Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits.
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Dan-Yu Lin | Christian Fuchsberger | Michael I Love | Johanna Kuusisto | Arthur Ko | Päivi Pajukanta | Michael Boehnke | Cassandra N. Spracklen | Francis S Collins | Cassandra N Spracklen | Karen L Mohlke | Mete Civelek | Aldons J Lusis | Laura J Scott | T. Furey | M. Laakso | F. Collins | M. Boehnke | D. Lin | L. Scott | K. Mohlke | H. Stringham | A. Jackson | N. Narisu | P. Pajukanta | M. Love | J. Kuusisto | A. Lusis | Ying Wu | C. Fuchsberger | R. Welch | A. Locke | M. Civelek | Maren E. Cannon | S. M. Brotman | Arthur Ko | C. Spracklen | Narisu Narisu | Markku Laakso | Anne U Jackson | Heather M Stringham | Chelsea K Raulerson | Ryan P Welch | Adam E Locke | Ying Wu | Terrence S Furey | Maren E Cannon | John C Kidd | Kevin W Currin | Sarah M Brotman | John Kidd | Sarah M. Brotman | K. Currin | Narisu Narisu | Ying Wu | Ying Wu | A. Jackson
[1] Anthony J. Payne,et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps , 2018, Nature Genetics.
[2] L. Keele,et al. Identification, Inference and Sensitivity Analysis for Causal Mediation Effects , 2010, 1011.1079.
[3] Howard Y. Chang,et al. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position , 2013, Nature Methods.
[4] Michael Q. Zhang,et al. Integrative analysis of 111 reference human epigenomes , 2015, Nature.
[5] A. Kimchi,et al. DAP-5, a novel homolog of eukaryotic translation initiation factor 4G isolated as a putative modulator of gamma interferon-induced programmed cell death , 1997, Molecular and cellular biology.
[6] Ross M. Fraser,et al. Genetic studies of body mass index yield new insights for obesity biology , 2015, Nature.
[7] Helen E. Parkinson,et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..
[8] H. Lodish,et al. T-cadherin is a receptor for hexameric and high-molecular-weight forms of Acrp30/adiponectin. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[9] M. Kanai,et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population , 2017, Nature Genetics.
[10] Emmanouil T. Dermitzakis,et al. Fast and efficient QTL mapper for thousands of molecular phenotypes , 2015, bioRxiv.
[11] Fred A. Wright,et al. Conditional eQTL analysis reveals allelic heterogeneity of gene expression , 2017, Human molecular genetics.
[12] R. Irizarry,et al. Accounting for cellular heterogeneity is critical in epigenome-wide association studies , 2014, Genome Biology.
[13] Daniel F. Gudbjartsson,et al. Parental origin of sequence variants associated with complex diseases , 2009, Nature.
[14] P. Farnham,et al. Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome , 2015, Epigenetics & Chromatin.
[15] J. V. Moran,et al. Initial sequencing and analysis of the human genome. , 2001, Nature.
[16] N. Risch,et al. A large electronic health record-based genome-wide study of serum lipids , 2018, Nature Genetics.
[17] H. Augustin,et al. The Wnt signaling regulator R-spondin 3 promotes angioblast and vascular development , 2008, Development.
[18] Walter C Willett,et al. Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men. , 2005, The American journal of clinical nutrition.
[19] R. Young,et al. Transcriptional Regulation and Its Misregulation in Disease , 2013, Cell.
[20] M. Matsuda,et al. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. , 1999, Diabetes care.
[21] Rob Patro,et al. Salmon provides fast and bias-aware quantification of transcript expression , 2017, Nature Methods.
[22] Karen L. Mohlke,et al. The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases , 2017, Journal of Lipid Research.
[23] Olivier Delaneau,et al. A complete tool set for molecular QTL discovery and analysis , 2016, Nature Communications.
[24] Tanya M. Teslovich,et al. Biological, Clinical, and Population Relevance of 95 Loci for Blood Lipids , 2010, Nature.
[25] Alan M. Kwong,et al. A reference panel of 64,976 haplotypes for genotype imputation , 2015, Nature Genetics.
[26] R. Durbin,et al. Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses , 2012, Nature Protocols.
[27] E. Dermitzakis,et al. Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations , 2010, PLoS genetics.
[28] H. Stefánsson,et al. Genetics of gene expression and its effect on disease , 2008, Nature.
[29] B. Christensen,et al. Cell-type deconvolution from DNA methylation: a review of recent applications , 2017, Human molecular genetics.
[30] M. Schulze,et al. General and abdominal adiposity and risk of death in Europe. , 2008, The New England journal of medicine.
[31] M. Robinson,et al. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. , 2015, F1000Research.
[32] M. E. Ràfols. Tejido adiposo: heterogeneidad celular y diversidad funcional , 2014 .
[33] Aiqing He,et al. Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits. , 2017, American journal of human genetics.
[34] G. Abecasis,et al. Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. , 2012, American journal of human genetics.
[35] A. Kimchi,et al. Isolation of DAP3, a Novel Mediator of Interferon-γ-induced Cell Death (*) , 1995, The Journal of Biological Chemistry.
