52 results found
David A, Khanna T, Hanna G, et al., 2021, Missense3D-DB web catalogue: an atom-based analysis and repository of 4M human protein-coding genetic variants, Human Genetics, Vol: 140, Pages: 805-812, ISSN: 0340-6717
The interpretation of human genetic variation is one of the greatest challenges of modern genetics. New approaches are urgently needed to prioritize variants, especially those that are rare or lack a definitive clinical interpretation. We examined 10,136,597 human missense genetic variants from GnomAD, ClinVar and UniProt. We were able to perform large-scale atom-based mapping and phenotype interpretation of 3,960,015 of these variants onto 18,874 experimental and 84,818 in house predicted three-dimensional coordinates of the human proteome. We demonstrate that 14% of amino acid substitutions from the GnomAD database that could be structurally analysed are predicted to affect protein structure (n = 568,548, of which 566,439 rare or extremely rare) and may, therefore, have a yet unknown disease-causing effect. The same is true for 19.0% (n = 6266) of variants of unknown clinical significance or conflicting interpretation reported in the ClinVar database. The results of the structural analysis are available in the dedicated web catalogue Missense3D-DB (http://missense3d.bc.ic.ac.uk/). For each of the 4 M variants, the results of the structural analysis are presented in a friendly concise format that can be included in clinical genetic reports. A detailed report of the structural analysis is also available for the non-experts in structural biology. Population frequency and predictions from SIFT and PolyPhen are included for a more comprehensive variant interpretation. This is the first large-scale atom-based structural interpretation of human genetic variation and offers geneticists and the biomedical community a new approach to genetic variant interpretation.
David A, Parkinson N, Peacock TP, et al., 2021, A common TMPRSS2 variant protects against severe COVID-19
<jats:title>Summary</jats:title><jats:p>Infection with SARS-CoV-2 has a wide range of clinical presentations, from asymptomatic to life-threatening. Old age is the strongest factor associated with increased COVID19-related mortality, followed by sex and pre-existing conditions. The importance of genetic and immunological factors on COVID19 outcome is also starting to emerge, as demonstrated by population studies and the discovery of damaging variants in genes controlling type I IFN immunity and of autoantibodies that neutralize type I IFNs. The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus’ spike protein, facilitating entry into target cells. We focused on the only common <jats:italic>TMPRSS2</jats:italic> non-synonymous variant predicted to be damaging (rs12329760), which has a minor allele frequency of ∼25% in the population. In a large population of SARS-CoV-2 positive patients, we show that this variant is associated with a reduced likelihood of developing severe COVID19 (OR 0.87, 95%CI:0.79-0.97, p=0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p=1.3×10<jats:sup>−3</jats:sup>). We demonstrate <jats:italic>in vitro</jats:italic> that this variant, which causes the amino acid substitution valine to methionine, impacts the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells.</jats:p><jats:p><jats:italic>TMPRSS2</jats:italic> rs12329760 is a common variant associated with a significantly decreased risk of severe COVID19. Further studies are needed to assess the expression of the <jats:italic>TMPRSS2</jats:italic> across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role f
Lagou V, Jiang L, Ulrich A, et al., 2021, Random glucose GWAS in 493,036 individuals provides insights into diabetes pathophysiology, complications and treatment stratification, medRxiv
