Endocrine Abstracts

Background: Neanderthals split from an ancestral human population ~500,000 years ago and lived in Eurasia until 40,000 years ago. Early modern humans emerged in Africa ~350,000 years ago migrating into Eurasia 50,000 years ago. Interbreeding occurred between early modern humans and Neanderthals leading to the introduction of Neanderthal DNA into the early human population, a process termed introgression. In modern Eurasian populations around 2-4% of DNA is of Neanderthal origin. The aim of this study was to examine whether genomic factors linked to response to growth hormone (GH) therapy are enriched for elements inherited from Neanderthals and whether these had been subject to selection during subsequent human evolution (a process referred to as selective sweep).

Methods: We identified 11 genes where transcript levels related to first year growth hormone response¹ and 17 SNPs related to growth hormone response from the PREDICT study² and a recent genome wide study³. These were mapped to known regions inherited from Neanderthals⁴. For each genomic region we calculated the minimum Neanderthal sweep score, normalised for genomic region length and compared this to sweep score in 10,000 randomly selected gene regions.

Results: 7 of the 11 transcripts and 13 of the 17 SNPs were located in regions with haplotypes inherited from Neanderthals providing strong evidence of Neanderthal introgression. Of the 17 SNPs, five had been included in the Neanderthal selective sweep scan⁴ and two of these 5 SNPs were identified as introgressed alleles. Median and Minimum Neanderthal selective sweep score across the year one growth response genes were negative but significantly lower than the randomly selected genes (P=4.88e^-13) indicating positive selection over time.

Conclusion: The genetic response to recombinant human growth hormone is enriched for regions showing evidence of introgression from Neanderthals with sweep scores indicating positive selection of these regions over time. Utilising Neanderthal haplotype data may optimise development of genetic tests predicting growth hormone response.

1. Stevens A. Pharmacogenomics J. 2021;21(5):594-607.

2. De Leonibus C. Pharmacogenomics J. 2016;16(6):540-550.

3. Dauber A. J Clin Endocrinol Metab. 2020;105(10):3203-3214.

4. Rinker D. Nat Ecol Evol. 2020;4(10):1332-1341.