hu5BB600 Frozen Validation Report
344 PRS models · 1,636 protein predictions · 143 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
Blood clotting and vascular structure
near-term focus
Your strongest inherited theme is a clotting and venous-inflammation pattern, with added blood-cell and vascular-structure context. This does not mean a clot will happen, but it is worth knowing before surgery, long travel, immobilization, hormone therapy, or unexplained leg or chest symptoms.
Full explanation
Several inherited signals point in the same direction around blood clotting, deep-vein clotting, and vein inflammation. The blood-cell signals also lean active, which makes this more than a single isolated result.
A blood-group protein signal and a confirmation-required ABCC6 finding add vascular biology context. The ABCC6 finding should not be treated as a diagnosis from this report, especially because it is reported as needing confirmation, but it is relevant enough to keep inside the vascular section.
The practical meaning is situational. Genetics may matter most when another trigger is present, such as major travel, surgery, long immobilization, smoking exposure, dehydration, acute illness, or a personal or family history of clotting.
This category becomes worth discussing if there is unexplained one-sided leg swelling or pain, shortness of breath, chest pain, sudden calf tenderness after immobility, a family history of clotting, or if a clinician is planning surgery or medication that can change clot risk.
What to watch forMention this clotting pattern before surgery, prolonged immobilization, long-haul travel planning, or any review for unexplained leg swelling, calf pain, chest pain, or shortness of breath.
Show technical evidence
Risk-score evidence
- blood clot or deep vein thrombosis: risk percentile 99.9%, coverage 85%, PGS000931.
- deep vein thrombosis: risk percentile 99.7%, coverage 89%, PGS001266.
- phlebitis and thrombophlebitis: risk percentile 98.6%, coverage 86%, PGS000961.
- haematocrit percentage: risk percentile 89.4%, coverage 100%, PGS001925.
- high light scatter reticulocyte percentage: risk percentile 87.8%, coverage 96%, PGS003951.
Protein pathway context
- ABO: predicted level percentile 1.2%, R2 0.6423; pathway context only.
- CFHR4: predicted level percentile 81.2%, R2 0.6355; pathway context only.
Candidate variants
- ABCC6 rs72653706 AG: confirmation_required.
- Variant rs11104870 TT: snpedia_context.
- RCL1 rs10758658 GG: snpedia_context.
- ATP2B4 rs10900585 TT: snpedia_context.
Heart and lipid risk with rhythm protection
near-term focus
Heart and lipid signals lean upward for coronary, angina, aortic valve, circulation, cholesterol, and heart-structure traits, but rhythm-related signals lean more protective. Statin handling is relevant if cholesterol treatment is ever considered.
Full explanation
The cardiovascular evidence is mixed but important. Several inherited signals point toward coronary artery disease, angina, aortic valve disease, high cholesterol, broader circulation traits, and heart-structure measures.
At the same time, rhythm-related signals for atrial fibrillation and atrial flutter lean lower. That means this does not look like a single across-the-board heart-risk pattern; it looks more like vascular, lipid, and structural context with relatively favorable rhythm context.
Protein-based pathway signals add immune, inflammation, blood-group, and metabolic context. A medication-handling finding also matters if a statin is ever prescribed, because statin choice and dose can be affected by inherited transport differences.
This category becomes worth discussing in the setting of chest pressure, exertional symptoms, fainting, a new murmur, unusual breathlessness, a strong family history of early heart disease, abnormal cholesterol results, or if a clinician is considering cholesterol-lowering medication.
What to watch forUse this as context for cholesterol and heart-risk conversations, especially with exertional symptoms, family history, abnormal lipids, or future statin prescribing.
Show technical evidence
Risk-score evidence
- coronary artery disease: risk percentile 94.8%, coverage 98%, PGS000058.
- angina pectoris: risk percentile 93.7%, coverage 89%, PGS001261.
- circulatory disease nec: risk percentile 96.5%, coverage 100%, PGS001847.
- high cholesterol: risk percentile 81.9%, coverage 90%, PGS000936.
- left ventricular mass index: risk percentile 92.8%, coverage 100%, PGS003427.
