Eat less, move more is true. It's not step one.Baseline First
Every coach, doctor and gym bro I talked to skipped the same thing: the body you're trying to change has a hormone profile, and that profile is partly written in your genes. I spent nine months learning that the hard way. This is the order I'd do it in if I started over, what normal is supposed to look like, and a path for wherever you're starting.
- ≤ 1%of body weight lost per week is a normal pace
- 600–1,000kcal/day deficit a normal body holds without a fight
- 3–5 lbof water a hard training session can add
- ~31 kcalper lb of fat per day: the ceiling on fat release
The deficit is math. Access to your fat is hormones.
A calorie deficit is the only way fat leaves the body. That part isn't up for debate. What nobody told me is that the deficit only works if your fat cells will hand over their fuel. Fat tissue is a vault with a hormone-controlled door. Insulin keeps it shut. When insulin runs high all day, which is what insulin resistance looks like, the body covers the gap with hunger, lower output and muscle.
There's a physical ceiling on how fast fat can leave even when the door is wide open. Alpert (2005) put it at roughly 31 kcal per pound of fat per day. Someone carrying 100 lb of fat has thousands of calories a day of theoretical capacity. Plenty of people with insulin resistance lose a fraction of that while doing everything right. The gap between the ceiling and reality is the hormone problem nobody measures.
The ceiling is a real formula. The gate is an illustration: nobody can tell you your exact number. Labs tell you which side of the slider you're on (fasting insulin, HOMA-IR, A1c). Your genes can tell you why.
Half the problem is not knowing what normal looks like.
You can't tell whether you're failing, coasting or doing great without a reference range. Here's what a normal body in a deficit should do. If yours does something different, that difference is the clue.
Example value. Change it to see your numbers.
| Marker | Normal | Look closer if |
|---|---|---|
| Pace of loss | Up to ~1% of body weight per week, averaged over a month | Well under half that for 6+ weeks with a verified deficit |
| Sustainable deficit | 600–1,000 kcal/day held for months | You can't hold even 500 without it unraveling |
| How a deficit feels | Some hunger before meals. Your body bridges the gap by burning stored fat | Irritable, snapping at family, cranky when a meal runs late, foggy between meals |
| Daily scale noise | 1–3 lb up or down day to day | Reading any single day as progress or failure |
| After hard training | Scale up 3–5 lb from water for 1–3 days | Panicking and cutting food the next day |
| Strength in a deficit | Holding steady or slowly rising | Falling across several sessions |
| What's lost | Mostly fat; lean mass roughly steady on scans | A quarter or more of the loss is lean mass |
| Fasted blood ketones | Measurable in a sustained deficit, often 0.2–0.5 mmol/L | 0.0–0.1 morning after morning while in a real deficit |
| HOMA-IR | Under ~2 | Above ~2.5–3 |
| Resting metabolism | Within ~10% of formula predictions | Measured far below predicted |
| Sleep and steps | 7+ hours; 7,000–10,000 steps | Under 6 hours most nights |
Where are you starting?
Every path ends in the same place: your data feeding an objective observer. Choose one and the steps that don't apply will fade back. You can still read them.
Full sequence: all ten steps, in order. Each one changes how you read the next.
Isolate the variables: labs to confirm nothing is hidden, a fuel-supply check, then food, metabolism, training and measurement.
Already on a GLP-1: understand why the drug works for you, check your fuel bridge, protect lean mass, and measure fat instead of weight.
Starting at $0: a mood log (add a ketone meter when you can), a food log, a tape, a scale, your step count, any resistance training, and a free LLM.
- Baseline · what you were dealt
- Intervene · with your doctor
- Isolate · what you eat and burn
- Load and observe · train, measure, correlate
Step 01: Read your genome before you fight it.
A consumer array (23andMe, Ancestry, or SelfDecode's own kit) uploaded to SelfDecode gives you reports on the genes that shape appetite, insulin, fat storage, thyroid conversion, testosterone and how you handle vitamins. None of it is destiny. All of it changes which questions you ask and which tests you push for.
