hu30888B Frozen Validation Report
342 PRS models · 1,636 protein predictions · 135 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 glucose handling
near-term focus
Genetics points toward higher visceral fat and glucose-handling strain, but lipid-related signals look protective.
Full explanation
The strongest metabolic theme is not just body weight. The evidence points especially toward visceral fat, waist size, body size, glucose, long-term glucose exposure, insulin resistance, and diabetes-related tendency.
That does not mean diabetes or obesity is present. It means this is one of the areas where lifestyle, sleep, training load, and routine lab context could matter more for this person than average.
The nuance is important: several cholesterol and lipid-particle signals are protective. This creates a divergent pattern where fat distribution and glucose handling deserve attention even if a standard cholesterol panel were to look reassuring.
This category becomes worth discussing or reviewing if there are rising waist measurements, weight gain despite stable habits, abnormal fasting glucose or long-term glucose labs, high blood pressure, fatty-liver concerns, strong family history of diabetes, or noticeable changes in energy after meals.
What to watch forPrioritize waist-friendly habits: steady resistance training, regular walking or cycling, high-fiber meals, and fewer large refined-starch or alcohol-heavy meals; review this sooner if glucose, waist, liver, or blood-pressure markers change.
Show technical evidence
Risk-score evidence
- predicted visceral adipose tissue: risk percentile 99.2%, coverage 97%, PGS000844.
- waist circumference: risk percentile 95.8%, coverage 99%, PGS000827.
- glucose: risk percentile 98.3%, coverage 100%, PGS001952.
- glycated haemoglobin: risk percentile 93.8%, coverage 100%, PGS001953.
- insulin resistance: risk percentile 89%, coverage 98%, PGS000877.
- non insulin dependent diabetes: risk percentile 88.6%, coverage 90%, PGS001294.
Protein pathway context
- INSL3: predicted level percentile 92.3%, R2 0.7312; pathway context only.
- MEP1B: predicted level percentile 89.6%, R2 0.6752; pathway context only.
- PNLIPRP2: predicted level percentile 87.8%, R2 0.7241; pathway context only.
- APOBR: predicted level percentile 10.2%, R2 0.67; pathway context only.
- LECT2: predicted level percentile 8.3%, R2 0.5765; pathway context only.
Candidate variants
- FN3KRP rs1046896 TT: snpedia_context.
- Variant rs10105606 CC: snpedia_context.
- Variant rs1024889 GG: snpedia_context.
- Variant rs10937273 GG: snpedia_context.
Blood pressure, heart structure, and rhythm
near-term focus
Heart-structure and blood-pressure signals are elevated, while lipid and clotting signals are relatively reassuring.
Full explanation
The cardiovascular evidence is split. Several signals point toward blood pressure, heart structure, aortic valve context, heart failure context, heart rate, and electrical timing.
At the same time, there are protective signals for LDL cholesterol, total cholesterol, clotting, pulmonary embolism, myocardial infarction, angina, and some inherited heart-muscle context. That makes this less of a simple heart-risk story and more of a blood-pressure and structure-awareness story.
The genetically predicted protein evidence adds pathway context around blood-group biology, inflammation, immune repair, and lipid or platelet-related biology. Medication-processing context also matters if antiplatelet therapy is ever considered.
This category becomes worth discussing or reviewing if there are repeated high blood-pressure readings, palpitations, fainting, unusual shortness of breath, chest pressure, new exercise intolerance, abnormal heart tests, or a family history of early heart disease, valve disease, or sudden cardiac events.
What to watch forTake routine blood-pressure readings seriously, keep aerobic fitness steady, and bring this context up if cardiac symptoms, abnormal readings, or relevant family history appear.
Show technical evidence
Risk-score evidence
- left ventricular mass index: risk percentile 99.2%, coverage 100%, PGS003427.
- systolic blood pressure automated reading: risk percentile 92.6%, coverage 100%, PGS002009.
- congestive heart failure nonhypertensive: risk percentile 86.2%, coverage 100%, PGS001842.
- heart rate: risk percentile 83.6%, coverage 98%, PGS000300.
