hu50B3F5 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
Heart, lipids, and circulation
near-term focus
Several inherited signals point toward artery, lipid, blood-pressure timing, heart-structure, and rhythm traits, partly offset by lower signals for some cholesterol and heart-attack models.
Full explanation
This category appeared because heart and circulation signals clustered across artery disease, lipid metabolism, blood-pressure timing, artery-wall measures, heart mass, and electrical timing.
The pattern is mixed rather than absolute. Some evidence points upward for artery and lipid pathways, while other evidence sits lower for heart attack, chronic ischemic heart disease, high cholesterol, and atrial fibrillation. Protein evidence adds inflammatory and vascular-remodeling context, and medication-processing evidence matters if statins or certain blood-pressure medicines ever enter the picture.
This becomes worth reviewing with a clinician if there is a strong family history of early heart disease, high cholesterol or blood-pressure readings, chest discomfort, breathlessness with exertion, fainting, palpitations, or if a statin or hydralazine is being considered.
What to watch forPrioritize routine blood pressure and lipid review, and flag the medication-safety findings before starting a statin or hydralazine.
Show technical evidence
Risk-score evidence
- coronary artery disease: risk percentile 97%, coverage 98%, PGS000058.
- disorders of lipoid metabolism: risk percentile 97%, coverage 100%, PGS001821.
- high blood pressure age at diagnosis: risk percentile 92.1%, coverage 88%, PGS000935.
- left ventricular mass index: risk percentile 92.7%, coverage 100%, PGS003427.
- qrs duration: risk percentile 96.7%, coverage 100%, PGS001948.
- mean carotid imtat 120 150 210 240 degrees: risk percentile 84.6%, coverage 100%, PGS001966.
Protein pathway context
- IL6R: predicted level percentile 97.4%, R2 0.666; pathway context only.
- CFHR2: predicted level percentile 87.3%, R2 0.7304; pathway context only.
- MST1: predicted level percentile 81.3%, R2 0.6781; pathway context only.
- VNN1: predicted level percentile 80.9%, R2 0.5856; pathway context only.
- MMP3: predicted level percentile 4.4%, R2 0.5052; pathway context only.
- PZP: predicted level percentile 8.8%, R2 0.5407; pathway context only.
Candidate variants
- CDKN2B rs1063192 AG: confirmation_required.
- LOC105377979 rs1015451 TT: snpedia_context.
Medication-response context
- SLCO1B1: Decreased Function, *14/*15; affected medicines include Simvastatin (myopathy risk), Atorvastatin, Rosuvastatin, Pravastatin.
- NAT2: Poor Metabolizer, *16/*30; affected medicines include hydralazine.
Weight, glucose, and insulin balance
near-term focus
Body-size and diabetes-related signals are elevated, but several insulin-sensitivity and waist-related signals are lower, creating a divergent metabolic pattern.
Full explanation
The evidence points to a tendency toward higher body-size and diabetes-related traits, including body mass, obesity, incident diabetes, and insulin secretion.
At the same time, the evidence does not look like a simple insulin-resistance pattern. Some insulin-action, insulin-sensitivity, insulin-resistance, and waist-related signals sit on the lower side, suggesting that weight regulation and glucose handling may diverge.
This becomes worth reviewing if weight changes are hard to explain, fasting glucose or long-term glucose markers rise, waist size changes quickly, there is a strong family history of diabetes, or energy levels and hunger patterns shift in a sustained way.
What to watch forUse a steady weight-stable routine built around fiber, protein, resistance training, and regular glucose-related lab review if clinical context supports it.
Show technical evidence
Risk-score evidence
- overweight obesity and other hyperalimentation: risk percentile 97.2%, coverage 100%, PGS001825.
- obesity: risk percentile 90.7%, coverage 96%, PGS003959.
- incident type 2 diabetes: risk percentile 92.3%, coverage 99%, PGS002779.
- non insulin dependent diabetes: risk percentile 84.1%, coverage 90%, PGS001294.
- type 2 diabetes: risk percentile 81.1%, coverage 99%, PGS000125.
- insulin secretion rate: risk percentile 81.1%, coverage 96%, PGS000835.