For me it turned thirty years of "try harder" into a hormone problem with names: weak natural GLP-1 signaling and strong insulin resistance. I had been treating a hormone problem as a willpower problem.
The genes worth looking up · tap one
TCF7L2
rs7903146 · rs34872471- What it does
- Transcription factor that controls how strongly your gut hormones (including GLP-1) trigger insulin release.
- Why it matters for fat
- Risk alleles weaken the incretin effect and raise type 2 diabetes risk. Less natural GLP-1 means weaker satiety and a looser brake on glucagon.
- What to do with it
- Ask for fasting insulin, glucose and A1c. A strong signal here is a reason to discuss a GLP-1-class medication early.
FTO
rs9939609- What it does
- The best-replicated obesity gene. Shapes appetite, food reward and how quickly you feel satisfied.
- Why it matters for fat
- Each A allele adds roughly 1.5 kg on average and raises the pull of calorie-dense food.
- What to do with it
- High-protein, high-volume meals blunt the effect. Carriers respond to deficits normally once intake is controlled.
MC4R
rs17782313- What it does
- The brain's main "I'm full" receptor in the hypothalamus.
- Why it matters for fat
- The C allele is linked to more snacking, larger portions and higher BMI.
- What to do with it
- A fixed menu and a food log matter more for carriers. Setmelanotide targets this pathway in rare monogenic cases.
LEPR
rs1137101- What it does
- Receptor for leptin, the hormone fat tissue uses to report how much fuel is stored.
- Why it matters for fat
- Weaker signaling means the brain under-reads your fat stores and keeps the starvation alarm on.
- What to do with it
- Expect stronger hunger in a deficit. Plan protein and fiber, and check the supply side (step 04) before blaming willpower.
PPARG
rs1801282 (Pro12Ala)- What it does
- Master switch for fat cell formation and insulin sensitivity in fat tissue.
- Why it matters for fat
- Modifies how fat tissue responds to insulin and dietary fat. Ala carriers often respond better to unsaturated fat.
- What to do with it
- Bias fats toward olive oil, fish and nuts. Track fasting insulin over time.
IRS1
rs2943641- What it does
- First relay inside the cell after insulin binds its receptor.
- Why it matters for fat
- The C allele is tied to impaired insulin signaling and higher insulin resistance.
- What to do with it
- Resistance training moves glucose into muscle through a separate, insulin-independent route.
PPARGC1A
rs8192678 (Gly482Ser)- What it does
- PGC-1α, the master regulator of mitochondrial biogenesis and fat oxidation.
- Why it matters for fat
- The Ser allele lowers fat-burning capacity and VO2 max.
- What to do with it
- Training is the strongest PGC-1α signal. Daily walking adds fat oxidation without recovery cost.
ADRB3
rs4994 (Trp64Arg)- What it does
- Beta-3 adrenergic receptor that tells fat cells to release fuel when adrenaline rises.
- Why it matters for fat
- The Arg variant blunts that release and is tied to slower weight loss.
- What to do with it
- Lean harder on steps and resistance training; stimulant fat burners do less for carriers.
DIO2
rs225014 (Thr92Ala)- What it does
- Converts inactive thyroid hormone (T4) into active T3 inside tissues.
- Why it matters for fat
- Ala carriers may convert poorly and feel hypothyroid on standard T4 therapy.
- What to do with it
- If you ever need thyroid medication, this helps decide whether T4 alone is reasonable. Get free T3 measured.
SHBG
multiple SNPs- What it does
- The binding protein that holds testosterone in the blood. Only the unbound share reaches tissue.
- Why it matters for fat
- Genes can make you a low-serum, high-availability type (low total T, low SHBG, plenty usable) or a high-serum, low-availability type (normal total T, high SHBG, little usable).
- What to do with it
- Always ask for SHBG and calculated free T, drawn in the morning. Read them against your strength and scan data.
MTNR1B
rs10830963- What it does
- Melatonin receptor on insulin-producing cells.
- Why it matters for fat
- The G allele impairs insulin release when melatonin is high, so late-night eating hits glucose harder.
- What to do with it
- Front-load calories. If you supplement melatonin, keep it away from your last meal.
