Chromosome 20p11.2 deletions cause congenital hyperinsulinism via the loss of FOXA2 or its regulatory elements.

Persistent congenital hyperinsulinism (HI) is a rare genetically heterogeneous condition characterised by dysregulated insulin secretion leading to life-threatening hypoglycaemia. For up to 50% of affected individuals screening of the known HI genes does not identify a disease-causing variant. Large deletions have previously been used to identify novel regulatory regions causing HI. Here, we used genome sequencing to search for novel large (>1 Mb) deletions in 180 probands with HI of unknown cause and replicated our findings in a large cohort of 883 genetically unsolved individuals with HI using off-target copy number variant calling from targeted gene panels. We identified overlapping heterozygous deletions in five individuals (range 3-8 Mb) spanning chromosome 20p11.2. The pancreatic beta-cell transcription factor gene, FOXA2, a known cause of HI was deleted in two of the five individuals. In the remaining three, we found a minimal deleted region of 2.4 Mb adjacent to FOXA2 that encompasses multiple non-coding regulatory elements that are in conformational contact with FOXA2. Our data suggests that the deletions in these three children may cause disease through the dysregulation of FOXA2 expression. These findings provide new insights into the regulation of FOXA2 in the beta-cell and confirm an aetiological role for chromosome 20p11.2 deletions in syndromic HI.

The Role of ONECUT1 Variants in Monogenic and Type 2 Diabetes Mellitus.

ONECUT1 (also known as HNF6) is a transcription factor involved in pancreatic development and ß-cell function. Recently, biallelic variants in ONECUT1 were reported as a cause of neonatal diabetes mellitus (NDM) in two subjects, and missense monoallelic variants were associated with type 2 diabetes and possibly maturity-onset diabetes of the young (MODY). Here we examine the role of ONECUT1 variants in NDM, MODY, and type 2 diabetes in large international cohorts of subjects with monogenic diabetes and >400,000 subjects from UK Biobank. We identified a biallelic frameshift ONECUT1 variant as the cause of NDM in one individual. However, we found no enrichment of missense or null ONECUT1 variants among 484 individuals clinically suspected of MODY, in whom all known genes had been excluded. Finally, using a rare variant burden test in the UK Biobank European cohort, we identified a significant association between heterozygous ONECUT1 null variants and type 2 diabetes (P = 0.006) but did not find an association between missense variants and type 2 diabetes. Our results confirm biallelic ONECUT1 variants as a cause of NDM and highlight monoallelic null variants as a risk factor for type 2 diabetes. These findings confirm the critical role of ONECUT1 in human ß-cell function.

Hyperinsulinemic Hypoglycemia Diagnosed in Childhood Can Be Monogenic.

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.

Non-coding variants disrupting a tissue-specific regulatory element in HK1 cause congenital hyperinsulinism.

Gene expression is tightly regulated, with many genes exhibiting cell-specific silencing when their protein product would disrupt normal cellular function1. This silencing is largely controlled by non-coding elements, and their disruption might cause human disease2. 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.

Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts.

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.

PLIN1 Haploinsufficiency Causes a Favorable Metabolic Profile.

CONTEXT: PLIN1 encodes perilipin-1, which coats lipid droplets in adipocytes and is involved in droplet formation, triglyceride storage, and lipolysis. Rare PLIN1 frameshift variants that extend the translated protein have been described to cause lipodystrophy. OBJECTIVE: This work aimed to test whether PLIN1 protein-truncating variants (PTVs) cause lipodystrophy in a large population-based cohort. METHODS: We identified individuals with PLIN1 PTVs in individuals with exome data in the UK Biobank. We performed gene-burden testing for individuals with PLIN1 PTVs. We replicated the associations using data from the T2D Knowledge portal. We performed a phenome-wide association study using publicly available association statistics. A total of 362 791 individuals in the UK Biobank, a population-based cohort, and 43 125 individuals in the T2D Knowledge portal, a type 2 diabetes (T2D) case-control study, were included in the analyses. Main outcome measures included 22 diseases and traits relevant to lipodystrophy. RESULTS: The 735 individuals with PLIN1 PTVs had a favorable metabolic profile. These individuals had increased high-density lipoprotein cholesterol (0.12 mmol/L; 95% CI, 0.09 to 0.14, P = 2 × 10-18), reduced triglycerides (-0.22 mmol/L; 95% CI, -0.29 to -0.14, P = 3 × 10-11), reduced waist-to-hip ratio (-0.02; 95% CI, -0.02 to -0.01, P = 9 × 10-12), and reduced systolic blood pressure (-1.67 mm Hg; 95% CI, -3.25 to -0.09, P = .05). These associations were consistent in the smaller T2D Knowledge portal cohort. In the UK Biobank, PLIN1 PTVs were associated with reduced risk of myocardial infarction (odds ratio [OR] = 0.59; 95% CI, 0.35 to 0.93, P = .02) and hypertension (OR = 0.85; 95% CI, 0.73 to 0.98, P = .03), but not T2D (OR = 0.99; 95% CI, 0.63-1.51, P = .99). CONCLUSION: Our study suggests that PLIN1 haploinsufficiency causes a favorable metabolic profile and may protect against cardiovascular disease.

