Gene expression is tightly regulated with many genes exhibiting cell-specific silencing when their protein product would disrupt normal cellular function. This silencing is largely controlled by non-coding elements and their disruption might cause human disease. 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 mutations affecting a 42bp conserved region encompassed by a regulatory. element in intron 2 of Hexokinase 1 (HK1), a pancreatic beta-cell ‘disallowed’ gene. We demonstrated that these mutations resulted in expression of HK1 in the pancreatic beta-cells causing inappropriate insulin secretion and congenital hyperinsulinism. These mutations identify a regulatory region critical for cell-specific silencing. Importantly, this has revealed a new disease mechanism for non-coding mutations that cause inappropriate expression of a disallowed gene.

Background
Congenital hyperinsulinism (HI) is characterised by inappropriate insulin secretion despite low blood glucose. Persistent HI is often monogenic, with the majority of cases diagnosed in infancy. Less is known about the contribution of monogenic forms of disease in those presenting in childhood. We investigated the likelihood of finding a genetic cause in childhood-onset HI and explored potential factors leading to the later age at presentation of disease.

Methods
We screened known disease-causing genes in 1848 individuals with HI, referred for genetic testing as part of routine clinical care. Individuals were classified as infancy-onset (when diagnosed with HI

AbstractIn silicopredictive tools can help determine the pathogenicity of variants. The 2015 ACMG guidelines recommended that scores from these tools can be used as supporting evidence of pathogenicity. A subsequent publication by the ClinGen Sequence Variant Interpretation Working Group suggested high scores from some tools were sufficiently predictive to be used as moderate or strong evidence of pathogenicity.REVEL is a widely used meta-predictor that uses the scores of 13 individualin-silicotools to calculate pathogenicity of missense variants. Its ability to predict missense pathogenicity has been assessed extensively, however, no study has previously tested whether its performance is affected by whether the missense variant acts via a loss of function (LoF) or gain of function (GoF) mechanism.We used a highly curated dataset of 66 confirmed LoF and 65 confirmed GoF variants to evaluate whether this affected the performance of REVEL.98% of LoF and 100% of GoF variants met the author-recommended REVEL threshold of 0.5 for pathogenicity, while 89% LoF and 88% GoF variants exceeded the 0.75 threshold. However, while 55% of LoF variants met the threshold recommended for a REVEL score to count as strong evidence of pathogenicity from the ACMG guidelines (0.932), only 35% of GoF variants met this threshold (P=0.0352).GoF variants are therefore less likely to receive the highest REVEL scores which would enable the REVEL score to be used as strong evidence of pathogenicity. This has implications for classification with the ACMG guidelines as GoF variants are less likely to meet the criteria for pathogenicity.