hu5FCE15 Frozen Validation Report
343 PRS models · 1,636 protein predictions · 139 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
Glucose, energy and pancreatic balance
near-term focus
Your genetics show a mixed metabolic pattern: several diabetes and pancreatic signals stand out, but several insulin-sensitivity and long-term glucose signals look protective.
Full explanation
This is not a simple high-risk metabolic result. Some signals point toward diabetes-related and pancreatic-hormone tendencies, including a tendency toward stronger insulin or glucose-regulation themes.
At the same time, several important counter-signals look favorable, including insulin sensitivity, long-term glucose and glucose-challenge context. That makes this a divergent category: the genetics suggest that metabolism may be responsive to weight, activity, sleep and diet, rather than pointing in only one direction.
This category would be worth discussing or reviewing if future blood sugar results change, if there is a strong family history of diabetes, or if real-world changes appear such as unexpected fatigue after meals, unusual thirst, unexplained weight change or recurrent low-energy episodes.
What to watch forKeep the focus on steady meals, regular activity and periodic routine metabolic labs if family history, symptoms or weight changes make that relevant.
Show technical evidence
Risk-score evidence
- non insulin dependent diabetes: risk percentile 93.8%, coverage 90%, PGS001294.
- diabetes: risk percentile 84.7%, coverage 90%, PGS001327.
- fasting proinsulin: risk percentile 83%, coverage 95%, PGS000840.
- hypoglycemia: risk percentile 99.7%, coverage 100%, PGS001820.
- insulin resistance: risk percentile 9.7%, coverage 98%, PGS000877.
- glycated haemoglobin: risk percentile 13.8%, coverage 100%, PGS001953.
Protein pathway context
- VNN1: predicted level percentile 11.2%, R2 0.5856; pathway context only.
- XPNPEP2: predicted level percentile 11.3%, R2 0.5305; pathway context only.
Candidate variants
- Variant rs10105606 CC: snpedia_context.
- Variant rs10937273 GG: snpedia_context.
Body composition and training response
near-term focus
Waist and weight-change signals suggest body-composition attention, while grip strength and limb-fat signals add a more favorable performance angle.
Full explanation
The body-composition pattern is mixed. Waist and weight-change signals suggest that central body composition may be a useful focus, especially if lifestyle, sleep or stress shift in an unfavorable direction.
The same evidence also includes favorable strength and limb-fat signals. That points toward a profile where resistance training, aerobic capacity and consistent routines may be especially useful, rather than relying only on weight as the main marker.
This category would be worth reviewing if waist size, fitness, recovery, blood pressure or metabolic labs change, or if training progress stalls despite consistent effort.
What to watch forUse waist trend, strength progress and aerobic fitness as practical feedback, rather than focusing only on scale weight.
Show technical evidence
Risk-score evidence
- waist circumference: risk percentile 89.7%, coverage 99%, PGS000827.
- weight change compared with 1 year ago: risk percentile 85.5%, coverage 91%, PGS001006.
- hand grip strength: risk percentile 5.799999999999997%, coverage 100%, PGS001927.
- arm fat percentage: risk percentile 10.7%, coverage 97%, PGS003915.
- hip circumference: risk percentile 6.3%, coverage 96%, PGS003894.
- height: risk percentile 6.400000000000006%, coverage 99%, PGS000758.
Protein pathway context
- CRTAC1: predicted level percentile 13.6%, R2 0.5057; pathway context only.
- TNN: predicted level percentile 10%, R2 0.5604; pathway context only.
- AFAP1: predicted level percentile 91.6%, R2 0.5176; pathway context only.
Candidate variants
- PCSK5 rs11144688 GG: snpedia_context.
- SLCO1C1 rs10770705 CC: snpedia_context.
- SUPT3H rs10948222 TT: snpedia_context.
Cholesterol and cardiovascular structure
useful to review
Lipid handling and heart-structure signals stand out, but several major vascular, clotting and rhythm signals lean protective.
Full explanation
This category is mixed rather than uniformly concerning. Cholesterol-handling, lipid-metabolism, blood-pressure timing, heart-valve and heart-muscle signals were among the stronger cardiovascular findings.
There is also meaningful protective balance. Signals related to ischemic heart disease, heart attack, clotting, atrial rhythm and triglycerides lean favorable, so the profile does not read as a broad cardiovascular-risk pattern.