MTHFR
rs1801133 (C677T)- What it does
- Converts folate into its active form for methylation.
- Why it matters for fat
- Indirect: affects homocysteine, energy and how you handle folic acid.
- What to do with it
- With variants, discuss methylfolate and test homocysteine.
APOA2
rs5082- What it does
- Apolipoprotein that affects how saturated fat influences intake and weight.
- Why it matters for fat
- C/C carriers gain more on high saturated-fat diets.
- What to do with it
- For C/C, keep saturated fat under ~22 g/day.
ACTN3
rs1815739 (R577X)- What it does
- Structural protein in fast-twitch muscle fibers.
- Why it matters for fat
- Shapes whether power or endurance training suits you better.
- What to do with it
- Pick training you'll do for years. Both fiber types respond to load.
Two kinds of "low testosterone"
Your genes can set how much testosterone you make and, separately, how much of it your tissues can actually use. SHBG is the protein that holds testosterone in the blood; only the unbound fraction does work. Two people with the same lab number can be in completely different hormonal states.
Low serum, high availability
Total testosterone reads low. SHBG is low, so a larger share is free and usable. The lab report looks bad while the body behaves well: strength climbs and muscle holds or grows, even in a deficit.
The tell: scans and force data show you building or keeping muscle while dieting. If testosterone were truly unavailable, that wouldn't happen.
High serum, low availability
Total testosterone looks normal or high. SHBG is high, so most of it is bound and little reaches tissue. The lab report looks fine while the person feels flat, recovers poorly and loses muscle easily.
The tell: a normal total T with symptoms that don't match. Free T and SHBG explain the gap.
Vitamin and mineral optimization
Methylation: the step most supplement advice skips.
Methylation is your body passing around a tiny chemical tag: one carbon and three hydrogens, called a methyl group (CH₃). It happens billions of times a second in every cell. Those tags turn genes up or down, build neurotransmitters, make creatine, maintain cell membranes and clear homocysteine from your blood.
Most vitamins arrive in a form your body has to convert before it can use. Folate is the clearest example. The folate in food and the folic acid in supplements have to pass through an enzyme called MTHFR, which turns them into methylfolate (5-MTHF), the form that actually carries a methyl group. A common variant in the MTHFR gene (C677T) slows that enzyme: one copy to roughly 65% of typical speed, two copies to roughly 30%. The folate is in your body. It's stuck one step short of useful.
That's where the pre-converted form comes in. Methylfolate has already been through the slow step, so it skips MTHFR and hands its methyl group straight to the next stage. Switch between the settings below and watch what reaches your DNA.
Typical MTHFR. Folate converts at full speed, nearly every lap hands off a methyl group, homocysteine stays low and most CpG sites stay tagged.
One slow copy (C677T, CT). The enzyme runs at roughly 65% of typical. Fewer folate carriers leave with a methyl group, and the tags thin out.
Two slow copies (TT). Roughly 30% of typical. Folate keeps circling without its methyl group, homocysteine builds up, and tags fade faster than they are replaced.
Two slow copies plus methylfolate. The supplement arrives already converted, skips MTHFR, and hands its methyl group straight to the methionine cycle. Delivery climbs back toward typical.
Illustration of the mechanism. Enzyme speeds are approximate in-lab figures for C677T; real-world effects depend on your folate, B2, B6 and B12 status.
How it reaches your genes
Methylation doesn't change your DNA sequence. It changes which parts get read. A methyl tag on a gene's control region, a stretch rich in spots called CpG sites, works like a dimmer: more tags usually turn that gene down, fewer let it run. SAMe, built in the methionine cycle, is the donor for nearly all of those tags, and creatine production uses a large share of the same supply.
So the loop runs both ways. Your genes set how fast you methylate, and your methylation shapes how your genes are used. Diet, age, sleep and stress shape the tags too, and the details are still an active research area. Treat it as a mechanism that tells you what to test, not as a diagnosis.
