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Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this ‘free data’ to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite .

Congenital hyperinsulinism (CHI) is a significant cause of hypoglycaemia in neonates and infants with the potential for permanent neurologic injury. Accurate calculations of the incidence of rare diseases such as CHI are important as they inform health care planning and can aid interpretation of genetic testing results when assessing the frequency of variants in large-scale, unselected sequencing databases. Whilst minimal incidence rates have been calculated for four European countries, the incidence of CHI in the UK is not known. In this study we have used referral rates to a central laboratory for genetic testing and annual birth rates from census data to calculate the minimal incidence of CHI within the UK from 2007 to 2016. CHI was diagnosed in 278 individuals based on inappropriately detectable insulin and/or C-peptide measurements at the time of hypoglycaemia which persisted beyond 6 months of age. From these data, we have calculated a minimum incidence of 1 in 28,389 live births for CHI in the UK. This is comparable to estimates from other outbred populations and provides an accurate estimate that will aid both health care provision and interpretation of genetic results, which will help advance our understanding of CHI.

Finding new causes of monogenic diabetes helps understand glycaemic regulation in humans. To find novel genetic causes of maturity-onset diabetes of the young (MODY), we sequenced MODY cases with unknown aetiology and compared variant frequencies to large public databases. From 36 European patients, we identify two probands with novel RFX6 heterozygous nonsense variants. RFX6 protein truncating variants are enriched in the MODY discovery cohort compared to the European control population within ExAC (odds ratio = 131, P  = 1 × 10 −4 ). We find similar results in non-Finnish European ( n  = 348, odds ratio = 43, P  = 5 × 10 −5 ) and Finnish ( n  = 80, odds ratio = 22, P  = 1 × 10 −6 ) replication cohorts. RFX6 heterozygotes have reduced penetrance of diabetes compared to common HNF1A and HNF4A -MODY mutations (27, 70 and 55% at 25 years of age, respectively). The hyperglycaemia results from beta-cell dysfunction and is associated with lower fasting and stimulated gastric inhibitory polypeptide (GIP) levels. Our study demonstrates that heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance. Maturity-onset diabetes of the young (MODY) is the most common subtype of familial diabetes. Here, Patel et al. use targeted DNA sequencing of MODY patients and large-scale publically available data to show that RFX6 heterozygous protein truncating variants cause reduced penetrance MODY.

Abstract Background Babies of women with heterozygous pathogenic glucokinase (GCK) variants causing mild fasting hyperglycemia are at risk of macrosomia if they do not inherit the variant. Conversely, babies who inherit a pathogenic hepatocyte nuclear factor 4α (HNF4A) diabetes variant are at increased risk of high birth weight. Noninvasive fetal genotyping for maternal pathogenic variants would inform pregnancy management. Methods Droplet digital PCR was used to quantify reference and variant alleles in cell-free DNA extracted from blood from 38 pregnant women heterozygous for a GCK or HNF4A variant and to determine fetal fraction by measurement of informative maternal and paternal variants. Droplet numbers positive for the reference/alternate allele together with the fetal fraction were used in a Bayesian analysis to derive probability for the fetal genotype. The babies’ genotypes were ascertained postnatally by Sanger sequencing. Results Droplet digital PCR assays for GCK or HNF4A variants were validated for testing in all 38 pregnancies. Fetal fraction of ≥2% was demonstrated in at least 1 cell-free DNA sample from 33 pregnancies. A threshold of ≥0.95 for calling homozygous reference genotypes and ≤0.05 for heterozygous fetal genotypes allowed correct genotype calls for all 33 pregnancies with no false-positive results. In 30 of 33 pregnancies, a result was obtained from a single blood sample. Conclusions This assay can be used to identify pregnancies at risk of macrosomia due to maternal monogenic diabetes variants.

The long-read sequencers from Pacific Bioscience (PacBio) and Oxford Nanopore Technologies (ONT) offer the opportunity to phase mutations multiple kilobases apart directly from sequencing reads. In this study, we used long-range PCR with ONT and PacBio sequencing to phase two variants 9 kb apart in the RET gene. We also re-analysed data from a recent paper which had apparently successfully used ONT to phase clinically important haplotypes at the CYP2D6 and HLA loci. From these analyses, we demonstrate PCR-chimera formation during PCR amplification and reference alignment bias are pitfalls that need to be considered when attempting to phase variants using amplicon-based long-read sequencing technologies. These methodological pitfalls need to be avoided if the opportunities provided by long-read sequencers are to be fully exploited.

Congenital hyperinsulinism (CHI) causes dysregulated insulin secretion which can lead to life‐threatening hypoglycaemia if not effectively managed. CHI can be sub‐classified into three distinct groups: diffuse, focal and mosaic pancreatic disease. Whilst the underlying causes of diffuse and focal disease have been widely characterised, the genetic basis of mosaic pancreatic disease is not known. To gain new insights into the underlying disease processes of mosaic‐CHI we studied the islet tissue histopathology derived from limited surgical resection from the tail of the pancreas in a patient with CHI. The underlying genetic aetiology was investigated using a combination of high depth next‐generation sequencing, microsatellite analysis and p57kip2 immunostaining. Histopathology of the pancreatic tissue confirmed the presence of a defined area associated with marked islet hypertrophy and a cytoarchitecture distinct from focal CHI but compatible with mosaic CHI localised to a discrete region within the pancreas. Analysis of DNA extracted from the lesion identified a de novo mosaic ABCC8 mutation and mosaic paternal uniparental disomy which were not present in leukocyte DNA or the surrounding unaffected pancreatic tissue. This study provides the first description of two independent disease‐causing somatic genetic events occurring within the pancreas of an individual with localised mosaic CHI. Our findings increase knowledge of the genetic causes of islet disease and provide further insights into the underlying developmental changes associated with β‐cell expansion in CHI.

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. De novo variants altering a conserved region in an intron of HK1 cause congenital hyperinsulinism by perturbing the activity of a putative cell type-specific regulatory element.

Abstract Context Congenital hyperinsulinism (HI) is characterized 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. Objective We investigated the likelihood of finding a genetic cause in childhood-onset HI and explored potential factors leading to 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 (diagnosed with HI < 12 months of age) or childhood-onset (diagnosed at age 1-16 years). We assessed clinical characteristics and the genotypes of individuals with monogenic HI diagnosed in childhood to gain insights into the later age at diagnosis of HI in these children. Results We identified the monogenic cause in 24% (n = 42/173) of the childhood-onset HI cohort; this was significantly lower than the proportion of genetic diagnoses in infancy-onset cases (74.5% [n = 1248/1675], P < 0.00001). Most (75%) individuals with genetically confirmed childhood-onset HI were diagnosed before 2.7 years, suggesting these cases represent the tail end of the normal distribution in age at diagnosis. This is supported by the finding that 81% of the variants identified in the childhood-onset cohort were detected in those diagnosed in infancy. Conclusion We have shown that monogenic HI is an important cause of hyperinsulinism presenting outside of infancy. Genetic testing should be considered in children with persistent hyperinsulinism, regardless of age at diagnosis.

In silico predictive tools can help determine the pathogenicity of variants. The 2015 American College of Medical Genetics and Genomics (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 that high scores from some tools were sufficiently predictive to be used as moderate or strong evidence of pathogenicity. REVEL is a widely used metapredictor that uses the scores of 13 individual in silico tools to calculate the 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% of LoF and 88% of 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.