This would be worth discussing if routine cholesterol or blood-pressure results are unusual, if there is a strong family history of early heart disease or cardiomyopathy, or if symptoms such as exertional chest pressure, fainting, unexplained breathlessness or persistent palpitations occur.
What to watch forTreat cholesterol, blood pressure and exercise tolerance as the practical anchors; seek medical review if symptoms or strong family history align with the heart-structure signals.
Show technical evidence
Risk-score evidence
- hdl cholesterol: risk percentile 99.9%, coverage 97%, PGS000660.
- disorders of lipoid metabolism: risk percentile 92.1%, coverage 100%, PGS001821.
- cholesterol: risk percentile 82%, coverage 100%, PGS001895.
- triglyceride levels: risk percentile 8.7%, coverage 97%, PGS003401.
- high blood pressure age at diagnosis: risk percentile 89.6%, coverage 88%, PGS000935.
- nstemi: risk percentile 1.1%, coverage 82%, PGS001048.
Protein pathway context
- APOBR: predicted level percentile 12.5%, R2 0.67; pathway context only.
- VNN1: predicted level percentile 11.2%, R2 0.5856; pathway context only.
- PDGFRB: predicted level percentile 85.1%, R2 0.5601; pathway context only.
Candidate variants
- Variant rs10105606 CC: snpedia_context.
- ZBTB17 rs10927875 TT: snpedia_context.
Skin barrier, eczema and sun response
near-term focus
Skin, hair-follicle, eczema and sun-response signals converge with skin-barrier and immune protein context.
Full explanation
The skin signal is one of the clearest clusters. The evidence points toward skin-barrier and follicle biology, with eczema or dermatitis context and sunlight response also standing out.
This does not mean a skin condition is present. It suggests that skin barrier, irritation, inflammation and sun response may be areas where genetics adds useful background.
This category would be worth reviewing if there are persistent rashes, recurrent follicle or cyst problems, unusual sun sensitivity, changing lesions, or a personal or family history that makes skin monitoring more relevant.
What to watch forUse practical skin protection and early attention to persistent irritation, recurrent cysts, eczema-like flares or unusual sun reactions.
Show technical evidence
Risk-score evidence
- sebaceous cyst: risk percentile 99.9%, coverage 100%, PGS001874.
- diseases of hair and hair follicles: risk percentile 99.9%, coverage 100%, PGS001873.
- follicular cysts of skin and subcutaneous tissue: risk percentile 99.9%, coverage 83%, PGS000963.
- eczema dermatitis: risk percentile 92.9%, coverage 87%, PGS000944.
- other dermatitis: risk percentile 93.6%, coverage 89%, PGS000927.
- atopic eczema or atopic disease: risk percentile 92.1%, coverage 98%, PGS003459.
Protein pathway context
- PRSS53: predicted level percentile 99.6%, R2 0.5164; pathway context only.
- KLK12: predicted level percentile 97.8%, R2 0.7889; pathway context only.
- CCL24: predicted level percentile 4.5%, R2 0.7115; pathway context only.
- TPSAB1: predicted level percentile 88.3%, R2 0.5954; pathway context only.
Allergy, airway and immune activation
near-term focus
Allergic rhinitis, atopic disease, asthma and broader inflammatory signals are prominent, with many immune-cell protein signals in the same area.
Full explanation
The immune pattern is broad. Allergy, atopic disease, rhinitis, asthma and inflammatory conditions all appear in the evidence, supported by several immune-cell signaling proteins.
There is nuance: some autoimmune-related signals are elevated, while other autoimmune signals are protective. This points to immune-system tuning rather than a single disease conclusion.
This category would be worth discussing if there are recurrent allergy or airway symptoms, persistent unexplained inflammation, mouth ulcers, joint symptoms, bowel inflammation, or if anti-inflammatory pain medicines are being used often enough that medication-processing context matters.
What to watch forPay attention to recurring allergy, airway, joint, skin or bowel inflammation patterns, and share medication-processing context before frequent anti-inflammatory medicine use.
Show technical evidence
Risk-score evidence
- vasomotor and allergic rhinitis: risk percentile 96.8%, coverage 89%, PGS001109.
- general atopic disease: risk percentile 96.5%, coverage 98%, PGS003458.
- asthma: risk percentile 87.2%, coverage 100%, PGS001849.
- psoriasis: risk percentile 94.9%, coverage 90%, PGS001313.
