Erdogan Taskesen
VU University Amsterdam
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Publication
Featured researches published by Erdogan Taskesen.
Nature Genetics | 2017
Suzanne Sniekers; Sven Stringer; Kyoko Watanabe; Philip R. Jansen; Jonathan R. I. Coleman; Eva Krapohl; Erdogan Taskesen; Anke R. Hammerschlag; Aysu Okbay; Delilah Zabaneh; Najaf Amin; Gerome Breen; David Cesarini; Christopher F. Chabris; William G. Iacono; M. Arfan Ikram; Magnus Johannesson; Philipp Koellinger; James J. Lee; Patrik K. E. Magnusson; Matt McGue; Mike Miller; William Ollier; Antony Payton; Neil Pendleton; Robert Plomin; Cornelius A. Rietveld; Henning Tiemeier; Cornelia van Duijn; Danielle Posthuma
Intelligence is associated with important economic and health-related life outcomes. Despite intelligence having substantial heritability (0.54) and a confirmed polygenic nature, initial genetic studies were mostly underpowered. Here we report a meta-analysis for intelligence of 78,308 individuals. We identify 336 associated SNPs (METAL P < 5 × 10−8) in 18 genomic loci, of which 15 are new. Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10−6), of which all but one had not been implicated previously. We show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10−6). Despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10−29). These findings provide new insight into the genetic architecture of intelligence.
Nature Communications | 2017
Kyoko Watanabe; Erdogan Taskesen; Arjen van Bochoven; Danielle Posthuma
A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.Prioritizing genetic variants is a major challenge in genome-wide association studies. Here, the authors develop FUMA, a web-based bioinformatics tool that uses a combination of positional, eQTL and chromatin interaction mapping to prioritize likely causal variants and genes.
Nature Genetics | 2017
Anke R. Hammerschlag; Sven Stringer; Christiaan de Leeuw; Suzanne Sniekers; Erdogan Taskesen; Kyoko Watanabe; Tessa F. Blanken; Kim Dekker; Bart H.W. te Lindert; Rick Wassing; Ingileif Jonsdottir; Gudmar Thorleifsson; Hreinn Stefansson; Thorarinn Gislason; Klaus Berger; Barbara Schormair; Juergen Wellmann; Juliane Winkelmann; Kari Stefansson; Konrad Oexle; Eus J. W. Van Someren; Danielle Posthuma
Persistent insomnia is among the most frequent complaints in general practice. To identify genetic factors for insomnia complaints, we performed a genome-wide association study (GWAS) and a genome-wide gene-based association study (GWGAS) in 113,006 individuals. We identify three loci and seven genes associated with insomnia complaints, with the associations for one locus and five genes supported by joint analysis with an independent sample (n = 7,565). Our top association (MEIS1, P < 5 × 10−8) has previously been implicated in restless legs syndrome (RLS). Additional analyses favor the hypothesis that MEIS1 exhibits pleiotropy for insomnia and RLS and show that the observed association with insomnia complaints cannot be explained only by the presence of an RLS subgroup within the cases. Sex-specific analyses suggest that there are different genetic architectures between the sexes in addition to shared genetic factors. We show substantial positive genetic correlation of insomnia complaints with internalizing personality traits and metabolic traits and negative correlation with subjective well-being and educational attainment. These findings provide new insight into the genetic architecture of insomnia.
Scientific Reports | 2017
Erdogan Taskesen; Aniket Mishra; S. van der Sluis; Raffaele Ferrari; Jan H. Veldink; M. A. van Es; August B. Smit; Danielle Posthuma; Yolande A.L. Pijnenburg
Frontotemporal dementia (FTD) is a neurodegenerative disorder predominantly affecting the frontal and temporal lobes. Genome-wide association studies (GWAS) on FTD identified only a few risk loci. One of the possible explanations is that FTD is clinically, pathologically, and genetically heterogeneous. An important open question is to what extent epigenetic factors contribute to FTD and whether these factors vary between FTD clinical subgroup. We compared the DNA-methylation levels of FTD cases (nu2009=u2009128), and of FTD cases with Amyotrophic Lateral Sclerosis (FTD-ALS; nu2009=u20097) to those of unaffected controls (nu2009=u2009193), which resulted in 14 and 224 candidate genes, respectively. Cluster analysis revealed significant class separation of FTD-ALS from controls. We could further specify genes with increased susceptibility for abnormal gene-transcript behavior by jointly analyzing DNA-methylation levels with the presence of mutations in a GWAS FTD-cohort. For FTD-ALS, this resulted in 9 potential candidate genes, whereas for FTD we detected 1 candidate gene (ELP2). Independent validation-sets confirmed the genes DLG1, METTL7A, KIAA1147, IGHMBP2, PCNX, UBTD2, WDR35, and ELP2/SLC39A6 among others. We could furthermore demonstrate that genes harboring mutations and/or displaying differential DNA-methylation, are involved in common pathways, and may therefore be critical for neurodegeneration in both FTD and FTD-ALS.
