hu315025 Frozen Validation Report
343 PRS models · 1,636 protein predictions · 144 candidate variants. This static snapshot is generated from the public report JSON artifact.
Overview-first report: suggested next steps are shown before technical PRS and protein tables. Genetic evidence is not diagnostic by itself.
Clinical Variant Status
✓No confirmed pathogenic
Body composition and weight tendency
near-term focus
Your strongest lifestyle-related signal is a tendency toward higher body weight, body-fat distribution, waist or hip size, and weight change. The best response is not extreme dieting; it is a steady strength-led plan with enough protein, fiber, walking, and recovery to make body composition easier to maintain.
Full explanation
Several independent inherited signals point in the same direction: higher body weight, higher arm fat, higher adult body-mass tendency, larger waist or hip measures, and higher visceral-fat tendency. That does not mean your current weight or fitness is known from genetics, but it does mean weight maintenance may require more structure than it does for someone without this pattern.
The evidence is not all negative. A high basal energy-use tendency appears in the favorable direction, and several glucose-related signals look relatively protective. That combination often argues for focusing on body composition, muscle, appetite environment, and consistency rather than assuming broad metabolic dysfunction.
Protein and inherited marker context also support a metabolic interpretation, especially around fat handling and body-size biology. These are pathway clues, not lab results.
This category is worth reviewing if weight, waist size, appetite control, sleep schedule, training recovery, or blood-pressure and lipid trends start changing in the real world. It is also relevant if a clinician is already tracking body composition, fatty liver markers, or cardiometabolic labs.
What to watch forUse a strength-led body-composition plan: progressive resistance training, regular walking or aerobic work, high-fiber meals, and stable meal timing. Review the category if weight, waist size, blood pressure, lipids, sleep, or training recovery changes meaningfully.
Show technical evidence
Risk-score evidence
- arm fat mass: risk percentile 98.9%, coverage 97%, PGS003919.
- weight: risk percentile 98.2%, coverage 96%, PGS003898.
- body mass index: risk percentile 97.2%, coverage 97%, PGS000829.
- arm fat percentage: risk percentile 96.4%, coverage 97%, PGS003915.
- predicted visceral adipose tissue: risk percentile 87.1%, coverage 97%, PGS000844.
- basal metabolic rate: risk percentile 3.5999999999999943%, coverage 96%, PGS003903.
Protein pathway context
- PNLIPRP2: predicted level percentile 90.3%, R2 0.7241; pathway context only.
- MEP1B: predicted level percentile 16%, R2 0.6752; pathway context only.
- ACP6: predicted level percentile 83.3%, R2 0.6207; pathway context only.
Candidate variants
- Variant rs10938397 GG: snpedia_context.
- Variant rs10182181 GG: snpedia_context.
- RMST rs11109072 CC: snpedia_context.
Glucose handling looks relatively favorable despite weight-pressure signals
near-term focus
Your body-composition genetics and glucose-related genetics point in different directions. Weight and fat-distribution tendency look high, but diabetes, glucose, insulin resistance, and long-term sugar-marker signals are mostly favorable.
Full explanation
This is one of the clearest divergent patterns in the report. The body-composition evidence points toward higher weight and fat-distribution tendency, but several glucose-handling and diabetes-related inherited signals are in a favorable direction.
That means the report should not flatten everything into a single generic metabolic-risk label. The more precise interpretation is that body composition may be the main pressure point, while inherited glucose handling appears comparatively resilient.
There is one inherited marker linked to long-term sugar-marker biology, so the favorable score pattern should not be treated as immunity from blood-sugar problems. Diet, activity, sleep, age, medication, and body composition still matter.
This category is worth discussing if fasting glucose, long-term sugar markers, triglycerides, waist size, blood pressure, or weight trend upward, or if there is a family history of diabetes. It is also relevant when choosing a diet strategy, because overly aggressive restriction is not the only reasonable response to this genetic pattern.
What to watch forKeep glucose-friendly habits in place, but aim them at sustainable body composition: fiber-rich carbohydrates, protein at meals, regular resistance training, walking after larger meals, and periodic review if labs or waist size change.
Show technical evidence
Risk-score evidence
- body mass index: risk percentile 97.2%, coverage 97%, PGS000829.
