for Sample Customer
Your sleep, energy, fitness, and recovery tendencies from your DNA, translated into clearer priorities and practical experiments.
Inside: the sleep and fitness patterns most worth noticing, what to track in real life, reassuring context, one 14-day starting point, and the supporting trait evidence.
Your report in one minute
What could clarify this. Build on your fitness strengths and train your aerobic capacity.
Everything below opens further if you want it — nothing needs to be read in order, and nothing here is a diagnosis.
Start with the areas you care about. Open any area to see the individual findings and percentiles behind it — 37 health areas are shown from 103 visible results; opt-in findings are not included.
8 leaning higher · 24 near the middle · 5 leaning lower
Trait percentiles compare your score with people from a similar ancestry background. They do not show absolute risk, which is usually low.
Public sample: Opt-in findings are not included. The 103 results shown are genuine and anonymised.
5 areas
24 areas
Higher and lower show where a score sits in the comparison group. They do not automatically mean worse and better.
No extra action from DNA alone. These sit quietly in the background unless symptoms or family history change the picture.
8 areas
The colour scale helps rank the map using health relevance, evidence quality, result confidence, background frequency, redundancy, and distance from the reference average. It is a ranking aid, not a health score or risk percentage. Higher is not automatically worse, and lower is not automatically better.
This focused view starts with the sleep and fitness patterns most likely to feel recognisable, then separates trainable priorities from reassuring context.
This points to a faster reaction-time tendency. It is not a verdict on intelligence or ability.
How to use it. Compare this with your own experience. If it does not sound like you, leave it as background rather than forcing a match.
Your DNA points a little more toward eveningness than early-morning ease.
How to use it. Compare this with your own experience. If it does not sound like you, leave it as background rather than forcing a match.
Start with the recommended habit, or choose one from the simple, moderate, and challenging set. Try it for 14 days and decide whether it suits you. For this sample, these habits aim to support long-term health.
An easy habit to try for 14 days
Why it fits: A short walk after a meal helps muscle take up glucose. Linked findings: Type 2 diabetes and HbA1c. Try this: After the largest carbohydrate meal, walk 10 to 15 minutes within an hour. If time is tight, use stairs or calf raises.
Choose one option that fits your routine.
Easy options to repeat
Why it fits: This is a practical fat-quality and snack-quality note. It works best when nuts replace crisps, biscuits, pastries, or sweets, not when they are simply added on top of usual intake. Linked findings: Type 2 diabetes and LDL cholesterol. Try this: Pre-portion a small handful, add nuts/seeds to oats or yoghurt, or keep them as the default afternoon snack. Choose unsalted versions for blood-pressure context.
Why it fits: This is a simple lipid-and-glucose breakfast swap: beta-glucan supports LDL/ApoB lowering ways it works, while the meal structure can reduce refined breakfast starches and improve satiety. Linked findings: Type 2 diabetes and LDL cholesterol. Try this: Pick one default: porridge, overnight oats, oat bran with yoghurt, barley in soup, or a low-sugar high-beta-glucan cereal. Pair it with nuts/seeds or protein, and avoid turning it into a sweet dessert bowl.
Why it fits: Metabolic consistency is mostly won on low-energy days. Linked findings: LDL cholesterol and HbA1c. Try this: Create three default meals that meet the metabolic pattern: protein, high-fiber plant, unsaturated fat, low refined starch. Repeat them on tired days rather than improvising takeaway.
Why it fits: This is a carb-quality experiment, not fruit restriction. Whole fruit is not the liver target in the way soda, juice, and sweet snacks are; the fibre and structure make the signal slower and usually more filling. Linked findings: Type 2 diabetes and Irritable bowel syndrome. Try this: Pick the easiest swap: berries with yoghurt, an apple with nuts, citrus after a meal, or fruit instead of juice at breakfast. Keep portions ordinary and choose lower-trigger fruits if IBS symptoms matter.
Why it fits: A default breakfast can lower refined sugar and saturated fat while adding fibre and protein early in the day. Linked findings: Type 2 diabetes and LDL cholesterol. Try this: Choose one repeatable breakfast: oats with nuts/berries, unsweetened yoghurt with nuts/fruit, or a tofu/egg/bean plate with vegetables.