Homeostatic control of blood glucose requires different physiological responses in the fasting and post-prandial states. We reasoned that glucose measurements under non-standardised conditions (random glucose; RG) may capture diverse glucoregulatory processes more effectively than previous genome-wide association studies (GWAS) of fasting glycaemia or after standardised glucose loads. Through GWAS meta-analysis of RG in 493,036 individuals without diabetes of diverse ethnicities we identified 128 associated loci represented by 162 distinct signals, including 14 with sex-dimorphic effects, 9 discovered through trans-ethnic analysis, and 70 novel signals for glycaemic traits. Novel RG loci were particularly enriched in expression in the ileum and colon, indicating a prominent role for the gastrointestinal tract in the control of blood glucose. Functional studies and molecular dynamics simulations of coding variants of GLP1R, a well-established type 2 diabetes treatment target, provided a genetic framework for optimal selection of GLP-1R agonist therapy. We also provided new evidence from Mendelian randomisation that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Thus, our approach based on RG GWAS provided wide-ranging insights into the biology of glucose regulation, diabetes complications and the potential for treatment stratification.Competing Interest StatementAlejandra Tomas has received grant funding from Sun Pharmaceuticals. Ivan R Corrêa, Jr is an employee of New England Biolabs, Inc., a manufacturer and vendor of reagents for life science research. Mark J Caulfield is Chief Scientist for Genomics England, a UK Government company. The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. Mark McCarthy has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo No
Jones B, Fang Z, Chen S, et al., 2020, Ligand-specific factors influencing GLP-1 receptor post-endocytic trafficking and degradation in pancreatic beta cells, International Journal of Molecular Sciences, Vol: 212, Pages: 1-24, ISSN: 1422-0067
The glucagon-like peptide-1 receptor (GLP-1R) is an important regulator of blood glucose homeostasis. Ligand-specific differences in membrane trafficking of the GLP-1R influence its signalling properties and therapeutic potential in type 2 diabetes. Here, we have evaluated how different factors combine to control the post-endocytic trafficking of GLP-1R to recycling versus degradative pathways. Experiments were performed in primary islet cells, INS-1 832/3 clonal beta cells and HEK293 cells, using biorthogonal labelling of GLP-1R to determine its localisation and degradation after treatment with GLP-1, exendin-4 and several further GLP-1R agonist peptides. We also characterised the effect of a rare GLP1R coding variant, T149M, and the role of endosomal peptidase endothelin-converting enzyme-1 (ECE-1), in GLP1R trafficking. Our data reveal how treatment with GLP-1 versus exendin-4 is associated with preferential GLP-1R targeting towards a recycling pathway. GLP-1, but not exendin-4, is a substrate for ECE-1, and the resultant propensity to intra-endosomal degradation, in conjunction with differences in binding affinity, contributes to alterations in GLP-1R trafficking behaviours and degradation. The T149M GLP-1R variant shows reduced signalling and internalisation responses, which is likely to be due to disruption of the cytoplasmic region that couples to intracellular effectors. These observations provide insights into how ligand- and genotype-specific factors can influence GLP-1R trafficking.
Zhang Q, Bastard P, Liu Z, et al., 2020, Inborn errors of type I IFN immunity in patients with life-threatening COVID-19, Science, Vol: 370, Pages: 1-16, ISSN: 0036-8075
Clinical outcome upon infection with SARS-CoV-2 ranges from silent infection to lethal COVID-19. We have found an enrichment in rare variants predicted to be loss-of-function (LOF) at the 13 human loci known to govern TLR3- and IRF7-dependent type I interferon (IFN) immunity to influenza virus, in 659 patients with life-threatening COVID-19 pneumonia, relative to 534 subjects with asymptomatic or benign infection. By testing these and other rare variants at these 13 loci, we experimentally define LOF variants in 23 patients (3.5%), aged 17 to 77 years, underlying autosomal recessive or dominant deficiencies. We show that human fibroblasts with mutations affecting this pathway are vulnerable to SARS-CoV-2. Inborn errors of TLR3- and IRF7-dependent type I IFN immunity can underlie life-threatening COVID-19 pneumonia in patients with no prior severe infection.