- glycated haemoglobin: risk percentile 4%, coverage 100%, PGS001953.
- glucose: risk percentile 13.1%, coverage 100%, PGS001952.
- type 2 diabetes: risk percentile 13.9%, coverage 99%, PGS000125.
- insulin resistance: risk percentile 18.9%, coverage 98%, PGS000877.
Candidate variants
- FN3KRP rs1046896 TT: snpedia_context.
Gallbladder and bile-flow tendency
useful to review
Gallbladder and biliary signals are among the strongest in the evidence. This does not diagnose gallstones, but it makes bile-flow symptoms, bilirubin changes, and food-triggered upper-abdominal symptoms worth taking seriously if they occur.
Full explanation
Several strong inherited signals point toward gallstones, gallbladder inflammation, and other biliary-tract disease. The same cluster also includes bilirubin and liver-enzyme context, which makes this more coherent than a single isolated finding.
Protein evidence connected to digestive fat handling adds support. This is not a measured enzyme or blood test, but it helps explain why the gallbladder and bile-flow category appears as a real cluster rather than an incidental result.
The useful practical response is not to avoid all fat. It is to avoid repeated very large high-fat meals if they trigger discomfort, maintain steady weight loss rather than crash dieting, and keep routine liver or bilirubin results in context if they are ever abnormal.
This category is worth discussing if there is right-upper-abdominal pain, nausea after fatty meals, jaundice, dark urine, pale stools, fever with abdominal pain, abnormal bilirubin or liver-enzyme results, or a personal or family history of gallstones.
What to watch forTreat gallbladder symptoms or abnormal bilirubin and liver-enzyme results as worth prompt review, especially if discomfort follows large fatty meals or rapid weight change.
Show technical evidence
Risk-score evidence
- cholelithiasis and cholecystitis: risk percentile 99.9%, coverage 100%, PGS001861.
- other biliary tract disease: risk percentile 99.9%, coverage 100%, PGS001862.
- cholecystitis: risk percentile 99.2%, coverage 88%, PGS000942.
- cholelithiasis: risk percentile 96.9%, coverage 92%, PGS001174.
- gallstones: risk percentile 96.4%, coverage 91%, PGS001256.
- total bilirubin: risk percentile 93.7%, coverage 100%, PGS001942.
Protein pathway context
- PNLIPRP2: predicted level percentile 90.3%, R2 0.7241; pathway context only.
- MEP1B: predicted level percentile 16%, R2 0.6752; pathway context only.
Candidate variants
- MIR22,MIR22HG,WDR81 rs11078597 TT: snpedia_context.
- Variant rs10892279 GG: snpedia_context.
Heart and circulation balance
useful to review
The circulation evidence is mostly favorable for common coronary and lipid traits, but not uniformly protective. Lower inherited signals appear for heart attack, high cholesterol, triglycerides, systolic blood pressure, and atrial fibrillation, while clotting and pulse-rate context deserve attention if real-world signs appear.
Full explanation
The heart-related evidence is balanced rather than alarmist. Several inherited signals are favorable for heart attack, high cholesterol, triglycerides, systolic blood pressure, angina, chronic ischemic heart disease, and heart failure context.
At the same time, there are risk-side signals for clotting and pulse rate, plus a mixed inherited marker near a cardiovascular and cell-cycle region. This means the category should be kept as a circulation pattern, not simplified into either low risk or high risk.
The high HDL-related and apolipoprotein context may be favorable, but real cholesterol interpretation still comes from measured lipid panels, blood pressure, smoking status, activity, sleep, and family history.
This category is worth reviewing if blood pressure, resting heart rate, cholesterol, clotting history, chest pain, breathlessness, leg swelling, fainting, palpitations, or family history changes the real-world context.
What to watch forKeep standard heart-health habits in place and use routine measured blood pressure, lipids, and resting heart rate to ground the genetics. Review promptly if clotting symptoms, chest symptoms, palpitations, or strong family history are present.
Show technical evidence
Risk-score evidence
- hdl cholesterol: risk percentile 99.9%, coverage 97%, PGS000660.
- triglycerides: risk percentile 1.5%, coverage 98%, PGS000847.
- high cholesterol: risk percentile 4.3%, coverage 90%, PGS000936.