The same idea applies to other vitamins
| Nutrient | Common form | Slow step your genes can cause | Pre-converted form |
|---|---|---|---|
| Folate (B9) | Folic acid, food folate | MTHFR converts it to methylfolate | L-methylfolate (5-MTHF) |
| B12 | Cyanocobalamin | MTR, MTRR use and recycle it; FUT2, TCN2 affect absorption and transport | Methylcobalamin, adenosylcobalamin, hydroxocobalamin |
| B6 | Pyridoxine HCl | PDXK, ALPL activate it | P5P (pyridoxal-5′-phosphate) |
| B2 | Riboflavin | MTHFR needs B2 to work. Two-copy C677T carriers lower homocysteine with riboflavin in trials | Riboflavin-5′-phosphate |
| Choline / betaine | Eggs, meat, choline salts | PEMT makes choline; BHMT runs a backup route that methylates homocysteine without folate | Betaine (TMG), phosphatidylcholine |
- Test before and after: homocysteine, serum B12 and folate. Most labs flag homocysteine above ~15 µmol/L; many clinicians aim lower. Retest 8–12 weeks after a change.
- Check B12 before high-dose folate. Folate can hide a B12 deficiency on a blood count while nerve damage continues.
- More isn't better. High-dose methyl donors make some people anxious, wired or irritable, especially carriers of slow COMT. Start low and let your doctor set the dose.
- Change one thing at a time. If you're logging mood for step 04, a new methyl supplement is a new variable. Write down the start date.
Other nutrients your genes can change
| Nutrient | Genes that can change your need | What to do |
|---|---|---|
| Vitamin D | GC rs2282679, VDR, CYP2R1 | Test 25-OH vitamin D. Dose to the blood level with your doctor, then retest. Low D tracks with higher body fat. |
| Magnesium | TRPM6, CNNM2 | Cofactor for insulin signaling and ATP. Serum is a poor marker; RBC magnesium is better. |
| Omega-3 | FADS1 / FADS2 | Some people convert plant omega-3 poorly. An omega-3 index test settles it. |
| CoQ10 | COQ2 | Relevant if your mitochondrial genes are weak. Ask before adding. |
| Iron | HFE, TMPRSS6 | Ferritin both ways: low wrecks energy, high (HFE) damages organs. |
Step 02: Get the bloodwork your doctor didn't order.
A standard physical runs a metabolic panel and lipids. That tells you almost nothing about why fat won't move. Bring a list. Ask for the extras by name. Get them drawn the same way every time: morning, fasted, same lab.
HOMA-IR · insulin resistance from two numbers
Example values. Glucose × insulin ÷ 405.
This is the gate from the top of the page, mostly shut. Bring this number to your doctor before cutting calories harder. Cutoffs vary by lab and population.
Step 03: Bring the data to your doctor. Then talk medication.
With genes and labs in hand, the medication conversation stops being "do I qualify" and becomes "which signal am I missing." The incretin drugs each hit a different set of receptors. Tap one.
GLP-1
targeted- Quiets appetite and food noise
- Slows stomach emptying
- Brakes glucagon
- Boosts insulin when glucose rises
GIP
targeted- Better insulin response
- Nutrient partitioning toward muscle
- Smooths GLP-1 nausea
- Fat tissue handling of lipids
Glucagon
not targeted- Liver releases stored fuel
- Raises energy expenditure
- Drives ketone production
- Clears liver fat
Semaglutide (Ozempic, Wegovy) is GLP-1 only. About 15% average weight loss at 68 weeks in STEP 1. Appetite goes quiet; glucagon is braked.
Tirzepatide (Mounjaro, Zepbound) adds GIP. About 21% average weight loss at 72 weeks on the top dose in SURMOUNT-1. Better partitioning; glucagon is still braked, which matters in step 04.
Retatrutide adds the glucagon receptor. About 24% at 48 weeks in phase 2. It is investigational and not FDA-approved; Lilly has said it plans to file in early 2027.
- Find a clinician who micro-titrates. Big jumps (2.5 → 5 → 10 mg) are where people stop eating and lose muscle. Small steps protect lean mass.
- Minimum effective dose, always. Ride a dose until it stops working before asking for more.
