A CACNA1D mutation in a patient with persistent hyperinsulinaemic hypoglycaemia, heart defects, and severe hypotonia.

Congenital hyperinsulinaemic hypoglycaemia (HH) can occur in isolation or it may present as part of a wider syndrome. For approximately 40%-50% of individuals with this condition, sequence analysis of the known HH genes identifies a causative mutation. Identifying the underlying genetic aetiology in the remaining cases is important as a genetic diagnosis will inform on recurrence risk, may guide medical management and will provide valuable insights into β-cell physiology. We sequenced the exome of a child with persistent diazoxide-responsive HH, mild aortic insufficiency, severe hypotonia, and developmental delay as well as the unaffected parents. This analysis identified a de novo mutation, p.G403D, in the proband's CACNA1D gene. CACNA1D encodes the main L-type voltage-gated calcium channel in the pancreatic β-cell, a key component of the insulin secretion pathway. The p.G403D mutation had been reported previously as an activating mutation in an individual with primary hyper-aldosteronism, neuromuscular abnormalities, and transient hypoglycaemia. Sequence analysis of the CACNA1D gene in 60 further cases with HH did not identify a pathogenic mutation. Identification of an activating CACNA1D mutation in a second patient with congenital HH confirms the aetiological role of CACNA1D mutations in this disorder. A genetic diagnosis is important as treatment with a calcium channel blocker may be an option for the medical management of this patient

Predicting the Occurrence of Variants in RAG1 and RAG2

Abstract: While widespread genome sequencing ushers in a new era of preventive medicine, the tools for predictive genomics are still lacking. Time and resource limitations mean that human diseases remain uncharacterized because of an inability to predict clinically relevant genetic variants. A strategy of targeting highly conserved protein regions is used commonly in functional studies. However, this benefit is lost for rare diseases where the attributable genes are mostly conserved. An immunological disorder exemplifying this challenge occurs through damaging mutations in RAG1 and RAG2 which presents at an early age with a distinct phenotype of life-threatening immunodeficiency or autoimmunity. Many tools exist for variant pathogenicity prediction, but these cannot account for the probability of variant occurrence. Here, we present a method that predicts the likelihood of mutation for every amino acid residue in the RAG1 and RAG2 proteins. Population genetics data from approximately 146,000 individuals was used for rare variant analysis. Forty-four known pathogenic variants reported in patients and recombination activity measurements from 110 RAG1/2 mutants were used to validate calculated scores. Probabilities were compared with 98 currently known human cases of disease. A genome sequence dataset of 558 patients who have primary immunodeficiency but that are negative for RAG deficiency were also used as validation controls. We compared the difference between mutation likelihood and pathogenicity prediction. Our method builds a map of most probable mutations allowing pre-emptive functional analysis. This method may be applied to other diseases with hopes of improving preparedness for clinical diagnosis

Improved genetic testing for monogenic diabetes using targeted next-generation sequencing

addresses: Institute for Biomedical and Clinical Science, University of Exeter Medical School, Barrack Road, Exeter EX2 5DW, UK. [email protected]: PMCID: PMC3737433types: Journal Article; Research Support, Non-U.S. Gov'tOpen Access ArticleCurrent genetic tests for diagnosing monogenic diabetes rely on selection of the appropriate gene for analysis according to the patient's phenotype. Next-generation sequencing enables the simultaneous analysis of multiple genes in a single test. Our aim was to develop a targeted next-generation sequencing assay to detect mutations in all known MODY and neonatal diabetes genes

MetaRanker 2.0: a web server for prioritization of genetic variation data

MetaRanker 2.0 is a web server for prioritization of common and rare frequency genetic variation data. Based on heterogeneous data sets including genetic association data, protein–protein interactions, large-scale text-mining data, copy number variation data and gene expression experiments, MetaRanker 2.0 prioritizes the protein-coding part of the human genome to shortlist candidate genes for targeted follow-up studies. MetaRanker 2.0 is made freely available at www.cbs.dtu.dk/services/MetaRanker-2.0

Exonic enhancers: proceed with caution in exome and genome sequencing studies

Exonic enhancers (eExons) are coding exons that also function as enhancers of the gene in which they reside or (a) nearby gene(s). Mutations that affect the enhancer activity of these eExons have been associated with human disease. Therefore, eExon mutations should be taken into account in exome and genome sequencing projects, not only because of the ability of these mutations to modify the encoded proteins but also because of their effects on enhancer activity

Allelic expression analysis of the osteoarthritis susceptibility locus that maps to MICAL3