Molecular Psychiatry | 2017
R. Karlsson Linner; Riccardo E. Marioni; Cornelius A. Rietveld; Andrew J Simpkin; Neil M Davies; Kyoko Watanabe; Nicola J. Armstrong; Kirsi Auro; Clemens Baumbach; Marc Jan Bonder; Jadwiga Buchwald; Giovanni Fiorito; Khadeeja Ismail; Stella Iurato; Anni Joensuu; Pauliina Karell; Silva Kasela; Jari Lahti; Allan F. McRae; P R Mandaviya; Ilkka Seppälä; Yunfei Wang; Laura Baglietto; Elisabeth B. Binder; Sarah E. Harris; Allison Hodge; Steve Horvath; Mikko Hurme; Magnus Johannesson; Antti Latvala
The epigenome is associated with biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here we provide evidence on the associations between epigenetic modifications—in our case, CpG methylation—and educational attainment (EA), a biologically distal environmental factor that is arguably among the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10u2009767 individuals. We find nine CpG probes significantly associated with EA. However, robustness analyses show that all nine probes have previously been found to be associated with smoking. Only two associations remain when we perform a sensitivity analysis in the subset of never-smokers, and these two probes are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, the effect sizes of the associations with EA are far smaller than the known associations with the biologically proximal environmental factors alcohol consumption, body mass index, smoking and maternal smoking during pregnancy. Follow-up analyses that combine the effects of many probes also point to small methylation associations with EA that are highly correlated with the combined effects of smoking. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.
bioRxiv | 2018
Richard Karlsson Linner; Pietro Biroli; Edward Kong; S. Fleur W. Meddens; Robbee Wedow; Mark Alan Fontana; Mael Lebreton; Abdel Abdellaoui; Anke R. Hammerschlag; Michel G. Nivard; Aysu Okbay; Cornelius A. Rietveld; Pascal Timshel; Stephen P Tino; Maciej Trzaskowski; Ronald de Vlaming; Christian L Zünd; Yanchun Bao; Laura Buzdugan; Ann H Caplin; Chia-Yen Chen; Peter Eibich; Pierre Fontanillas; Juan R. González; Peter K. Joshi; Ville Karhunen; Aaron Kleinman; Remy Z Levin; Christina M. Lill; Gerardus A. Meddens
Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated ( to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated (|rˆ g | ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.
bioRxiv | 2017
Richard Karlsson Linner; Riccardo E. Marioni; Cornelius A. Rietveld; Andrew J Simpkin; Neil M Davies; Kyoko Watanabe; Nicola J. Armstrong; Kirsi Auro; Clemens Baumbach; Marc Jan Bonder; Jadwiga Buchwald; Giovanni Fiorito; Khadeeja Ismail; Stella Iurato; Anni Joensuu; Pauliina Karell; Silva Kasela; Jari Lahti; Allan F. McRae; Pooja R. Mandaviya; Ilkka Seppälä; Yunzhang Wang; Laura Baglietto; Elisabeth B. Binder; Sarah E. Harris; Allison Hodge; Steve Horvath; Mikko Hurme; Magnus Johannesson; Antti Latvala
The epigenome has been shown to be influenced by biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption, and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here, we provide evidence on the associations between epigenetic modifications—in our case, CpG methylation—and educational attainment (EA), a biologically distal environmental factor that is arguably among of the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10,767 individuals. While we find that 9 CpG probes are significantly associated with EA, only two remain associated when we restrict the sample to never-smokers. These two are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, their effect sizes on EA are far smaller than the known associations between CpG probes and biologically proximal environmental factors. Two analyses that combine the effects of many probes—polygenic methylation score and epigenetic-clock analyses—both suggest small associations with EA. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.
Behavior Genetics | 2017
Richard Karlsson Linner; Pietro Biroli; Mark Alan Fontana; Anke Hammerschlaag; Edward Kong; Mael Lebreton; Fleur Meddens; Michel G. Nivard; Aysu Okbay; Niels Rietveld; Erdogan Taskesen; Patrick Turley; Ronald de Vlaming; Robbee Wedow; Abdel Abdellaoui; Yanchun Bao; Laura Buzdugan; Chia-Yen Chen; Peter Eibich; Pierre Fontanillas; Peter K. Joshi; Ville Karhunen; Christina M. Lill; Gerardus A. Meddens; Gerard Muntane; Sandra Sanchez-Roige; Frank J. A. van Rooij; Murray B. Stein; Adam Auton; David M. Clark
Behavior Genetics | 2017
Edward Kong; Adam Auton; Pierre Fontanillas; Sonia Jain; Chia-Yen Chen; Murray B. Stein; Lars Bertram; Peter Eibich; Christina M. Lill; Gert G. Wagner; Anke Hammerschlaag; Danielle Posthuma; Erdogan Taskesen; Andrew Conlin; Ville Karhunen; Minna Männikkö; Rauli Svento; Michel G. Nivard; Dorret I. Boomsma; Abdel Abdellaoui; Conor V. Dolan; Harriet de Wit; Abraham A. Palmer; James Mackillop; Sandra Sanchez-Roige; Albert Hofman; M. Arfan Ikram; Henning Tiemeier; André G. Uitterlinden; Frank J. A. van Rooij