- Don't use the dose to move the scale. Water and glycogen swings will mislead you for weeks.
- Expect blood-sugar crashes in the days after a dose change. Sequence food: protein and fat early, fast carbs only when you need them. Keep honey on hand.
- Eat the protein even when you aren't hungry. The drug removes the hunger signal, not the need.
Step 04: You can feel full and still have a brain that thinks it's starving.
I put fat back on one summer. It would be easy to call that a discipline problem. It wasn't. My stomach felt fine. My brain was screaming that we were dying. I was carrying an enormous amount of stored energy and the freezer was locked. So the brain did what brains do when they think fuel is running out: it got irritable, it got short with the people I love, and it found food. Eventually that signal was loud enough to override the medication.
That's the distinction this step is about. Feeling hungry and having a fuel supply problem are two different signals. You have to separate them, because they're fixed in completely different ways.
Do I feel hungry?
Stomach emptiness, food noise, cravings. GLP-1 drugs turn this down hard. GIP improves where the calories you do eat go.
Is my brain getting fuel?
Between meals, the body should bridge the gap from stored fat: fatty acids for muscle, ketones for the brain. If that bridge is blocked, the brain reads a fuel shortage as an emergency.
Illustration. Same meals, same calories, same suppressed appetite in both views. Only the bridge changes.
Why would the bridge be blocked? Glucagon is the hormone that tells your liver to release stored fuel and make ketones between meals. GLP-1 activity brakes glucagon. On a GLP-1 or GLP-1/GIP drug, some people simply stop producing meaningful ketones, even fasted and in a real deficit. The appetite side is quiet. The supply side is starving. Add insulin resistance from step 02 and the fat cells are holding the door shut too.
Supply-side warning signs · check what's true for you
Check anything that sounds like you. Nothing is saved.
Test it: fasted blood ketones (β-hydroxybutyrate)
- 0.0–0.1In a real deficit, morning after morning: the bridge may be blocked.
- 0.1–0.2Normal after an overnight fast at maintenance. Weak for a sustained deficit.
- 0.2–0.5The bridge is running. Fat is fueling the gaps.
- 0.5–3.0Nutritional ketosis: low-carb diets or longer fasts.
- Use a blood meter, not urine strips. Urine strips go quiet once you adapt and miss low but real levels.
- Test fasted, same time each morning, for two weeks. Write a 1–5 irritability score next to each reading.
- Log mood the way you log food: how you treated the people around you, how cranky you got when a meal ran late, when the fog hit.
- Bring the pattern to your doctor. Options people discuss with their clinicians include MCT oil (C8) as a daily fuel source, ketone esters for hard days, adjusting meal timing, or a medication with a glucagon component.
Step 05: Write down what you eat. All of it.
If your genes and labs come back normal, the problem usually lives somewhere between your mouth and your memory. Weigh and log everything for two weeks in an app like MacroFactor. Then turn the result into a fixed daily menu you can repeat without weighing.
If you catch yourself eating past the plan without feeling physically hungry, go back to step 04 before you blame yourself. Off-plan eating driven by a brain fuel alarm looks exactly like a discipline problem from the outside.
Example: a logged day versus the real day
Bites off a spoon, dried fruit, kids' leftovers. None of it feels like a meal, and a few hundred calories of it erases a 600 kcal deficit.
- Protein first: about 0.8–1 g per pound of goal body weight. It's the muscle shield and the most filling macro.
- Log the bites. Calibrate once, then repeat the menu. Re-weigh for a week whenever progress stalls.
- Keep real life inside the plan. Birthday parties happen; eat protein first and participate.
Step 06: Measure your metabolism. Don't guess it.
A resting metabolic rate test sends your breath through a metabolic cart and measures what you burn lying still. Every calorie target you'll ever set sits on that number. The formulas apps use are averages, and they disagree with each other by hundreds of calories. Try it with your own stats.
Example values. Add a measured RMR to compare.
The formulas disagree by 247 kcal/day. Over a month that's 2.1 lb of fat you could misplan. Normal is within about 10% of the formulas. A cart test tells you which side you're on.
Step 07: Train to keep the muscle. Use a machine that shows you the data.
