🧬 Genetics
Nutrition & Nutrients
Weight Loss
December 13, 2025
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If you’ve ever wondered why some people feel full after a small meal, why others constantly crave sweets, or why weight loss feels harder for you than it “should,” your genetics may hold important clues.
A personalised nutrigenetic functional test can help identify metabolic tendencies and guide a tailored nutrition plan based on your unique biology. With this information, you can shape a nutrition plan that works with your biology instead of against it.
How DNA Is Measured in Genetic Testing
Genetic tests don’t read your whole genome. Instead, they scan specific locations called SNPs (single nucleotide polymorphisms). Here’s how it works:
• A saliva or cheek-swab sample is collected.
• Your DNA is broken into small fragments.
• A microarray chip checks thousands of SNP sites.
• At each site, the machine identifies which two bases you carry (A, T, C or G).
• If the SNP changes a protein, the result is also shown as amino acids (e.g., Thr/Ile).
• For some older SNPs, historical labels (A1/A2) are used.
The final report tells you which versions of each SNP you have. SNPs can influence how enzymes work, how receptors respond to hormones and how effectively your body performs metabolic tasks. Some SNPs change the shape of a protein (shown as amino acids like Pro, Ala, Gly). Others simply affect regulation (shown as A/T/C/G). A few still use historical names like A1/A2. Each SNP below affects a different aspect of metabolism or appetite regulation.
ADRB2 (Adrenergic Beta-2 Receptor)— How Efficiently You Mobilise Stored Energy
SNPs: rs1042713 (Arg16Gly), rs1042714 (Gln27Glu)
ADRB2 affects how your fat cells respond to adrenaline — which determines how easily you burn stored fat, how quickly you mobilise glucose and how metabolically “flexible” you are.
rs1042713 (Arg16Gly)
AA (Arg/Arg): slower fat mobilisation; may feel sluggish with high carb intake
AG (Arg/Gly): moderate response
GG (Gly/Gly): sustained fat oxidation; better carb tolerance
rs1042714 (Gln27Glu)
CC (Gln/Gln): receptors desensitise quickly
CG (Gln/Glu): average response
GG (Glu/Glu): stable receptors; improved metabolic flexibility
What this means for you
If your receptors down-regulate easily, high-sugar foods may lead to energy crashes and easier fat gain. You may feel your best with steady meals built around lean protein, fibre and controlled carbohydrates.
MC4R (Melanocortin 4 Receptor) — The Gene That Sets Your Appetite “Volume”
SNP: rs17782313
MC4R influences your natural hunger signals and how satisfied you feel after eating.
Genotypes
TT: typical satiety
TC: slightly increased hunger
CC: reduced fullness → large portions, snacking, emotional eating
What this means
If you carry the C allele, hunger is not “your fault” — your brain’s satiety signals simply reset more slowly. You may thrive with structured eating, high-protein breakfasts and high-volume meals that stretch the stomach without adding calories.
PPARG (Peroxisome Proliferator-Activated Receptor Gamma) — Your Insulin-Sensitivity Master Switch
SNP: rs1805192 (Pro12Ala)
PPARG is essential for glucose metabolism and how efficiently your body stores and releases energy.
Genotypes
CC (Pro/Pro): higher risk of insulin resistance
CG (Pro/Ala): improved insulin response
GG (Ala/Ala): most insulin-sensitive profile
What this means
If you are Pro/Pro, your body may struggle with large carb-heavy meals. A Mediterranean dietary pattern (olive oil, legumes, vegetables, fish) is especially beneficial for this genotype.
AGER / RAGE (Advanced Glycation Endproduct Receptor) — Glycation, Inflammation and Metabolic Ageing
SNP: rs2070600 (Gly82Ser)
AGER controls how strongly your cells react to AGEs — inflammatory compounds produced from sugar and high-temperature cooking.