David A, Barbié V, Attimonelli M, et al., 2020, Annotation and curation of human genomic variations: an ELIXIR Implementation Study, F1000Research, Vol: 9, Pages: 1207-1207
<ns4:p><ns4:bold>Background:</ns4:bold> ELIXIR is an intergovernmental organization, primarily based around European countries, established to host life science resources, including databases, software tools, training material and cloud storage for the scientific community under a single infrastructure.</ns4:p><ns4:p> <ns4:bold>Methods:</ns4:bold> In 2018, ELIXIR commissioned an international survey on the usage of databases and tools for annotating and curating human genomic variants with the aim of improving ELIXIR resources. The 27-question survey was made available on-line between September and December 2018 to rank the importance and explore the usage and limitations of a wide range of databases and tools for annotating and curating human genomic variants, including resources specific for next generation sequencing, research into mitochondria and protein structure.</ns4:p><ns4:p> <ns4:bold>Results:</ns4:bold> Eighteen countries participated in the survey and a total of 92 questionnaires were collected and analysed. Most respondents (89%, n=82) were from academia or a research environment. 51% (n=47) of respondents gave answers on behalf of a small research group (<10 people), 33% (n=30) in relation to individual work and 16% (n=15) on behalf of a large group (>10 people). The survey showed that the scientific community considers several resources supported by ELIXIR crucial or very important. Moreover, it showed that the work done by ELIXIR is greatly valued. In particular, most respondents acknowledged the importance of key features and benefits promoted by ELIXIR, such as the verified scientific quality and maintenance of ELIXIR-approved resources.</ns4:p><ns4:p> <ns4:bold>Conclusions</ns4:bold> ELIXIR is a “one-stop-shop” that helps researchers identify the most suitable, robust and well-maintained bioinformatics resources for delivering their
Mancini A, Howard SR, Marelli F, et al., 2020, LGR4 deficiency results in delayed puberty through impaired Wnt/β-catenin signaling, JCI insight, Vol: 5, Pages: 1-17, ISSN: 2379-3708
The initiation of puberty is driven by an upsurge in hypothalamic gonadotropin-releasing hormone (GnRH) secretion. In turn, GnRH secretion upsurge depends on the development of a complex GnRH neuroendocrine network during embryonic life. Although delayed puberty (DP) affects up to 2% of the population, is highly heritable, and is associated with adverse health outcomes, the genes underlying DP remain largely unknown. We aimed to discover regulators by whole-exome sequencing of 160 individuals of 67 multigenerational families in our large, accurately phenotyped DP cohort. LGR4 was the only gene remaining after analysis that was significantly enriched for potentially pathogenic, rare variants in 6 probands. Expression analysis identified specific Lgr4 expression at the site of GnRH neuron development. LGR4 mutant proteins showed impaired Wnt/β-catenin signaling, owing to defective protein expression, trafficking, and degradation. Mice deficient in Lgr4 had significantly delayed onset of puberty and fewer GnRH neurons compared with WT, whereas lgr4 knockdown in zebrafish embryos prevented formation and migration of GnRH neurons. Further, genetic lineage tracing showed strong Lgr4-mediated Wnt/β-catenin signaling pathway activation during GnRH neuron development. In conclusion, our results show that LGR4 deficiency impairs Wnt/β-catenin signaling with observed defects in GnRH neuron development, resulting in a DP phenotype.
David A, Sternberg M, 2020, Structure, function and variants analysis of the androgen-regulated TMPRSS2, a drug target candidate for COVID-19 infection, bioRxiv
David A, 2020, A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin, Molecular Genetics and Genomic Medicine, Vol: 8, Pages: 1-9, ISSN: 2324-9269
BackgroundSevere hypercholesterolemia (HC, LDL‐C > 4.9 mmol/L) affects over 30 million people worldwide. In this study, we validated a new polygenic risk score (PRS) for LDL‐C.MethodsSummary statistics from the Global Lipid Genome Consortium and genotype data from two large populations were used.ResultsA 36‐SNP PRS was generated using data for 2,197 white Americans. In a replication cohort of 4,787 Finns, the PRS was strongly associated with the LDL‐C trait and explained 8% of its variability (p = 10–41). After risk categorization, the risk of having HC was higher in the high‐ versus low‐risk group (RR = 4.17, p < 1 × 10−7). Compared to a 12‐SNP LDL‐C raising score (currently used in the United Kingdom), the PRS explained more LDL‐C variability (8% vs. 6%). Among Finns with severe HC, 53% (66/124) versus 44% (55/124) were classified as high risk by the PRS and LDL‐C raising score, respectively. Moreover, 54% of individuals with severe HC defined as low risk by the LDL‐C raising score were reclassified to intermediate or high risk by the new PRS.ConclusionThe new PRS has a better predictive role in identifying HC of polygenic origin compared to the currently available method and can better stratify patients into diagnostic and therapeutic algorithms.