- lv ejection fraction: risk percentile 87.6%, coverage 82%, PGS001412.
Protein pathway context
- ABO: predicted level percentile 1.2%, R2 0.6423; pathway context only.
- IL6R: predicted level percentile 12%, R2 0.666; pathway context only.
- GC: predicted level percentile 86.7%, R2 0.6763; pathway context only.
- CFHR4: predicted level percentile 81.2%, R2 0.6355; pathway context only.
Candidate variants
- ZBTB17 rs10927875 TT: snpedia_context.
- C9orf3 rs10821415 CC: snpedia_context.
- AGPAT1,EGFL8,PPT2-EGFL8 rs1061808 GG: snpedia_context.
Medication-response context
- SLCO1B1: Decreased Function, *15/*37; affected medicines include Simvastatin (myopathy risk), Atorvastatin, Rosuvastatin, Pravastatin.
Metabolic fuel handling
near-term focus
Diabetes-labelled signals are elevated, but glucose tolerance, waist size, early body size, and progression-related signals lean more favorable. The best interpretation is mixed metabolic tendency, not a simple prediction.
Full explanation
This section is divergent. Several inherited signals point toward type 2 diabetes or diabetes-related labels, including eye-related diabetes context. That makes blood-sugar biology a meaningful category.
The counterweight is that other signals point toward lower two-hour glucose, lower waist size, lower early body size, and lower likelihood of early insulin requirement after diabetes diagnosis. Those signals soften the interpretation and suggest that lifestyle, body composition, and real lab values would matter a lot.
Protein and variant context adds lipid, adiponectin, amino-acid, and metabolic-pathway support. Together, the evidence suggests paying attention to metabolic resilience rather than assuming a fixed outcome.
This category becomes worth reviewing if fasting glucose, long-term glucose, triglycerides, waist size, weight trajectory, energy swings, thirst, frequent urination, vision changes, or family history make blood-sugar control a real-world question.
What to watch forKeep habits aimed at stable blood sugar and lipids; review this context if glucose, triglycerides, waist size, energy swings, vision changes, or family history become relevant.
Show technical evidence
Risk-score evidence
- type 2 diabetes: risk percentile 88.1%, coverage 99%, PGS000125.
- non insulin dependent diabetes: risk percentile 86.5%, coverage 90%, PGS001294.
- diabetes: risk percentile 84.8%, coverage 90%, PGS001327.
- diabetic eye disease: risk percentile 83.5%, coverage 80%, PGS001028.
- two hour glucose during ogtt: risk percentile 0.7%, coverage 95%, PGS000839.
- waist circumference: risk percentile 17.5%, coverage 99%, PGS000827.
Protein pathway context
- GC: predicted level percentile 86.7%, R2 0.6763; pathway context only.
- MEP1B: predicted level percentile 13.9%, R2 0.6752; pathway context only.
- INSL3: predicted level percentile 85%, R2 0.7312; pathway context only.
Candidate variants
- Variant rs10503669 CC: snpedia_context.
- Variant rs10105606 CC: snpedia_context.
- Variant rs10937273 GG: snpedia_context.
- LOC107984063 rs10211524 GG: snpedia_context.
Immune and inflammatory balance
useful to review
Inflammatory joint and psoriasis signals lean upward, while eczema, dermatitis, thyroid, and some systemic inflammatory signals lean lower. Protein evidence shows both immune activation and immune dampening.
Full explanation
The immune picture is not one-directional. Arthritis, rheumatoid arthritis, psoriasis, and viral-immune context appear on the elevated side, so inflammatory joint and skin overlap is a meaningful inherited theme.
Protective-leaning evidence also appears. Eczema, dermatitis, thyroid conditions, polymyalgia, and some systemic connective-tissue or lung-fibrosis signals lean lower, which means this is not a broad immune-risk conclusion.
Protein signals add pathway depth: some point toward immune activation and complement biology, while others point lower for immune-cell signaling and viral sensing. That pattern fits an immune system with specific inflammatory channels rather than general immune fragility.