Protein pathway context
- VNN1: predicted level percentile 80.9%, R2 0.5856; pathway context only.
- DPEP1: predicted level percentile 95.3%, R2 0.548; pathway context only.
- PNLIPRP2: predicted level percentile 83.7%, R2 0.7241; pathway context only.
- LRPAP1: predicted level percentile 14.5%, R2 0.6658; pathway context only.
- MAN2B2: predicted level percentile 12%, R2 0.599; pathway context only.
- CGA: predicted level percentile 15.2%, R2 0.5201; pathway context only.
Candidate variants
- RMST rs11109072 CC: snpedia_context.
- PCSK5 rs11144688 GG: snpedia_context.
- Variant rs10089517 CC: snpedia_context.
- LOC101929727 rs10509540 TT: snpedia_context.
- APOA1-AS,SIK3 rs10047462 TT: snpedia_context.
Bilirubin, kidney, liver, and gallbladder chemistry
near-term focus
The strongest chemistry cluster involves bilirubin, urinary blood, urine creatinine, urea, kidney disease context, liver enzymes, and gallbladder inflammation.
Full explanation
This category is one of the clearest chemistry clusters in the report. It combines very strong bilirubin evidence with urinary and kidney-related signals, including hematuria, urine creatinine, urea, and chronic kidney disease context.
The same cluster also includes liver-enzyme and gallbladder evidence, plus variant and protein context around kidney, liver, immune, and alkaline-phosphatase biology. A medication-processing finding related to bilirubin handling adds extra context, but it is not a diagnosis by itself.
This becomes worth discussing if there is visible blood in urine, persistent dark urine, jaundice, unexplained itching, right-upper-abdominal pain, abnormal kidney or liver labs, gallbladder symptoms, or a family history of kidney or liver conditions.
What to watch forTreat unusual urine color, blood in urine, jaundice, gallbladder-type pain, or abnormal kidney or liver labs as reasons to bring this genetic context into a clinical review.
Show technical evidence
Risk-score evidence
- total bilirubin: risk percentile 99.9%, coverage 100%, PGS001942.
- hematuria: risk percentile 99.7%, coverage 100%, PGS001863.
- creatininein urine: risk percentile 96.9%, coverage 100%, PGS001944.
- urea: risk percentile 93.3%, coverage 100%, PGS001980.
- urea mmol l: risk percentile 84.6%, coverage 92%, PGS000701.
- chronic kidney disease: risk percentile 80%, coverage 100%, PGS004128.
Protein pathway context
- DPEP1: predicted level percentile 95.3%, R2 0.548; pathway context only.
- LCP1: predicted level percentile 80.1%, R2 0.5128; pathway context only.
- VNN1: predicted level percentile 80.9%, R2 0.5856; pathway context only.
Candidate variants
- LOC107986166 rs10937329 TT: snpedia_context.
- MIR22,MIR22HG,WDR81 rs11078597 TT: snpedia_context.
- Variant rs11117432 GG: snpedia_context.
- Variant rs10892279 GG: snpedia_context.
Medication-response context
- UGT1A1: Indeterminate, *80/*80; affected medicines include Irinotecan, Atazanavir.
Immune and inflammatory balance
useful to review
Immune evidence is broad and mixed: inflammation, psoriasis-like, bowel, lupus-related, and white-cell signals are higher, while allergy, eczema, rheumatoid arthritis, and monocyte signals are lower.
Full explanation
This category appeared because many immune and inflammation signals cluster together, including inflammatory markers, psoriasis-like skin traits, bowel inflammation, lupus context, white-cell traits, and immune-signaling proteins.
The direction is not uniformly high. Allergy, eczema, rheumatoid arthritis, and monocyte signals sit lower, and some protein evidence points to immune regulation as much as immune activation. Variant evidence supports bowel, skin, autoimmune, and immune-response context, but these are not diagnoses.
This becomes worth reviewing if there are persistent inflammatory symptoms, recurring unexplained rashes, bowel symptoms, unusual joint pain with stiffness, recurrent infections, abnormal inflammatory markers, or if immune-modulating or anti-inflammatory medicines are being considered.
