220 research outputs found

    Adult-Onset ANCA-Associated Vasculitis in SAVI: Extension of the Phenotypic Spectrum, Case Report and Review of the Literature.

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    STING-associated vasculopathy with onset in infancy (SAVI) is an autosomal dominant disorder due to gain-of-function mutations in STING1, also known as TMEM173, encoding for STING. It was reported as a vasculopathy of infancy. However, since its description a wider spectrum of associated manifestations and disease-onset has been observed. We report a kindred with a heterozygous STING mutation (p.V155M) in which the 19-year-old proband suffered from isolated adult-onset ANCA-associated vasculitis. His father suffered from childhood-onset pulmonary fibrosis and renal failure attributed to ANCA-associated vasculitis, and died at the age of 30 years due to respiratory failure. In addition, an overview of the phenotypic spectrum of SAVI is provided highlighting (a) a high phenotypic variability with in some cases isolated manifestations, (b) the potential of adult-onset disease, and (c) a novel manifestation with ANCA-associated vasculitis

    Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

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    Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis

    Maternal milk consumption, fetal growth, and the risks of neonatal complications: The Generation R Study

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    Background: Maternal cow-milk consumption may increase birth weight. Previous studies did not assess the association of maternal milk consumption with trimester-specific fetal growth. Objective: The objective was to assess associations of first-trimester maternal milk consumption with fetal growth characteristics in different trimesters and the risk of neonatal complications. Design: In total, 3405 mothers participating in a prospective cohort study completed a 293-item semiquantitative food-frequency questionnaire to obtain information about dairy consumption during the first trimester of pregnancy. Fetal head circumference, femur length, and weight were estimated in the second and third trimesters by ultrasonography. Results: Maternal milk consumption of >3 glasses/d was associated with greater fetal weight gain in the third trimester of pregnancy, which led to an 88-g (95% CI: 39, 135 g) higher birth weight than that with milk consumption of 0 to 1 glass/d. In addition, head circumference tended to be 2.3 cm (95% CI: -0.0, 4.6 cm) larger when mothers consumed >3 glasses/d. Maternal milk consumption was not associated with length growth. Maternal protein intake (P for trend = 0.01), but not fat or carbohydrate intake, from dairy products was associated with higher birth weight. This association appeared to be limited to milk (P for trend < 0.01), whereas protein intake from nondairy food or cheese was not associated with birth weight. Conclusions: Maternal milk consumption is associated with greater fetal weight gain. The association seems to be due to milk protein, or milk components closely associated with protein, rather than to the fat or carbohydrate fraction of milk

    An Integrative Cross-Omics Analysis of DNA Methylation Sites of Glucose and Insulin Homeostasis

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    Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

    Glucose transporter-1 deficiency syndrome: the expanding clinical and genetic spectrum of a treatable disorder

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    Glucose transporter-1 deficiency syndrome is caused by mutations in the SLC2A1 gene in the majority of patients and results in impaired glucose transport into the brain. From 2004-2008, 132 requests for mutational analysis of the SLC2A1 gene were studied by automated Sanger sequencing and multiplex ligation-dependent probe amplification. Mutations in the SLC2A1 gene were detected in 54 patients (41%) and subsequently in three clinically affected family members. In these 57 patients we identified 49 different mutations, including six multiple exon deletions, six known mutations and 37 novel mutations (13 missense, five nonsense, 13 frame shift, four splice site and two translation initiation mutations). Clinical data were retrospectively collected from referring physicians by means of a questionnaire. Three different phenotypes were recognized: (i) the classical phenotype (84%), subdivided into early-onset (<2 years) (65%) and late-onset (18%); (ii) a non-classical phenotype, with mental retardation and movement disorder, without epilepsy (15%); and (iii) one adult case of glucose transporter-1 deficiency syndrome with minimal symptoms. Recognizing glucose transporter-1 deficiency syndrome is important, since a ketogenic diet was effective in most of the patients with epilepsy (86%) and also reduced movement disorders in 48% of the patients with a classical phenotype and 71% of the patients with a non-classical phenotype. The average delay in diagnosing classical glucose transporter-1 deficiency syndrome was 6.6 years (range 1 month-16 years). Cerebrospinal fluid glucose was below 2.5 mmol/l (range 0.9-2.4 mmol/l) in all patients and cerebrospinal fluid : blood glucose ratio was below 0.50 in all but one patient (range 0.19-0.52). Cerebrospinal fluid lactate was low to normal in all patients. Our relatively large series of 57 patients with glucose transporter-1 deficiency syndrome allowed us to identify correlations between genotype, phenotype and biochemical data. Type of mutation was related to the severity of mental retardation and the presence of complex movement disorders. Cerebrospinal fluid : blood glucose ratio was related to type of mutation and phenotype. In conclusion, a substantial number of the patients with glucose transporter-1 deficiency syndrome do not have epilepsy. Our study demonstrates that a lumbar puncture provides the diagnostic clue to glucose transporter-1 deficiency syndrome and can thereby dramatically reduce diagnostic delay to allow early start of the ketogenic die

    Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

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    Funding Information: Researchers were funded by investment from the European Regional Development Fund (ERDF) and the European Social Fund (ESF) Convergence Programme for Cornwall and the Isles of Scilly [J.T.]; European Research Council (ERC) [grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC to T.M.F., A.R.W.], [ERC Consolidator Grant, ERC-2014-CoG-648916 to V.W.V.J.], [P.R.N.]; University of Bergen, KG Jebsen and Helse Vest [P.R.N.]; Wellcome Trust Senior Investigator Awards [A.T.H. (WT098395), M.I.M. (WT098381)]; National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611–10219); Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150) [R.M.F., R.N.B.]; 4-year studentship (Grant Code: WT083431MF) [R.C.R]; the European Research Council under the European Union’s Seventh Framework Programme (FP/2007– 2013)/ERC Grant Agreement (grant number 669545; Develop Obese) [D.A.L.]; US National Institute of Health (grant: R01 DK10324) [D.A.L, C.L.R]; Wellcome Trust GWAS grant (WT088806) [D.A.L] and NIHR Senior Investigator Award (NF-SI-0611–10196) [D.A.L]; Wellcome Trust Institutional Strategic Support Award (WT097835MF) [M.A.T.]; The Diabetes Research and Wellness Foundation Non-Clinical Fellowship [J.T.]; Australian National Health and Medical Research Council Early Career Fellowship (APP1104818) [N.M.W.]; Daniel B. Burke Endowed Chair for Diabetes Research [S.F.A.G.]; UK Medical Research Council Unit grants MC_UU_12013_5 [R.C.R, L.P, S.R, C.L.R, D.M.E., D.A.L.] and MC_UU_12013_4 [D.M.E.]; Medical Research Council (grant: MR/M005070/1) [M.N.W., S.E.J.]; Australian Research Council Future Fellowship (FT130101709) [D.M.E] and (FT110100548) [S.E.M.]; NIHR Oxford Biomedical Research Centre (BRC); Oak Foundation Fellowship and Novo Nordisk Foundation (12955) [B.F.]; FRQS research scholar and Clinical Scientist Award by the Canadian Diabetes Association and the Maud Menten Award from the Institute of Genetics– Canadian Institute of Health Research (CIHR) [MFH]; CIHR— Frederick Banting and Charles Best Canada Graduate Scholarships [C.A.]; FRQS [L.B.]; Netherlands Organization for Health Research and Development (ZonMw–VIDI 016.136.361) [V.W.V.J.]; National Institute on Aging (R01AG29451) [J.M.M.]; 2010–2011 PRIN funds of the University of Ferrara—Holder: Prof. Guido Barbujani, Supervisor: Prof. Chiara Scapoli—and in part sponsored by the European Foundation for the Study of Diabetes (EFSD) Albert Renold Travel Fellowships for Young Scientists, ‘5 per mille’ contribution assigned to the University of Ferrara, income tax return year 2009 and the ENGAGE Exchange and Mobility Program for ENGAGE training funds, ENGAGE project, grant agreement HEALTH-F4–2007-201413 [L.M.]; ESRC (RES-060–23-0011) [C.L.R.]; National Institute of Health Research ([S.D., M.I.M.], Senior Investigator Award (NF-SI-0611–10196) [D.A.L]); Australian NHMRC Fellowships Scheme (619667) [G.W.M]. For study-specific funding, please see Supplementary Material. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Funding to pay the Open Access publication charges for this article was provided by the Charity Open Access Fund (COAF). Funding Information: We are extremely grateful to the participants and families who contributed to all of the studies and the teams of investigators involved in each one. These include interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. This research has been conducted using the UK Biobank Resource (Application numbers 7036 and 12703). For additional study-specific acknowledgements, please see Supplementary Material. Conflict of Interest statement. D.A.L. has received support from Roche Diagnostics and Medtronic for biomarker research unrelated to the work presented here. Funding Researchers were funded by investment from the European Regional Development Fund (ERDF) and the European Social Fund (ESF) Convergence Programme for Cornwall and the Isles of Scilly [J.T.]; European Research Council (ERC) [grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC to T.M.F., A.R.W.], [ERC Consolidator Grant, ERC-2014-CoG-648916 to V.W.V.J.], [P.R.N.]; University of Bergen, KG Jebsen and Helse Vest [P.R.N.]; Wellcome Trust Senior Investigator Awards [A.T.H. (WT098395), M.I.M. (WT098381)]; National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611-10219); Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150) [R.M.F., R.N.B.]; 4-year studentship (Grant Code: WT083431MF) [R.C.R]; the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement (grant number 669545; Develop Obese) [D.A.L.]; US National Institute of Health (grant: R01 DK10324) [D.A.L, C.L.R]; Wellcome Trust GWAS grant (WT088806) [D.A.L] and NIHR Senior Investigator Award (NF-SI-0611-10196) [D.A.L]; Wellcome Trust Institutional Strategic Support Award (WT097835MF) [M.A.T.]; The Diabetes Research and Wellness Foundation Non-Clinical Fellowship [J.T.]; Australian National Health and Medical Research Council Early Career Fellowship (APP1104818) [N.M.W.]; Daniel B. Burke Endowed Chair for Diabetes Research [S.F.A.G.]; UK Medical Research Council Unit grants MC_UU_12013_5 [R.C.R, L.P, S.R, C.L.R, D.M.E., D.A.L.] and MC_UU_12013_4 [D.M.E.]; Medical Research Council (grant: MR/M005070/1) [M.N.W., S.E.J.]; Australian Research Council Future Fellowship (FT130101709) [D.M.E] and (FT110100548) [S.E.M.]; NIHR Oxford Biomedical Research Centre (BRC); Oak Foundation Fellowship and Novo Nordisk Foundation (12955) [B.F.]; FRQS research scholar and Clinical Scientist Award by the Canadian Diabetes Association and the Maud Menten Award from the Institute of Genetics-Canadian Institute of Health Research (CIHR) [MFH]; CIHR-Frederick Banting and Charles Best Canada Graduate Scholarships [C.A.]; FRQS [L.B.]; Netherlands Organization for Health Research and Development (ZonMw-VIDI 016.136.361) [V.W.V.J.]; National Institute on Aging (R01AG29451) [J.M.M.]; 2010-2011 PRIN funds of the University of Ferrara-Holder: Prof. Guido Barbujani, Supervisor: Prof. Chiara Scapoli-and in part sponsored by the European Foundation for the Study of Diabetes (EFSD) Albert Renold Travel Fellowships for Young Scientists, '5 per mille' contribution assigned to the University of Ferrara, income tax return year 2009 and the ENGAGE Exchange and Mobility Program for ENGAGE training funds, ENGAGE project, grant agreement HEALTH-F4-2007-201413 [L.M.]; ESRC (RES-060-23-0011) [C.L.R.]; National Institute of Health Research ([S.D., M.I.M.], Senior Investigator Award (NFSI-0611-10196) [D.A.L]); Australian NHMRC Fellowships Scheme (619667) [G.W.M]. For study-specific funding, please see Supplementary Material. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Funding to pay the Open Access publication charges for this article was provided by the Charity Open Access Fund (COAF). Publisher Copyright: © The Author(s) 2018.Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P<5 x 10(-8). In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.Peer reviewe