This category becomes worth discussing if there is persistent joint swelling, prolonged morning stiffness, recurrent unexplained rashes, psoriasis-like plaques, unusual inflammatory flares, eye inflammation, family history of autoimmune disease, or lab changes that suggest inflammation.
What to watch forTreat this as inflammatory-context awareness; discuss it if persistent joint stiffness, swelling, psoriasis-like skin changes, unexplained rashes, or family history appear.
Show technical evidence
Risk-score evidence
- arthritis: risk percentile 98.4%, coverage 88%, PGS001135.
- psoriasis: risk percentile 84.8%, coverage 90%, PGS001313.
- zebra antigen for epstein barr virus: risk percentile 87.9%, coverage 79%, PGS001772.
- eczema dermatitis: risk percentile 0.1%, coverage 87%, PGS000944.
- atopic eczema or atopic disease: risk percentile 1.6%, coverage 98%, PGS003459.
- other dermatitis: risk percentile 3.4%, coverage 89%, PGS000927.
Protein pathway context
- IL1RAP: predicted level percentile 96.9%, R2 0.706; pathway context only.
- PILRB: predicted level percentile 82.6%, R2 0.6283; pathway context only.
- CFHR4: predicted level percentile 81.2%, R2 0.6355; pathway context only.
- IL6R: predicted level percentile 12%, R2 0.666; pathway context only.
- LILRB5: predicted level percentile 0.8%, R2 0.7926; pathway context only.
- TLR3: predicted level percentile 11.7%, R2 0.8019; pathway context only.
Candidate variants
- Variant rs10892279 GG: snpedia_context.
- Variant rs10484561 TT: snpedia_context.
Sun, skin, and hair tendencies
useful to review
Skin evidence points toward sunburn, tanning response, sunlight-related skin change, facial aging, hair-follicle traits, balding pattern, and sebaceous cyst tendency. This is mainly practical skin-care context.
Full explanation
The skin-related evidence clusters strongly around sunlight response. Childhood sunburn, tanning response, chronic sunlight-related skin change, and facial-aging signals all appear together.
Hair and surface-skin traits also show up, including hair-follicle disease, balding pattern, and sebaceous-cyst context. These are not dangerous by themselves, but they help explain why this becomes a visible-trait and prevention category.
A lower signal for use of sun protection is included as behavior context, not as proof of current habits. The useful takeaway is that the inherited skin profile makes consistent sun protection and attention to changing lesions more relevant.
This category becomes worth discussing if there are changing moles, non-healing skin spots, repeated sunburns, strong family history of skin cancer, unusual cysts, inflammatory scalp changes, or hair changes that feel rapid or distressing.
What to watch forPrioritize consistent sun protection and review changing or non-healing skin spots, repeated sunburns, unusual cysts, or rapid hair-pattern changes with a clinician.
Show technical evidence
Risk-score evidence
- childhood sunburn: risk percentile 99.5%, coverage 87%, PGS001257.
- ease of skin tanning: risk percentile 94.6%, coverage 100%, PGS001937.
- skin changes due to chronic exposure to nonionising radiation: risk percentile 90.2%, coverage 84%, PGS000950.
- facial aging looking about your age: risk percentile 82.8%, coverage 91%, PGS001071.
- use of sun uv protection: risk percentile 15%, coverage 100%, PGS001993.
- diseases of hair and hair follicles: risk percentile 85.4%, coverage 100%, PGS001873.
Mood, sleep, and reward sensitivity
useful to review
Mood, anxiety-care, insomnia, tiredness, risk-taking, addiction, smoking, cannabis, and alcohol signals cluster strongly. This does not mean these issues are present, but it supports a lower threshold for sleep and stress hygiene.
Full explanation
The brain-behavior evidence clusters around mood, sleep, reward, and substance-use sensitivity. Depression-labelled signals, anxiety-care signals, recent low-mood context, insomnia, tiredness, addiction-related traits, risk-taking, smoking initiation, cannabis exposure, and alcohol-use context all appear.
There are also protective-leaning signals, including lower attention-deficit context and lower unenthusiasm/disinterest context. That means this is not a diagnosis and not a fixed personality description.