- myocardial infarction: risk percentile 1.4%, coverage 87%, PGS001316.
- systolic blood pressure automated reading: risk percentile 13.1%, coverage 100%, PGS002009.
- blood clot or deep vein thrombosis: risk percentile 83.5%, coverage 85%, PGS000931.
Protein pathway context
- APOBR: predicted level percentile 13.5%, R2 0.67; pathway context only.
- MST1: predicted level percentile 80.2%, R2 0.6781; pathway context only.
Candidate variants
- CDKN2B rs1063192 AG: confirmation_required.
- C9orf3 rs10821415 CC: snpedia_context.
Attention, mood, migraine, and stress reactivity
useful to review
A strong brain-behavior cluster appears around attention, mood, migraine, neuroticism, loneliness, and stress-response traits. This is not a diagnosis, but it supports paying attention to sleep, workload, recovery, alcohol patterns, and headache triggers.
Full explanation
Several inherited signals sit high for attention, mood-related traits, migraine, neuroticism, loneliness, and post-traumatic stress context. These results do not say that any condition is present; they describe tendencies that may or may not show up depending on environment and life history.
There is also nuance. A favorable addiction-risk signal and favorable sleep-related scores soften the overall picture, while an alcohol-use-disorder signal points in the opposite direction. That makes this a mixed resilience-and-vulnerability category.
Nervous-system protein and marker context supports keeping this as a real brain-behavior cluster. The neuroimaging research-context evidence is used only as background, not as a medical conclusion.
This category is worth discussing if attention, mood, anxiety, irritability, migraine, sleep disruption, alcohol use, stress recovery, or work and relationship functioning become difficult or change noticeably.
What to watch forBuild routines that reduce volatility: consistent sleep, regular training without overreaching, planned recovery, migraine-trigger awareness, and low-friction support if attention or mood starts affecting daily function.
Show technical evidence
Risk-score evidence
- attention deficit hyperactivity disorder: risk percentile 99.4%, coverage 100%, PGS003753.
- major depression: risk percentile 96.5%, coverage 97%, PGS000141.
- migraine: risk percentile 93%, coverage 88%, PGS001282.
- neuroticism score: risk percentile 93%, coverage 100%, PGS001996.
- addiction risk factors: risk percentile 0.3%, coverage 100%, PGS005215.
Protein pathway context
- ENPP5: predicted level percentile 94%, R2 0.6477; pathway context only.
- MDGA1: predicted level percentile 9.6%, R2 0.7077; pathway context only.
Candidate variants
- Variant rs10789369 GG: snpedia_context.
- LRP1B rs10210358 GG: snpedia_context.
Immune, allergy, and skin inflammation
useful to review
Immune biology is one of the most nuanced areas. Several autoimmune and airway disease scores look favorable, but immune pathway signals, eosinophil context, eczema, mouth ulcers, and sun-skin traits keep this category relevant.
Full explanation
The immune evidence does not point in one simple direction. Some inherited disease scores are favorable for rheumatoid arthritis, Crohn's disease, inflammatory bowel disease, lupus, asthma, and general atopic disease.
At the same time, there are risk-side signals for eosinophil percentage, eczema or dermatitis, mouth ulcers, childhood sunburn, and chronic sun-related skin changes. Protein evidence also points strongly into immune signaling, including innate recognition, natural killer cell activation, cytokine signaling, and tissue-repair pathways.
Several inherited markers add immune and inflammatory bowel, psoriasis, arthritis, or infection-susceptibility context. These are not diagnoses, especially where confirmation is required, but they explain why this category remains prominent despite favorable disease-score tails.
This category is worth discussing if persistent rashes, mouth ulcers, wheeze, bowel inflammation symptoms, unexplained fevers, recurrent infections, unusual inflammatory labs, strong family history, or sun-sensitive skin changes become relevant.
What to watch forUse this as an awareness category: protect skin from excess sun, take persistent inflammatory symptoms seriously, and interpret immune or allergy symptoms alongside real clinical signs rather than genetics alone.
Show technical evidence
Risk-score evidence
- eosinophil percentage: risk percentile 92.7%, coverage 96%, PGS003944.
- eczema dermatitis: risk percentile 83.1%, coverage 87%, PGS000944.
- mouth ulcers: risk percentile 81.5%, coverage 90%, PGS000947.