What to watch forUse this as immune-context awareness, especially if inflammatory symptoms, bowel changes, rashes, or relevant medication decisions arise.
Show technical evidence
Risk-score evidence
- polymyalgia rheumatica: risk percentile 98.4%, coverage 100%, PGS001878.
- psoriasis: risk percentile 96.5%, coverage 90%, PGS001313.
- c reactive protein mg l: risk percentile 93.3%, coverage 93%, PGS000675.
- inflammatory bowel disease: risk percentile 90.7%, coverage 100%, PGS004013.
- white blood cellcount: risk percentile 90%, coverage 96%, PGS003924.
- neutrophil percentage: risk percentile 88.7%, coverage 96%, PGS003943.
Protein pathway context
- IL6R: predicted level percentile 97.4%, R2 0.666; pathway context only.
- LILRA6: predicted level percentile 97.1%, R2 0.5266; pathway context only.
- CCL24: predicted level percentile 96.8%, R2 0.7115; pathway context only.
- CFHR2: predicted level percentile 87.3%, R2 0.7304; pathway context only.
- MST1: predicted level percentile 81.3%, R2 0.6781; pathway context only.
- PGLYRP2: predicted level percentile 89.9%, R2 0.5671; pathway context only.
Candidate variants
- IL23R rs10889677 CC: snpedia_context.
- Variant rs10995271 GG: snpedia_context.
- Variant rs11117432 GG: snpedia_context.
- Variant rs10892279 GG: snpedia_context.
- LOC101929727 rs10509540 TT: snpedia_context.
- ZHX2 rs10108684 GG: snpedia_context.
Medication-response context
- CYP2C9: Intermediate Metabolizer, *1/*2; affected medicines include Warfarin, Phenytoin, Celecoxib, Flurbiprofen, Losartan, Simvastatin.
- CYP3A5: Poor Metabolizer, *3/*3; affected medicines include Tacrolimus, Sirolimus.
- NAT2: Poor Metabolizer, *16/*30; affected medicines include hydralazine.
Sleep, airway, and daytime energy
near-term focus
Snoring, daytime dozing, sleep duration, napping, insomnia, lung-function, airway-obstruction, and lung immune-protein evidence cluster together.
Full explanation
This category links sleep quality with airway and lung biology. The strongest practical signals involve snoring, daytime dozing, sleep duration, napping, and insomnia.
Airway and lung evidence adds depth, including lung-function, chronic airway obstruction, lung-surfactant protein, immune-complement context, and asthma-related variant context. Genetics cannot say whether sleep apnea, asthma, or another breathing condition is present, but it can flag a tendency worth noticing.
This becomes worth reviewing if loud snoring, witnessed breathing pauses, daytime sleepiness, morning headaches, reduced exercise tolerance, wheeze, chronic cough, or persistent insomnia becomes a real-world pattern.
What to watch forIf snoring, daytime sleepiness, breathing symptoms, or persistent insomnia show up, bring up both sleep and airway context rather than treating them separately.
Show technical evidence
Risk-score evidence
- snoring: risk percentile 98.3%, coverage 100%, PGS002006.
- daytime dozing sleeping: risk percentile 97.6%, coverage 100%, PGS001995.
- sleep duration: risk percentile 90.2%, coverage 100%, PGS001978.
- nap during day: risk percentile 87.5%, coverage 92%, PGS001000.
- sleeplessness insomnia: risk percentile 84.3%, coverage 100%, PGS001932.
- lung function: risk percentile 96.1%, coverage 92%, PGS001237.
Protein pathway context
- SFTPD: predicted level percentile 86.5%, R2 0.5378; pathway context only.
- CFHR2: predicted level percentile 87.3%, R2 0.7304; pathway context only.
- IL6R: predicted level percentile 97.4%, R2 0.666; pathway context only.
Candidate variants
- PYHIN1 rs1101999 TT: snpedia_context.
Clotting, veins, and blood-flow awareness
useful to review
Clot and varicose-vein signals are elevated, with platelet and blood-cell context adding nuance.