Leal Ayala LG, David A, Jarvelin MR, et al., 2019, Identification of disease-associated loci using machine learning for genotype and network data integration, Bioinformatics, Vol: 35, Pages: 5182-5190, ISSN: 1367-4803
MotivationIntegration of different omics data could markedly help to identify biological signatures, understand the missing heritability of complex diseases and ultimately achieve personalized medicine. Standard regression models used in Genome-Wide Association Studies (GWAS) identify loci with a strong effect size, whereas GWAS meta-analyses are often needed to capture weak loci contributing to the missing heritability. Development of novel machine learning algorithms for merging genotype data with other omics data is highly needed as it could enhance the prioritization of weak loci.ResultsWe developed cNMTF (corrected non-negative matrix tri-factorization), an integrative algorithm based on clustering techniques of biological data. This method assesses the inter-relatedness between genotypes, phenotypes, the damaging effect of the variants and gene networks in order to identify loci-trait associations. cNMTF was used to prioritize genes associated with lipid traits in two population cohorts. We replicated 129 genes reported in GWAS world-wide and provided evidence that supports 85% of our findings (226 out of 265 genes), including recent associations in literature (NLGN1), regulators of lipid metabolism (DAB1) and pleiotropic genes for lipid traits (CARM1). Moreover, cNMTF performed efficiently against strong population structures by accounting for the individuals’ ancestry. As the method is flexible in the incorporation of diverse omics data sources, it can be easily adapted to the user’s research needs.
Trivedi N, Loh W, David A, et al., 2019, Lipoprotein(a) as a predictive biomarker for subclinical coronary atherosclerosis, Endocrine Abstracts
David A, Hart T, Cegla J, et al., 2019, CORONARY CALCIUM SCORE IN PATIENTS WITH CLINICAL CRITERIA FOR FAMILIAL HYPERCHOLESTEROLAEMIA, HEART UK 33rd Annual Medical and Scientific Conference, Publisher: ELSEVIER IRELAND LTD, Pages: E2-E2, ISSN: 1567-5688
Ragavan A, David A, Scott J, et al., 2019, EVOLOCUMAB THERAPY AND A POSSIBLE ASSOCIATION WITH SKIN REACTIONS, HEART UK 33rd Annual Medical and Scientific Conference, Publisher: ELSEVIER IRELAND LTD, Pages: E7-E7, ISSN: 1567-5688
Ittisoponpisan S, Islam S, Khanna T, et al., 2019, Can predicted protein 3D-structures provide reliable insights into whether missense variants are disease-associated?, Journal of Molecular Biology, Vol: 431, Pages: 2197-2212, ISSN: 0022-2836
Knowledge of protein structure can be used to predict the phenotypic consequence of a missense variant. Since structural coverage of the human proteome can be roughly tripled to over 50% of the residues if homology-predicted structures are included in addition to experimentally determined coordinates, it is important to assess the reliability of using predicted models when analyzing missense variants. Accordingly, we assess whether a missense variant is structurally damaging by using experimental and predicted structures. We considered 606 experimental structures and show that 40% of the 1965 disease-associated missense variants analyzed have a structurally damaging change in the mutant structure. Only 11% of the 2134 neutral variants are structurally damaging. Importantly, similar results are obtained when 1052 structures predicted using Phyre2 algorithm were used, even when the model shares low (< 40%) sequence identity to the template. Thus, structure-based analysis of the effects of missense variants can be effectively applied to homology models. Our in-house pipeline, Missense3D, for structurally assessing missense variants was made available at http://www.sbg.bio.ic.ac.uk/~missense3d
Ofoegbu T, David A, Kelley L, et al., 2019, PhyreRisk: a dynamic web application to bridge genomics, proteomics and 3D structural data to guide interpretation of human genetic variants, Journal of Molecular Biology, Vol: 431, Pages: 2460-2466, ISSN: 0022-2836
