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Practitioner Sample Report

Practitioner DNA Evidence Review

Raw DNA file -> personalized metabolic pathway priorities -> matched gene/SNP evidence -> plain-language explanation -> biomarkers to validate.

DNA findings are treated as hypotheses, not conclusions. The report prioritizes pathways to review and biomarkers to validate.

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For practitioners, coaches, and clinicians who want to review this with client cases.

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Workflow viewBuilt for client reviewTriage pathway hypotheses, inspect evidence strength, then decide which biomarkers or clinical context deserve review.
Sample profileJohn Doe
GenderMaleInferred from X/Y chromosome SNP coverage in the raw file.
GeneratedJune 22, 2025
Data sourceConsumer raw DNA export (MyHeritage)

Brain and heart metabolism

Brain and cardiometabolic context

Long-term brain and cardiovascular follow-up often comes back to metabolic systems: glucose control, blood-fat transport, oxidative stress, inflammation, vascular tone, methylation, and cellular energy. This section groups the relevant DNA pathway signals so they can be validated with labs and real-world context.

Use this as a review cluster for cardiometabolic and brain-health-adjacent hypotheses. It should be compared with history, family history, medications, ECG/echo context where relevant, and current biomarkers.

High priority

Blood sugar

0.442

Blood-sugar and insulin strain can affect energy stability, vascular load, and long-term cardiometabolic follow-up.

May increase glucose strainValidate with: Fasting insulin, fasting glucose, HbA1c
High priority

B vitamins

0.433

Homocysteine, folate, and B12 context connect this pathway to vascular and nerve-health follow-up.

May lower B-vitamin use efficiencyValidate with: Homocysteine, methylmalonic acid, folate
High priority

Stress recovery

0.408

Oxidative-stress buffering matters when inflammation, poor sleep, alcohol, illness, pollution, or heavy training create extra cellular load.

May reduce stress-recovery capacityValidate with: Glutathione balance (GSH/GSSG ratio), oxidized LDL
High priority

Cholesterol / blood fats

0.363

ApoB, LDL-C, triglycerides, HDL-C, and Lp(a) show whether lipid-particle transport is visible in current blood chemistry.

May reduce blood-fat clearanceValidate with: ApoB, triglycerides, LDL-C
Moderate priority

Detox / cleanup

0.164

This pathway can add antioxidant-cleanup context when homocysteine, liver markers, recovery, or oxidative-stress markers are relevant.

May reduce cleanup supportValidate with: Homocysteine, liver enzymes, oxidative-stress or recovery context

Scored LDL result

LDL and lipid genes tracked in this report

The lipid pathway separates LDL clearance, LDL-receptor regulation, cholesterol synthesis, HDL remodeling, triglyceride-rich particles, sterol transport, and Lp(a) context instead of treating cholesterol as one number.

High priority

LDL-C / ApoB follow-up score

May increase LDL-C / ApoB follow-up burden

0.380

This sample has more LDL/ApoB-raising evidence than LDL-lowering evidence. The practical next step is lipid blood testing, not assuming disease.

Check ApoB first if possible, plus LDL-C, non-HDL-C, triglycerides, HDL-C, Lp(a), blood pressure, and glucose markers.
LDL/ApoB-raising evidence
0.678
LDL/ApoB-lowering evidence
0.298

Raises the LDL/ApoB score

TRIB1 rs2954029+0.285

rs2954029 AT carries one TRIB1 rs2954029 A allele and is associated with higher triglyceride-rich and apoB-containing lipid biomarker tendency.

The matched lipid claim points toward higher LDL/ApoB burden.
ABCG8 rs4299376+0.259

rs4299376 GT carries one ABCG8 rs4299376 G allele and is associated with higher LDL cholesterol and cholesterol-absorption tendency.

The matched lipid claim points toward higher LDL/ApoB burden.
HMGCR rs12916+0.258

rs12916 CT carries one HMGCR rs12916 C allele, the non-LDL-lowering allele relative to T, and is associated with higher LDL cholesterol tendency than TT.

The matched lipid claim points toward higher LDL/ApoB burden.
LDLR rs688+0.182

rs688 CT is associated with reduced LDLR transport activity.