Increased referrals for congenital hyperinsulinism genetic testing in children with trisomy 21 reflects the high burden of non-genetic risk factors in this group.

BACKGROUND: Hyperinsulinism results from inappropriate insulin secretion during hypoglycaemia. Down syndrome is causally linked to a number of endocrine disorders including Type 1 diabetes and neonatal diabetes. We noted a high number of individuals with Down syndrome referred for hyperinsulinism genetic testing, and therefore aimed to investigate whether the prevalence of Down syndrome was increased in our hyperinsulinism cohort compared to the population. METHODS: We identified individuals with Down syndrome referred for hyperinsulinism genetic testing to the Exeter Genomics Laboratory between 2008 and 2020. We sequenced the known hyperinsulinism genes in all individuals and investigated their clinical features. RESULTS: We identified 11 individuals with Down syndrome in a cohort of 2011 patients referred for genetic testing for hyperinsulinism. This represents an increased prevalence compared to the population (2.5/2011 expected vs. 11/2011 observed, p = 6.8 × 10-5 ). A pathogenic ABCC8 mutation was identified in one of the 11 individuals. Of the remaining 10 individuals, five had non-genetic risk factors for hyperinsulinism resulting from the Down syndrome phenotype: intrauterine growth restriction, prematurity, gastric/oesophageal surgery, and asparaginase treatment for leukaemia. For five individuals no risk factors for hypoglycaemia were reported although two of these individuals had transient hyperinsulinism and one was lost to follow-up. CONCLUSIONS: Down syndrome is more common in patients with hyperinsulinism than in the population. This is likely due to an increased burden of non-genetic risk factors resulting from the Down syndrome phenotype. Down syndrome should not preclude genetic testing as coincidental monogenic hyperinsulinism and Down syndrome is possible.

SavvyCNV: Genome-wide CNV calling from off-target reads.

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.

Evaluation of Evidence for Pathogenicity Demonstrates That BLK, KLF11, and PAX4 Should Not Be Included in Diagnostic Testing for MODY.

Maturity-onset diabetes of the young (MODY) is an autosomal dominant form of monogenic diabetes, reported to be caused by variants in 16 genes. Concern has been raised about whether variants in BLK (MODY11), KLF11 (MODY7), and PAX4 (MODY9) cause MODY. We examined variant-level genetic evidence (cosegregation with diabetes and frequency in population) for published putative pathogenic variants in these genes and used burden testing to test gene-level evidence in a MODY cohort (n = 1,227) compared with a control population (UK Biobank [n = 185,898]). For comparison we analyzed well-established causes of MODY, HNF1A, and HNF4A. The published variants in BLK, KLF11, and PAX4 showed poor cosegregation with diabetes (combined logarithm of the odds [LOD] scores ≤1.2), compared with HNF1A and HNF4A (LOD scores >9), and are all too common to cause MODY (minor allele frequency >4.95 × 10-5). Ultra-rare missense and protein-truncating variants (PTV) were not enriched in a MODY cohort compared with the UK Biobank population (PTV P > 0.05, missense P > 0.1 for all three genes) while HNF1A and HNF4A were enriched (P < 10-6). Findings of sensitivity analyses with different population cohorts supported our results. Variant and gene-level genetic evidence does not support BLK, KLF11, or PAX4 as a cause of MODY. They should not be included in MODY diagnostic genetic testing.

Birth weight and diazoxide unresponsiveness strongly predict the likelihood of congenital hyperinsulinism due to a mutation in ABCC8 or KCNJ11.