Neurological protein signals and a smoking-initiation variant context add support, but the practical value is still behavioral: sleep regularity, alcohol moderation, avoiding nicotine initiation or relapse, and noticing stress-reward loops early.
This category becomes worth discussing if low mood, anxiety, insomnia, fatigue, substance cravings, escalating alcohol use, nicotine use, or major stress begins affecting work, relationships, training, or daily functioning.
What to watch forUse this as a cue to protect sleep regularity, alcohol boundaries, and nicotine avoidance; discuss it if mood, sleep, fatigue, cravings, or stress-reward loops start affecting daily life.
Show technical evidence
Risk-score evidence
- addiction risk factors: risk percentile 99.3%, coverage 100%, PGS005215.
- lifetime major depressive disorder: risk percentile 94.1%, coverage 98%, PGS000139.
- major depression: risk percentile 87.7%, coverage 98%, PGS000140.
- sleeplessness insomnia: risk percentile 84.9%, coverage 100%, PGS001932.
- freq of tiredness lethargy in last 2 weeks: risk percentile 82.4%, coverage 92%, PGS001080.
- risk taking behaviour: risk percentile 90.2%, coverage 91%, PGS001049.
Protein pathway context
- ENPP5: predicted level percentile 91.9%, R2 0.6477; pathway context only.
- PDCD6: predicted level percentile 87.5%, R2 0.6598; pathway context only.
Candidate variants
- Variant rs10789369 GG: snpedia_context.
Cancer screening and family-history context
useful to review
Cancer-related evidence appears across lung, glioma, blood cancer, digestive neoplasm, and colorectal-polyp context. It should be used to personalize screening conversations, not to conclude that cancer is present.
Full explanation
Several inherited cancer-related signals are present, including lung cancer, glioma, lymphocytic leukemia, overall cancer-count context, digestive neoplasm, and anal or rectal polyp context. These are not diagnostic findings.
There is also protective-leaning early colorectal cancer evidence, which softens the digestive-cancer interpretation. Variant evidence adds colorectal and cancer-context support, but it should be handled as background unless confirmed and interpreted clinically.
The strongest practical use is family-history and screening context. Smoking-related inherited behavior signals also matter because avoiding smoke exposure is one of the most actionable ways to lower lung-related risk.
This category becomes worth discussing if there is a strong family history of cancer, smoking exposure, unexplained weight loss, blood in stool, persistent bowel changes, new neurological symptoms, unusual bruising, persistent swollen glands, or if age-based screening decisions are being planned.
What to watch forUse this as context for routine age-based screening and family-history review, especially with smoke exposure, bowel changes, blood in stool, neurological changes, unusual bruising, or persistent swollen glands.
Show technical evidence
Risk-score evidence
- lung cancer: risk percentile 98.1%, coverage 87%, PGS001392.
- lymphocytic leukemia: risk percentile 86.1%, coverage 99%, PGS000077.
- number of self reported cancers: risk percentile 95.9%, coverage 88%, PGS001005.
- benign neoplasm of other parts of digestive system: risk percentile 97.5%, coverage 100%, PGS001812.
- anal and rectal polyp: risk percentile 89.6%, coverage 100%, PGS001859.
- smoking initiation: risk percentile 80.6%, coverage 100%, PGS003747.
Protein pathway context
- DKKL1: predicted level percentile 93.6%, R2 0.8321; pathway context only.
Candidate variants
- Intergenic rs10795668 GG: snpedia_context.
- CDKN2B rs1063192 AG: confirmation_required.
- Variant rs10484561 TT: snpedia_context.
Prostate and male hormone context
useful to review
Prostate enlargement, prostate cancer variant context, low predicted PSA-pathway signal, estradiol, hormone-binding, growth-factor, and testicular hormone-pathway evidence form a male-specific background category.
Full explanation
The male-specific evidence deserves its own section. There is an elevated inherited signal for prostate enlargement, plus several prostate cancer variant associations. These are not diagnoses and do not say that prostate disease is present.