Genotypes
GG (Gly/Gly): typical AGE signalling
GA (Gly/Ser): higher inflammatory response
AA (Ser/Ser): highest AGE accumulation
What this means
If you carry the Ser allele, charred foods, fried foods and sugary products can have a bigger impact on inflammation, skin ageing and metabolic health. Antioxidant-rich foods (berries, herbs, turmeric) and gentle cooking methods are protective.
TCF7L2 (Transcription Factor 7-Like 2) — Insulin Release and Diabetes Risk
SNP: rs12255372
This gene affects how effectively your pancreas releases insulin.
Genotypes
GG: normal insulin secretion
GT: reduced β-cell performance
TT: significantly reduced insulin output
What this means
If you have the T allele, your body may struggle with blood sugar spikes. Balanced meals (protein + fibre + healthy fats) and lower-GI carbohydrates help keep glucose stable.
KCNJ11 (Potassium Inwardly-Rectifying Channel Subfamily J Member 11) — First-Phase Insulin Release
SNP: rs5219 (E23K)
Controls the potassium channel that triggers early insulin release after meals.
Genotypes
GG (E/E): strong early insulin response
GA (E/K): reduced insulin release
AA (K/K): weakest response
What this means
If your early insulin release is impaired, you may experience post-meal fatigue or cravings. Magnesium intake, balanced meals and regular movement can support glucose control.
GLUT2 (Glucose Transporter Type 2) — Sugar Transport and Sweet Preference
SNP: rs5400 (Thr110Ile)
Influences how efficiently you transport glucose/fructose and how sensitive you are to sweetness.
Genotypes
CC: typical sugar sensitivity
CT: increased sugar preference
TT: strongest sweet cravings and altered glucose sensing
What this means
If you have the Ile allele, managing sugar cravings becomes essential. Natural sweeteners (allulose, erythritol), fruit-based snacks and removing sugary foods from the home environment can help.
FTO (Fat Mass and Obesity-Associated Gene) — Appetite, Satiety and Weight-Gain Risk
SNP: rs9939609
FTO does not change protein structure but shifts the way your brain regulates hunger.
Genotypes
TT: typical appetite
AT: increased appetite and snacking
AA: highest hunger drive
What this means
The A allele is strongly linked with grazing, portion size and preference for calorie-dense foods. Protein-rich meals and planned eating strategies reduce its impact.
DRD2 / ANKK1 (Dopamine Receptor D2 / Ankyrin Repeat And Kinase Domain Containing 1) — Reward, Cravings and Emotional Eating
SNP: rs1800497 (Taq1A)
This variant reduces dopamine receptor density, changing how rewarding food feels.
Genotypes
GG (A2/A2): normal reward processing
GA (A1/A2): mild reward deficiency
AA (A1/A1): strong reward deficiency → cravings and emotional eating
What this means
If you carry the A1 allele, your brain compensates by seeking more stimulation — often from high-calorie foods. Supporting dopamine through protein, exercise and non-food rewards is key.
Summary Table
Gene | SNP | Role | Genotype Effects | Practical Focus |
|---|---|---|---|---|
ADRB2 | rs1042713 / rs1042714 | Fat oxidation, adrenaline response | Arg/Gly and Gln/Glu variants alter metabolic flexibility | Reduce refined carbs; exercise |
MC4R | rs17782313 | Appetite, satiety | C allele → increased hunger | High-protein, structured meals |
PPARG | rs1805192 | Insulin sensitivity | Pro allele → insulin resistance | Mediterranean diet; limit saturated fat |
AGER | rs2070600 | Glycation, inflammation | Ser allele → higher inflammation | Avoid sugar, fried foods |
TCF7L2 | rs12255372 | Insulin secretion | T allele → impaired β-cell response | Low-GI diet; balanced meals |
KCNJ11 | rs5219 | Early insulin release | K allele → reduced insulin signalling | Balanced plates; magnesium |
GLUT2 | rs5400 | Sugar transport, sweet taste | Ile allele → sugar preference | Substitute sweeteners; manage cravings |
FTO | rs9939609 | Appetite regulation | A allele → increased hunger | Protein-rich meals; planning |
DRD2 | rs1800497 | Reward pathways | A1 allele → emotional eating | Exercise; dopamine support |
Are Your Genes Contributing to Weight-Loss Resistance?
