Author
Leonid Padyukov
Other affiliations: University of Gothenburg, Karolinska Institutet, Sahlgrenska University Hospital ...read more
Bio: Leonid Padyukov is an academic researcher from Karolinska University Hospital. The author has contributed to research in topics: Genome-wide association study & Single-nucleotide polymorphism. The author has an hindex of 74, co-authored 276 publications receiving 27451 citations. Previous affiliations of Leonid Padyukov include University of Gothenburg & Karolinska Institutet.
Papers published on a yearly basis
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Harvard University1, Broad Institute2, Monash University3, Kyoto University4, Genentech5, Vanderbilt University6, New York University7, NewYork–Presbyterian Hospital8, Second Military Medical University9, University of Queensland10, University of Toronto11, University of Groningen12, University of Tartu13, Beijing Jiaotong University14, Icahn School of Medicine at Mount Sinai15, Radboud University Nijmegen16, Medisch Spectrum Twente17, Leiden University18, University of Paris19, French Institute of Health and Medical Research20, University of Alabama at Birmingham21, University of Cambridge22, GlaxoSmithKline23, University of Amsterdam24, Hanyang University25, Spanish National Research Council26, Complutense University of Madrid27, Umeå University28, Boston University29, Council on Education for Public Health30, McGill University31, University of Manchester32, National Health Service33, University of Pittsburgh34, University of California, San Francisco35, Karolinska Institutet36, North Shore-LIJ Health System37, University of Chicago38, University of Tokyo39
TL;DR: A genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries provides empirical evidence that the genetics of RA can provide important information for drug discovery, and sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis.
Abstract: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
1,910 citations
TL;DR: An etiology involving a specific genotype, an environmental provocation, and the induction of specific autoimmunity are suggested, all restricted to a distinct subset of RA.
Abstract: A new model for an etiology of rheumatoid arthritis : smoking may trigger HLA-DR (shared epitope)-restricted immune reactions to autoantigens modified by citrullination.
1,425 citations
Verneri Anttila1, Verneri Anttila2, Brendan Bulik-Sullivan2, Brendan Bulik-Sullivan1 +717 more•Institutions (270)
TL;DR: It is demonstrated that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine, and it is shown that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures.
Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
1,357 citations
Brigham and Women's Hospital1, Massachusetts Institute of Technology2, Harvard University3, National Institutes of Health4, University of Toronto5, University of Manchester6, Celera Corporation7, Leiden University8, Karolinska Institutet9, University of Texas at Austin10, Radboud University Nijmegen Medical Centre11, University of California, San Francisco12, VU University Amsterdam13, University of Leeds14, University of Oxford15, University of Aberdeen16, The Feinstein Institute for Medical Research17, Karolinska University Hospital18, University of Groningen19, University of California, Davis20, King's College21, University of Amsterdam22, University of Sheffield23, Hoffmann-La Roche24, University Health Network25, North Shore-LIJ Health System26, Broad Institute27
TL;DR: Seven new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 × 10−8) in an analysis of all 41,282 samples, and an additional 11 SNPs replicated at P < 0.05, suggesting that most represent genuine rhearatoid arthritisrisk alleles.
Abstract: To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 x 10(-8)) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P < 0.05, many of which are validated autoimmune risk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles.
1,277 citations
National Institutes of Health1, Broad Institute2, North Shore-LIJ Health System3, Brigham and Women's Hospital4, Genentech5, Hanyang University6, Biogen Idec7, Karolinska Institutet8, University of Texas MD Anderson Cancer Center9, University of California, San Francisco10, University of California, Davis11
TL;DR: A haplotype of STAT4 is associated with increased risk for both rheumatoid arthritis and systemic lupus erythematosus, suggesting a shared pathway for these illnesses.
Abstract: A SNP haplotype in the third intron of STAT4 was associated with susceptibility to both rheumatoid arthritis and systemic lupus erythematosus. The minor alleles of the haplotype-defining SNPs were present in 27% of chromosomes of patients with established rheumatoid arthritis, as compared with 22% of those of controls (for the SNP rs7574865, P = 2.81×10 −7 ; odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.32). The association was replicated in Swedish patients with recent-onset rheumatoid arthritis (P = 0.02) and matched controls. The haplotype marked by rs7574865 was strongly associated with lupus, being present on 31% of chromosomes of case patients and 22% of those of controls (P = 1.87×10 −9 ; odds ratio for having the risk allele in chromosomes of patients vs. those of controls, 1.55). Homozygosity of the risk allele, as compared with absence of the allele, was associated with a more than doubled risk for lupus and a 60% increased risk for rheumatoid arthritis. CONCLUSIONS
1,008 citations
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01 Feb 2009
TL;DR: This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale, and what might be coming next.
Abstract: Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?
5,234 citations
Massachusetts Institute of Technology1, Broad Institute2, University of California, Los Angeles3, University of British Columbia4, Baylor College of Medicine5, Howard Hughes Medical Institute6, University of Washington7, Ludwig Institute for Cancer Research8, University of California, San Francisco9, University of Connecticut10, University of Zagreb11, University of Texas at Austin12, Washington University in St. Louis13, University of Queensland14, Harvard University15, Cold Spring Harbor Laboratory16, University of Southern California17, University of California, Santa Cruz18, Simon Fraser University19, Morgridge Institute for Research20, University of Texas at Dallas21, National Institutes of Health22
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
5,037 citations
01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
4,409 citations
TL;DR: It is proposed that DNA methylation age measures the cumulative effect of an epigenetic maintenance system, and can be used to address a host of questions in developmental biology, cancer and aging research.
Abstract: It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
4,233 citations