- polymyalgia rheumatica: risk percentile 99.9%, coverage 100%, PGS001878.
- arthritis: risk percentile 91.2%, coverage 88%, PGS001135.
Protein pathway context
- FCGR2A: predicted level percentile 96.5%, R2 0.5811; pathway context only.
- CD300LF: predicted level percentile 96.5%, R2 0.5333; pathway context only.
- SIGLEC5: predicted level percentile 95.4%, R2 0.505; pathway context only.
- IL17RA: predicted level percentile 4.1%, R2 0.5078; pathway context only.
- IL1RL1: predicted level percentile 8.2%, R2 0.5009; pathway context only.
- LILRB2: predicted level percentile 11.4%, R2 0.5829; pathway context only.
Candidate variants
- Variant rs10892279 GG: snpedia_context.
- Variant rs10276619 GG: snpedia_context.
- Variant rs10484561 TT: snpedia_context.
- SQRDL rs1044032 TT: snpedia_context.
Medication-response context
- CYP2C9: Intermediate Metabolizer, *1/*2; affected medicines include Warfarin, Phenytoin, Celecoxib, Flurbiprofen, Losartan, Simvastatin.
Gut, bowel and colorectal context
useful to review
Bowel polyp, colon neoplasm, intestinal inflammation and duodenitis signals appear together, with one early colorectal signal leaning protective.
Full explanation
The gut-related evidence forms a meaningful cluster. It includes bowel polyp and benign colon-neoplasm context, broader intestinal-disease signals, duodenitis and inflammatory-bowel context.
This is not a diagnosis and does not replace normal age-based screening rules. The protective early colorectal signal also softens the interpretation, so the result is best treated as awareness and context.
This category would be worth discussing if there is blood in stool, persistent bowel change, unexplained abdominal symptoms, iron-related abnormalities, a strong family history of colorectal disease, or when routine screening timing is being planned.
What to watch forFollow normal bowel-screening guidance and treat persistent bowel changes, bleeding, strong family history or unexplained iron changes as reasons to review this context.
Show technical evidence
Risk-score evidence
- anal and rectal polyp: risk percentile 98.8%, coverage 100%, PGS001859.
- benign neoplasm of colon: risk percentile 87.9%, coverage 100%, PGS001811.
- other diseases of intestine: risk percentile 88.6%, coverage 80%, PGS001516.
- duodenitis: risk percentile 81.5%, coverage 100%, PGS001852.
- inflammatory bowel disease: risk percentile 80.2%, coverage 100%, PGS004013.
- mouth ulcers: risk percentile 81.2%, coverage 90%, PGS000947.
Protein pathway context
- IL17RA: predicted level percentile 4.1%, R2 0.5078; pathway context only.
- FCGR2A: predicted level percentile 96.5%, R2 0.5811; pathway context only.
- CLEC7A: predicted level percentile 7.8%, R2 0.5374; pathway context only.
- PGLYRP2: predicted level percentile 85.9%, R2 0.5671; pathway context only.
Candidate variants
- Intergenic rs10795668 GG: snpedia_context.
- Variant rs10892279 GG: snpedia_context.
Eye and retinal awareness
useful to review
Retinal and eye-shape related signals are elevated, especially in areas that can overlap with metabolic or age-related eye health.
Full explanation
The eye-related category is mostly driven by genetic score evidence. Retinal, macular and eye-shape signals stand out, with some corneal measurements also appearing in the background.
Because some retinal signals can overlap with metabolic health, this category should be read alongside the mixed glucose findings rather than as a standalone eye diagnosis.
This would be worth reviewing if vision changes, distortion, new floaters, diabetes-related lab changes, high blood pressure, strong family history of retinal disease or routine optometry findings make eye health more relevant.
What to watch forKeep routine eye care in place, and treat new visual changes or metabolic lab changes as reasons to bring this genetic context into the conversation.
Show technical evidence
Risk-score evidence
- diabetic eye disease: risk percentile 98.6%, coverage 80%, PGS001028.
- retinal disorders in diseases classified elsewhere: risk percentile 98.4%, coverage 80%, PGS001276.
- macular degenerationof retina nos: risk percentile 87%, coverage 100%, PGS001834.
- 3mm weak meridian: risk percentile 93.9%, coverage 93%, PGS001362.