Lower LDLR clearance signal raises LDL/ApoB follow-up burden.

Offsets the LDL/ApoB score

PCSK9 rs562556-0.298

rs562556 AG carries one PCSK9 rs562556 G allele and is associated with lower LDL cholesterol tendency.

PCSK9 LDL-lowering signal offsets LDL/ApoB follow-up burden.
PCSK9-0.298

LDL-receptor regulation; PCSK9 changes how many LDL receptors remain available for LDL particle clearance.

Contributes in this sample
LDLR-0.182

LDL particle clearance; LDLR directly removes LDL particles from circulation.

Contributes in this sample
HMGCR+0.258

Cholesterol synthesis context; HMGCR is the rate-limiting cholesterol-synthesis target used as statin biology context.

Contributes in this sample
TRIB1+0.285

Triglyceride-rich and ApoB-containing particle context; TRIB1-region evidence links to triglycerides, LDL-C, and ApoB-containing lipid patterns.

Contributes in this sample
ABCG8+0.259

Sterol transport and absorption context; ABCG8 affects intestinal and biliary sterol handling and can shift LDL-C tendency.

Contributes in this sample
CETP-0.288

HDL and lipid remodeling context; CETP changes lipid transfer between HDL and ApoB-containing particles.

Contributes in this sample
ABCA1+0.252

Cholesterol efflux and HDL formation context; ABCA1 helps move cholesterol out of cells toward HDL particles.

Contributes in this sample
APOEcontext

Lipid-particle handling context; APOE is tracked as a backup/context gene for lipid transport and brain-lipid discussions.

Tracked as pathway context; no scored contribution in this sample
LPAcontext

Lipoprotein(a) context; LPA is usually validated directly with an Lp(a) blood test.

Tracked as pathway context; no scored contribution in this sample
APOBcontext

ApoB particle structure and LDL receptor binding context; ApoB helps define particle burden and LDL clearance biology.

Tracked as pathway context; no scored contribution in this sample
SORT1context

Hepatic VLDL-LDL trafficking context; SORT1-region evidence connects liver lipoprotein handling to LDL-C.

Tracked as pathway context; no scored contribution in this sample
TM6SF2context

Hepatic VLDL secretion context; reduced secretion can coexist with liver-lipid retention caveats.

Tracked as pathway context; no scored contribution in this sample

Key lipid checks: ApoBLDL-Cnon-HDL-CtriglyceridesHDL-CLp(a)

Scored cardiac genetics result

HCM / inherited cardiomyopathy screen score

No curated HCM-relevant variant signal was detected in this sample report.

No scored HCM variant signal

No scored HCM variant signal detected

Clinical-grade follow-up required if history, symptoms, ECG, echo, or MRI raise concern.

0.000

This means the current curated evidence registry did not find an HCM-relevant variant in this sample. It does not rule out HCM because consumer raw DNA files do not cover all sarcomeric genes, rare variants, copy-number changes, or clinical interpretation rules.

Scores only direct curated HCM/cardiomyopathy evidence in HCM core or phenocopy genes. Metabolic pathway SNPs and vague cardiomyopathy context are not allowed to create an HCM score.

Escalate when present

  • Known personal or family history of HCM or unexplained thickened heart muscle
  • Family history of sudden unexplained cardiac death, especially at young age
  • Fainting, chest pain, abnormal shortness of breath, or palpitations during exertion
  • Abnormal ECG, echocardiogram, cardiac MRI, or clinician concern

Genes to discuss

MYH7MYBPC3TNNT2TNNI3TPM1ACTC1MYL2MYL3HCM phenocopy genes when ordered by a clinician

Appropriate follow-up

If HCM is a real question, use cardiology review, ECG/echocardiography or cardiac MRI as appropriate, and clinical-grade cardiomyopathy genetic testing with genetic counseling.

2024 AHA/ACC multisociety HCM guideline GeneReviews: Nonsyndromic Hypertrophic Cardiomyopathy 2023 ESC cardiomyopathy guideline

Client Evidence Table

Pathway triage for review

This view foregrounds direction, evidence strength, matched genes/claims, and directness before the client-facing explanation.