The protein evidence includes a low predicted PSA-pathway signal. That matters because real PSA blood-test interpretation can be influenced by biology; actual PSA results still need clinical context.
Hormone-related inherited signals also appear, including estradiol, hormone-binding, growth-factor, and testicular hormone-pathway context. These are pathway signals, not evidence of a current hormone problem.
This category becomes worth discussing if urinary symptoms, night urination, weak stream, pelvic pain, abnormal PSA results, fertility concerns, libido or energy changes, family history of prostate cancer, or age-based screening questions become relevant.
What to watch forUse this for prostate and hormone-context conversations if urinary symptoms, abnormal PSA results, family history, fertility concerns, or age-based screening questions arise.
Show technical evidence
Risk-score evidence
- hyperplasia of prostate: risk percentile 95%, coverage 80%, PGS001338.
- estradiol 212 pmol l: risk percentile 83.6%, coverage 88%, PGS001182.
- sex hormone binding globulin: risk percentile 4.6%, coverage 100%, PGS001977.
- igf 1: risk percentile 4.9%, coverage 100%, PGS001960.
Protein pathway context
- KLK3: predicted level percentile 12%, R2 0.6695; pathway context only.
- INSL3: predicted level percentile 85%, R2 0.7312; pathway context only.
Candidate variants
- Intergenic rs10896449 GG: snpedia_context.
- EEFSEC rs10934853 CC: snpedia_context.
- Variant rs10505483 CC: snpedia_context.
- C9orf3 rs10821415 CC: snpedia_context.
Digestive and liver-pattern context
useful to review
Digestive sensitivity, abdominal pain, bowel-frequency, malabsorption, digestive neoplasm, polyp, and liver-enzyme signals appear, while gallbladder and some functional digestive signals lean lower.
Full explanation
Digestive evidence appears across several angles: sensitive stomach, abdominal pain, bowel frequency, intestinal malabsorption, digestive neoplasm, and anal or rectal polyp context. Liver-enzyme signals also appear.
This is balanced by lower gallbladder-related signals and lower functional digestive disorder and diverticular disease signals. That makes the section mixed rather than simply risk-skewed.
Protein and variant context adds digestive enzyme, folate-immune, liver-enzyme, bilirubin, and colorectal context. The useful interpretation is to take persistent digestive change seriously while recognizing that genetics alone does not identify the cause.
This category becomes worth discussing if bowel habits change persistently, blood appears in stool, abdominal pain is recurrent or severe, unexplained weight loss occurs, food tolerance changes, liver enzymes are abnormal, or age-based digestive screening is being planned.
What to watch forKeep this in mind for persistent bowel changes, blood in stool, recurrent abdominal pain, food-tolerance changes, abnormal liver enzymes, or routine digestive screening decisions.
Show technical evidence
Risk-score evidence
- benign neoplasm of other parts of digestive system: risk percentile 97.5%, coverage 100%, PGS001812.
- anal and rectal polyp: risk percentile 89.6%, coverage 100%, PGS001859.
- abdominal pain: risk percentile 86.2%, coverage 100%, PGS001884.
- sensitive stomach: risk percentile 83.3%, coverage 100%, PGS002004.
- average number of times bowels opened per day: risk percentile 81.2%, coverage 85%, PGS001376.
- intestinal malabsorption: risk percentile 80.3%, coverage 88%, PGS000940.
Protein pathway context
- SPINT3: predicted level percentile 87.1%, R2 0.7363; pathway context only.
- MEP1B: predicted level percentile 13.9%, R2 0.6752; pathway context only.
- FOLR3: predicted level percentile 9.8%, R2 0.9226; pathway context only.
Candidate variants
- MIR22,MIR22HG,WDR81 rs11078597 TT: snpedia_context.
- Intergenic rs10795668 GG: snpedia_context.
- UGT1A6,UGT1A7,UGT1A8,UGT1A9,UGT1A10 rs1105879 AA: snpedia_context.
Eye pressure and vision context
background
Refraction, eye pressure, and glasses-related signals are elevated, while myopia diagnosis, retinal detachment, cataract, and corneal measures lean lower. This is useful context for eye exams.