PhyreRisk is an open-access, publicly accessible web application for interactively bridging genomic, proteomic and structural data facilitating the mapping of human variants onto protein structures. A major advance over other tools for sequence-structure variant mapping is that PhyreRisk provides information on 20,214 human canonical proteins and an additional 22,271 alternative protein sequences (isoforms). Specifically, PhyreRisk provides structural coverage (partial or complete) for 70% (14,035 of 20,214 canonical proteins) of the human proteome, by storing 18,874 experimental structures and 84,818 pre-built models of canonical proteins and their isoforms generated using our in house Phyre2. PhyreRisk reports 55,732 experimentally, multi-validated protein interactions from IntAct and 24,260 experimental structures of protein complexes.Another major feature of PhyreRisk is that, rather than presenting a limited set of precomputed variant-structure mapping of known genetic variants, it allows the user to explore novel variants using, as input, genomic coordinates formats (Ensembl, VCF, reference SNP ID and HGVS notations) and Human Build GRCh37 and GRCh38. PhyreRisk also supports mapping variants using amino acid coordinates and searching for genes or proteins of interest.PhyreRisk is designed to empower researchers to translate genetic data into protein structural information, thereby providing a more comprehensive appreciation of the functional impact of variants. PhyreRisk is freely available at http://phyrerisk.bc.ic.ac.uk
Mancini A, Howard SR, Cabrera CP, et al., 2019, EAP1 regulation of GnRH promoter activity is important for human pubertal timing, HUMAN MOLECULAR GENETICS, Vol: 28, Pages: 1357-1368, ISSN: 0964-6906
David A, Ittisoponpisan S, Sternberg MJE, 2018, PROTEIN STRUCTURE ANALYSIS AIDS IN THE INTERPRETATION OF GENETIC VARIANTS OF UNCERTAIN CLINICAL SIGNIFICANCE IDENTIFIED IN THE LDL RECEPTOR, HEART UK 32nd Annual Medical and Scientific Conference on Hot Topics in Atheroscloerosis and Cardiovascular Disease, Publisher: ELSEVIER IRELAND LTD, Pages: E2-E3, ISSN: 1567-5688
David A, Cegla J, Walji S, et al., 2018, Hypercholesterolemia with low versus high likelihood of polygenic origin: a single centre experience, HEART UK 32nd Annual Medical and Scientific Conference on Hot Topics in Atheroscloerosis and Cardiovascular Disease, Publisher: Elsevier, Pages: E7-E7, ISSN: 1567-5688
Introduction: A large proportion of patients that meet Simon Broome diagnostic criteria for Familial Hypercholesterolemia (FH) have no single-gene mutations (FH-negative patients) and an LDL-C SNP score suggestive of a low likelihood of hypercholesterolemia (HC) of polygenic origin. In these patients, unknown genetic causes of FH may be present. Aims: to compare the clinical characteristics of: 1) FH-negative versus FH-positive patients and 2) FH-negative patients with high versus low likelihood of polygenic (LPg) HC.Methods: Genetic data, lipid profile, history of cardiovascular events (CVE) and family history of CVE were obtained in 109 index cases (age range 17-81years) with a clinical diagnosis of possible or definite FH.Results: FH-negative patients (n=78) were older when diagnosed with HC compared to FH-positive patients (n=31): age at diagnosis 50±11 vs 31±12, p<0.001. Moreover, they had lower LDL cholesterol (C) levels pre-treatment (5.8±0. 9 vs 6.8±1.5mmol/L, p<0.001), but higher HDL-C levels (1.6±0.5 vs 1.3±0.3mmol/L, p<0.03) compared to FH-positive patients. No difference in age at diagnosis (p=0.92), LDL-C (p=0.63) and HDL-C (p=0.25) levels pre-treatment was present between FH-negative with high-LPg (n=50) versus low-LPg (n=28). Physical stigmata of HC were commoner in FH-negative low-LPg (8/21, 38.1%) versus high-LPg (3/40, 7.5%) patients (p<0.001). Moreover, 22% low-LPg patients had suffered a CVE versus 8% high-LPg patients, although this was not statistically significant (p=0.15). No difference was found in the prevalence of physical stigmata of HC (p=0.93) or history of CVE (p=0.64) in FH-negative versus FH-positive patients. There was no significant difference in total cholesterol, triglycerides, Lp(a) levels as well as the prevalence of hypertension, smoking, diabetes/IGT or family history of premature CVE between FH-negative versus FH-positive or FH-negative with high-LPg versus low-LPg patien
Loh WJ, David A, Walji S, et al., 2018, POSITIVE ASSOCIATION OF LIPOPROTEIN(A) WITH CT CORONARY CALCIUM SCORE IN ASYMPTOMATIC CAUCASIANS BUT NOT IN OTHER ETHNICITIES, 86th Congress of the European-Atherosclerosis-Society (EAS), Publisher: ELSEVIER IRELAND LTD, Pages: E161-E161, ISSN: 0021-9150