If you feel like you’re doing “everything right” but still struggle with appetite, cravings, carb intolerance or stubborn weight, your genetics may offer missing insights.
If you’d like support with testing or interpretation, you can book a consultation or contact me to order a test.
Reference list:
Zhang, H., Wu, J. and Yu, L. (2014) ‘Association of Gln27Glu and Arg16Gly polymorphisms in β2-adrenergic receptor gene with obesity susceptibility: A meta-analysis’, PLoS ONE, 9(6), p. e100489. Available at: https://doi.org/10.1371/journal.pone.0100489
Vesnina, A., Prosekov, A., Kozlova, O. and Atuchin, V. (2020) ‘Genes and eating preferences, their roles in personalized nutrition’, Genes, 11(4), p. 357. Available at: https://doi.org/10.3390/genes11040357
Álvarez-Martín, C., Caballero, F.F., de la Iglesia, R. and Alonso-Aperte, E. (2025) ‘Association of MC4R rs17782313 genotype with energy intake and appetite: A systematic review and meta-analysis’, Nutrition Reviews, 83(3), pp. e931–e946. Available at: https://doi.org/10.1093/nutrit/nuae075
Deeb, S.S. et al. (1998) ‘A Pro12Ala substitution in PPARγ2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity’, Nature Genetics, 20(3), pp. 284–287. Available at: https://doi.org/10.1038/3099
Stumvoll, M. et al. (2002) ‘The peroxisome proliferator-activated receptor-γ2 Pro12Ala polymorphism determines diabetes risk in obesity’, Diabetes, 51(8), pp. 242–247. Available at: https://pubmed.ncbi.nlm.nih.gov/12145143/
Larsen, H.G. et al. (2024) ‘The Gly82Ser polymorphism in the receptor for advanced glycation endproducts increases the risk for coronary events in the general population’, Scientific Reports, 14, p. 11567. Available at: https://doi.org/10.1038/s41598-024-62385-5
Grant, S.F. et al. (2006) ‘Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes’, Nature Genetics, 38(3), pp. 320–323. Available at: https://doi.org/10.1038/ng1732
Lyssenko, V. et al. (2007) ‘Mechanisms by which common variants in the TCF7L2 gene increase risk of type 2 diabetes’, Journal of Clinical Investigation, 117(8), pp. 2155–2163. Available at: https://doi.org/10.1172/JCI30706
Eny, K.M. et al. (2008) ‘Genetic variant in the glucose transporter type 2 is associated with higher intakes of sugars in two distinct populations’, Physiological Genomics, 33(3), pp. 355–360. Available at: https://doi.org/10.1152/physiolgenomics.00148.2007
Frayling, T.M. et al. (2007) ‘A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity’, Science, 316(5826), pp. 889–894. Available at: https://doi.org/10.1126/science.1141634
Wardle, J. et al. (2008) ‘Obesity-associated genetic variation in FTO is associated with diminished satiety’, Journal of Clinical Endocrinology & Metabolism, 93(9), pp. 3640–3643. Available at: https://doi.org/10.1210/jc.2008-0472
Sun, X., Luquet, S. and Small, D.M. (2017) ‘DRD2: Bridging the genome and ingestive behavior’, Trends in Cognitive Sciences, 21(5), pp. 372–384. Available at: https://doi.org/10.1016/j.tics.2017.03.004
Blum, K., Thanos, P.K. and Gold, M.S. (2014) ‘Dopamine and glucose, obesity, and reward deficiency syndrome’, Frontiers in Psychology, 5, p. 919. Available at: https://doi.org/10.3389/fpsyg.2014.00919
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