Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition.
Kerrin S. Small,Marijana Todorčević,Mete Civelek,Mete Civelek,Julia S. El-Sayed Moustafa,Xiao Wang,Michelle Simon,Juan Fernández-Tajes,Anubha Mahajan,Momoko Horikoshi,Alison Hugill,Craig A. Glastonbury,Lydia Quaye,Matt J. Neville,Matt J. Neville,Siddharth Sethi,Marianne Yon,Calvin Pan,Nam Che,Ana Viñuela,Pei-Chien Tsai,Abhishek Nag,Alfonso Buil,Gudmar Thorleifsson,Avanthi Raghavan,Qiurong Ding,Andrew P. Morris,Andrew P. Morris,Jordana T. Bell,Unnur Thorsteinsdottir,Unnur Thorsteinsdottir,Kari Stefansson,Kari Stefansson,Markku Laakso,Ingrid Dahlman,Peter Arner,Anna L. Gloyn,Anna L. Gloyn,Kiran Musunuru,Aldons J. Lusis,Roger D. Cox,Fredrik Karpe,Fredrik Karpe,Mark I. McCarthy,Mark I. McCarthy +44 more
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Analysis of the imprinted KLF 14 locus shows that the type 2 diabetes risk alleles in this region act in adipocytes to reduce KLF14 expression and modulate the expression of almost 400 genes in trans, leading to a shift in body-fat distribution and insulin resistance specifically in females.Abstract:
Individual risk of type 2 diabetes (T2D) is modified by perturbations to the mass, distribution and function of adipose tissue. To investigate the mechanisms underlying these associations, we explored the molecular, cellular and whole-body effects of T2D-associated alleles near KLF14. We show that KLF14 diabetes-risk alleles act in adipose tissue to reduce KLF14 expression and modulate, in trans, the expression of 385 genes. We demonstrate, in human cellular studies, that reduced KLF14 expression increases pre-adipocyte proliferation but disrupts lipogenesis, and in mice, that adipose tissue-specific deletion of Klf14 partially recapitulates the human phenotype of insulin resistance, dyslipidemia and T2D. We show that carriers of the KLF14 T2D risk allele shift body fat from gynoid stores to abdominal stores and display a marked increase in adipocyte cell size, and that these effects on fat distribution, and the T2D association, are female specific. The metabolic risk associated with variation at this imprinted locus depends on the sex both of the subject and of the parent from whom the risk allele derives.read more
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Integrative analysis of 111 reference human epigenomes
Anshul Kundaje,Wouter Meuleman,Jason Ernst,Angela Yen,Pouya Kheradpour,Zhizhuo Zhang,Jianrong Wang,Lucas D. Ward,Abhishek Sarkar,Gerald Quon,Matthew L. Eaton,Yi-Chieh Wu,Andreas R. Pfenning,Xinchen Wang,Melina Claussnitzer,Yaping Liu,Mukul S. Bansal,Soheil Feizi-Khankandi,Ah Ram Kim,Richard C Sallari,Nicholas A Sinnott-Armstrong,Laurie A. Boyer,Elizabeta Gjoneska,Li-Huei Tsai,Manolis Kellis +24 more
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.
Journal ArticleDOI
Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.
Anubha Mahajan,Daniel Taliun,Matthias Thurner,Neil R. Robertson,Jason M. Torres,N. William Rayner,N. William Rayner,Anthony Payne,Valgerdur Steinthorsdottir,Robert A. Scott,Niels Grarup,James P. Cook,Ellen M. Schmidt,Matthias Wuttke,Chloé Sarnowski,Reedik Mägi,Jana Nano,Christian Gieger,Stella Trompet,Cécile Lecoeur,Michael Preuss,Bram P. Prins,Xiuqing Guo,Lawrence F. Bielak,Jennifer E. Below,Donald W. Bowden,John C. Chambers,Young-Jin Kim,Maggie C.Y. Ng,Lauren E. Petty,Xueling Sim,Weihua Zhang,Weihua Zhang,Amanda J. Bennett,Jette Bork-Jensen,Chad M. Brummett,Mickaël Canouil,Kai-Uwe Ec Kardt,Krista Fischer,Sharon L.R. Kardia,Florian Kronenberg,Kristi Läll,Ching-Ti Liu,Adam E. Locke,Jian'an Luan,Ioanna Ntalla,Vibe Nylander,Sebastian Schönherr,Claudia Schurmann,Loic Yengo,Erwin P. Bottinger,Ivan Brandslund,Cramer Christensen,George Dedoussis,Jose C. Florez,Ian Ford,Oscar H. Franco,Timothy M. Frayling,Vilmantas Giedraitis,Sophie Hackinger,Andrew T. Hattersley,Christian Herder,M. Arfan Ikram,Martin Ingelsson,Marit E. Jørgensen,Marit E. Jørgensen,Torben Jørgensen,Torben Jørgensen,Jennifer Kriebel,Johanna Kuusisto,Symen Ligthart,Cecilia M. Lindgren,Cecilia M. Lindgren,Allan Linneberg,Allan Linneberg,Valeriya Lyssenko,Valeriya Lyssenko,Vasiliki Mamakou,Thomas Meitinger,Karen L. Mohlke,Andrew D. Morris,Andrew D. Morris,Girish