Options that need some planning
Why it fits: LDL falls more reliably when the replacement is unsaturated fat or high-fiber carbohydrate, not refined starch. Linked findings: LDL cholesterol and Reduced CYP2C9 statin metabolism. Try this: Choose the swaps in advance: butter to olive/rapeseed oil, cream to Greek yoghurt, fatty processed meat to fish/poultry/legumes, cheese-heavy lunches to hummus/beans/eggs or lean protein.
Why it fits: This is a two-for-one metabolic swap: legumes add fermentable and soluble fibre while replacing higher-saturated-fat or refined-carbohydrate defaults that often drive LDL, ApoB, triglycerides, and glucose patterns. Linked findings: Type 2 diabetes and LDL cholesterol. Try this: Start with familiar meals: lentil soup, bean chilli, chickpea curry, daal, tofu stir-fry, edamame bowls, or beans added to salads. Use smaller portions and canned/rinsed beans if gut tolerance is the barrier.
Why it fits: Different LDL-lowering foods work through different ways it works that add up. Linked findings: LDL cholesterol and Triglycerides. Try this: Add one portfolio component at a time: oats or barley, psyllium, nuts, soy/legumes, and plant sterols/stanols if appropriate. Use it with, not instead of, indicated statin therapy.
Why it fits: Lower-GI starches usually enter the bloodstream more slowly and often bring fibre with them. Linked findings: Type 2 diabetes and HbA1c. Try this: Replace white bread/rice/pasta/cereal defaults with legumes, intact grains, oats/barley or cooled/reheated starches when they fit the meal.
Why it fits: This is a food-rotation habit for fatty-liver, triglyceride, LDL, BP, and gout context. It shifts the whole plate toward fish, nuts, legumes, and unsaturated fats without asking for a perfect diet overhaul. Linked findings: Type 2 diabetes and LDL cholesterol. Try this: Plan two swaps for the week: one bean/lentil/tofu meal and one fish or nut/seed-supported meal. Keep processed meat out of the default slot and add vegetables so the swap is filling.
Options for a settled routine
Why it fits: Intervals are a capacity tool, not a starter requirement. They belong after a tolerable walking/aerobic base and should be adjusted around sleep, soreness, HRV/RHR trend, illness, pain, and motivation. Linked findings: Asthma. Try this: Pick one weekly session and keep the first two weeks conservative. Warm up, do the interval set, cool down, and leave at least 48 hours before another hard session unless coached.
Why it fits: Circadian guideline supports timed light, sleep scheduling and melatonin strategies; implementation requires context. Linked findings: Daytime sleepiness. Try this: Anchor a protected sleep block, bright light during the biological day/shift start, sunglasses or dark commute after night shift, caffeine only in shift first half, and fixed post-shift wind-down.
Why it fits: Polarised or 80/20-style training can help trained users organise intensity, but it is not a beginner requirement or a universal best model. The customer-safe point is simple: most volume should not feel hard if hard sessions are also present. Linked findings: Matched signals and Evidence. Try this: Plan the week before it starts: easy aerobic sessions, one or two harder interval/tempo sessions only if safe, and at least one true recovery day. Keep the easy sessions conversational rather than drifting into medium-hard work.
Use these ordinary moments to see whether the focused patterns show up in real life. They are prompts to notice, not evidence that every inherited tendency applies to you.
Use the first hour of the day as a reality check. If waking feels heavy, unrefreshed, headachy, or sleepy despite enough time in bed, the useful question is sleep quality and breathing, not willpower.
The midday meal is where blood sugar, blood lipids, weight trend, and gut comfort become practical rather than abstract. Tests such as HbA1c or fasting glucose, ApoB or non-HDL cholesterol, blood pressure, and post-meal symptoms can help decide what matters.
If energy drops later in the day, start with the basics before exotic explanations: full blood count, ferritin or iron studies, B12 or folate, vitamin D, thyroid, medicines, and whether the previous night was actually restorative.
Favourable grip-strength, hormone, or bone-density signals point to capacities worth maintaining. Keep strength training, enough protein, sleep, and recovery in the week.