OBJECTIVE: Mutations in the KATP channel genes, ABCC8 and KCNJ11, are the most common cause of congenital hyperinsulinism. The diagnosis of KATP-hyperinsulinism is important for the clinical management of the condition. We aimed to determine the clinical features that help to identify KATP-hyperinsulinism at diagnosis. DESIGN: We studied 761 individuals with KATP-hyperinsulinism and 862 probands with hyperinsulinism of unknown aetiology diagnosed before 6 months of age. All were referred as part of routine clinical care. METHODS: We compared the clinical features of KATP-hyperinsulinism and unknown hyperinsulinism cases. We performed logistic regression and receiver operator characteristic (ROC) analysis to identify the features that predict KATP-hyperinsulinism. RESULTS: Higher birth weight, diazoxide unresponsiveness and diagnosis in the first week of life were independently associated with KATP-hyperinsulinism (adjusted odds ratio: 4.5 (95% CI: 3.4-5.9), 0.09 (0.06-0.13) and 3.3 (2.0-5.0) respectively). Birth weight and diazoxide unresponsiveness were additive and highly discriminatory for identifying KATP-hyperinsulinism (ROC area under the curve for birth weight 0.80, diazoxide responsiveness 0.77, and together 0.88, 95% CI: 0.85-0.90). In this study, 86% born large for gestation and 78% born appropriate for gestation and who did not respond to diazoxide treatment had KATP-hyperinsulinism. In contrast, of those individuals born small for gestation, none who were diazoxide responsive and only 4% of those who were diazoxide unresponsive had KATP-hyperinsulinism. CONCLUSIONS: Individuals with hyperinsulinism born appropriate or large for gestation and unresponsive to diazoxide treatment are most likely to have an ABCC8 or KCNJ11 mutation. These patients should be prioritised for genetic testing of KATP channel genes.

YIPF5 mutations cause neonatal diabetes and microcephaly through endoplasmic reticulum stress.

Neonatal diabetes is caused by single gene mutations reducing pancreatic ß cell number or impairing ß cell function. Understanding the genetic basis of rare diabetes subtypes highlights fundamental biological processes in ß cells. We identified 6 patients from 5 families with homozygous mutations in the YIPF5 gene, which is involved in trafficking between the endoplasmic reticulum (ER) and the Golgi. All patients had neonatal/early-onset diabetes, severe microcephaly, and epilepsy. YIPF5 is expressed during human brain development, in adult brain and pancreatic islets. We used 3 human ß cell models (YIPF5 silencing in EndoC-ßH1 cells, YIPF5 knockout and mutation knockin in embryonic stem cells, and patient-derived induced pluripotent stem cells) to investigate the mechanism through which YIPF5 loss of function affects ß cells. Loss of YIPF5 function in stem cell-derived islet cells resulted in proinsulin retention in the ER, marked ER stress, and ß cell failure. Partial YIPF5 silencing in EndoC-ßH1 cells and a patient mutation in stem cells increased the ß cell sensitivity to ER stress-induced apoptosis. We report recessive YIPF5 mutations as the genetic cause of a congenital syndrome of microcephaly, epilepsy, and neonatal/early-onset diabetes, highlighting a critical role of YIPF5 in ß cells and neurons. We believe this is the first report of mutations disrupting the ER-to-Golgi trafficking, resulting in diabetes.

Noninvasive Fetal Genotyping by Droplet Digital PCR to Identify Maternally Inherited Monogenic Diabetes Variants.

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.

Update of variants identified in the pancreatic ß-cell KATP channel genes KCNJ11 and ABCC8 in individuals with congenital hyperinsulinism and diabetes.

The most common genetic cause of neonatal diabetes and hyperinsulinism is pathogenic variants in ABCC8 and KCNJ11. These genes encode the subunits of the ß-cell ATP-sensitive potassium channel, a key component of the glucose-stimulated insulin secretion pathway. Mutations in the two genes cause dysregulated insulin secretion; inactivating mutations cause an oversecretion of insulin, leading to congenital hyperinsulinism, whereas activating mutations cause the opposing phenotype, diabetes. This review focuses on variants identified in ABCC8 and KCNJ11, the phenotypic spectrum and the treatment implications for individuals with pathogenic variants.

Using referral rates for genetic testing to determine the incidence of a rare disease: The minimal incidence of congenital hyperinsulinism in the UK is 1 in 28,389.

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.

Unravelling the genetic causes of mosaic islet morphology in congenital hyperinsulinism.

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 ß-cell expansion in CHI.

Assessing the Pathogenicity, Penetrance, and Expressivity of Putative Disease-Causing Variants in a Population Setting.

More than 100,000 genetic variants are classified as disease causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and might be over-estimated by clinical ascertainment. Here, we use data from 379,768 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants. Although rare variants are harder to genotype accurately than common variants, we were able to classify as high quality 1,244 of 4,585 (27%) putatively clinically relevant rare (MAF < 1%) variants genotyped on the UKB microarray. We defined as "clinically relevant" variants that were classified as either pathogenic or likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases: maturity-onset diabetes of the young (MODY) and severe developmental disorders (DDs). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically relevant traits. 27 of the variants were associated with a UKB trait, and we were able to refine the penetrance estimate for some of the variants. For example, the HNF4A c.340C>T (p.Arg114Trp) (GenBank: NM_175914.4) variant associated with diabetes is <10% penetrant by the time an individual is 40 years old. We also observed associations with relevant traits for heterozygous carriers of some rare recessive conditions, e.g., heterozygous carriers of the ERCC4 c.2395C>T (p.Arg799Trp) variant that causes Xeroderma pigmentosum were more susceptible to sunburn. Finally, we refute the previous disease association of RNF135 in developmental disorders. In conclusion, this study shows that very large population-based studies will help refine our understanding of the pathogenicity of rare genetic variants.

