Publications
74 results found
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, <i>EAP1</i> regulation of GnRH promoter activity is important for human pubertal timing, HUMAN MOLECULAR GENETICS, Vol: 28, Pages: 1357-1368, ISSN: 0964-6906
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- Citations: 23
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
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.
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
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- Citations: 1
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: m.sternberg@imperial.ac.uk. 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
Metherell LA, Guerra-Assunção JA, Sternberg M, et al., 2016, Three-dimensional model of human Nicotinamide Nucleotide Transhydrogenase (NNT) and sequence-structure analysis of its disease-causing variations, Human Mutation, Vol: 37, Pages: 1074-1084, ISSN: 1098-1004
Defective mitochondrial proteins are emerging as major contributors to human disease. Nicotinamide nucleotide transhydrogenase (NNT), a widely expressed mitochondrial protein, has a crucial role in the defence against oxidative stress. NNT variations have recently been reported in patients with familial glucocorticoid deficiency (FGD) and in patients with heart failure. Moreover, knockout animal models suggest that NNT has a major role in diabetes mellitus and obesity. In this study, we used experimental structures of bacterial transhydrogenases to generate a structural model of human NNT (H-NNT). Structure-based analysis allowed the identification of H-NNT residues forming the NAD binding site, the proton canal and the large interaction site on the H-NNT dimer. In addition, we were able to identify key motifs that allow conformational changes adopted by domain III in relation to its functional status, such as the flexible linker between domains II and III and the salt bridge formed by H-NNT Arg882 and Asp830. Moreover, integration of sequence and structure data allowed us to study the structural and functional effect of deleterious amino acid substitutions causing FGD and left ventricular non-compaction cardiomyopathy. In conclusion, interpretation of the function–structure relationship of H-NNT contributes to our understanding of mitochondrial disorders.
Howard SR, Guasti L, Ruiz-Babot G, et al., 2016, IGSF10 mutations dysregulate gonadotropin-releasing hormone neuronal migration resulting in delayed puberty., EMBO Molecular Medicine, Vol: 8, Pages: 626-642, ISSN: 1757-4676
Early or late pubertal onset affects up to 5% of adolescents and is associated with adverse health and psychosocial outcomes. Self-limited delayed puberty (DP) segregates predominantly in an autosomal dominant pattern, but the underlying genetic background is unknown. Using exome and candidate gene sequencing, we have identified rare mutations in IGSF10 in 6 unrelated families, which resulted in intracellular retention with failure in the secretion of mutant proteins. IGSF10 mRNA was strongly expressed in embryonic nasal mesenchyme, during gonadotropin-releasing hormone (GnRH) neuronal migration to the hypothalamus. IGSF10 knockdown caused a reduced migration of immature GnRH neurons in vitro, and perturbed migration and extension of GnRH neurons in a gnrh3:EGFP zebrafish model. Additionally, loss-of-function mutations in IGSF10 were identified in hypothalamic amenorrhea patients. Our evidence strongly suggests that mutations in IGSF10 cause DP in humans, and points to a common genetic basis for conditions of functional hypogonadotropic hypogonadism (HH). While dysregulation of GnRH neuronal migration is known to cause permanent HH, this is the first time that this has been demonstrated as a casual mechanism in DP.
Howard S, Guasti L, Ruiz-Babot G, et al., 2016, Role of IGSF10 mutations in self-limited delayed puberty, Spring Meeting for Clinician Scientists in Training 2016, Publisher: Elsevier, Pages: S14-S14, ISSN: 0140-6736
BackgroundAbnormal timing of puberty affects over 4% of adolescents and is associated with adverse health and psychosocial outcomes. Previous studies estimate that 60–80% of variation in the timing of pubertal onset is genetically determined. However, little is known about the genetic control of human puberty. Self-limited delayed puberty segregates in an autosomal dominant pattern; our study aimed to identify novel genetic regulators of disease in these patients.MethodsWe performed whole-exome sequencing in 18 families with self-limited delayed puberty from our cohort, followed by candidate gene sequencing in a further 42 families. The functional consequences of the identified mutations in one candidate gene were interrogated via expression of wild type and mutant proteins in mammalian cells. For this gene we defined tissue expression in human and mouse embryos. The effects of gene knockdown were assessed via in-vitro neuronal migration assays, and in vivo with a transgenic zebrafish model.FindingsIn ten unrelated families, we identified four rare mutations in IGSF10 in individuals with self-limited delayed puberty (adjusted p value after rare variant burden testing=3·4 × 10–2). The identified mutations were in evolutionarily conserved positions, and two mutations resulted in intracellular retention with failure in secretion of the N-terminal fragment of the protein. IGSF10 mRNA was strongly expressed in the nasal mesenchyme in mouse and human embryos during migration of gonadotropin-releasing hormone (GnRH) neurons from their nasal origin towards the hypothalamus. IGSF10 knockdown caused reduced migration of immature GnRH neurons in the in-vitro analysis, and perturbed migration and extension of GnRH neurons in the zebrafish model.InterpretationOur findings strongly support the contention that mutations in IGSF10 cause delayed puberty in human beings, through misregulation of GnRH neuronal migration during embryonic development.
Howard S, Guasti L, Ruiz-Babot G, et al., 2015, Mutations in IGSF10 cause self-limited delayed puberty, Endocrine Abstracts
Howard S, Guasti L, Ruiz-Babot G, et al., 2015, Mutations in IGSF10 cause self-limited delayed puberty, via disturbance of GnRH neuronal migration, Endocrine Abstracts
Cornish AJ, Filippis I, David A, et al., 2015, Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types, Genome Medicine, Vol: 7, ISSN: 1756-994X
David A, Sternberg MJ, 2015, The contribution of missense mutations in core and rim residues of protein-protein interfaces to human disease., Journal of Molecular Biology, Vol: 427, Pages: 2886-2898, ISSN: 1089-8638
Missense mutations at protein-protein interaction (PPIs) sites, called interfaces, are important contributors to human disease. Interfaces are non-uniform surface areas characterized by two main regions, 'core' and 'rim', which differ in terms of evolutionary conservation and physico-chemical properties. Moreover, within interfaces, only a small subset of residues ('hot spots') is crucial for the binding free energy of the protein-protein complex. We performed a large-scale structural analysis of human single amino acid variations (SAVs) and demonstrated that disease-causing mutations are preferentially located within the interface core, as opposed to the rim (p< 0.01). In contrast, the interface rim is significantly enriched in polymorphisms, similar to the remaining non-interacting surface. Energetic hot spots tend to be enriched in disease-causing mutations compared to non-hot spots (p=0.05), regardless of their occurrence in core or rim residues. For individual amino acids, the frequency of substitution into a polymorphism or disease-causing mutation differed to other amino acids and was related to its structural location, as was the type of physico-chemical change introduced by the SAV. In conclusion, this study demonstrated the different distribution and properties of disease-causing SAVs and polymorphisms within different structural regions and in relation to the energetic contribution of amino acid in protein-protein interfaces, thus highlighting the importance of a structural system biology approach for predicting the effect of SAVs.
David A, Kelley LA, Sternberg MJE, 2012, A new structural model of the acid-labile subunit: pathogenetic mechanisms of short stature-causing mutations, JOURNAL OF MOLECULAR ENDOCRINOLOGY, Vol: 49, Pages: 213-220, ISSN: 0952-5041
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David A, Razali R, Wass MN, et al., 2012, Protein-Protein Interaction Sites are Hot Spots for Disease-Associated Nonsynonymous SNPs, HUMAN MUTATION, Vol: 33, Pages: 359-363, ISSN: 1059-7794
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