Genome-wide associations of human gut microbiome variation and implications for causal inference analyses

[1]  Devin C. Koestler,et al.  pwrEWAS: a user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS) , 2019, BMC Bioinformatics.

[2]  P. Donnelly,et al.  A new multipoint method for genome-wide association studies by imputation of genotypes , 2007, Nature Genetics.

[3]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[4]  Fernando Pires Hartwig,et al.  Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption , 2017, bioRxiv.

[5]  Sonja W. Scholz,et al.  Genome-Wide Association Study reveals genetic risk underlying Parkinson’s disease , 2009, Nature Genetics.

[6]  Ewan Birney,et al.  GARFIELD - GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction , 2016, bioRxiv.

[7]  U. Nöthlings,et al.  Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota , 2016, Nature Genetics.

[8]  J. Marchini,et al.  Genotype imputation for genome-wide association studies , 2010, Nature Reviews Genetics.

[9]  Judy H. Cho,et al.  Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations , 2015, Nature Genetics.

[10]  J. Hirschhorn,et al.  Biological interpretation of genome-wide association studies using predicted gene functions , 2015, Nature Communications.

[11]  Michael Krawczak,et al.  PopGen: Population-Based Recruitment of Patients and Controls for the Analysis of Complex Genotype-Phenotype Relationships , 2006, Public Health Genomics.

[12]  Emily R. Davenport,et al.  Genetic Determinants of the Gut Microbiome in UK Twins. , 2016, Cell host & microbe.

[13]  Rob Knight,et al.  Current understanding of the human microbiome , 2018, Nature Medicine.

[14]  Shiraz A. Shah,et al.  Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative , 2018, Microbiome.

[15]  Erdogan Taskesen,et al.  Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.

[16]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[17]  J. Raes,et al.  Population-level analysis of gut microbiome variation , 2016, Science.

[18]  E. Birney,et al.  GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals , 2019, Nature Genetics.

[19]  Yurii S. Aulchenko,et al.  The GenABEL Project for statistical genomics , 2016, F1000Research.

[20]  S. S. Andrade,et al.  Action and function of Faecalibacterium prausnitzii in health and disease. , 2017, Best practice & research. Clinical gastroenterology.

[21]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[22]  P. Bork,et al.  Population-level analysis of Blastocystis subtype prevalence and variation in the human gut microbiota , 2018, Gut.

[23]  Louis J. Cohen,et al.  Commensal bacteria produce GPCR ligands that mimic human signaling molecules , 2017, Nature.

[24]  Christian Gieger,et al.  Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality , 2015, PLoS genetics.

[25]  Tamara S. Roman,et al.  New genetic loci link adipose and insulin biology to body fat distribution , 2014, Nature.

[26]  G. Davey Smith,et al.  Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator , 2016, Genetic epidemiology.

[27]  Falk Hildebrand,et al.  Correction: LotuS: an efficient and user-friendly OTU processing pipeline , 2014, Microbiome.

[28]  Nick C Fox,et al.  Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease , 2013, Nature Genetics.

[29]  Emily R. Davenport,et al.  Genome-Wide Association Studies of the Human Gut Microbiota , 2015, PloS one.

[30]  Peer Bork,et al.  Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees , 2016, Nucleic Acids Res..

[31]  C. Quince,et al.  Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics , 2012, PloS one.

[32]  Falk Hildebrand,et al.  Erratum to: LotuS: an efficient and user-friendly OTU processing pipeline , 2014, Microbiome.

[33]  G. Davey Smith,et al.  Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.

[34]  L. Wain,et al.  Haplotype estimation for biobank scale datasets , 2016, Nature Genetics.

[35]  J. Raes,et al.  Practical considerations for large-scale gut microbiome studies , 2017, FEMS microbiology reviews.

[36]  Joseph T. Glessner,et al.  PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. , 2007, Genome research.

[37]  Paul J. McMurdie,et al.  DADA2: High resolution sample inference from Illumina amplicon data , 2016, Nature Methods.

