SAT-053 - Evolutionary Pressures on Ghrelin Signalling Determine Metabolic Strategy in Mammals

Background
Mammalian evolution has occurred under sustained metabolic and growth pressures, providing a framework to interrogate gene–phenotype relationships with possible translational relevance to humans. Ghrelin signalling via the growth hormone secretagogue receptor (GHSR) links metabolic state to growth hormone (GH) secretion, positioning this axis at the interface of growth and metabolism. Humans have evolved a high metabolic output yet how ghrelin versus GH contribute to this is not known.
Methods
Phylogenetic tree structure was examined across 13 metabolically divergent mammalian species grouped as high metabolism (human, bonobo, macaques), low metabolism (sloth, koala, manatee), seasonal metabolic cycling (black and brown bears), and extreme fasting (walrus, seal, polar bear). Coding sequences from the GH axis (GH1, GHR, GHRH, GHRHR) and ghrelin axis (GHSR, GHRL, MBOAT4, LEAP2, MLN) were analysed using complementary topology based metrics. Jaccard similarity quantified preservation of species groupings independent of branching order, while mutual clustering information (MCI) captured overall phylogenetic concordance. Bootstrap resampling estimated 95% confidence intervals for differences in topological metrics across metabolic categories relative to high metabolism species. P-values were adjusted for multiple testing.
Results
Across mammals, GH axis genes showed near perfect recovery of phylogenetic structure with consistently high concordance (95%CI Jaccard=0.89–0.96; 95%CI MCI=0.60–0.69), indicating a strongly constrained growth control core. Ghrelin axis genes showed similarly high overall conservation (95%CI Jaccard=0.87–0.95; 95%CI MCI=0.56–0.68). However, stratification by metabolic status revealed divergence in the ghrelin axis. Species with seasonal metabolic cycling showed increased ghrelin axis divergence relative to high metabolism species (Δmean Jaccard=–0.13; Δmean MCI=–0.31; P< 0.0001), indicating increased regulatory control, not observed in the GH-axis (Δmean Jaccard=0.009; Δmean MCI=–0.09; P>0.1). Also, low metabolism species showed increased divergence in the ghrelin axis (Δmean Jaccard=–0.13; Δmean MCI=–0.13; P< 0.0001), with limited impact in the GH-axis (Δmean Jaccard=–0.078; Δmean MCI=–0.046; P< 0.1).
Conclusions
The GH-axis exhibits strong evolutionary constraint across metabolically divergent mammals. In contrast, the ghrelin-axis combines a conserved signalling core with regulatory flexibility in species with seasonal or low metabolic output. These findings suggest metabolic diversification is primarily accommodated through evolutionary divergence in ghrelin axis genes, while GH axis genes preserve stability of growth regulation. Overall, GH biology is stable and predictable whilst ghrelin is an interface through which metabolism influences growth.

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