In a deficit, the job of training is to tell your body the muscle is still needed. Without that signal, a quarter or more of the weight lost on GLP-1 drugs can come from lean tissue. ARX is a motor that matches your force through every inch of every rep and records it. Twenty minutes, twice a week. If you're truly pushing, most people can't recover from more than once a week at first.
A fixed weight can only be as heavy as your weakest point in the rep. Everywhere else you're coasting. Adaptive resistance follows your strength curve, so every position gets loaded.
- Split the stimulus. One split that works: one day lowering-only (eccentric), another lifting-only (concentric).
- Cap intensity once recovery suffers. Running around 87% of max protects sleep and output without giving up the stimulus.
- Judge sessions by consistency: time spent above your target across the whole rep beats a single peak number.
- No ARX nearby? Slow, controlled lifts close to failure, twice a week, logged. The principle carries.
Step 08: Track sleep and steps every day.
An Oura ring or similar tracker gives you two numbers that quietly run fat loss: how long you actually slept, and how much you moved outside the gym. Steps are the deficit you can widen without touching food or recovery. Sleep sets how ready your body is the next day. A treadmill under a standing desk can add thousands of steps without changing your workday.
Bedtime math
That window is 0.3 h short of 7. Every 15 minutes earlier adds back a quarter hour of the sleep your recovery runs on. Closing the gap to 10,000 steps adds roughly 160 kcal/day to your deficit without touching food.
Step 09: Weigh daily. Measure monthly. Trust the trend.
Get an electronic scale that reports body composition, a tape measure, and a professional scan every month or two (InBody or DEXA). The daily scale tells you direction. The tape tells you where. The scan tells you what. None of them is the truth alone.
Same body, same week, three body-fat readings · typical spread
- Home scale (BIA)~20%
- InBody~30%
- DEXA~35%
Methods can land 10–15 points apart on a muscular body. Pick one method per question and never splice their numbers into one line. Home scales are good for weight trend and water, and weak on body-fat percentage when you carry a lot of muscle.
- Weigh every morning, read the 7-day average. A single week's change is mostly water and glycogen.
- A hard training day can add 3–5 lb of water. Expect the scale to rise after you push.
- Tape at the navel, neck, chest, arms, thighs. Same spot, same time, same tension.
- Scan at a consistent point in your week, ideally the same number of days after your hardest session.
- On a scan, the signal is fat mass falling and muscle holding. Weight is the least useful number on the page.
Step 10: Put all of it in front of an objective observer.
Every step above produces data. Alone, each stream is noise. Together, an LLM can correlate them: mood against ketones, sleep against readiness, food against the weekly trend, a dose change against crashes, a lab against a scan. It becomes the mirror that doesn't get tired of you and doesn't care how hard you tried. It shows you the numbers and pushes.
Correlations worth asking for
- Mood × ketonesDo irritable days line up with 0.0 morning readings? That's step 04 in one chart.
- Bedtime × readiness × weightDoes a streak of earlier nights come before your best weekly drops?
- Dose × crashes × intakeDo off-plan days cluster after a dose change or on a particular day of the injection week?
- Strength × scans × free TIs muscle holding in a deficit? What does that say about your testosterone type?
- Scan fat loss × logged foodBack-calculate your real deficit and compare it to the 600–1,000 normal range.
- Training day × scaleHow much water does a hard session add for you, and for how many days?
Starter prompt · paste your data where marked
You are my objective observer for a fat-loss protocol. Correlate my data across sources and push me with what it shows. Rules: 1. Before judging any number, state what normal, exceptional and underperforming look like for someone my size. 2. For every number you use, say which file or message it came from. 3. Label each statement as read from my data or inferred. 4. If you need a number I haven't given you, ask for it. 5. Look for cross-source correlations, not just single-metric trends. 6. Flag anything that belongs with my doctor. Medication decisions stay with them. My baseline: - Genes: [key SelfDecode findings: TCF7L2, FTO, insulin resistance, SHBG / testosterone, DIO2, MTHFR...] - Labs: [results + date + time of draw + fasted or fed] - RMR: [measured value, method, date] - Medication: [drug, dose, injection day, start date] This week: - Mood + ketones: [daily irritability 1-5, fasted BHB] - Food: [7-day log or fixed menu + anything off-menu] - Training: [session export] - Sleep / steps: [tracker export] - Body: [7-day average weight, waist, latest scan] Question: [what you want to know]
How fast should your fat come off?
