Waist-Hip Ratio and Smoking
WHR Genetics in Never-Smokers: RSPO3 and ADAMTS9 | ExomeDNA
By the ExomeDNA Research Team | Last reviewed May 2026
Research base: Robust.
What is waist-to-hip ratio adjusted for BMI?
Waist-to-hip ratio (WHR) adjusted for body mass index captures fat distribution—where fat is stored relative to body size—by measuring waist circumference relative to hip circumference and removing the influence of overall weight. Studying WHR genetics specifically in people who have never smoked creates a targeted research design: tobacco use independently promotes central fat accumulation through nicotine-driven neuroendocrine effects and altered lipid metabolism, and its presence in a study population can confound or obscure underlying genetic signals. Restricting analysis to non-smokers isolates fat distribution genetics from this environmental layer.
Where fat accumulates around the waist versus the hips is partly heritable. The genetic signals identified in never-smoker populations may reflect the core genetic architecture of fat distribution more cleanly than signals estimated in mixed populations where smoking creates background noise.
The genetics behind fat distribution
The strongest genetic signals for BMI-adjusted WHR in never-smokers include variants near RSPO3, ADAMTS9, EYA4, ANKRD55, CCDC122, HOXC12, and TBX15. The gene set partially overlaps with general-population WHR studies but shows some distinct signals that emerge more clearly when tobacco exposure is absent.
RSPO3 is consistently the top signal across multiple WHR analyses—general and never-smoker alike. It encodes a secreted Wnt pathway amplifier expressed in fat tissue that shapes how fat depots develop and are maintained through Wnt-dependent signaling. Its persistence as the leading signal across study designs confirms a robust, tobacco-independent genetic contribution to fat distribution.
ADAMTS9 encodes a secreted metalloproteinase that cleaves extracellular matrix proteoglycans, particularly versican and aggrecan. Metalloproteinase-mediated ECM remodeling affects the structural properties of connective tissue in mesenchymal tissues, including fat depots. Variants near ADAMTS9 may influence the remodeling capacity of connective tissue scaffolding surrounding fat cells, with effects on how easily fat depots expand. Notably, ADAMTS9 appears more prominently in never-smoker analyses than in general-population WHR studies, suggesting its genetic signal may be partially obscured in populations where smoking-related ECM effects operate alongside genetic ones.
A genome-wide meta-analysis accounting for smoking behavior identified novel loci for WHR in never-smoker subsets, including genes involved in extracellular matrix remodeling and developmental patterning not clearly resolved in general population analyses (Justice et al., 2017).
EYA4 is a transcription coactivator with roles in developmental gene regulation, expressed during organogenesis and in adult tissues. ANKRD55, located near the gene encoding the IL-6 receptor subunit gp130 (IL6ST), may connect fat distribution genetics to inflammatory cytokine signaling biology. HOXC12 is a Hox developmental transcription factor that specifies positional identity in tissues during embryonic development. HOX family genes have appeared across multiple fat distribution phenotypes, consistently supporting the hypothesis that the regional identity of fat depots—abdominal versus gluteal—is programmed during development and partly encoded by developmental transcription factor genetics.
What the research says
Justice et al. (2017) conducted a large-scale genome-wide meta-analysis of obesity traits that explicitly modeled and stratified by smoking behavior, enabling analysis of never-smoker subsets with sufficient statistical power. The study identified loci for central adiposity measures including WHR, with some signals appearing more strongly or newly in the tobacco-free group. This design addresses an important limitation of general-population GWAS: smoking confounds fat distribution because it independently promotes central adiposity, and its effects can mask or distort the genetic signal.
Lee et al. (2022) extended this approach, examining how smoking-interaction loci affect obesity-related traits across populations. Their findings confirmed that the genetic architecture of fat distribution shifts meaningfully when smoking exposure is removed as a variable, with some signals strengthening and others—particularly those in ECM remodeling pathways—becoming more clearly detectable in tobacco-naive individuals.
Accountability for smoking behavior in genome-wide WHR analyses revealed distinct genetic signals, including ADAMTS9 and developmental patterning genes, that were more clearly detectable in never-smoker subsets (Justice et al., 2017; Lee et al., 2022).
The never-smoker design is an example of gene-environment interaction analysis: by holding the environmental variable (smoking) constant, the study increases the signal-to-noise ratio for detecting the underlying genetic architecture. This approach is informative for traits where a common behavioral exposure creates substantial confounding, and the methods developed for WHR have been applied to other adiposity traits with similar benefits.
How fat distribution affects you
Central fat accumulation measured by elevated WHR is linked to elevated susceptibility for cardiometabolic conditions, greater visceral fat mass, and higher inflammatory burden compared to peripheral fat storage at equivalent total body weight. In individuals who have never smoked, the contribution of genetics to central adiposity is more cleanly separated from the tobacco exposure pathway, which itself promotes abdominal fat through cortisol activation and altered lipolysis regulation.
For people who have never used tobacco, the WHR genetics studied in this population represent a particularly direct window into the underlying hereditary architecture of fat distribution—without the metabolic and hormonal changes that smoking superimposes. This does not mean that lifestyle factors are irrelevant; rather, the genetic predispositions identified here operate more directly through intrinsic biological pathways.
Working with your profile
The same lifestyle approaches relevant to fat distribution in the general population apply to never-smokers. Aerobic exercise, resistance training, and Mediterranean-style dietary patterns all associate with reduced central adiposity in controlled studies. Monitoring waist-to-hip ratio alongside body weight provides more complete information about fat distribution changes over time, since WHR responds to dietary and exercise interventions even when total weight is stable.
Sleep quality and stress management also shape fat distribution trajectories. Cortisol—elevated by poor sleep and chronic stress—preferentially promotes central fat accumulation. Managing these factors reduces one of the modifiable drivers of abdominal adiposity, even in individuals with genetic tendencies toward central fat deposition.
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Related traits and genes
RSPO3 is a recurring genetic signal across WHR studies regardless of smoking stratification, confirming a fundamental role in fat distribution biology. ADAMTS9 appears more prominently in never-smoker analyses, making it informative for fat distribution in tobacco-naive populations specifically. ANKRD55 near IL6ST suggests connections between fat distribution genetics and inflammatory cytokine biology. HOX family transcription factors—including HOXC12 and related genes—appear across fat distribution phenotypes, consistently supporting the developmental programming hypothesis for fat depot regional identity.