[36] Mark Gerstein,et al. Pseudogene.org: a comprehensive database and comparison platform for pseudogene annotation , 2006, Nucleic Acids Res..
[37] P. Tsai,et al. Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition , 2018, Nature Genetics.
[38] Benjamin A. Logsdon,et al. Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS , 2018, American journal of human genetics.
[39] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[40] Nicola J. Rinaldi,et al. Genetic effects on gene expression across human tissues , 2017, Nature.
[41] P. Visscher,et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets , 2016, Nature Genetics.
[42] U. Smith,et al. Adipose tissue regulates insulin sensitivity: role of adipogenesis, de novo lipogenesis and novel lipids , 2016, Journal of internal medicine.
[43] Tamara S. Roman,et al. New genetic loci link adipose and insulin biology to body fat distribution , 2014, Nature.
[44] P. Visscher,et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700,000 individuals of European ancestry , 2018, bioRxiv.
[45] Ayellet V. Segrè,et al. Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation , 2018, Nature Genetics.
[46] O. Delaneau,et al. Estimating the causal tissues for complex traits and diseases , 2016, Nature Genetics.
[47] Jun Liu,et al. JAZF1 can regulate the expression of lipid metabolic genes and inhibit lipid accumulation in adipocytes. , 2014, Biochemical and biophysical research communications.
[48] Xia Yang,et al. Sherlock: detecting gene-disease associations by matching patterns of expression QTL and GWAS. , 2013, American journal of human genetics.
[49] Samuel E. Jones,et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry , 2018, bioRxiv.
[50] Karen L. Mohlke,et al. Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals , 2012, PLoS genetics.
[51] Ying Li,et al. Measure transcript integrity using RNA-seq data , 2016, BMC Bioinformatics.
[52] David M. Sabatini,et al. mTOR Signaling in Growth, Metabolism, and Disease , 2017, Cell.
[53] Ayellet V. Segrè,et al. Colocalization of GWAS and eQTL Signals Detects Target Genes , 2016, bioRxiv.
[54] Jonathan K. Pritchard,et al. The Genetic and Mechanistic Basis for Variation in Gene Regulation , 2015, PLoS genetics.
[55] P. Hughes,et al. Sulfation of “Estrogenic” Alkylphenols and 17β-Estradiol by Human Platelet Phenol Sulfotransferases* , 2000, The Journal of Biological Chemistry.
[56] Dexter Canoy,et al. Distribution of body fat and risk of coronary heart disease in men and women , 2008, Current opinion in cardiology.
[57] Richard Durbin,et al. Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins , 2014, Nature Genetics.
[58] C. Wallace,et al. Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics , 2013, PLoS genetics.
[59] D. Koller,et al. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals , 2013, Genome research.
[60] Ritsert C. Jansen,et al. MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects , 2011, Bioinform..
[61] M. Jensen,et al. Measuring committed preadipocytes in human adipose tissue from severely obese patients by using adipocyte fatty acid binding protein. , 2004, American journal of physiology. Regulatory, integrative and comparative physiology.
[62] G. Jasienska,et al. 17-beta-estradiol in relation to age at menarche and adult obesity in premenopausal women. , 2008, Human reproduction.
[63] R. Vasan,et al. Abdominal Subcutaneous Adipose Tissue: A Protective Fat Depot? , 2009, Diabetes Care.
[64] A. Engin,et al. The Interactions Between Kynurenine, Folate, Methionine and Pteridine Pathways in Obesity. , 2017, Advances in experimental medicine and biology.
[65] Teresa Oliveira,et al. Biochemistry of adipose tissue: an endocrine organ , 2013, Archives of medical science : AMS.
[66] Wei Li,et al. RSeQC: quality control of RNA-seq experiments , 2012, Bioinform..
[67] Luke R. Lloyd-Jones,et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes , 2018, Nature Communications.
[68] Ji Zhang,et al. GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach , 2015, Bioinform..
[69] Xihong Lin,et al. JOINT ANALYSIS OF SNP AND GENE EXPRESSION DATA IN GENETIC ASSOCIATION STUDIES OF COMPLEX DISEASES. , 2014, The annals of applied statistics.
[70] Tom Michoel,et al. Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases , 2016, Science.
[71] S. Gogg,et al. Insulin resistance and impaired adipogenesis , 2015, Trends in Endocrinology & Metabolism.
[72] M. Blüher,et al. A novel ChREBP isoform in adipose tissue regulates systemic glucose metabolism , 2012, Nature.
[73] R. Seeley,et al. Expression of New Loci Associated With Obesity in Diet‐Induced Obese Rats: From Genetics to Physiology , 2012, Obesity.
[74] Ayellet V. Segrè,et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis , 2010, Nature Genetics.
[75] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[76] T. Lappalainen,et al. Associating cellular epigenetic models with human phenotypes , 2017, Nature Reviews Genetics.
[77] A. Chen-Plotkin,et al. The Post-GWAS Era: From Association to Function. , 2018, American journal of human genetics.
[78] M. Sewer,et al. Diacylglycerol kinase θ couples farnesoid X receptor-dependent bile acid signalling to Akt activation and glucose homoeostasis in hepatocytes. , 2013, The Biochemical journal.