Misannotation of multiple-nucleotide variants risks misdiagnosis.

Multiple Nucleotide Variants (MNVs) are miscalled by the most widely utilised next generation sequencing analysis (NGS) pipelines, presenting the potential for missing diagnoses that would previously have been made by standard Sanger (dideoxy) sequencing. These variants, which should be treated as a single insertion-deletion mutation event, are commonly called as separate single nucleotide variants. This can result in misannotation, incorrect amino acid predictions and potentially false positive and false negative diagnostic results. This risk will be increased as confirmatory Sanger sequencing of Single Nucleotide variants (SNVs) ceases to be standard practice. Using simulated data and re-analysis of sequencing data from a diagnostic targeted gene panel, we demonstrate that the widely adopted pipeline, GATK best practices, results in miscalling of MNVs and that alternative tools can call these variants correctly. The adoption of calling methods that annotate MNVs correctly would present a solution for individual laboratories, however GATK best practices are the basis for important public resources such as the gnomAD database. We suggest integrating a solution into these guidelines would be the optimal approach.

Refinement of the critical genomic region for congenital hyperinsulinism in the Chromosome 9p deletion syndrome.

Background: Large contiguous gene deletions at the distal end of the short arm of chromosome 9 result in the complex multi-organ condition chromosome 9p deletion syndrome.  A range of clinical features can result from these deletions with the most common being facial dysmorphisms and neurological impairment. Congenital hyperinsulinism is a rarely reported feature of the syndrome with the genetic mechanism for the dysregulated insulin secretion being unknown.  Methods: We studied the clinical and genetic characteristics of 12 individuals with chromosome 9p deletions who had a history of neonatal hypoglycaemia. Using off-target reads generated from targeted next-generation sequencing of the genes known to cause hyperinsulinaemic hypoglycaemia (n=9), or microarray analysis (n=3), we mapped the minimal shared deleted region on chromosome 9 in this cohort. Targeted sequencing was performed in three patients to search for a recessive mutation unmasked by the deletion. Results: In 10/12 patients with hypoglycaemia, hyperinsulinism was confirmed biochemically. A range of extra-pancreatic features were also reported in these patients consistent with the diagnosis of the Chromosome 9p deletion syndrome. The minimal deleted region was mapped to 7.2 Mb, encompassing 38 protein-coding genes. In silico analysis of these genes highlighted SMARCA2 and RFX3 as potential candidates for the hypoglycaemia. Targeted sequencing performed on three of the patients did not identify a second disease-causing variant within the minimal deleted region. Conclusions: This study identifies 9p deletions as an important cause of hyperinsulinaemic hypoglycaemia and increases the number of cases reported with 9p deletions and hypoglycaemia to 15 making this a more common feature of the syndrome than previously appreciated.  Whilst the precise genetic mechanism of the dysregulated insulin secretion could not be determined in these patients, mapping the deletion breakpoints highlighted potential candidate genes for hypoglycaemia within the deleted region.

Homozygosity mapping provides supporting evidence of pathogenicity in recessive Mendelian disease.

PURPOSE: One of the greatest challenges currently facing those studying Mendelian disease is identifying the pathogenic variant from the long list produced by a next-generation sequencing test. We investigate the predictive ability of homozygosity mapping for identifying the regions likely to contain the causative variant. METHODS: We use 179 homozygous pathogenic variants from three independent cohorts to investigate the predictive power of homozygosity mapping. RESULTS: We demonstrate that homozygous pathogenic variants in our cohorts are disproportionately likely to be found within one of the largest regions of homozygosity: 80% of pathogenic variants are found in a homozygous region that is in the ten largest regions in a sample. The maximal predictive power is achieved in patients with <8% homozygosity and variants >3 Mb from a telomere; this gives an area under the curve (AUC) of 0.735 and results in 92% of the causative variants being in one of the ten largest homozygous regions. CONCLUSION: This predictive power can be used to prioritize the list of candidate variants in gene discovery studies. When classifying a homozygous variant the size and rank of the region of homozygosity in which the candidate variant is located can also be considered as supporting evidence for pathogenicity.

Correction: Homozygosity mapping provides supporting evidence of pathogenicity in recessive Mendelian disease.

The original version of this Article contained an error in the top left of Figure 2: the number 1 on the y-axis had been changed to 0 during the typesetting process. This has now been corrected in both the PDF and HTML versions of the Article.