- qrs duration: risk percentile 83.6%, coverage 100%, PGS001948.
- myocardial infarction: risk percentile 10.8%, coverage 87%, PGS001316.
Protein pathway context
- ABO: predicted level percentile 1%, R2 0.6423; pathway context only.
- MST1: predicted level percentile 96.3%, R2 0.6781; pathway context only.
- IL6R: predicted level percentile 94.1%, R2 0.666; pathway context only.
- APOBR: predicted level percentile 10.2%, R2 0.67; pathway context only.
Candidate variants
- LOC105377979 rs1015451 TT: snpedia_context.
- RCL1 rs10758658 GG: snpedia_context.
- ATP2B4 rs10900585 TT: snpedia_context.
Medication-response context
- CYP2C19: Rapid Metabolizer, *1/*17; affected medicines include Clopidogrel, Omeprazole, Pantoprazole, Citalopram, Escitalopram, Voriconazole.
Kidney, urate, and hydration context
useful to review
Kidney-marker, urate, and urine-salt signals make routine kidney and hydration context worth keeping in view.
Full explanation
The kidney-related evidence includes creatinine, urine creatinine, chronic kidney context, serum urate, and urinary sodium. These are genetic tendencies, not proof of kidney disease or gout.
There is also protective kidney-function context, which softens the interpretation. The best reading is that kidney filtration, urate handling, salt balance, and metabolic load should be considered together rather than as separate isolated findings.
Protein and variant evidence add pathway context around kidney membrane biology, immune-kidney overlap, and blood urea traits. This matters because kidney signals can be influenced by blood pressure, body composition, hydration, medications, and protein intake.
This category becomes worth discussing or reviewing if kidney labs are abnormal, blood pressure is high, gout-like joint pain appears, kidney stones occur, there is swelling, there are medication changes involving kidney-cleared drugs, or family history points toward kidney disease.
What to watch forKeep hydration, blood pressure, and routine kidney labs in context; review sooner if kidney markers, gout-like symptoms, stones, or medication changes make this clinically relevant.
Show technical evidence
Risk-score evidence
- creatinine: risk percentile 97.5%, coverage 100%, PGS001945.
- creatininein urine: risk percentile 93.6%, coverage 100%, PGS001944.
- chronic kidney disease: risk percentile 90.9%, coverage 100%, PGS004004.
- serum urate: risk percentile 94.7%, coverage 99%, PGS000126.
- estimated glomerular filtration rate: risk percentile 7.5%, coverage 100%, PGS000884.
- sodium in urine mmol l: risk percentile 82.5%, coverage 91%, PGS000695.
Protein pathway context
- DPEP1: predicted level percentile 13.1%, R2 0.548; pathway context only.
- LCP1: predicted level percentile 97.7%, R2 0.5128; pathway context only.
- MST1: predicted level percentile 96.3%, R2 0.6781; pathway context only.
- LECT2: predicted level percentile 8.3%, R2 0.5765; pathway context only.
Candidate variants
- LOC107986166 rs10937329 TT: snpedia_context.
Gut resilience and diverticular tendency
useful to review
Digestive sensitivity and diverticular signals are prominent, with some protective functional-gut context.
Full explanation
The digestive evidence is broad: diverticulosis, diverticular disease, diverticulitis, sensitive stomach, duodenitis, bowel-frequency context, and digestive neoplasm context all appear in the evidence.
This does not mean these conditions are present. It means gut resilience, bowel regularity, and inflammation-sensitive digestion may be areas where prevention and symptom context matter.
The protective functional-digestive signal is useful nuance. It suggests the report should not frame this as a generalized fragile-gut finding, but rather as a diverticular and irritation-pattern awareness category.
This category becomes worth discussing or reviewing if there is persistent abdominal pain, fever with bowel symptoms, blood in stool, unexplained weight loss, a sustained change in bowel pattern, recurrent reflux or upper-abdominal pain, or family history of bowel disease or early bowel cancer.
What to watch forFavor consistent fiber from food, hydration, and regular movement; seek review if bowel changes, bleeding, fever, persistent pain, or strong family history enter the picture.