- corneal hysteresis: risk percentile 13.6%, coverage 91%, PGS001381.
- corneal resistance factor: risk percentile 14.5%, coverage 91%, PGS001383.
Urinary and mineral-handling context
background
Urinary creatinine, potassium and blood-in-urine signals appear, but stone, calcium and phosphate signals add protective nuance.
Full explanation
This category points toward urinary and mineral-handling context. It includes urinary creatinine, urinary potassium and blood-in-urine signals, which can be relevant to kidney, urinary tract or hydration-related interpretation.
The result is mixed because urinary-stone, calcium and phosphate signals lean protective. That makes it an awareness category rather than a strong disease-risk conclusion.
This would be worth discussing if urine tests, kidney-function labs, recurrent urinary symptoms, visible blood in urine, high blood pressure or a history of stones ever make the urinary system clinically relevant.
What to watch forUse routine urine or kidney labs as the real-world anchor, and review this context if urinary symptoms, abnormal urine results or stone history appear.
Show technical evidence
Risk-score evidence
- creatininein urine: risk percentile 98.1%, coverage 100%, PGS001944.
- potassium in urine: risk percentile 95.9%, coverage 100%, PGS001974.
- hematuria: risk percentile 87.6%, coverage 100%, PGS001863.
- urinary calculus: risk percentile 17.8%, coverage 100%, PGS001864.
- phosphate mmol l: risk percentile 5.4%, coverage 92%, PGS000692.
- calcium: risk percentile 6.7%, coverage 100%, PGS001893.
Protein pathway context
- XPNPEP2: predicted level percentile 11.3%, R2 0.5305; pathway context only.
- VNN1: predicted level percentile 11.2%, R2 0.5856; pathway context only.
Candidate variants
- B4GALT1-AS1 rs10813960 TT: snpedia_context.
Brain ageing, cognition and hearing
background
Brain-ageing and hearing signals are present, but cognition and several mood-related signals provide protective or favorable context.
Full explanation
The brain-related evidence is mixed and should be read carefully. Alzheimer-related and ventricular-volume signals appear, while selected brain-region scores are included only as research context and are not medical conclusions by themselves.
There are also favorable signals, including fluid-intelligence context and lower signals for loneliness, probable depression and tinnitus severity. The overall result is awareness rather than a prediction of cognitive decline.
This category would be worth discussing if there is strong family history of dementia, noticeable memory or thinking changes, new hearing problems, significant head injury history, or persistent mood changes that are affecting daily life.
What to watch forTreat sleep, hearing, cardiovascular fitness and cognitive engagement as practical anchors, and review this context if family history or real-world changes line up.
Show technical evidence
Risk-score evidence
- alzheimers disease: risk percentile 94.5%, coverage 100%, PGS002035.
- volume of ventricular cerebrospinal fluid: risk percentile 81.3%, coverage 87%, PGS001070.
- volume of white matter: risk percentile 4.9%, coverage 88%, PGS001641.
- volume of brain stem 4th ventricle: risk percentile 18.4%, coverage 88%, PGS001539.
- fluid intelligence score: risk percentile 18.700000000000003%, coverage 100%, PGS001919.
- hearing difficulty problems: risk percentile 96.5%, coverage 100%, PGS001891.
Protein pathway context
- CD33: predicted level percentile 12.3%, R2 0.7974; pathway context only.
- ADGRB3: predicted level percentile 12%, R2 0.597; pathway context only.
- DBH: predicted level percentile 82.9%, R2 0.6647; pathway context only.
Candidate variants
- CACNA1C rs1006737 GG: snpedia_context; Post-traumatic stress disorder.
- Variant rs10276619 GG: snpedia_context.
Male hormone and prostate biology
background
Prostate, sex-hormone and male reproductive protein signals appear together, but this is pathway context rather than a diagnosis.
Full explanation
This category is specific to male hormone and prostate biology. Prostate enlargement context, sex-hormone binding, estradiol and several reproductive or prostate-related protein signals appeared together.
A prostate-related variant signal adds context, but this should not be read as a diagnosis or as a reason to assume current prostate disease.
This would be worth discussing if urinary flow changes, nighttime urination, pelvic symptoms, fertility questions, hormone-related symptoms, abnormal prostate screening results or strong family history make the topic relevant.
What to watch forUse symptoms, family history and routine age-appropriate prostate discussions as the trigger for review, rather than acting on genetics alone.