Full explanation
The eye evidence is mixed. Signals related to refraction, intraocular pressure, and wearing glasses or contact lenses are elevated.
Protective-leaning signals are also present for myopia diagnosis, retinal detachment, cataract, and corneal measures. That means the category should not be read as broad eye disease risk.
A CDKN2B-region variant adds optic-nerve and glaucoma-context evidence, but it is not a diagnosis. The practical value is to make sure pressure and optic-nerve context are not ignored during routine eye care.
This category becomes worth discussing if there is a family history of glaucoma, rising eye pressure, optic-nerve findings, sudden vision changes, halos, eye pain, new floaters, or unexplained changes in prescription.
What to watch forUse this as context during routine eye care, especially with family history of glaucoma, high eye pressure, optic-nerve findings, eye pain, sudden vision changes, or changing prescription.
Show technical evidence
Risk-score evidence
- spherical power: risk percentile 97.6%, coverage 93%, PGS001100.
- intraocular pressure: risk percentile 86.3%, coverage 93%, PGS000879.
- wears glasses or contact lenses: risk percentile 82.5%, coverage 100%, PGS001924.
- myopia diagnosis: risk percentile 1.2%, coverage 100%, PGS001994.
- retinal detachments and breaks: risk percentile 7.5%, coverage 85%, PGS000990.
- cataract: risk percentile 8.6%, coverage 100%, PGS001837.
Candidate variants
- CDKN2B rs1063192 AG: confirmation_required.
Bone, joint, and training structure
background
Joint and knee-arthritis signals appear alongside high heel-ultrasound traits and lower hip, spine, body-size, arm-mass, and hip-circumference signals. Training should build strength progressively without overloading joints.
Full explanation
The musculoskeletal pattern is mixed. Arthritis and knee-arthrosis signals are elevated, and other arthropathy context also appears.
At the same time, hip arthrosis and spine-disc disorder signals lean lower, while heel-ultrasound traits are high. Body-structure signals such as arm mass, hip circumference, and early body size lean lower, which makes strength and tissue-capacity training especially relevant.
Variant context adds bone and height-related background, but the main practical conclusion is about load management: build capacity steadily, avoid abrupt volume jumps, and use resistance training to protect joints and metabolic health.
This category becomes worth reviewing if joint swelling, persistent knee pain, repeated tendon pain, stress injuries, back or hip symptoms, loss of strength, or a major change in training load affects daily movement or exercise.
What to watch forPrioritize progressive strength, mobility, and joint-friendly conditioning; adjust load if knee pain, tendon pain, swelling, stress injuries, or sudden training changes appear.
Show technical evidence
Risk-score evidence
- arthritis: risk percentile 98.4%, coverage 88%, PGS001135.
- gonarthrosis arthrosis of knee: risk percentile 82.8%, coverage 90%, PGS001192.
- other arthropathies: risk percentile 82.1%, coverage 100%, PGS001877.
- heel quantitative ultrasound index direct entry: risk percentile 90.9%, coverage 93%, PGS000952.
- heel broadband ultrasound attenuation direct entry: risk percentile 90.6%, coverage 100%, PGS001956.
- coxarthrosis arthrosis of hip: risk percentile 12.2%, coverage 88%, PGS000967.
Candidate variants
- Variant rs10494112 GG: snpedia_context.
- Variant rs10748128 TT: snpedia_context.
Kidney, urate, and mineral handling
background
Kidney filtration, urine albumin, urate, gout, calcium, and phosphate evidence mostly leans favorable. This is a protective-context category rather than a warning sign.
Full explanation
This is one of the more favorable categories. Urea, cystatin, urine albumin, urate, gout, calcium, and phosphate signals mostly lean lower or protective.
A kidney-related immune protein signal and a blood-urea variant context are included as background, but the overall direction is protective rather than concerning.
The value of this section is nuance. It helps balance the report so that not every category is framed as risk, and it shows that inherited kidney and urate context is not a major pressure point in this evidence set.