[38]  Ross M. Fraser,et al.  Genetic studies of body mass index yield new insights for obesity biology , 2015, Nature.

[39]  R. Freedland,et al.  Effects of propionate on lipid biosynthesis in isolated rat hepatocytes. , 1990, The Journal of nutrition.

[40]  D. Gagnon,et al.  Identification of a Novel Na+/myo-Inositol Cotransporter* , 2002, The Journal of Biological Chemistry.

[41]  Katherine H. Huang,et al.  Host genetic variation impacts microbiome composition across human body sites , 2015, Genome Biology.

[42]  Robert W. Williams,et al.  Murine Gut Microbiota Is Defined by Host Genetics and Modulates Variation of Metabolic Traits , 2012, PloS one.

[43]  A. Paterson,et al.  Association of host genome with intestinal microbial composition in a large healthy cohort , 2016, Nature Genetics.

[44]  A. Kurilshikov,et al.  Environment dominates over host genetics in shaping human gut microbiota , 2018, Nature.

[45]  Stephen Burgess,et al.  PhenoScanner V2: an expanded tool for searching human genotype–phenotype associations , 2019, Bioinform..

[46]  Jun S. Liu,et al.  The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans , 2015, Science.

[47]  Tanya M. Teslovich,et al.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes , 2012, Nature Genetics.

[48]  Mitchell J. Machiela,et al.  LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants , 2015, Bioinform..

[49]  Jun S. Liu,et al.  Genetics of rheumatoid arthritis contributes to biology and drug discovery , 2013 .

[50]  N. Wray,et al.  A mega-analysis of genome-wide association studies for major depressive disorder , 2013, Molecular Psychiatry.

[51]  Rob Knight,et al.  American Gut: an Open Platform for Citizen Science Microbiome Research , 2018, mSystems.

[52]  Claude Bouchard,et al.  Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults , 2017 .

[53]  Paramvir S. Dehal,et al.  FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments , 2010, PloS one.

[54]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[55]  Alan M. Kwong,et al.  A reference panel of 64,976 haplotypes for genotype imputation , 2015, Nature Genetics.

[56]  L. Hall,et al.  Improving causality in microbiome research: can human genetic epidemiology help? , 2019, Wellcome open research.

[57]  E. Birney,et al.  Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt , 2009, Nature Protocols.

[58]  Tariq Ahmad,et al.  Meta-analysis and imputation refines the association of 15q25 with smoking quantity , 2010, Nature Genetics.

[59]  Morris A. Swertz,et al.  Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity , 2016, Science.

[60]  G. Davey Smith,et al.  Mendelian randomization: genetic anchors for causal inference in epidemiological studies , 2014, Human molecular genetics.

[61]  F. Montecucco,et al.  Evidence for the Gut Microbiota Short-Chain Fatty Acids as Key Pathophysiological Molecules Improving Diabetes , 2014, Mediators of inflammation.

[62]  W. Cefalu,et al.  Butyrate Improves Insulin Sensitivity and Increases Energy Expenditure in Mice , 2009, Diabetes.

[63]  Heorhiy Byelas,et al.  Improved imputation quality of low-frequency and rare variants in European samples using the ‘Genome of The Netherlands' , 2014, European Journal of Human Genetics.

[64]  S. Fleming,et al.  Acetate and butyrate are the major substrates for de novo lipogenesis in rat colonic epithelial cells. , 2003, The Journal of nutrition.

[65]  T. Vatanen,et al.  The effect of host genetics on the gut microbiome , 2016, Nature Genetics.

[66]  J. Graff,et al.  Circulating glucose levels inversely correlate with Drosophila larval feeding through insulin signaling and SLC5A11 , 2018, Communications Biology.

[67]  Robert C. Edgar,et al.  MUSCLE: multiple sequence alignment with high accuracy and high throughput. , 2004, Nucleic acids research.

[68]  Valeriia Haberland,et al.  The MR-Base platform supports systematic causal inference across the human phenome , 2018, eLife.