- childhood sunburn: risk percentile 90.7%, coverage 87%, PGS001257.
- skin changes due to chronic exposure to nonionising radiation: risk percentile 83.5%, coverage 84%, PGS000950.
- crohn s disease: risk percentile 3%, coverage 83%, PGS001331.
Protein pathway context
- MICB_MICA: predicted level percentile 2.2%, R2 0.7159; pathway context only.
- CSF2RB: predicted level percentile 4.8%, R2 0.6449; pathway context only.
- MBL2: predicted level percentile 94%, R2 0.6024; pathway context only.
- KIR2DS4: predicted level percentile 86%, R2 0.7795; pathway context only.
- IFNGR2: predicted level percentile 18.6%, R2 0.6902; pathway context only.
- MST1: predicted level percentile 80.2%, R2 0.6781; pathway context only.
Candidate variants
- IL10 rs1800896 CT: confirmation_required.
- IL23R rs10889677 CC: snpedia_context.
- Variant rs10995271 GG: snpedia_context.
- Variant rs10865331 GG: snpedia_context.
Male urinary, prostate, and testicular context
background
Male-specific signals include benign prostate enlargement context, urinary-stone tendency, testicular cancer context, hormone context, and genetically influenced prostate-marker biology. This is an awareness category, not a diagnosis.
Full explanation
Because the sex metadata is male, several male-specific signals are relevant. The evidence includes higher inherited context for benign prostate enlargement, testicular cancer, urinary stones, and estradiol, with lower inherited context for prostate-marker levels.
Protein evidence adds male reproductive and prostate-marker context. A lower predicted prostate-marker signal can make interpretation of future blood results more context-dependent, but it does not replace standard clinical interpretation.
Inherited marker evidence also points to prostate-related biology. These markers are context only and do not mean cancer is present.
This category is worth discussing if urinary flow changes, frequent nighttime urination, blood in urine, kidney-stone pain, testicular lumps or swelling, pelvic pain, abnormal prostate-marker results, or close family history become relevant.
What to watch forFollow ordinary age- and family-history-based male health guidance, and review promptly if urinary changes, testicular changes, stone symptoms, or unusual prostate-marker results occur.
Show technical evidence
Risk-score evidence
- hyperplasia of prostate: risk percentile 89.3%, coverage 80%, PGS001338.
- urinary calculus: risk percentile 80.8%, coverage 100%, PGS001864.
- testicular cancer: risk percentile 95.1%, coverage 71%, PGS001164.
- estradiol 212 pmol l: risk percentile 83.2%, coverage 88%, PGS001182.
- prostate specific antigenlevels: risk percentile 14.5%, coverage 84%, PGS003378.
Protein pathway context
- KLK3: predicted level percentile 12.8%, R2 0.6695; pathway context only.
- EDDM3B: predicted level percentile 98.3%, R2 0.659; pathway context only.
- ZP3: predicted level percentile 82.7%, R2 0.7546; pathway context only.
- TDGF1: predicted level percentile 3.8%, R2 0.7616; pathway context only.
- KLK1: predicted level percentile 6.9%, R2 0.6165; pathway context only.
Candidate variants
- KLK2 rs10424878 GG: snpedia_context.
- Variant rs10505483 CC: snpedia_context.
- C9orf3 rs10821415 CC: snpedia_context.
Blood-cell and clotting context
useful to review
Blood-related evidence includes red-cell and reticulocyte traits, polycythemia context, lower platelet-count tendency, clotting context, and a confirmation-required hemoglobin finding. This should be grounded in ordinary blood counts if it ever matters clinically.
Full explanation
Several inherited signals relate to blood-cell traits, including reticulocyte measures, red-cell size, polycythemia context, platelet count, and clotting. These results are not blood-test results; they are inherited tendencies.
A confirmation-required hemoglobin-related marker appears in the evidence. That should not be treated as a diagnosis or carrier call from this report alone, but it does make the category worth preserving as context.
Other inherited markers relate to red-cell, platelet, and malaria or blood-cell traits. The practical way to interpret this is through ordinary complete blood counts and clinical history, not through genetics in isolation.
This category is worth discussing if blood counts are repeatedly high or low, there is unexplained anemia, unusual fatigue, breathlessness, clotting history, abnormal platelet results, family history of hemoglobin conditions, or before decisions where clotting risk matters.
