Genetics influence starting muscle size, fat distribution, skeleton, and some of the variability in training response. They do not let an online calculator predict your final size or rate of growth. A slower first response can also reflect training quality, food, recovery, or measurement noise—not an immutable “bad glute gene.”
What genes can influence
Large genetic studies show that body-fat distribution has a heritable component and many associated variants, often with sex-specific effects. Genetics can also influence lean mass, limb proportions, and the biological response to resistance training. None of these operate as a single on/off gene for a large butt.
Why “non-responder” is too simple
Studies find large differences in measured hypertrophy, but an apparent low response in one muscle, program, or time period does not prove a person cannot grow. Measurement error, training status, adherence, exercise fit, dose, nutrition, and the length of the study all affect the result.
Use your own response curve
The most practical test is a block of consistent training with measurements taken under similar conditions. If strength and repetitions rise but circumference does not, continue long enough to separate better technique from tissue change. If neither rises, review the part of the plan most likely to be holding you back.
A flat starting shape means your glutes cannot grow.
Starting shape affects appearance, but it does not demonstrate the absence of trainable muscle tissue.
References
These sources support the explanations above. They cannot replace individual medical, nutrition, or training advice.
- Pulit et al. (2019), genetics of body-fat distribution Genome-wide association meta-analysis
- Karastergiou et al. (2012), sex differences in human adipose tissue Physiology review
- Roberts et al. (2018), low and high hypertrophic responders Training-response study
- American College of Sports Medicine 2026 resistance-training position stand Position stand
- Currier et al. (2023), resistance-training prescription network meta-analysis Systematic review and network meta-analysis
- Pelland et al. (2026), resistance-training dose response Meta-regression