Ittisoponpisan S, David A, 2018, Structural biology helps interpret variants of uncertain significance in genes causing endocrine and metabolic disorders, Journal of the Endocrine Society, Vol: 2, Pages: 842-854, ISSN: 2472-1972
ContextVariants of uncertain significance (VUSs) lack sufficient evidence, in terms of statistical power or experimental studies, to allow unequivocal determination of their damaging effect. VUSs are a major burden in performing genetic analysis. Although in silico prediction tools are widely used, their specificity is low, thus urgently calling for methods for prioritizing and characterizing variants.ObjectiveTo assess the frequency of VUSs in genes causing endocrine and metabolic disorders, the concordance rate of predictions from different in silico methods, and the added value of three-dimensional protein structure analysis in discerning and prioritizing damaging variants.ResultsA total of 12,266 missense variants reported in 641 genes causing endocrine and metabolic disorders were analyzed. Among these, 4123 (33.7%) were VUSs, of which 2010 (48.8%) were predicted to be damaging and 1452 (35.2%) were predicted to be tolerated according to in silico tools. A total of 5383 (87.7%) of 6133 disease-causing variants and 823 (55.8%) of 1474 benign variants were correctly predicted. In silico predictions were noninformative in 5.7%, 14.4%, and 16% of damaging, benign, and VUSs, respectively. A damaging effect on 3D protein structure was present in 240 (30.9%) of predicted damaging and 40 (9.7%) of predicted tolerated VUSs (P < 0.001). An in-depth analysis of nine VUSs occurring in TSHR, LDLR, CASR, and APOE showed that they greatly affect protein stability and are therefore strong candidates for disease.ConclusionsIn our dataset, we confirmed the high sensitivity but low specificity of in silico predictions tools. 3D protein structural analysis is a compelling tool for characterizing and prioritizing VUSs and should be a part of genetic variant analysis.
Cornish AJ, David A, Sternberg MJE, 2018, PhenoRank: reducing study bias in gene prioritisation through simulation, Bioinformatics, Vol: 34, Pages: 2087-2095, ISSN: 1367-4803
Motivation: Genome-wide association studies have identified thousands of loci associated with human disease, but identifying the causal genes at these loci is often difficult. Several methods prioritise genes most likely to be disease causing through the integration of biological data, including protein-protein interaction and phenotypic data. Data availability is not the same for all genes however, potentially influencing the performance of these methods. Results: We demonstrate that whilst disease genes tend to be associated with greater numbers of data, this may be at least partially a result of them being better studied. With this observation we develop PhenoRank, which prioritises disease genes whilst avoiding being biased towards genes with more available data. Bias is avoided by comparing gene scores generated for the query disease against gene scores generated using simulated sets of phenotype terms, which ensures that differences in data availability do not affect the ranking of genes. We demonstrate that whilst existing prioritisation methods are biased by data availability, PhenoRank is not similarly biased. Avoiding this bias allows PhenoRank to effectively prioritise genes with fewer available data and improves its overall performance. PhenoRank outperforms three available prioritisation methods in cross-validation (PhenoRank area under receiver operating characteristic curve [AUC]=0.89, DADA AUC=0.87, EXOMISER AUC=0.71, PRINCE AUC=0.83, P < 2.2 × 10-16). Availability: PhenoRank is freely available for download at https://github.com/alexjcornish/PhenoRank. Contact: email@example.com. Supplementary information: Supplementary data are available at Bioinformatics online.
Dimopoulos K, David A, 2018, Future research, Heart Failure in Adult Congenital Heart Disease, Editors: Swan, Frogoudaki, Publisher: Springer, Pages: 251-263, ISBN: 9783319778020
This book sheds new light on the diagnosis and treatment of Heart Failure in adult patients with congenital heart disease. This is a rapidly growing clinical issue for this group of patients and the clinical teams caring for them.