RankPathwayDirectionScoreEvidence strengthGenes / claimsDirectnessDetails
1
Coffee / stimulantsCaffeine / stimulant sensitivity
 May increase stimulant sensitivity 0.490 Strong signal 5 genes / 7 evidence items Direct target support present

Practitioner pathway review

Coffee / stimulants

Caffeine / stimulant sensitivity

Learn about this pathway in the KB
High priority0.490May increase stimulant sensitivity How to read this score
What this system does

This is about how strongly your body reacts to caffeine and stimulant-like substances.

Client-facing interpretation

Coffee may hit hard: wired, shaky, anxious, or awake too long.

Why this pathway is ranked here

Caffeine / stimulant sensitivity is ranked from 5 matched gene signals and 7 matched evidence items. The strongest matched driver is COMT rs4680 AG; the topology model resolves this as may increase stimulant sensitivity.

Evidence strength

Strong signal ยท Direct target support present

Estimated burden signal

This pathway contains both burden and capacity-loss blocks. The displayed score (49%) shows the stronger side in this sample: burden.

Biomarker validation

  • Caffeine tolerance historyCaffeine tolerance history is the practical record of dose, timing, sleep, anxiety, heart rate, and blood-pressure response.
  • sleep latencySleep latency is how long it takes to fall asleep and is useful when stimulant sensitivity is suspected.
  • blood pressure responseBlood pressure response helps validate whether a pathway signal is visible under stress, stimulants, or vascular load.

Review context

Useful checks include caffeine timing and dose response, sleep latency, resting heart rate, blood pressure response, anxiety or palpitations after caffeine, and wearable sleep/recovery trends. This pathway contains both burden and capacity-loss blocks. The displayed score (49%) shows the stronger side in this sample: burden.

Practitioner review prompts

  • Check whether the Caffeine / stimulant sensitivity signal matches the client history before treating it as relevant.
  • Prioritize validation with Caffeine tolerance history, sleep latency, blood pressure response before targeted practitioner action.
  • Review medications, symptoms, diet pattern, and recent illness or training load as possible non-genetic drivers.

Evidence and Audit Trail

Genes, SNPs, evidence items, studies, and method

This pathway-level audit trail shows the 5 matched gene signals, 7 evidence items, source studies, and topology method behind this result.

2
Lactose digestionLactose digestion
 May lower lactose digestion 0.457 Strong signal 1 gene / 2 evidence items Direct target support present
3
Blood sugarGlucose
 May increase glucose strain 0.442 Strong signal 4 genes / 5 evidence items Close target support present
4
B vitaminsMethylation
 May lower B-vitamin use efficiency 0.433 Strong signal 6 genes / 6 evidence items Direct target support present
5
Stress recoveryOxidative stress
 May reduce stress-recovery capacity 0.408 Strong signal 2 genes / 2 evidence items Direct target support present
6
Gluten immune riskGluten / celiac immune risk
 May increase celiac immune risk 0.399 Strong signal 6 genes / 6 evidence items Direct target support present
7
Cholesterol / blood fatsLipids
 May reduce blood-fat clearance 0.363 Strong signal 7 genes / 8 evidence items Direct target support present
8
Food / allergy reactionsHistamine
 May slow histamine breakdown 0.312 Moderate signal 1 gene / 1 evidence item Direct target support present
9
HormonesEstrogen metabolism
 May slow estrogen clearance 0.283 Moderate signal 2 genes / 2 evidence items Direct target support present
10
CholineCholine support
 May lower choline support 0.240 Moderate signal 1 gene / 1 evidence item Direct target support present
11
Detox / cleanupSulfur / transsulfuration
 May reduce cleanup support 0.164 Moderate signal 1 gene / 1 evidence item Direct target support present
12
IronIron handling
 May increase iron-loading tendency 0.115 Limited signal 3 genes / 3 evidence items Close target support present
Important: These are structured hypotheses, not medical conclusions. The next step is validation, not action from DNA alone.
Disclaimer: This is a DNA-derived pathway hypothesis, not a medical conclusion. The report does not confirm current metabolite levels or disease status. Biomarkers, symptoms, medication context, and clinician review decide whether a pathway signal is currently relevant.