Full explanation
This category appeared because inherited evidence points toward blood clot or deep-vein-thrombosis context, previous clot-related traits, and varicose veins.
The evidence does not prove a clotting disorder. Platelet and blood-cell signals are mixed, and protein evidence points more broadly to immune-complement, cell adhesion, and platelet-related biology.
This becomes worth discussing if there is a personal or family history of clots, unexplained leg swelling or pain, shortness of breath with chest pain, pregnancy or estrogen-related clot concerns, planned major surgery, long immobilization, or prominent symptomatic varicose veins.
What to watch forTreat clot history, new one-sided leg swelling, chest pain with breathlessness, or planned high-risk immobilization as reasons to mention this context clinically.
Show technical evidence
Risk-score evidence
- blood clot or deep vein thrombosis: risk percentile 94.9%, coverage 84%, PGS000931.
- previously blood clot in the legor lung: risk percentile 85%, coverage 86%, PGS001278.
- varicose veins: risk percentile 81.3%, coverage 100%, PGS001845.
- platelet count: risk percentile 5.3%, coverage 96%, PGS003932.
- rr interval: risk percentile 5.1%, coverage 100%, PGS001907.
Protein pathway context
- SIGLEC5: predicted level percentile 80.7%, R2 0.505; pathway context only.
- CFHR2: predicted level percentile 87.3%, R2 0.7304; pathway context only.
- ICAM2: predicted level percentile 15.3%, R2 0.5536; pathway context only.
- PZP: predicted level percentile 8.8%, R2 0.5407; pathway context only.
Candidate variants
- RCL1 rs10758658 GG: snpedia_context.
Cancer screening and family-history context
useful to review
Breast, lung, endometrial, colon, and ovarian-context evidence appears, balanced by lower signals for several cancer or polyp models.
Full explanation
This category is screening context, not a cancer prediction. The evidence includes several breast subtype signals, lung cancer, endometrial cancer, benign colon neoplasm, and ovarian variant context.
The interpretation is mixed because early colorectal cancer, ovarian cancer, basal cell carcinoma, and anal or rectal polyp signals are lower in the same evidence set. Protein and variant evidence add context but do not confirm disease.
This becomes worth reviewing if there is a strong family history of breast, ovarian, uterine, colon, or lung cancer; unusual bleeding; new breast changes; persistent cough; unexplained weight change; bowel changes; or if screening timing is uncertain.
What to watch forStay current with age- and sex-appropriate screening, and use family history or new symptoms to decide whether earlier review is warranted.
Show technical evidence
Risk-score evidence
- lung cancer: risk percentile 93%, coverage 87%, PGS001392.
- endometrial cancer: risk percentile 83.9%, coverage 96%, PGS002737.
- benign neoplasm of colon: risk percentile 90.9%, coverage 100%, PGS001811.
- basal cell carcinoma: risk percentile 12%, coverage 100%, PGS003416.
- anal and rectal polyp: risk percentile 7.4%, coverage 100%, PGS001859.
Protein pathway context
- PSCA: predicted level percentile 5%, R2 0.7849; pathway context only.
- HDGF: predicted level percentile 92.4%, R2 0.6401; pathway context only.
- MST1: predicted level percentile 81.3%, R2 0.6781; pathway context only.
Candidate variants
- LINC00824 rs10088218 GG: snpedia_context.
- CDKN2B rs1063192 AG: confirmation_required.
- Variant rs10484561 TT: snpedia_context.
Vision and hearing awareness
useful to review
Macular, hearing, visual-focus, and glaucoma-context evidence appears, while tinnitus evidence is lower.
Full explanation
This category combines eye and hearing evidence. The strongest eye signal involves macular degeneration context, with additional visual-focus and glaucoma-related context from variant evidence.
Hearing difficulty signals are also elevated, while tinnitus severity sits lower. This means the category is about practical sensory awareness, not a conclusion that a vision or hearing condition is present.
This becomes worth reviewing if there are changes in central vision, new distortion, reduced night or reading vision, eye pressure concerns, family history of glaucoma or macular disease, hearing difficulty in conversation, or sudden hearing changes.