Show technical evidence
Risk-score evidence
- diverticulosis: risk percentile 98.5%, coverage 100%, PGS001857.
- diverticular disease of intestine: risk percentile 96.3%, coverage 91%, PGS000997.
- diverticular disease diverticulitis: risk percentile 93%, coverage 88%, PGS000996.
- sensitive stomach: risk percentile 96.6%, coverage 100%, PGS002004.
- duodenitis: risk percentile 88.4%, coverage 100%, PGS001852.
- average number of times bowels opened per day: risk percentile 88.8%, coverage 85%, PGS001376.
Protein pathway context
- PNLIPRP2: predicted level percentile 87.8%, R2 0.7241; pathway context only.
- MEP1B: predicted level percentile 89.6%, R2 0.6752; pathway context only.
- KLK12: predicted level percentile 0.8%, R2 0.7889; pathway context only.
Candidate variants
- Intergenic rs10795668 GG: snpedia_context.
Immune, skin, and airway reactivity
near-term focus
Immune-cell, inflammatory, eczema, eosinophil, and airway signals converge strongly.
Full explanation
The immune lane is one of the clearest multi-evidence themes. The evidence includes inflammation, eczema or dermatitis, eosinophil context, respiratory infection, chronic airway obstruction, lower lung-function ratio, and mouth-ulcer tendency.
The genetically predicted protein pattern also leans heavily into immune signaling: immune checkpoints, natural-killer-cell activation, inflammatory receptors, antibody receptors, and immune-cell growth signals all appear.
There are protective autoimmune and nasal-polyp signals, so this should not be read as a generic autoimmune-risk conclusion. A better interpretation is immune reactivity with skin, airway, and inflammation overlap.
This category becomes worth discussing or reviewing if there is recurrent wheeze, persistent cough, exercise-related breathing limitation, frequent unusual infections, persistent eczema, repeated mouth ulcers, unexplained inflammation markers, or a family pattern of immune or allergic disease.
What to watch forTreat persistent skin, airway, mouth-ulcer, or inflammatory symptoms as worth proper review, especially if they recur or affect training, sleep, or daily function.
Show technical evidence
Risk-score evidence
- c reactive protein: risk percentile 93.9%, coverage 94%, PGS000314.
- eczema dermatitis: risk percentile 89%, coverage 87%, PGS000944.
- eosinophil percentage: risk percentile 81.5%, coverage 96%, PGS003944.
- unspecified acute lower respiratory infection: risk percentile 85.6%, coverage 86%, PGS000925.
- chronic airway obstruction: risk percentile 81.9%, coverage 100%, PGS001850.
- mouth ulcers: risk percentile 87.2%, coverage 90%, PGS000947.
Protein pathway context
- CD200R1: predicted level percentile 0.6%, R2 0.5497; pathway context only.
- KIR2DS4: predicted level percentile 99.1%, R2 0.7795; pathway context only.
- TNFRSF10C: predicted level percentile 98.4%, R2 0.5968; pathway context only.
- CSF2RB: predicted level percentile 95%, R2 0.6449; pathway context only.
- FCGR2A: predicted level percentile 94.9%, R2 0.5811; pathway context only.
- IL6R: predicted level percentile 94.1%, R2 0.666; pathway context only.
Candidate variants
- Variant rs10484561 TT: snpedia_context.
- SQRDL rs1044032 TT: snpedia_context.
Joint and spine load tolerance
useful to review
Osteoarthritis and disc-related signals suggest paying attention to joint loading and recovery.
Full explanation
The musculoskeletal evidence points most clearly toward osteoarthritis and intervertebral disc context. These are common, load-sensitive areas where genetics can influence vulnerability without determining outcome.
There are also protective signals for osteoporosis and hand-fascia contracture, so the issue is not a broad bone-and-connective-tissue risk. The more useful interpretation is joint-surface and spine-load tolerance.
This matters for training because high body-composition signals and joint signals can reinforce each other. The goal is not to avoid training, but to make strength, mobility, and progression more deliberate.
