ESPE Abstracts (2018) 89 RFC4.2

ESPE2018 Rapid Free Communications GH & IGFs (6 abstracts)

Data Mining and Computational Analysis of Human Growth Hormone Gene (GH1) Sequence in Normal Population to Identify Potential Variants with Disease-Causing Effects

Sonia Verma a, & Amit V Pandey a,

aUniversity Children’s Hospital Bern, Bern, Switzerland; bUniversity of Bern, Bern, Switzerland

Background: Mutations in GH1 gene cause isolated growth hormone deficiency. Several disease-causing mutations from patients with IGHD have been reported. These mutations have been shown to (a) produce shorter isoforms of GH that does not bind to growth hormone receptor, (b) cause diminished secretion of GH or (c) result in misfolded GH protein. Large sequencing studies from the non-clinical population show several hundred genetic variations in GH1 gene. Role of common polymorphic variants in GH1 gene in relation to effects of GH protein has not been systematically studied.

Aim: Searching the genomics data to find and analyze the effects of potentially disease-causing variants in GH1 gene.

Methods: We used hidden Markov Model methods to generate position-specific scoring matrices for analyzing the sequence conservation of GH amino acids across species using both structural and genomics data. A potential list of structurally and functionally important residues was compiled for further analysis. Computational molecular dynamics using AMBER and GH-GHR interaction analysis was performed to study the effects of potentially disease-causing variants.

Results: We generated an evolutionary conservation score of all the amino acids in the human growth hormone sequence by comparing with all the GH sequences in the Uniref90 database. The Arg16, His21, Gln84, Asp169, Lys172, Cys189 residues are functionally conserved while residues Ala17, Ala24, Cys53, Ser79, Leu162, Cys172 structurally conserved. A detailed contact map of GH with amino acids in GHR revealed that GH residues His18, His21, Phe25, Leu45, Pro48, Ser62, Asn63, Tyr164, Lys172, Glu174, Ile179, Cys182, Cys189, Gly190 and Pro2, Ile4, Arg8, Asn12, Leu15, Arg16, Asp116, Glu119, Gly120, Thr123 interact with the GHR via hydrogen bonding or Vander Waal interactions\. We found several potentially disease-causing variants in the GH1 gene from sequencing data deposited from non-clinical samples. Three different categories of changes in the amino acid sequence of GH were observed. Mutations at the interface of GH-GHR interactions were predicted to affect binding and affinity of GH towards GHR, while 31 mutations were found to cause structural instabilities. An overview of GH1 variants with the potential to cause IGHD will be presented.

Conclusion: Identification of potentially negative effects of variations in GH1 gene from non-clinical populations can be utilized to study links to growth variations. Identification of potentially disease-causing variants in GH1 will help in the further functional characterization of these variants when these are later found in patients with growth hormone deficiency.

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