06-08 · last updated: 2026-06-14 (specialist callers, PGx recovery from BAM, both haplogroups, HLA class II) · Status: research-grade, not diagnostic — every actionable item below is a topic to raise with a clinician/pharmacist, and findings worth acting on should be confirmed with a clinical-grade test. For PRS detail see output/pgsc_calc/percentile_results.md; raw findings in output/findings/genomic_findings.json. Every clinical claim here was independently adversarially verified against the source files.

TL;DR — what actually matters (ranked)

  1. CYP2C19 Poor Metabolizer (*2/*2). You make no functional CYP2C19 enzyme. Highest-impact PGx finding. Clopidogrel (Plavix) is expected to be much less effective — if an antiplatelet is ever needed (stent/ACS), prasugrel or ticagrelor are usually preferred. Some SSRIs/TCAs and PPIs are cleared more slowly (higher exposure).
  2. ALDH2 *1/*2 (alcohol-flush carrier). One inactive aldehyde-dehydrogenase allele → alcohol hits you harder and raises alcohol-associated upper-GI/esophageal cancer risk (compounds your already-elevated esophageal-cancer PRS). Simplest high-value lever: minimize alcohol.
  3. Stroke and Type-2-diabetes polygenic risk are genuinely elevated (EAS-calibrated, corroborated by independent East-Asian scores). Worth standard screening + the lifestyle factors that dominate absolute risk. (CAD and AFib came out average once properly calibrated.)
  4. VKORC1 warfarin-sensitive genotype. If warfarin is ever prescribed, a lower starting dose + early INR monitoring — and the full warfarin algorithm now completes (CYP2C9, initially a no-call, was recovered from the BAM as *1/*1 normal).
  5. The two highest-value PGx gaps are now filled from the BAM — both reassuring: HLA-B*58:01 is negative → allopurinol carries no added SJS/TEN risk for you (matters because your gout PRS is elevated and allopurinol is the standard gout drug), and CYP2D6 is *1/*36+*10 (low-normal metabolizer → codeine/tramadol, some antidepressants, tamoxifen at roughly standard dosing). See §6.

1. Pharmacogenomics — how you process drugs

(PharmCAT 3.2.0 on WGS; verified.)

GeneGenotypePhenotypeWhat it means
CYP2C19*2/*2Poor Metabolizer (high conf)Clopidogrel: avoid/expect reduced efficacy → prasugrel/ticagrelor. PPIs & some SSRIs/TCAs (citalopram, escitalopram, sertraline, amitriptyline), voriconazole: higher exposure, consider dose/monitoring.
CYP3A5*3/*3Non-expressor (high conf)Common state. Only matters for tacrolimus → standard starting dose + trough monitoring (not the higher expressor dose).
VKORC1−1639 A/AWarfarin-sensitive (mod conf)Lower warfarin dose typically needed. CYP2C9 recovered from the BAM (*1/*1 normal) → full warfarin algorithm now completes.
ALDH2*1/*2 (rs671 G/A)~Reduced activityAlcohol flush; alcohol = stronger carcinogen for you. Lifestyle lever, not a prescription.
IFNL3rs12979860 C/TIntermediateOnly relevant to interferon-based hepatitis-C therapy (largely obsolete). Background.

No-Call ≠ "normal" — and these are now all recovered. In the position-limited PGx VCF, CYP2D6, CYP2C9, DPYD, TPMT, NUDT15, UGT1A1, NAT2 returned No Call and SLCO1B1 was ambiguous (~50 candidate diplotypes) — because those positions were missing from the VCF, not because the data was absent. All have since been re-genotyped directly from the 34× BAM (§6): every one resolved, all normal-function / standard-risk. The lesson generalizes — absence of a finding in a position-limited VCF means not measured, not reassuring.

2. Disease-risk variants (ClinVar / ACMG)

3. Structural variants (SV / CNV)

4. Polygenic risk (ancestry-calibrated to East Asian)

Trait PRS — height & cognition (interest only, not predictive for you)

You asked to see these. They are European-GWAS scores with near-zero individual predictive validity for you — curiosities, not facts. Two reasons they don't transfer: (a) you're EAS 100% and these were built in European cohorts (cross-ancestry portability is poor — worst for education/cognition, where much of even the within-population signal is population stratification + assortative-mating + "genetic-nurture"/environmental confounding, not direct effects on the brain); (b) this platform's documented inflation (the height null-control, below).

TraitScore (matched variants)EAS-calibrated %ilesource
HeightPGS002804 (1.1M)95.8th (raw Z +3.7)the null controlproved this platform inflates EUR genome-wide scores (~+1.8 baseline); the "96th" is mostly artifact
Educational attainmentPGS002012 (28k/50k)75thPrivé 2022, EUR
Educational attainment (EA4)EA4 lead-SNP (350/848)51stOkbay 2022 (~3M, SSGAC), EUR — my GWS-lead-SNP build, not the 12–16% PGI
IntelligencePGS001919 (16k/26k)80thPrivé 2022, EUR
IntelligencePGS002135 (476k/903k)35thPrivé 2022, EUR
Intelligence (fluid)PGS004427 (549k/1.06M)58thJung 2024, EUR
Intelligence (IQ/VNR)PGS003724 (2.3M/6.7M)17thHatoum 2022, EUR

The kicker: six education/cognition scores — spanning 2018–2024, up to 6.7M variants, and including the 3-million-person EA4 flagship — scatter from the 17th to the 80th percentile with no convergence (even the two education scores sit 24 points apart: EA4 51st vs Privé 75th). That scatter is the result: a cognitive PRS cannot place an individual, and newer / bigger / ancestry-calibrated doesn't fix it.

On "ancestry-calibration" (the obvious next thought): the percentiles above are already ranked against an East-Asian reference (FRAPOSA) — that's the calibration. But calibration only re-ranks; the variant weights are still European, and you fundamentally cannot compare polygenic scores across ancestry groups — the once-famous European "height-selection" PRS signals were retracted as population-stratification artifacts. A genuinely EAS-derived education GWAS now exists (Chen 2023, 176k Taiwan+Korea; EAS↔EUR genetic correlation 0.87) — encouraging, but it ships as summary statistics (not a plug-in score), it's education not IQ, and even ancestry-matched it explains only 1.5–4% of years-of-schooling. EA4 (Okbay 2022, 3M; obtained via SSGAC) is now in the table above as a lead-SNP build — and it lands at the 51st percentile, no different in kind. None of these is a statement about your actual height, education, or intelligence.

Data credit (per SSGAC policy): EA4 = Okbay et al., "Polygenic prediction of educational attainment within and between families…", Nat Genet 54:437–449 (2022), PMID 35361970; summary statistics obtained from the Social Science Genetic Association Consortium (SSGAC) under its data-use agreement.

5. Ancestry & traits (interest layer)

6. Specialist callers (from the aligned 34× BAM) — gaps now resolved

The FASTQ was aligned to GRCh38, and the BAM unlocked the analyses the DRAGEN VCF couldn't:

All major callers now complete. HLA class I + II, CYP2D6, SMA, mtDNA, the full PGx panel, the carrier special tier, and the Y-haplogroup (§5) are all resolved. Remaining items are research-depth refinements only (e.g. orthogonal confirmation of the short-read SV calls; clinical-grade re-typing of anything actionable), not gaps in coverage.


Provenance & reliability