This category becomes worth discussing or reviewing if there is persistent joint pain, swelling, locking, loss of range, back pain with nerve symptoms, repeated training setbacks, or family history of early joint replacement or severe spine disease.
What to watch forUse progressive strength work, avoid sudden jumps in impact volume, and review persistent joint or back symptoms rather than training through them indefinitely.
Show technical evidence
Risk-score evidence
- osteoarthritis: risk percentile 98.9%, coverage 90%, PGS001290.
- other intervertebral disk disorders: risk percentile 95.4%, coverage 88%, PGS000932.
- osteoporosis without pathological fracture: risk percentile 14.2%, coverage 93%, PGS001274.
- contracture of palmar fascia dupuytren s disease: risk percentile 14.3%, coverage 100%, PGS001880.
Protein pathway context
- TNN: predicted level percentile 97.7%, R2 0.5604; pathway context only.
Sleep, energy, and recovery rhythm
useful to review
Daytime dozing, long sleep, tiredness, and sedentary-screen-time signals appear, but insomnia context is protective.
Full explanation
The sleep and energy evidence is mixed. Daytime dozing, sleep duration, tiredness or lethargy, and time spent watching television or using a computer are elevated.
At the same time, insomnia-related evidence is protective. That means this is not mainly a sleeplessness pattern; it is more about sleep quantity, daytime alertness, recovery rhythm, and sedentary drift.
This can interact with the metabolic and training findings. Poor recovery, inconsistent activity, and long sedentary periods can make weight, glucose, mood, and joint tolerance harder to manage.
This category becomes worth discussing or reviewing if there is heavy daytime sleepiness, loud snoring, witnessed breathing pauses during sleep, non-restorative sleep, persistent fatigue, a major change in sleep need, or performance decline despite adequate training.
What to watch forAnchor sleep timing, break up long seated blocks, and treat persistent daytime sleepiness or recovery failure as a reason for review.
Show technical evidence
Risk-score evidence
- daytime dozing sleeping: risk percentile 97.5%, coverage 100%, PGS001995.
- sleep duration: risk percentile 96.1%, coverage 100%, PGS001978.
- freq of tiredness lethargy in last 2 weeks: risk percentile 88.6%, coverage 92%, PGS001080.
- time spent watching televisionor using computer: risk percentile 92.7%, coverage 100%, PGS001923.
- sleeplessness insomnia: risk percentile 1.2%, coverage 100%, PGS001932.
Alcohol, tobacco, and reward sensitivity
near-term focus
Alcohol and tobacco signals are high, but broad addiction-risk context is strongly protective.
Full explanation
The behavioral evidence is divergent. Alcohol-use-disorder context is very high, tobacco-use context is elevated, and there is also context around increased alcohol intake and risk-taking behavior.
However, a broad addiction-risk signal is strongly protective. That means this should not be written as a prediction of addiction or current behavior. It is better treated as a sensitivity signal where environment, stress, habit loops, and social context may matter.
The practical value is prevention. Genetics can suggest where boundaries and early course-correction may be more useful, especially around alcohol escalation or tobacco exposure.
This category becomes worth discussing or reviewing if alcohol intake is increasing, cutting down feels hard, tobacco use starts or returns, risk-taking becomes costly, mood and drinking become linked, or there is family history of substance-use problems.
What to watch forKeep firm boundaries around alcohol and tobacco exposure; take escalation, cravings, or repeated failed cut-backs seriously if they occur.
Show technical evidence
Risk-score evidence
- alcohol use disorder: risk percentile 99.6%, coverage 100%, PGS002739.
- tobacco use disorder: risk percentile 90.4%, coverage 100%, PGS001830.
- increased alcohol consumption versus 10 years ago: risk percentile 88%, coverage 87%, PGS001085.
- risk taking behaviour: risk percentile 83.1%, coverage 91%, PGS001049.
- addiction risk factors: risk percentile 0.1%, coverage 100%, PGS005215.
Candidate variants
- Variant rs10789369 GG: snpedia_context.
Mood, stress, and brain-wiring background
background
Mood and stress-reactivity signals appear alongside non-diagnostic brain-structure context and some protective mental-health context.
