78 research outputs found
Modulation of genetic associations with serum urate levels by body-mass-index in humans
No full textWe tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.</p
Microarray-based Genome-Wide Association Studies (GWAS) using data generated by Allelotyping and by individual Genotyping
No full textGenome-wide association studies (GWAS) are used to identify genetic markers linked with at least partially heritable diseases or phenotypes without prior knowledge of any disease-associated genetic loci. In summer 2008, all individuals of the population based cohort Study of Health in Pomerania (SHIP) were individually genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0 microarray. The aim of this work was to establish an efficient workflow for GWAS using the more than 4000 individually genotyped samples of the SHIP cohort as well as pooled samples, focusing exclusively on analyzing genetic variations based on single nucleotide polymorphisms (SNPs). Firstly, an optimal array platform for the genotyping analysis had to be chosen that detected most of the available genetic variants at a high level of accuracy. Secondly, extensive quality controls had to be performed starting from DNA extraction and including tests of the generated array data by the analysis software to obtain the most reliable data for the subsequent association studies. For the identification of loci with smaller genetic influences, individual cohorts were meta-analyzed in large nationally and internationally organized consortia (e.g. CHARGE, BPGen, HaemGen, GIANT, CKD Gen). To participate in those meta-analyses, a comparable common set of genetic data had to be generated. This was done by imputation of the data generated by individual array-based genotyping on the basis of a reference panel using chromosomal linkage information. Due to the extensive phenotype information in the SHIP study, it was possible to perform many genome-wide discovery analyses and replication studies of possible susceptibility loci in a short time once the genetic data was available and processed. This resulted in the necessity to set up an efficient workflow for storing the huge amount of genetic data, converting it into different formats readable for specific analysis software, performing the association analyses and processing the results into a human-readable and clear format. This included replications, GWAS and meta-analyses of several cohorts. Many susceptibility loci were newly identified in different association studies with the SHIP data included and were subsequently published. In this work, genetic association studies with the SHIP data included were performed and published on blood pressure, uric acid concentrations, cardiac structure and function, lipid metabolism, hematological parameters, kidney functions, smoking quantity, circulating IGF-I and IGFBP-3 concentrations and thyroid volume including the risk of goiter development. Besides the SHIP cohort, there was a need to use other, especially patient cohorts for GWAS. Since no genotype information from these patient cohorts was available and the individual genotyping of many probands is still expensive and therefore often not affordable, we established the cost-effective allelotyping method that relied on pooling of DNA samples prior to the hybridization with microarrays. After estimating the pooling-specific error of a case-control allelotyping study, the allelotyping approach was used for identifying genetic susceptibility loci associated with aggressive periodontitis. If not referring to work of collaborators, all statistical analyses, data handling and in silico work concerning the SHIP data described in this context was performed by the author of this dissertation.Genomweite Assoziationsstudien (GWAS) werden verwendet, um genetische Marker zu identifizieren, die mit zumindest teilweise vererbbaren Krankheiten oder Phänotypen assoziiert sind, ohne dabei vorab Informationen von bekannten krankheits-assoziierten genetischen Loci zu berücksichtigen. Im Sommer 2008 wurden alle Personen der bevölkerungsbasierten Kohorte Study of Health in Pomerania (SHIP) individuell mit Hilfe des Affymetrix Genome-Wide Human SNP Array 6.0 genotypisiert. Das Ziel dieser Arbeit war es, einen effizienten Workflow für GWAS basierend auf den mehr als 4000 einzeln genotypisierten Probanden der SHIP Kohorte sowie gepoolten DNA-Proben zu schaffen, wobei sich ausschließlich auf die Analyse genetischer Variationen von Einzelbasen-Polymorphismen (SNPs) beschränkt wurde. Zuerst mußte eine optimale Array-Plattform für die Genotypisierung ausgewählt werden, die die meisten bekannten genetischen Varianten mit hoher Genauigkeit detektieren kann. Zweitens mußten umfangreiche Qualitätskontrollen durchgeführt werden, beginnend bei der DNA-Extraktion bis hin zu Tests der durch die Analyse-Software erzeugten Array-Daten, um verlässliche Daten für die nachfolgenden Assoziationsstudien zu erhalten. Für die Identifizierung von Loci mit kleineren genetischen Einflüssen wurden Ergebnisse einzelner Kohorten in großen national und international organisierten Konsortien meta-analysiert (z.B. CHARGE, BPGen, HaemGen, GIANT, CKD Gen). Zur Teilnahme an diesen Meta-Analysen, mußte eine gemeinsame Basis genetischer Daten erzeugt werden. Dieses wurde durch sogenannte Imputation der Daten der einzelnen Array-basierten Genotypisierungen auf der Grundlage eines Referenz-Panels unter Berücksichtigung chromosomaler Kopplungsinformationen durchgeführt. Aufgrund der umfangreichen Phänotypinformationen der SHIP-Studie war es möglich, viele genomweite Analysen und Replikationsstudien zur Endeckung genetischer Anfälligkeits-Loci in kurzer Zeit durchzuführen, sobald die genetischen Daten zur Verfügung standen. Dafür war es notwendig, einen effizienten Workflow