This category becomes worth discussing only if real-world kidney labs change, blood pressure becomes persistently high, gout-like joint pain appears, kidney stones occur, urine findings are abnormal, or medication choices place extra load on kidney handling.
What to watch forTreat this as favorable background, and revisit it only if kidney labs, urine findings, gout-like pain, stones, blood pressure, or kidney-relevant medications become important.
Show technical evidence
Risk-score evidence
- urea mmol l: risk percentile 0.9%, coverage 92%, PGS000701.
- urea: risk percentile 1.5%, coverage 100%, PGS001980.
- cystatin c mg l: risk percentile 11%, coverage 93%, PGS000680.
- microalbumin in urine: risk percentile 13%, coverage 100%, PGS001967.
- serum urate: risk percentile 16.1%, coverage 99%, PGS000126.
- gout: risk percentile 18.3%, coverage 83%, PGS001249.
Protein pathway context
- LILRB5: predicted level percentile 0.8%, R2 0.7926; pathway context only.
Candidate variants
- LOC107986166 rs10937329 TT: snpedia_context.
Brain structure research context
background
Several brain-region research signals are high or low, but these are background findings only. They should not be read as a diagnosis, disease prediction, or fixed cognitive profile.
Full explanation
The evidence includes research-context signals for brain-region measures such as hippocampus, frontal grey matter, putamen, white matter changes, ventricle-related measures, caudate, thalamus, and visual-cortex region context.
These models are not clinical brain scans and do not show what is happening in the brain today. They are best used as background for how inherited variation can relate to brain structure in research datasets.
Neurological protein-pathway signals support this as a brain-background category, but they do not turn it into a disease conclusion. The mood, sleep, and reward section is more practically actionable.
This category becomes worth discussing only if there are real neurological changes, such as new memory concerns, seizures, weakness, speech changes, head injury effects, unexplained headaches, or a strong family history of neurological disease.
What to watch forKeep this as research background; review it only if real neurological symptoms, cognitive changes, head injury effects, or strong family history make it relevant.
Show technical evidence
Risk-score evidence
- volume of hippocampus: risk percentile 97.3%, coverage 88%, PGS001630.
- volume of grey matter in superior frontal gyrus: risk percentile 96.3%, coverage 89%, PGS001597.
- volume of putamen: risk percentile 95.5%, coverage 88%, PGS001636.
- total volume of white matter hyperintensities: risk percentile 92.8%, coverage 88%, PGS001534.
- volume of brain stem 4th ventricle: risk percentile 92.3%, coverage 88%, PGS001539.
- volume of caudate: risk percentile 85%, coverage 89%, PGS001543.
Protein pathway context
- ENPP5: predicted level percentile 91.9%, R2 0.6477; pathway context only.
- PDCD6: predicted level percentile 87.5%, R2 0.6598; pathway context only.
Dental and oral-health tendency
background
A very strong dental-related inherited signal appears as a standalone finding. It is lower-confidence because it is not supported by other evidence lanes, but it is practical enough to include.
Full explanation
One dental-related inherited signal is very high. It does not diagnose current dental disease and does not say anything about current oral hygiene, diet, dental history, or access to dental care.
Because this is a single-lane finding, it is lower confidence than categories supported by multiple evidence types. Still, oral health is practical and modifiable, so the signal is worth surfacing.
The most sensible use is preventive: regular dental care, attention to gum health, and early response to tooth or mouth changes.
This category becomes worth discussing if there is gum bleeding, tooth loosening, recurring dental infections, jaw pain, mouth ulcers that do not heal, tooth loss, or a family pattern of significant dental disease.
What to watch forUse this as a preventive oral-health cue, especially if gum bleeding, tooth loosening, recurring infections, jaw pain, mouth ulcers, or family dental history are relevant.
Show technical evidence
Risk-score evidence
- dentures: risk percentile 99.3%, coverage 92%, PGS000995.
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.
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
SLCO1B1
DECREASED FUNCTION
*15/*37
Affected drugs: Simvastatin (myopathy risk), Atorvastatin, Rosuvastatin, Pravastatin
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.