What to watch forUse routine blood-count results as the anchor. Review this category if anemia, high red-cell counts, unusual platelet counts, clotting history, or family history of hemoglobin conditions is present.
Show technical evidence
Risk-score evidence
- polycythemia vera: risk percentile 85.2%, coverage 100%, PGS001810.
- mean reticulocyte volume: risk percentile 85.4%, coverage 100%, PGS002003.
- mean corpuscular volume: risk percentile 81.8%, coverage 100%, PGS001990.
- platelet count: risk percentile 7.1%, coverage 96%, PGS003932.
- blood clot or deep vein thrombosis: risk percentile 83.5%, coverage 85%, PGS000931.
Protein pathway context
- APOBR: predicted level percentile 13.5%, R2 0.67; pathway context only.
Candidate variants
- HBB rs35939489 GT: confirmation_required.
- RCL1 rs10758658 GG: snpedia_context.
- ATP2B4 rs10900585 TT: snpedia_context.
- Variant rs11104870 TT: snpedia_context.
- GPT,LOC101928953 rs1063739 CC: snpedia_context.
Kidney stone and hydration context
background
A urinary-stone signal appears alongside low water-intake tendency, while urate and gout signals are favorable. The practical response is steady hydration and attention to stone symptoms, not broad kidney-risk assumptions.
Full explanation
The urinary-stone signal is high enough to keep as its own practical category. It is paired with low water-intake tendency, which makes hydration behavior especially relevant.
Other mineral and kidney-adjacent signals are mixed. Gout and urate signals are favorable, and kidney-filtration context appears higher, but none of this is a kidney-function test.
For diet, the useful emphasis is steady fluid intake, fiber-rich meals, and avoiding repeated dehydration around hard training, alcohol, heat, or travel. Stone-specific diet advice should depend on actual stone type if stones ever occur.
This category is worth discussing if there is flank pain, blood in urine, recurrent urinary symptoms, known kidney stones, abnormal kidney labs, or repeated dehydration from training, work, heat, or travel.
What to watch forKeep hydration consistent, especially around training and heat. Review if flank pain, blood in urine, recurrent stones, or abnormal kidney results appear.
Show technical evidence
Risk-score evidence
- urinary calculus: risk percentile 80.8%, coverage 100%, PGS001864.
- water intake: risk percentile 3.2%, coverage 100%, PGS002011.
- egfr: risk percentile 80.1%, coverage 100%, PGS004005.
- gout: risk percentile 6.5%, coverage 100%, PGS004006.
- serum urate: risk percentile 19.1%, coverage 99%, PGS000126.
- phosphate mmol l: risk percentile 5.1%, coverage 92%, PGS000692.
Colon and digestive screening context
background
Lower digestive evidence includes benign colon-neoplasm context and a colorectal marker association, while some bowel and inflammatory signals are favorable. This supports being disciplined about standard screening and symptom review when age or family history makes it relevant.
Full explanation
This category is included because colon and lower digestive evidence appears in more than one lane. There is an inherited score for benign colon neoplasm context and an inherited marker associated with colorectal cancer context.
The evidence is not one-sided. Some digestive and inflammatory bowel disease signals are favorable, so the right framing is screening background rather than a disease conclusion.
The practical response is to follow ordinary age-based and family-history-based colorectal screening guidance. Genetics here should not replace screening rules, stool testing, colonoscopy decisions, or clinician judgment.
This category is worth discussing if there is rectal bleeding, persistent bowel-habit change, unexplained iron deficiency, unexplained weight loss, abdominal pain, personal polyp history, or close family history of colorectal cancer or advanced polyps.
What to watch forUse standard colorectal screening rules as the anchor, and review earlier if bowel symptoms, iron deficiency, polyp history, or close family history is present.
Show technical evidence
Risk-score evidence
- benign neoplasm of colon: risk percentile 81%, coverage 100%, PGS001811.
- benign neoplasm of other parts of digestive system: risk percentile 9%, coverage 100%, PGS001812.
- diverticulosis: risk percentile 9.9%, coverage 100%, PGS001857.
- other diseases of intestine: risk percentile 17.3%, coverage 80%, PGS001516.