<p>Abstract</p> <p>Background</p> <p>A genome-wide association scan with subsequent replication study that involved over 67,000 individuals of European ancestry has produced evidence of association of single nucleotide polymorphism rs2277831 to primary osteoarthritis (OA) with a P-value of 2.9 × 10^-5. rs2277831, an A/G transition, is located in an intron of <it>MICAL3</it>. This gene is located on chromosome 22q11.21 and the association signal encompasses two additional genes, <it>BCL2L13 </it>and <it>BID</it>. It is becoming increasingly apparent that many common complex traits are mediated by <it>cis</it>-acting regulatory polymorphisms that influence, in a tissue-specific manner, gene expression or transcript stability.</p> <p>Methods</p> <p>We used total and allelic expression analysis to assess whether the OA association to rs2277831 is mediated by an influence on MICAL3, BCL2L13 or BID expression. Using RNA extracted from joint tissues of 60 patients who had undergone elective joint replacement surgery, we assessed whether rs2277831 correlated with allelic expression of either of the three genes by: 1) measuring the expression of each gene by quantitative PCR and then stratifying the data by genotype at rs2277831 and 2) accurately discriminating and quantifying the mRNA synthesised from the alleles of OA patients using allelic-quantitative PCR.</p> <p>Results</p> <p>We found no evidence for a correlation between gene expression and genotype at rs2277831, with P-values of 0.09 for <it>BCL2L13</it>, 0.07 for <it>BID </it>and 0.33 for <it>MICAL3</it>. In the allelic expression analysis we observed several examples of significant (p < 0.05) allelic imbalances, with an allelic expression ratio of 2.82 observed in <it>BCL2L13 </it>(P = 0.004), 2.09 at <it>BID </it>(P = 0.001) and the most extreme case being at <it>MICAL3</it>, with an allelic expression ratio of 5.47 (P = 0.001). However, there was no correlation observed between the pattern of allelic expression and the genotype at rs2277831.</p> <p>Conclusions</p> <p>In the tissues that we have studied, our data do not support our hypothesis that the association between rs2277831 and OA is due to the effect this SNP has on <it>MICAL3, BCL2L13 </it>or <it>BID </it>gene expression. Instead, our data point towards other functional effects accounting for the OA associated signal.</p

An in-frame deletion at the polymerase active site of POLD1 causes a multisystem disorder with lipodystrophy

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.DNA polymerase δ, whose catalytic subunit is encoded by POLD1, is responsible for lagging-strand DNA synthesis during DNA replication. It carries out this synthesis with high fidelity owing to its intrinsic 3'- to 5'-exonuclease activity, which confers proofreading ability. Missense mutations affecting the exonuclease domain of POLD1 have recently been shown to predispose to colorectal and endometrial cancers. Here we report a recurring heterozygous single-codon deletion in POLD1 affecting the polymerase active site that abolishes DNA polymerase activity but only mildly impairs 3'- to 5'-exonuclease activity. This mutation causes a distinct multisystem disorder that includes subcutaneous lipodystrophy, deafness, mandibular hypoplasia and hypogonadism in males. This discovery suggests that perturbing the function of the ubiquitously expressed POLD1 polymerase has unexpectedly tissue-specific effects in humans and argues for an important role for POLD1 function in adipose tissue homeostasis.This work was supported by NIHR Exeter Clinical Research Facility through funding for SE and ATH and general infrastructure. The authors thank Michael Day, Annet Damhuis and Richard Gilbert for technical assistance. We thank Karen Knapp for providing the data for the DEXA calculations. SE, ATH, SO are supported by Wellcome Weedon et al. Page 6 Nat Genet. Author manuscript; available in PMC 2014 February 01. Europe PMC Funders Author Manuscripts Europe PMC Funders Author Manuscripts Trust Senior Investigator awards. DS and RKS (098498/Z/12/Z) are supported by Wellcome Trust Senior Research Fellowships in Clinical Science. MNW is supported by the Wellcome Trust as part of the WT Biomedical Informatics Hub funding. RO is supported by Diabetes UK. DS, RKS and SO are supported by the UK National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. KJG is supported by the Agency for Science, Technology and Research, Singapore (A*STAR). LAL and MJP are supported by grants NCI-61-6845 and 62-4860

Novel genetic analysis for case-control genome-wide association studies: quantification of power and genomic prediction accuracy

Genome-wide association studies (GWAS) are routinely conducted for both quantitative and binary (disease) traits. We present two analytical tools for use in the experimental design of GWAS. Firstly, we present power calculations quantifying power in a unified framework for a range of scenarios. In this context we consider the utility of quantitative scores (e.g. endophenotypes) that may be available on cases only or both cases and controls. Secondly, we consider, the accuracy of prediction of genetic risk from genome-wide SNPs and derive an expression for genomic prediction accuracy using a liability threshold model for disease traits in a case-control design. The expected values based on our derived equations for both power and prediction accuracy agree well with observed estimates from simulations