zur Speicherung der enormen Menge genetischer Informationen, deren Konvertierung in andere Formate welche lesbar für die spezielle Analyse-Software sind, die Durchführung der Assoziationsstudien und die Aufarbeitung der Ergebnisse in ein lesbares und übersichtliches Format zu erstellen. Dazu gehörten Replikationen, GWAS und Meta-Analysen von mehreren Kohorten. Viele neue Anfälligkeits-Loci konnten dabei in verschiedenen Assoziationsstudien unter Einbeziehung der SHIP-Daten identifiziert und anschließend veröffentlicht werden. In dieser Arbeit sind genetische Assoziationsstudien aufgeführt, die basieren auf Blutdruckdaten, Harnsäure-Konzentration, Herz-Struktur und -funktion, Fettstoffwechsel, hämatologischen Parametern, Nierenfunktion, Rauchen, IGF-I und IGFBP-3-Konzentrationen und Schilddrüsen-Volumen einschließlich des Risikos der Kropfbildung unter Einbeziehung der SHIP-Daten durchgeführt und veröffentlicht wurden. Neben der SHIP Kohorte gab es die Notwendigkeit GWAS in anderen Gruppen, besonders in Patientengruppen durchzuführen. Da keine Genotypinformationen aus diesen Patientengruppen zur Verfügung standen und die individuelle Genotypisierung von vielen Probanden noch teuer und daher oft nicht erschwinglich war, haben wir die kostengünstige Allelotypisierungs-Methode, die auf dem Poolen von DNA-Proben vor der Hybridisierung mit Microarrays basiert, umgesetzt. Nach Schätzung des pooling-spezifischen Fehlers anhand einer Fall-Kontroll-Allelotypisierungsstudie, wurde der Allelotypisierungsansatz zur Ermittlung genetischer Anfälligkeits-Loci, welche mit aggressiver Parodontitis assoziiert sind, angewendet. Falls nicht auf die Arbeit von Kooperatoren referenziert wurde, sind alle hier beschriebenen statistischen Analysen, die Datenverarbeitung und die in silico Arbeit basierend auf den SHIP-Daten vom Autor dieser Dissertation durchgeführt worden
Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
No full textWaist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions
Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
No full textApproaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups
Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index
No full textThe phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ~4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity. © 2014 Hoggart et al
Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia (Molecular Psychiatry, (2018), 10.1038/s41380-018-0118-1)
No full textPrior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused
Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk
No full textBlood pressure is a heritable trait1 influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (90mmHg diastolic blood pressure)2. Even small increments in blood pressure are associated with an increased risk of cardiovascular events3. This genome-wide associationstudy of systolic and diastolic blood pressure, which useda multi-stage design in 200,000 individuals of European descent,identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure(GUCY1A3–GUCY1B3, NPR3–C5orf23, ADM, FURIN–FES, GOSR2, GNAS–EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genomewide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggestpotential novel therapeutic pathways for cardiovascular disease prevention
Stratified medicine for mental disorders
No full textThere is recognition that biomedical research into the causes of mental disorders and their treatment needs to adopt new approaches to research. Novel biomedical techniques have advanced our understanding of how the brain develops and is shaped by behaviour and environment. This has led to the advent of stratified medicine, which translates advances in basic research by targeting aetiological mechanisms underlying mental disorder. The resulting increase in diagnostic precision and targeted treatments may provide a window of opportunity to address the large public health burden, and individual suffering associated with mental disorders. While mental health and mental disorders have significant representation in the "health, demographic change and wellbeing" challenge identified in Horizon 2020, the framework programme for research and innovation of the European Commission (2014-2020), and in national funding agencies, clear advice on a potential strategy for mental health research investment is needed. The development of such a strategy is supported by the EC-funded "Roadmap for Mental Health Research" (ROAMER) which will provide recommendations for a European mental health research strategy integrating the areas of biomedicine, psychology, public health well being, research integration and structuring, and stakeholder participation. Leading experts on biomedical research on mental disorders have provided an assessment of the state of the art in core psychopathological domains, including arousal and stress regulation, affect, cognition social processes, comorbidity and pharmacotherapy. They have identified major advances and promising methods and pointed out gaps to be addressed in order to achieve the promise of a stratified medicine for mental disorders
Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study (vol 11, e1005378, 2015)
No full textThe arcOGEN Consortium should be listed as an author of this article. They contributed to the genome-wide association study results presented in this work. They should be listed in the author byline at position 292 and affiliated with The Arthritis Research UK Osteoarthritis Genetics Consortium. They should also be included in the footnote designating consortia which is underneath the author affiliation list in the PDF version of the article, and in the S2 Text. Please view the correct S2 Text below, containing correct consortia members
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