DNA is a prioritisation layer, not a diagnosis. PRS percentiles compare you with the scoring comparison group; ancestry match can affect how portable that comparison is. Marker calls note presence or absence of a specific variant; PGx notes matter only when a matching medicine is chosen. Measured results, symptoms, family history, and clinician judgement decide what changes now.
These are the few checks most likely to clarify what DNA cannot establish. You can discuss them with your GP or arrange common tests yourself; symptoms, history, medicines, and previous results still decide what matters.
What to discuss or check. If fatigue or sleepiness is affecting daily life, ask whether sleep history, medicines, alcohol, training load, full blood count, ferritin, thyroid, B12/folate, or vitamin D context is relevant.
Why it made the cut. This is relevant only if fatigue or sleepiness affects daily life. The DNA finding does not establish a sleep disorder or explain fatigue by itself.
What to discuss or check. If exercise capacity seems unexpectedly low, ask whether current fitness, breathing symptoms, inhaler use, iron status, or a measured fitness assessment would clarify the picture.
Why it made the cut. This is relevant only if current capacity or symptoms are concerning. The lower fitness signal is trainable context; chest pain, fainting, severe breathlessness, or new symptoms need ordinary medical assessment.
What to discuss or check. If there is fracture history, recurrent injury, low energy availability, steroid exposure, or another clinical reason, ask whether bone-health review or measured vitamin D and calcium context is appropriate.
Why it made the cut. This is relevant only if fracture, injury, exposure, or other clinical context fits. The inherited signal is not a diagnosis or a reason for imaging on its own.
For each biological relative, record the facts below. Start with every biological parent, full sibling, and child. Then add any half-sibling, grandparent, aunt, or uncle known to have the same condition or event.
If a fact is not known, write “unknown.” Do not guess, and do not include partners or other non-biological relatives in this genetics history.
“I have a DNA report that pulls forward a few areas. Could we check whether these measurements or symptom questions are relevant for me now?”
Your percentile shows where your score ranks in its reference group. Predictive power describes how much information similar scores have added in research. Neither number is a diagnosis.
Results may be less precise when the reference group differs from your ancestry.
Predictive power is not your personal probability or proof that this exact score performs the same.
Pathway diagrams show which parts of a score contribute more or less. They do not measure what is happening in your body. Use symptoms, family history and current test results to decide what matters.
How to understand the evidence and its limits.
Many DNA associations are too weak, repetitive, or ancestry-dependent to interpret reliably. Real-world context still matters.
5 layers
A DNA association needs enough evidence to interpret. Weak, repetitive, or ancestry-dependent associations can mislead. Symptoms, measurements, family history, and age determine whether a sound association matters to you.
103 signals, including polygenic scores, marker calls, medication-response genetics, HLA context where callable, evidence links, actionability, redundancy, and safety boundaries.
DNA cannot replace current lab tests, symptom assessment, medication review, routine screening, or clinical whole-genome analysis.
Use these findings to decide what to measure or discuss. Measured results, symptoms, family history, medicines, and clinical judgement decide what changes now.
Strong evidence and clear limits come first. Age, symptoms, family history, and measurements decide whether a finding matters now.
Your DNA is harmonised to a modern genome build, imputed against reference data, and mapped with LD-aware polygenic scoring approaches.
We look for the routes that make a result usable: relevant biomarkers, symptoms, family-history questions, clinician conversations, and everyday habits.
We connect results to biomarkers, practical actions, clinician discussion points, and safety limits before they become guidance.
DNA fileYour raw DNA data is processed securely.
Imputation QCQuality checks and confidence tiers are applied.
PRS scoringPolygenic scores are calibrated to reference data.
Evidence mappingFindings are linked to checks, actions, and safety context.
InterpretationEvidence, measurements, symptoms, and history are brought together with clear limits.How quality is managed: Spoke DNA reviews the evidence and quality checks behind each finding. Evidence included: 103 traits/signals: 87 polygenic scores and 16 marker, medication-response, and HLA findings. Clinical care still uses measured results, symptoms, and professional judgement.