N. Nadkarni,James S. Pankow,Annette Peters,Naveed Sattar,Alena Stančáková,Konstantin Strauch,Kent D. Taylor,Barbara Thorand,Gudmar Thorleifsson,Unnur Thorsteinsdottir,Unnur Thorsteinsdottir,Jaakko Tuomilehto,Daniel R. Witte,Josée Dupuis,Patricia A. Peyser,Eleftheria Zeggini,Ruth J. F. Loos,Philippe Froguel,Philippe Froguel,Erik Ingelsson,Erik Ingelsson,Lars Lind,Leif Groop,Leif Groop,Markku Laakso,Francis S. Collins,J. Wouter Jukema,Colin N. A. Palmer,Harald Grallert,Andres Metspalu,Abbas Dehghan,Abbas Dehghan,Anna Köttgen,Gonçalo R. Abecasis,James B. Meigs,Jerome I. Rotter,Jonathan Marchini,Oluf Pedersen,Torben Hansen,Torben Hansen,Claudia Langenberg,Nicholas J. Wareham,Kari Stefansson,Kari Stefansson,Anna L. Gloyn,Andrew P. Morris,Andrew P. Morris,Andrew P. Morris,Michael Boehnke,Mark I. McCarthy +131 more
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps
Anubha Mahajan,Daniel Taliun,Matthias Thurner,Neil R. Robertson,Jason M. Torres,N. William Rayner,Anthony Payne,Valgerdur Steinthorsdottir,Robert A. Scott,Niels Grarup,James P. Cook,Ellen M. Schmidt,Matthias Wuttke,Chloé Sarnowski,Reedik Magill,Jana Nano,Christian Gieger,Stella Trompet,Cécile Lecoeur,Michael Preuss,Bram P. Prins,Xiuqing Guo,Lawrence F. Bielak,Jennifer E. Below,Donald W. Bowden,John C. Chambers,Young-Jin Kim,Maggie C.Y. Ng,Lauren E. Petty,Xueling Sim,Weihua Zhang,Amanda J. Bennett,Jette Bork-Jensen,Chad M. Brummett,Mickaël Canouil,Kai-Uwe Ec Kardt,Krista Fischer,Sharon L.R. Kardia,Florian Kronenberg,Kristi Läll,Ching-Ti Liu,Adam E. Locke,Jian'an Luan,Loanna Ntalla,Vibe Nylander,Sebastian Schoenherr,Claudia Schurmann,Loic Yengo,Erwin P. Bottinger,Ivan Brandslund,Cramer Christensen,George Dedoussis,Jose C. Florez,Ian Ford,Timothy M. Frayling,Vilmantas Giedraitis,Sophie Hackinger,Andrew T. Hattersley,Christian Herder,M. Arfan Ikram,Martin Ingelsson,Marit E. Jørgensen,Torben Jørgensen,Jennifer Kriebel,Johanna Kuusisto,Symen Ligthart,Cecilia M. Lindgren,Allan Linneberg,Valeriya Lyssenko,Vasiliki Mamakou,Thomas Meitinger,Karen L. Mohlke,Andrew D. Morris,Girish N. Nadkarni,James S. Pankow,Annette Peters,Naveed Sattar,Alena Stančáková,Konstantin Strauch,Kent D. Taylor,Barbara Thorand,Gudmar Thorleifsson,Unnur Thorsteinsdottir,Jaakko Tuomilehto,Daniel R. Witte,Josée Dupuis,Patricia A. Peyser,Eleftheria Zeggini,Ruth J. F. Loos,Philippe Froguel,Erik Ingelsson,Lars Lind,Leif Groop,Markku Laakso,Francis S. Collins,J. Wouter Jukema,Colin N. A. Palmer,Harald Grallert,Andres Metspalu,Abbas Dehghan,Anna Koettgen,Gonçalo R. Abecasis,James B. Meigs,Rotter, Jerome, I,Jonathan Marchini,Oluf Pedersen,Torben Hansen,Claudia Langenberg,Nicholas J. Wareham,Kari Stefansson,Anna L. Gloyn,Andrew P. Morris,Michael Boehnke,McCarthy, Mark, I +113 more
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
ChromHMM: automating chromatin-state discovery and characterization
TL;DR: ChromHMM is developed, an automated computational system for learning chromatin states, characterizing their biological functions and correlations with large-scale functional datasets, and visualizing the resulting genome-wide maps of chromatin state annotations.
Journal ArticleDOI
A brief history of human disease genetics.
Melina Claussnitzer,Melina Claussnitzer,Melina Claussnitzer,Judy H. Cho,Rory Collins,Nancy J. Cox,Emmanouil T. Dermitzakis,Matthew E. Hurles,Sekar Kathiresan,Sekar Kathiresan,Eimear E. Kenny,Cecilia M. Lindgren,Cecilia M. Lindgren,Daniel G. MacArthur,Daniel G. MacArthur,Kathryn N. North,Sharon E. Plon,Sharon E. Plon,Heidi L. Rehm,Neil Risch,Charles N. Rotimi,Jay Shendure,Jay Shendure,Nicole Soranzo,Nicole Soranzo,Mark I. McCarthy +25 more
TL;DR: Progress is described in the study of human genetics, in which rapid advances in technology, foundational genomic resources and analytical tools have contributed to the understanding of the mechanisms responsible for many rare and common diseases and to preventative and therapeutic strategies for many of these conditions.
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Integrative analysis of 111 reference human epigenomes
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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.
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