Alhuzimi E, Leal LG, Sternberg MJE, et al., 2017, Properties of human genes guided by their enrichment in rare and common variants, Human Mutation, Vol: 39, Pages: 365-370, ISSN: 1059-7794
We analyzed 563,099 common (minor allele frequency, MAF≥0.01) and rare (MAF < 0.01) genetic variants annotated in ExAC and UniProt and 26,884 disease-causing variants from ClinVar and UniProt occurring in the coding region of 17,975 human protein-coding genes. Three novel sets of genes were identified: those enriched in rare variants (n = 32 genes), in common variants (n = 282 genes), and in disease-causing variants (n = 800 genes). Genes enriched in rare variants have far greater similarities in terms of biological and network properties to genes enriched in disease-causing variants, than to genes enriched in common variants. However, in half of the genes enriched in rare variants (AOC2, MAMDC4, ANKHD1, CDC42BPB, SPAG5, TRRAP, TANC2, IQCH, USP54, SRRM2, DOPEY2, and PITPNM1), no disease-causing variants have been identified in major, publicly available databases. Thus, genetic variants in these genes are strong candidates for disease and their identification, as part of sequencing studies, should prompt further in vitro analyses.
Howard SR, Guasti L, Poliandri A, et al., 2017, Contributions of function-altering variants in genes implicated in pubertal timing and body mass for self-limited delayed puberty, Journal of Clinical Endocrinology and Metabolism, Vol: 103, Pages: 649-659, ISSN: 0021-972X
Context:Self-limited delayed puberty (DP) is often associated with a delay in physical maturation, but although highly heritable the causal genetic factors remain elusive. Genome-wide association studies of the timing of puberty have identified multiple loci for age at menarche in females and voice break in males, particularly in pathways controlling energy balance.Objective/Main Outcome Measures:We sought to assess the contribution of rare variants in such genes to the phenotype of familial DP.Design/Patients:We performed whole-exome sequencing in 67 pedigrees (125 individuals with DP and 35 unaffected controls) from our unique cohort of familial self-limited DP. Using a whole-exome sequencing filtering pipeline one candidate gene [fat mass and obesity–associated gene (FTO)] was identified. In silico, in vitro, and mouse model studies were performed to investigate the pathogenicity of FTO variants and timing of puberty in FTO+/− mice.Results:We identified potentially pathogenic, rare variants in genes in linkage disequilibrium with genome-wide association studies of age at menarche loci in 283 genes. Of these, five genes were implicated in the control of body mass. After filtering for segregation with trait, one candidate, FTO, was retained. Two FTO variants, found in 14 affected individuals from three families, were also associated with leanness in these patients with DP. One variant (p.Leu44Val) demonstrated altered demethylation activity of the mutant protein in vitro. Fto+/− mice displayed a significantly delayed timing of pubertal onset (P < 0.05).Conclusions:Mutations in genes implicated in body mass and timing of puberty in the general population may contribute to the pathogenesis of self-limited DP.
Salvatori R, Radian S, Diekmann Y, et al., 2017, In-frame seven amino-acid duplication in AIP arose over the last 3000 years, disrupts protein interaction and stability and is associated with gigantism, European Journal of Endocrinology, Vol: 177, Pages: 257-266, ISSN: 0804-4643
Objective Mutations in the aryl hydrocarbon receptor-interacting protein (AIP) gene are associated with pituitary adenoma, acromegaly and gigantism. Identical alleles in unrelated pedigrees could be inherited from a common ancestor or result from recurrent mutation events.Design and methods Observational, inferential and experimental study, including: AIP mutation testing; reconstruction of 14 AIP-region (8.3 Mbp) haplotypes; coalescent-based approximate Bayesian estimation of the time to most recent common ancestor (tMRCA) of the derived allele; forward population simulations to estimate current number of allele carriers; proposal of mutation mechanism; protein structure predictions; co-immunoprecipitation and cycloheximide chase experiments.Results Nine European-origin, unrelated c.805_825dup-positive pedigrees (four familial, five sporadic from the UK, USA and France) included 16 affected (nine gigantism/four acromegaly/two non-functioning pituitary adenoma patients and one prospectively diagnosed acromegaly patient) and nine unaffected carriers. All pedigrees shared a 2.79 Mbp haploblock around AIP with additional haploblocks privately shared between subsets of the pedigrees, indicating the existence of an evolutionarily recent common ancestor, the ‘English founder’, with an estimated median tMRCA of 47 generations (corresponding to 1175 years) with a confidence interval (9–113 generations, equivalent to 225–2825 years). The mutation occurred in a small tandem repeat region predisposed to slipped strand mispairing. The resulting seven amino-acid duplication disrupts interaction with HSP90 and leads to a marked reduction in protein stability.Conclusions The c.805_825dup allele, originating from a common ancestor, associates with a severe clinical phenotype and a high frequency of gigantism. The mutation is likely to be the result of slipped strand mispairing and affects protein–protein interactions and AIP protein stabi