    CERT1 mutations perturb human development by disrupting sphingolipid homeostasis

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    Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome.This work was supported by the National Institute of Neurological Disorders and Stroke (NINDS), NIH (R01NS109858, to VAG); the Paul A. Marks Scholar Program at the Columbia University Vagelos College of Physicians and Surgeons (to VAG); a TIGER grant from the TAUB Institute at the Columbia Vagelos College of Physicians and Scientists (to VAG); the Swiss National Science Foundation (SNF 31003A-179371, to TH); the European Joint Program on Rare Diseases (EJP RD+SNF 32ER30-187505, to TH); the Swiss Cancer League (KFS-4999-02-2020, to GD); the EPFL institutional fund (to GD); the Kristian Gerhard Jebsen Foundation (to GD); the Swiss National Science Foundation (SNSF) (310030_184926, to GD); the Swiss Foundation for Research on Muscle Disease (FSRMM, to MAL); the Natural Science and Engineering Research Council of Canada (Discovery Grant 2020-04241, to JEB); the Italian Ministry of Health Young Investigator Grant (GR-2011-02347754, to EL); the Fondazione Istituto di Ricerca Pediatrica – Città della Speranza (18-04, to EL); the Wroclaw Medical University (SUB.E160.21.004, to RS); the National Science Centre, Poland (2017/27/B/NZ5/0222, to RS); Telethon Undiagnosed Diseases Program (TUDP) (GSP15001); the Temple Street Foundation/Children’s Health Foundation Ireland (RPAC 19-02, to IK); the Deutsche Forschungsgemeinschaft (DFG) (PO2366/2–1, to BP); the Instituto de Salud Carlos III, Spain (to ELM, EBS, and BMD); the National Natural Science Foundation of China (81871079 and 81730036, to HG and KX); and the National Institutes of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH (R01 DK115574, to SSC).The DEFIDIAG study is funded by grants from the French Ministry of Health in the framewok of the national French initiative for genomic medicine. The funders were not involved in the study design, data acquisition, analysis, or writing of the manuscript. Funding for the DECIPHER project was provided by Wellcome. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between Wellcome and the Department of Health, and the Wellcome Sanger Institute (grant number WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of Wellcome or the Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12, granted by the Republic of Ireland REC). The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network.S
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