Full explanation
The brain and mood evidence should be handled carefully. There are signals related to neuroticism, recent low mood, broad depression context, major depression context, and autism-spectrum context.
There are also protective signals around loneliness, nerves, and Alzheimer-related context. Separately, several brain-structure research signals appear, but these are non-diagnostic background and should not be treated as medical-risk conclusions.
The useful interpretation is stress reactivity and brain-wiring awareness, not a claim that any mental-health condition is present. This can still be valuable because sleep, alcohol, exercise, and inflammation can all influence how this category plays out in real life.
This category becomes worth discussing or reviewing if there is persistent low mood, anxiety, loss of interest, social withdrawal, major changes in focus or routine, self-harm thoughts, functional decline, or family history of significant mental-health conditions.
What to watch forUse this as background for stress, sleep, alcohol, and exercise choices; seek support promptly if mood, anxiety, or functioning changes persist.
Show technical evidence
Risk-score evidence
- neuroticism score: risk percentile 90.2%, coverage 100%, PGS001996.
- major depression: risk percentile 80.6%, coverage 98%, PGS000142.
- autism spectrum disorder: risk percentile 97.1%, coverage 73%, PGS000327.
- loneliness: risk percentile 4.7%, coverage 86%, PGS001091.
- suffer from nerves: risk percentile 14.5%, coverage 90%, PGS001017.
- alzheimers disease: risk percentile 18.7%, coverage 100%, PGS002035.
Protein pathway context
- MDGA1: predicted level percentile 86.2%, R2 0.7077; pathway context only.
Candidate variants
- Variant rs10789369 GG: snpedia_context.
Eye structure and vision-change awareness
useful to review
Retinal detachment, cataract, and optical-shape signals are elevated, while eye-pressure and glaucoma context are protective.
Full explanation
The eye-related evidence is a clear single-lane finding. Retinal detachment or break context, cataract context, and optical-shape context are elevated.
This is balanced by protective eye-pressure and open-angle glaucoma context. That makes the category less about broad eye disease and more about structural vision-change awareness.
The value here is knowing which eye symptoms should not be ignored. Sudden vision changes are always clinical, regardless of genetics.
This category becomes worth discussing or reviewing if there are new flashes, floaters, a curtain-like shadow, sudden vision loss, new double vision, rapidly changing prescription, glare, cloudy vision, or family history of serious retinal disease.
What to watch forDo not ignore sudden flashes, floaters, curtain-like shadows, or abrupt vision changes; use routine eye care to keep cataract and prescription changes in context.
Show technical evidence
Risk-score evidence
- retinal detachments and breaks: risk percentile 95.6%, coverage 85%, PGS000990.
- cataract: risk percentile 94%, coverage 100%, PGS001837.
- spherical power: risk percentile 84.7%, coverage 93%, PGS001100.
- intraocular pressure: risk percentile 7%, coverage 93%, PGS000879.
- primary open angle glaucoma: risk percentile 18.7%, coverage 87%, PGS002741.
Hormone, thyroid, and prostate context
background
Male hormone and thyroid-nodule signals appear, while prostate cancer genetic context is comparatively protective.
Full explanation
The endocrine evidence includes testosterone, estradiol, thyroid-nodule context, and protective thyrotoxicosis context. In a male report, these are best treated as hormone and thyroid-awareness signals, not as a diagnosis.
The prostate picture is mixed. Genetically predicted prostate-related proteins are high, but prostate cancer genetic scores are comparatively protective.
This means real-world interpretation would depend heavily on symptoms, age, examination, and actual blood tests if they are ever done. Genetics alone cannot interpret a prostate blood test or hormone panel.
This category becomes worth discussing or reviewing if there are urinary symptoms, fertility concerns, testicular symptoms, unexplained breast tissue changes, symptoms of thyroid overactivity or underactivity, a thyroid lump, abnormal hormone labs, or family history of prostate or thyroid disease.
What to watch forUse this as context for thyroid, hormone, urinary, or fertility discussions if symptoms, labs, age-related screening, or family history make them relevant.