What to watch forUse vision or hearing changes, family history, or eye-pressure concerns as triggers for routine optometry, ophthalmology, or audiology review.
Show technical evidence
Risk-score evidence
- macular degenerationof retina nos: risk percentile 98.4%, coverage 100%, PGS001834.
- hearing difficulty problems: risk percentile 90.8%, coverage 100%, PGS001891.
- hearing difficulty and deafness: risk percentile 89.6%, coverage 90%, PGS001252.
- hearing difficulty: risk percentile 86.5%, coverage 89%, PGS001253.
- tinnitus severity: risk percentile 1%, coverage 87%, PGS001533.
- 3mm weak meridian: risk percentile 84.4%, coverage 93%, PGS001362.
Protein pathway context
- ENPP5: predicted level percentile 8.6%, R2 0.6477; pathway context only.
Candidate variants
- Variant rs10089517 CC: snpedia_context.
- CDKN2B rs1063192 AG: confirmation_required.
Bones, joints, tendons, and strength
useful to review
Osteoarthritis, osteoporosis, tendon or cyst, fibroblastic, foot-shape, and lower grip-strength signals appear, with lower signals for some disk and hip-arthritis models.
Full explanation
This category points to connective tissue, joint, bone-density, and strength context. Elevated signals include osteoarthritis, osteoporosis without fracture, ganglion or tendon cysts, fibroblastic disorders, hallux valgus, and lower hand-grip strength.
The evidence is mixed because some intervertebral disk, broad arthropathy, and hip-arthritis signals are lower. Protein evidence points to tissue remodeling and structural support, and medication-processing evidence is relevant if certain anti-inflammatory pain medicines are used.
This becomes worth reviewing if joint pain limits activity, grip strength changes, stress fractures or low bone-density results appear, recurrent tendon problems develop, foot pain affects walking, or anti-inflammatory medicines are used often.
What to watch forBuild a strength and bone-loading routine, and mention the medication-safety finding if anti-inflammatory pain medicines become regular or prescription-level.
Show technical evidence
Risk-score evidence
- osteoarthritis: risk percentile 99.2%, coverage 89%, PGS001290.
- osteoporosis without pathological fracture: risk percentile 94.6%, coverage 93%, PGS001274.
- ganglion and cyst of synovium tendon and bursa: risk percentile 96.8%, coverage 100%, PGS001879.
- fibroblastic disorders: risk percentile 95.1%, coverage 81%, PGS001031.
- hallux valgus: risk percentile 88.9%, coverage 100%, PGS001881.
- hand grip strength: risk percentile 86.7%, coverage 100%, PGS001927.
Protein pathway context
- MMP3: predicted level percentile 4.4%, R2 0.5052; pathway context only.
- TNN: predicted level percentile 83.7%, R2 0.5604; pathway context only.
- MST1: predicted level percentile 81.3%, R2 0.6781; pathway context only.
Candidate variants
- Variant rs10892279 GG: snpedia_context.
- Variant rs11177669 GG: snpedia_context.
Medication-response context
- CYP2C9: Intermediate Metabolizer, *1/*2; affected medicines include Warfarin, Phenytoin, Celecoxib, Flurbiprofen, Losartan, Simvastatin.
Brain, stress sensitivity, and habit patterns
background
Mood-care, neuroticism, sensitivity, addiction-context, cannabis-context, sleep, and brain-region research signals cluster, but brain-region evidence is background only.
Full explanation
This category combines behavioral and nervous-system context. There are elevated signals for having sought care for nerves, anxiety, tension, or depression, neuroticism, sensitivity to hurt feelings, addiction-related factors, cannabis-use context, and sleep traits.
Brain-region signals are included only as research context. They can support awareness of brain and sleep biology, but they must not be read as a brain disease diagnosis or a medical-risk conclusion by themselves. Lower Alzheimer-related evidence adds protective nuance.
This becomes worth reviewing if stress sensitivity affects daily life, sleep disruption persists, substance-use patterns become hard to control, mood or anxiety symptoms emerge, there is a strong family history, or a medication with nervous-system effects is being considered.
