Non-coding variants disrupting a tissue-specific regulatory element in HK1 cause congenital hyperinsulinism.
Matthew N WakelingNick D L OwensJessica R HopkinsonMatthew B JohnsonJayne A L HoughtonAntonia DastamaniChristine S FlaxmanRebecca C WyattThomas I HewatJasmin J HopkinsThomas W LaverRachel van HeugtenMichael N WeedonElisa De FrancoKashyap A PatelSian EllardNoel G MorganEdmund CheesmanIndraneel BanerjeeAndrew T HattersleyMark J Dunnenull nullSarah J RichardsonSarah E. FlanaganPublished in: Nature genetics (2022)
Gene expression is tightly regulated, with many genes exhibiting cell-specific silencing when their protein product would disrupt normal cellular function 1 . This silencing is largely controlled by non-coding elements, and their disruption might cause human disease 2 . We performed gene-agnostic screening of the non-coding regions to discover new molecular causes of congenital hyperinsulinism. This identified 14 non-coding de novo variants affecting a 42-bp conserved region encompassed by a regulatory element in intron 2 of the hexokinase 1 gene (HK1). HK1 is widely expressed across all tissues except in the liver and pancreatic beta cells and is thus termed a 'disallowed gene' in these specific tissues. We demonstrated that the variants result in a loss of repression of HK1 in pancreatic beta cells, thereby causing insulin secretion and congenital hyperinsulinism. Using epigenomic data accessed from public repositories, we demonstrated that these variants reside within a regulatory region that we determine to be critical for cell-specific silencing. Importantly, this has revealed a disease mechanism for non-coding variants that cause inappropriate expression of a disallowed gene.
Keyphrases
- copy number
- genome wide
- gene expression
- transcription factor
- genome wide identification
- dna methylation
- induced apoptosis
- single cell
- high glucose
- endothelial cells
- cell cycle arrest
- healthcare
- poor prognosis
- cell therapy
- mesenchymal stem cells
- binding protein
- cell proliferation
- bone marrow
- long non coding rna
- big data
- small molecule
- amino acid
- deep learning