Sternberg M, David A, Yates C, et al., 2017, The protein interactome provides insights into the disease association of missense mutations, 42nd Congress of the Federation-of-European-Biochemical-Societies (FEBS) on From Molecules to Cells and Back, Publisher: WILEY, Pages: 11-11, ISSN: 1742-464X
David A, Vairamani K, Merjaneh L, et al., 2017, Novel dominant-negative GH receptor mutations expands the spectrum of GHI and IGF-I deficiency, Journal of the Endocrine Society, Vol: 1, Pages: 345-358, ISSN: 2472-1972
Context: Autosomal recessive mutations in the growth hormone receptor (GHR) are the most common causes for primary growth hormone insensitivity (GHI) syndrome with classical GHI phenotypically characterized by severe short stature and marked insulin-like growth factor (IGF)-I deficiency. We report three families with novel dominant-negative heterozygous mutations in the intracellular domain of the GHR causing a non-classical GHI phenotype.Objective: To determine if the identified GHR heterozygous variants exert potential dominant negative effects and are the cause for the GHI phenotype in our patients. Results: All three mutations (c.964dupG, c.920_921insTCTCAAAGATTACA, and c.945+2T>C) are predicted to result in frameshift and early protein termination. In vitro functional analysis of variants c.964dupG and c.920_921insTCTCAAAGATTACA (c.920_921ins14) suggests that these variants are expressed as truncated proteins and when co-expressed with wild-type GHR, mimicking the heterozygous state in our patients, exert dominant negative effects. Additionally, we provide evidence that a combination therapy of recombinant human growth hormone (rhGH) and rhIGF-I improved linear growth to within normal range for one of our previously reported patients with a characterized, dominant-negative, GHR (c.899dupC) mutation.Conclusion: Dominant-negative GHR mutations are causal of the mild GHI with significant growth failure observed in our patients. Heterozygous defects in the intracellular domain of GHR should, therefore, be considered in cases of idiopathic short stature and IGF-I deficiency. Combination therapy of rhGH and rhIGF-I improved growth in one of our patients.
Ittisoponpisan S, Sternberg MJE, Alhuzimi E, et al., 2017, Landscape of pleiotropic proteins causing human disease: structural and system biology insights, Human Mutation, Vol: 38, Pages: 289-296, ISSN: 1098-1004
Pleiotropyis the phenomenon by which the same gene can result in multiple phenotypes. Pleiotropic proteins are emerging as important contributors to rare and common disorders. Nevertheless, little is known on the mechanisms underlying pleiotropy and the characteristic of pleiotropic proteins.We analysed disease-causing proteins reported in UniProt and observed that 12% are pleiotropic (variants in the same protein cause more than one disease). Pleiotropic proteins were enriched indeleterious and rare variants, but not in common variants. Pleiotropic proteins were more likely to be involved in the pathogenesis of neoplasms, neurological and circulatory diseases, and congenital malformations, whereas non-pleiotropicproteinsin endocrine and metabolic disorders. Pleiotropic proteins were more essential and hada higher number of interacting partners compared to non-pleiotropic proteins. Significantly more pleiotropic than non-pleiotropic proteins contained at least one intrinsically long disordered region (p<0.001). Deleterious variants occurring in structurally disordered regions were more commonly found in pleiotropic, rather than non-pleiotropic proteins. 14In conclusion, pleiotropic proteins are an important contributor to human disease. They represent a biologically different class of proteins compared to non-pleiotropic proteins anda better understanding of their characteristicsand genetic variants, cangreatly aid in the interpretation of genetic studies and drug design.
Vairamani K, Merjaneh L, Casano-Sancho P, et al., 2017, NOVEL DOMINANT-NEGATIVE GH RECEPTOR MUTATIONS EXPANDS THE SPECTRUM OF GHI AND IGF-I DEFICIENCY, Publisher: KARGER, Pages: 32-32, ISSN: 1663-2818
Metherell L, Guerra-Assuncao JA, Sternberg M, et al., 2016, Structural analysis of nicotinamide nucleotide transhydrogenase (NNT) genetic variants causing adrenal disorders, Society for endocinology BES 2016
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