Show technical evidence
Risk-score evidence
- hyperplasia of prostate: risk percentile 83%, coverage 80%, PGS001338.
- estradiol 212 pmol l: risk percentile 95%, coverage 88%, PGS001182.
- sex hormone binding globulin: risk percentile 88.1%, coverage 100%, PGS001977.
Protein pathway context
- MSMB: predicted level percentile 97.1%, R2 0.5861; pathway context only.
- FSHB: predicted level percentile 89.9%, R2 0.6068; pathway context only.
- INSL3: predicted level percentile 85.6%, R2 0.7312; pathway context only.
- EDDM3B: predicted level percentile 92%, R2 0.659; pathway context only.
- ACRV1: predicted level percentile 10.2%, R2 0.5881; pathway context only.
- CRISP2: predicted level percentile 17.8%, R2 0.5552; pathway context only.
Candidate variants
- Variant rs10505483 CC: snpedia_context.
Blood-cell and nutrient-status context
background
Red-cell, hematocrit, total-protein and vitamin-related anemia signals are present, while some blood-cell size and platelet signals are more favorable.
Full explanation
The blood-cell pattern includes hematocrit, red-cell count, total-protein and vitamin-related anemia context. Variant evidence also points toward blood-cell and iron-status background.
This is not enough to say there is anemia, high hematocrit or a nutrient deficiency. It means routine blood results would be the correct place to interpret whether this genetic background matters.
This category would be worth reviewing if a complete blood count, iron markers, fatigue pattern, dietary restriction, vegan or low-animal-food diet, numbness or unexplained exercise intolerance ever raises the question.
What to watch forLet routine blood counts and iron or vitamin markers guide interpretation if symptoms, diet pattern or lab results make this relevant.
Show technical evidence
Risk-score evidence
- haematocrit percentage: risk percentile 94.5%, coverage 100%, PGS001925.
- red blood cellcount: risk percentile 92%, coverage 96%, PGS003925.
- total protein: risk percentile 89.9%, coverage 100%, PGS002001.
- vitamin b12 deficiency induced anemia: risk percentile 80.4%, coverage 86%, PGS001305.
- mean corpuscular volume: risk percentile 11.1%, coverage 100%, PGS001990.
- mean corpuscular hemoglobin: risk percentile 12.4%, coverage 100%, PGS001989.
Protein pathway context
- APOBR: predicted level percentile 12.5%, R2 0.67; pathway context only.
Candidate variants
- GPT,LOC101928953 rs1063739 CC: snpedia_context.
- APOA1-AS,SIK3 rs10047462 TT: snpedia_context.
- LOC105376219 rs10980800 TT: snpedia_context.
- ATP2B4 rs10900585 TT: snpedia_context.
Liver, bile and urate context
background
A liver-enzyme signal and urate context appear, while bilirubin and gallbladder-related signals lean protective.
Full explanation
This category is lower priority but still evidence-backed. A liver-enzyme signal appears alongside urate-related context and metabolic oxidative-stress protein context.
There is also protective balance: bilirubin and gallbladder-related signals lean favorable. This makes the finding a background metabolic category rather than a strong liver or gout conclusion.
This would be worth discussing if liver enzymes, uric acid, gout-like joint episodes, heavy alcohol exposure, medication changes, abdominal pain or gallbladder history ever make the topic clinically relevant.
What to watch forUse routine liver and urate results as the deciding evidence if symptoms, alcohol exposure, medication changes or family history make this relevant.
Show technical evidence
Risk-score evidence
- chronic elevation of alanine aminotransferase: risk percentile 82.6%, coverage 96%, PGS002732.
- ast to alt ratio: risk percentile 19.1%, coverage 93%, PGS000674.
- total bilirubin: risk percentile 12.5%, coverage 100%, PGS001942.
- cholelithiasis and cholecystitis: risk percentile 11.3%, coverage 100%, PGS001861.
Protein pathway context
- VNN1: predicted level percentile 11.2%, R2 0.5856; pathway context only.
- XPNPEP2: predicted level percentile 11.3%, R2 0.5305; pathway context only.
Candidate variants
- B4GALT1-AS1 rs10813960 TT: 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
NAT2
POOR METABOLIZER
*5/*5
Affected drugs: hydralazine
This report comes from consumer microarray data with statistical imputation. Confirm clinically before changing prescriptions.