What to watch forTreat sleep stability, stress load, and substance-use patterns as the practical levers, and mention the medication-safety finding if relevant medicines are prescribed.
Show technical evidence
Risk-score evidence
- total volume of white matter hyperintensities: risk percentile 99.8%, coverage 87%, PGS001534.
- volume of caudate: risk percentile 96%, coverage 89%, PGS001543.
- volume of thalamus: risk percentile 91%, coverage 89%, PGS001637.
- volume of brain stem 4th ventricle: risk percentile 89.3%, coverage 88%, PGS001539.
- volume of grey matter in superior frontal gyrus: risk percentile 18.5%, coverage 88%, PGS001597.
- neuroticism score: risk percentile 89.6%, coverage 100%, PGS001996.
Protein pathway context
- PSPN: predicted level percentile 98.8%, R2 0.5175; pathway context only.
- ENPP5: predicted level percentile 8.6%, R2 0.6477; pathway context only.
- ADGRB3: predicted level percentile 82.2%, R2 0.597; pathway context only.
Candidate variants
- Variant rs10427255 TT: snpedia_context.
Medication-response context
- CYP2B6: Intermediate Metabolizer, *1/*9; affected medicines include Efavirenz, Bupropion, Methadone.
Blood count and immune-cell balance
background
Red-cell distribution, white-cell, neutrophil, platelet, hemoglobin, red-cell, hematocrit, and monocyte signals form a mixed lab-context category.
Full explanation
This category is about routine blood-count context. The evidence includes higher red-cell distribution, white-cell count, and neutrophil percentage signals, alongside lower platelet, hemoglobin, red-cell, hematocrit, monocyte percentage, and monocyte count signals.
Protein and variant evidence adds immune-cell, platelet, folate-handling, bacterial-defense, and iron-status context. This does not mean blood counts are abnormal; it only suggests which routine lab patterns may be more informative if they appear.
This becomes worth reviewing if routine blood tests show repeated abnormalities, unexplained fatigue, recurrent infections, easy bruising, inflammatory symptoms, or a clinician is already evaluating anemia, high white cells, low platelets, or unusual blood indices.
What to watch forIf routine blood counts are abnormal more than once, interpret them with attention to both inflammation and red-cell or platelet patterns.
Show technical evidence
Risk-score evidence
- red blood celldistribution width: risk percentile 95.9%, coverage 100%, PGS001908.
- white blood cellcount: risk percentile 90%, coverage 96%, PGS003924.
- neutrophil percentage: risk percentile 88.7%, coverage 96%, PGS003943.
- platelet count: risk percentile 5.3%, coverage 96%, PGS003932.
- haemoglobin concentration: risk percentile 1.6%, coverage 92%, PGS001400.
- red blood cellcount: risk percentile 11.4%, coverage 96%, PGS003925.
Protein pathway context
- SIGLEC5: predicted level percentile 80.7%, R2 0.505; pathway context only.
- FOLR3: predicted level percentile 9.3%, R2 0.9226; pathway context only.
- PGLYRP2: predicted level percentile 89.9%, R2 0.5671; pathway context only.
- LCP1: predicted level percentile 80.1%, R2 0.5128; pathway context only.
Candidate variants
- RCL1 rs10758658 GG: snpedia_context.
- LOC105376219 rs10980800 TT: snpedia_context.
- APOA1-AS,SIK3 rs10047462 TT: snpedia_context.
Mouth, stomach, and gut lining
useful to review
Mouth-ulcer, duodenal-ulcer, bowel-inflammation, gallbladder, and gut-lining evidence is present, while malabsorption, celiac, and rectal-polyp signals are lower.
Full explanation
This category appeared because mouth ulcers, duodenal ulcer, inflammatory bowel context, and gallbladder evidence clustered with digestive and immune proteins.
The picture is mixed. Malabsorption, celiac disease, and anal or rectal polyp signals are lower, so the evidence does not point to a single digestive condition. Variant evidence adds Crohn, ulcerative colitis, rheumatoid or celiac-context, and immune-gut background.
This becomes worth reviewing if recurring mouth ulcers, persistent upper-abdominal pain, black stools, unexplained digestive symptoms, bowel habit changes, blood in stool, food-triggered symptoms, or gallbladder-type pain becomes relevant.