Show technical evidence
Risk-score evidence
- testosterone nmol l: risk percentile 91.5%, coverage 93%, PGS000696.
- testosterone: risk percentile 90.9%, coverage 100%, PGS001914.
- estradiol 212 pmol l: risk percentile 90.5%, coverage 88%, PGS001182.
- nontoxic multinodular goiter: risk percentile 82.5%, coverage 100%, PGS001814.
- thyrotoxicosis with or without goiter: risk percentile 10.2%, coverage 100%, PGS001815.
- prostate cancer: risk percentile 9.3%, coverage 87%, PGS001292.
Protein pathway context
- INSL3: predicted level percentile 92.3%, R2 0.7312; pathway context only.
- KLK3: predicted level percentile 94%, R2 0.6695; pathway context only.
- MSMB: predicted level percentile 84.6%, R2 0.5861; pathway context only.
- PSCA: predicted level percentile 17.9%, R2 0.7849; pathway context only.
Candidate variants
- Variant rs10505483 CC: snpedia_context.
Cancer screening context
background
Cancer-related evidence is mixed, with digestive, brain-tumor, lymphoma, skin, and prostate context pointing in different directions.
Full explanation
The cancer-related evidence is not a single clean signal. There is elevated context for number of self-reported cancers, digestive neoplasm, and glioma, plus variant context for colorectal cancer and lymphoma-related immune traits.
At the same time, prostate cancer, early-onset colorectal cancer, non-melanoma skin cancer, and male genital tract cancer genetic scores are protective or comparatively low. This is why the category is framed as screening context, not cancer risk prediction.
The most practical use is to make family history and standard screening conversations more complete. Genetics should not override age-appropriate screening guidance.
This category becomes worth discussing or reviewing if there is strong family history of cancer, unusually early cancers in relatives, rectal bleeding, unexplained weight loss, persistent new headaches or neurological symptoms, changing skin lesions, or a clinician is deciding how to tailor screening.
What to watch forKeep standard age-appropriate screening on track, and use family history or persistent warning signs as the main trigger for a more tailored review.
Show technical evidence
Risk-score evidence
- number of self reported cancers: risk percentile 95.3%, coverage 88%, PGS001005.
- benign neoplasm of other parts of digestive system: risk percentile 97.5%, coverage 100%, PGS001812.
- non melanoma skin cancer: risk percentile 16.4%, coverage 89%, PGS001040.
- prostate cancer: risk percentile 9.3%, coverage 87%, PGS001292.
- male genital tract cancer: risk percentile 16.5%, coverage 69%, PGS001111.
Protein pathway context
- KLK12: predicted level percentile 0.8%, R2 0.7889; pathway context only.
- KLK3: predicted level percentile 94%, R2 0.6695; pathway context only.
- MSMB: predicted level percentile 84.6%, R2 0.5861; pathway context only.
- PSCA: predicted level percentile 17.9%, R2 0.7849; pathway context only.
Candidate variants
- Intergenic rs10795668 GG: snpedia_context.
- Variant rs10484561 TT: snpedia_context.
- Variant rs10505483 CC: 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.
CYP2C19
RAPID METABOLIZER
*1/*17
Affected drugs: Clopidogrel, Omeprazole, Pantoprazole, Citalopram, Escitalopram, Voriconazole
CYP2C9
INTERMEDIATE METABOLIZER
*1/*3
Affected drugs: Warfarin, Phenytoin, Celecoxib, Flurbiprofen, Losartan, Simvastatin
CYP3A5
POOR METABOLIZER
*3/*3
Affected drugs: Tacrolimus, Sirolimus
UGT1A1
INDETERMINATE
*1/*80
Affected drugs: Irinotecan, Atazanavir
CYP2B6
INTERMEDIATE METABOLIZER
*1/*9
Affected drugs: Efavirenz, Bupropion, Methadone
NAT2
POOR METABOLIZER
*5/*5
Affected drugs: hydralazine
This report comes from consumer microarray data with statistical imputation. Confirm clinically before changing prescriptions.