Up to 1% of body weight a week is the normal benchmark. The Alpert ceiling tells you whether your fat stores can actually supply the deficit you're asking for. Runs in your browser; nothing is saved.
- Fat mass
- 87.5
- Lean mass
- 162.5
- Ceiling kcal/day
- 2,748
- Fat lb/week now
- 1.60
- 1% benchmark
- 2.5
This deficit is inside the normal 600–1,000 range. It removes about 1.60 lb of fat a week, or 0.64% of body weight against a normal upper bound of 1%. You reach 18% body fat at about 198 lb, assuming lean mass holds. This assumes the gate is open and the bridge is running. With insulin resistance or a blocked bridge, real numbers run lower, which is the point of steps 01–04.
What I believed. What the data said.
I believed: Eat less, move more is the whole story.
The data said: It's the mechanism. Hormones decide how much of the deficit comes from fat. Measure them first.
I believed: I put fat back on because I lacked discipline.
The data said: My brain read a locked fuel supply as starvation. That signal can override a GLP-1. It was a supply problem with a test attached.
I believed: Not feeling hungry means I'm fine.
The data said: Felt hunger and brain fuel are separate signals. Mood is the readout for the second one.
I believed: The scale tells me how I'm doing.
The data said: A week of scale data is mostly water and glycogen. 7-day averages and monthly scans are the signal.
I believed: If the scale stalls, raise the dose.
The data said: Dose changes caused crashes and stalls of their own. Minimum effective dose, held until it stops working.
I believed: I know what I eat.
The data said: Weighed meals and real intake were hundreds of calories apart. The bites count.
I believed: My testosterone is low, so that's the problem.
The data said: Total T was low, and that's true. Strength and muscle rising in a deficit showed a low-serum, high-availability type. Free T matters more than the headline number.
I believed: My genetic report settles the question.
The data said: Two reports on the same DNA disagreed. Genes pick the tests; tests make the call.
I believed: More training burns more fat.
The data said: Two short sessions near 87% beat all-out work I couldn't recover from. Steps carried the extra burn.
I believed: I can tell if I'm doing well.
The data said: Not without a benchmark. Up to 1% a week and a 600–1,000 kcal deficit held without misery is normal. Anything far from that is a clue.
I believed: The protocol has to come first.
The data said: Family, work and birthday parties stay. The protocol has to fit inside a real life or it won't survive one.
This is my experience, not medical advice. Every medication and dose decision belongs with your clinician. Retatrutide is investigational and not FDA-approved. Consumer genetic reports are directional. Ketone ranges here are general reference points, not diagnostic thresholds. Bring your data to a doctor and decide together.
References
- Alpert SS. A limit on the energy transfer rate from the human fat store in hypophagia. J Theor Biol. 2005;233(1):1–7.
- Wilding JPH et al. Once-weekly semaglutide in adults with overweight or obesity (STEP 1). NEJM. 2021;384:989–1002.
- Jastreboff AM et al. Tirzepatide once weekly for the treatment of obesity (SURMOUNT-1). NEJM. 2022;387:205–216.
- Jastreboff AM et al. Triple-hormone-receptor agonist retatrutide for obesity: a phase 2 trial. NEJM. 2023;389:514–526.
- Matthews DR et al. Homeostasis model assessment: insulin resistance and β-cell function. Diabetologia. 1985;28:412–419.
- Frosst P et al. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet. 1995;10:111–113.
- McNulty H et al. Riboflavin lowers homocysteine in individuals homozygous for the MTHFR 677C→T polymorphism. Circulation. 2006;113:74–80.
- Mifflin MD, St Jeor ST et al. A new predictive equation for resting energy expenditure. Am J Clin Nutr. 1990;51:241–247.