What to watch forUse recurring mouth, stomach, bowel, or gallbladder symptoms as the trigger to bring this gut-lining context into a medical review.
Show technical evidence
Risk-score evidence
- mouth ulcers: risk percentile 96.3%, coverage 90%, PGS000947.
- duodenal ulcer: risk percentile 96.2%, coverage 79%, PGS001390.
- inflammatory bowel disease: risk percentile 90.7%, coverage 100%, PGS004013.
- cholecystitis: risk percentile 82.9%, coverage 87%, PGS000942.
- intestinal malabsorption: risk percentile 0.1%, coverage 88%, PGS000940.
- celiac disease: risk percentile 17.9%, coverage 100%, PGS001856.
Protein pathway context
- PNLIPRP2: predicted level percentile 83.7%, R2 0.7241; pathway context only.
- MST1: predicted level percentile 81.3%, R2 0.6781; pathway context only.
- IL6R: predicted level percentile 97.4%, R2 0.666; pathway context only.
Candidate variants
- Variant rs10995271 GG: snpedia_context.
- IL23R rs10889677 CC: snpedia_context.
- Variant rs10892279 GG: snpedia_context.
Skin, hair, hormone, and reproductive signaling
background
Skin, hair-follicle, balding-pattern, testosterone, thyroid, growth-factor, and reproductive-protein signals create a background hormone and tissue-signaling card.
Full explanation
This category is mostly pathway context. It includes psoriasis-like skin evidence, sebaceous cyst, hair and hair-follicle traits, balding pattern, testosterone, estrogen, thyroid, growth-factor, and reproductive hormone or egg-recognition protein evidence.
Some protein names come from reproductive biology, but in this report they are treated only as genetically predicted pathway signals. They do not diagnose fertility status, hormone levels, thyroid disease, or skin disease.
This becomes worth reviewing if there are persistent skin flares, cysts, notable hair changes, menstrual-cycle changes, fertility planning questions, thyroid-like symptoms, or abnormal hormone labs.
What to watch forUse real skin, hair, cycle, fertility-planning, thyroid-like, or hormone-lab changes as the reason to make this background evidence clinically relevant.
Show technical evidence
Risk-score evidence
- psoriasis: risk percentile 96.5%, coverage 90%, PGS001313.
- sebaceous cyst: risk percentile 93.7%, coverage 100%, PGS001874.
- diseases of hair and hair follicles: risk percentile 90.8%, coverage 100%, PGS001873.
- hair balding pattern: risk percentile 81.1%, coverage 100%, PGS001987.
- testosterone: risk percentile 81.2%, coverage 100%, PGS001914.
- estradiol 212 pmol l: risk percentile 6.8%, coverage 88%, PGS001182.
Protein pathway context
- ZP3: predicted level percentile 99.8%, R2 0.7546; pathway context only.
- FSHB: predicted level percentile 80.6%, R2 0.6068; pathway context only.
- CGA: predicted level percentile 15.2%, R2 0.5201; pathway context only.
- CCL24: predicted level percentile 96.8%, R2 0.7115; pathway context only.
- CRISP2: predicted level percentile 98.3%, R2 0.5552; pathway context only.
- ACRV1: predicted level percentile 97.6%, R2 0.5881; pathway context only.
Candidate variants
- C9orf3 rs10821415 CC: snpedia_context.
- MIR22,MIR22HG,WDR81 rs11078597 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
SLCO1B1
DECREASED FUNCTION
*14/*15
Affected drugs: Simvastatin (myopathy risk), Atorvastatin, Rosuvastatin, Pravastatin
UGT1A1
INDETERMINATE
*80/*80
Affected drugs: Irinotecan, Atazanavir
CYP2B6
INTERMEDIATE METABOLIZER
*1/*9
Affected drugs: Efavirenz, Bupropion, Methadone
NAT2
POOR METABOLIZER
*16/*30
Affected drugs: hydralazine
This report comes from consumer microarray data with statistical imputation. Confirm clinically before changing prescriptions.