- inflammatory bowel disease: risk percentile 5%, coverage 100%, PGS004013.
Candidate variants
- Intergenic rs10795668 GG: snpedia_context.
Eye and optic-nerve background
background
Eye-related evidence is mostly background: several retinal signals are favorable, while corneal and optic-nerve context make routine eye care worth keeping in mind.
Full explanation
The eye-related evidence does not point to a strong current-risk category. Several inherited signals for retinal disorders, retinal defects, and visual acuity context are favorable.
There is still useful background context. Corneal biomechanics and optic-nerve or cup-disc marker evidence appear, which can matter when eye pressure or glaucoma history is part of the real-world picture.
Because genetics is indirect here, this category should be interpreted through routine optometry or ophthalmology findings: eye pressure, optic-nerve appearance, visual fields, and family history.
This category is worth discussing if there is high eye pressure, glaucoma family history, visual-field changes, sudden flashes or floaters, retinal symptoms, or a clinician has already noted optic-nerve or corneal findings.
What to watch forKeep routine eye exams current and mention family history or prior eye-pressure findings if present. Review promptly for sudden visual changes, flashes, floaters, or visual-field symptoms.
Show technical evidence
Risk-score evidence
- retinal disorders in diseases classified elsewhere: risk percentile 5.6%, coverage 80%, PGS001276.
- retinal detachments and defects: risk percentile 8.2%, coverage 100%, PGS001833.
- corneal hysteresis: risk percentile 4.5%, coverage 91%, PGS001381.
- corneal resistance factor: risk percentile 5%, coverage 91%, PGS001383.
- logmar in round: risk percentile 12.3%, coverage 100%, PGS001985.
Candidate variants
- CDKN2B rs1063192 AG: confirmation_required.
Joint, hip, and balance loading
background
Musculoskeletal evidence points to hip-joint and fall-context awareness, with favorable disc-disease context. The best practical response is strength, balance, mobility, and body-composition work rather than avoiding activity.
Full explanation
There is an inherited signal for hip arthrosis context and another for falls in the last year. These are not diagnoses or predictions, but they fit with the broader body-composition pattern because joint load and movement quality matter more when weight tendency is higher.
The evidence also includes favorable intervertebral-disc context, so this is not a broad spine-risk category. A bone-remodeling marker association adds background, but it does not establish a bone disease.
Training should lean toward strength and balance, not fragility. Hips usually benefit from progressive loading, walking capacity, single-leg control, and mobility work when done within tolerance.
This category is worth discussing if hip or groin pain, repeated falls, unexplained balance changes, reduced walking tolerance, persistent joint swelling, or abnormal bone-health findings become relevant.
What to watch forPrioritize progressive lower-body strength, balance work, walking capacity, and hip mobility. Review if hip pain, falls, balance changes, or bone-health concerns appear.
Show technical evidence
Risk-score evidence
- coxarthrosis arthrosis of hip: risk percentile 84.8%, coverage 88%, PGS000967.
- falls in the last year: risk percentile 82.1%, coverage 100%, PGS001916.
- other intervertebral disk disorders: risk percentile 3%, coverage 88%, PGS000932.
- hip circumference: risk percentile 89.7%, coverage 96%, PGS003894.
Candidate variants
- Variant rs10494112 GG: snpedia_context.
Medication Safety
Genes below have pharmacogenomic phenotypes that may affect drug choice or dose review. Use this as a clinical discussion aid, not as a standalone prescribing instruction.
CYP2C9
INTERMEDIATE METABOLIZER
*1/*2
Affected drugs: Warfarin, Phenytoin, Celecoxib, Flurbiprofen, Losartan, Simvastatin
CYP3A5
POOR METABOLIZER
*3/*3
Affected drugs: Tacrolimus, Sirolimus
DPYD
INTERMEDIATE METABOLIZER
c.1129-5923C>G/c.1129-5923C>G, c.1236G>A (HapB3)
Affected drugs: Fluorouracil, Capecitabine
UGT1A1
INDETERMINATE
*1/*80
Affected drugs: Irinotecan, Atazanavir
NAT2
POOR METABOLIZER
*5/*5
Affected drugs: hydralazine
This report comes from consumer microarray data with statistical imputation. Confirm clinically before changing prescriptions.