%0 Journal Article %J Am J Hum Genet %D 2018 %T Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. %A Ligthart, Symen %A Vaez, Ahmad %A Võsa, Urmo %A Stathopoulou, Maria G %A de Vries, Paul S %A Prins, Bram P %A van der Most, Peter J %A Tanaka, Toshiko %A Naderi, Elnaz %A Rose, Lynda M %A Wu, Ying %A Karlsson, Robert %A Barbalic, Maja %A Lin, Honghuang %A Pool, René %A Zhu, Gu %A Macé, Aurélien %A Sidore, Carlo %A Trompet, Stella %A Mangino, Massimo %A Sabater-Lleal, Maria %A Kemp, John P %A Abbasi, Ali %A Kacprowski, Tim %A Verweij, Niek %A Smith, Albert V %A Huang, Tao %A Marzi, Carola %A Feitosa, Mary F %A Lohman, Kurt K %A Kleber, Marcus E %A Milaneschi, Yuri %A Mueller, Christian %A Huq, Mahmudul %A Vlachopoulou, Efthymia %A Lyytikäinen, Leo-Pekka %A Oldmeadow, Christopher %A Deelen, Joris %A Perola, Markus %A Zhao, Jing Hua %A Feenstra, Bjarke %A Amini, Marzyeh %A Lahti, Jari %A Schraut, Katharina E %A Fornage, Myriam %A Suktitipat, Bhoom %A Chen, Wei-Min %A Li, Xiaohui %A Nutile, Teresa %A Malerba, Giovanni %A Luan, Jian'an %A Bak, Tom %A Schork, Nicholas %A del Greco M, Fabiola %A Thiering, Elisabeth %A Mahajan, Anubha %A Marioni, Riccardo E %A Mihailov, Evelin %A Eriksson, Joel %A Ozel, Ayse Bilge %A Zhang, Weihua %A Nethander, Maria %A Cheng, Yu-Ching %A Aslibekyan, Stella %A Ang, Wei %A Gandin, Ilaria %A Yengo, Loic %A Portas, Laura %A Kooperberg, Charles %A Hofer, Edith %A Rajan, Kumar B %A Schurmann, Claudia %A den Hollander, Wouter %A Ahluwalia, Tarunveer S %A Zhao, Jing %A Draisma, Harmen H M %A Ford, Ian %A Timpson, Nicholas %A Teumer, Alexander %A Huang, Hongyan %A Wahl, Simone %A Liu, Yongmei %A Huang, Jie %A Uh, Hae-Won %A Geller, Frank %A Joshi, Peter K %A Yanek, Lisa R %A Trabetti, Elisabetta %A Lehne, Benjamin %A Vozzi, Diego %A Verbanck, Marie %A Biino, Ginevra %A Saba, Yasaman %A Meulenbelt, Ingrid %A O'Connell, Jeff R %A Laakso, Markku %A Giulianini, Franco %A Magnusson, Patrik K E %A Ballantyne, Christie M %A Hottenga, Jouke Jan %A Montgomery, Grant W %A Rivadineira, Fernando %A Rueedi, Rico %A Steri, Maristella %A Herzig, Karl-Heinz %A Stott, David J %A Menni, Cristina %A Frånberg, Mattias %A St Pourcain, Beate %A Felix, Stephan B %A Pers, Tune H %A Bakker, Stephan J L %A Kraft, Peter %A Peters, Annette %A Vaidya, Dhananjay %A Delgado, Graciela %A Smit, Johannes H %A Großmann, Vera %A Sinisalo, Juha %A Seppälä, Ilkka %A Williams, Stephen R %A Holliday, Elizabeth G %A Moed, Matthijs %A Langenberg, Claudia %A Räikkönen, Katri %A Ding, Jingzhong %A Campbell, Harry %A Sale, Michele M %A Chen, Yii-Der I %A James, Alan L %A Ruggiero, Daniela %A Soranzo, Nicole %A Hartman, Catharina A %A Smith, Erin N %A Berenson, Gerald S %A Fuchsberger, Christian %A Hernandez, Dena %A Tiesler, Carla M T %A Giedraitis, Vilmantas %A Liewald, David %A Fischer, Krista %A Mellström, Dan %A Larsson, Anders %A Wang, Yunmei %A Scott, William R %A Lorentzon, Matthias %A Beilby, John %A Ryan, Kathleen A %A Pennell, Craig E %A Vuckovic, Dragana %A Balkau, Beverly %A Concas, Maria Pina %A Schmidt, Reinhold %A Mendes de Leon, Carlos F %A Bottinger, Erwin P %A Kloppenburg, Margreet %A Paternoster, Lavinia %A Boehnke, Michael %A Musk, A W %A Willemsen, Gonneke %A Evans, David M %A Madden, Pamela A F %A Kähönen, Mika %A Kutalik, Zoltán %A Zoledziewska, Magdalena %A Karhunen, Ville %A Kritchevsky, Stephen B %A Sattar, Naveed %A LaChance, Genevieve %A Clarke, Robert %A Harris, Tamara B %A Raitakari, Olli T %A Attia, John R %A van Heemst, Diana %A Kajantie, Eero %A Sorice, Rossella %A Gambaro, Giovanni %A Scott, Robert A %A Hicks, Andrew A %A Ferrucci, Luigi %A Standl, Marie %A Lindgren, Cecilia M %A Starr, John M %A Karlsson, Magnus %A Lind, Lars %A Li, Jun Z %A Chambers, John C %A Mori, Trevor A %A de Geus, Eco J C N %A Heath, Andrew C %A Martin, Nicholas G %A Auvinen, Juha %A Buckley, Brendan M %A de Craen, Anton J M %A Waldenberger, Melanie %A Strauch, Konstantin %A Meitinger, Thomas %A Scott, Rodney J %A McEvoy, Mark %A Beekman, Marian %A Bombieri, Cristina %A Ridker, Paul M %A Mohlke, Karen L %A Pedersen, Nancy L %A Morrison, Alanna C %A Boomsma, Dorret I %A Whitfield, John B %A Strachan, David P %A Hofman, Albert %A Vollenweider, Peter %A Cucca, Francesco %A Järvelin, Marjo-Riitta %A Jukema, J Wouter %A Spector, Tim D %A Hamsten, Anders %A Zeller, Tanja %A Uitterlinden, André G %A Nauck, Matthias %A Gudnason, Vilmundur %A Qi, Lu %A Grallert, Harald %A Borecki, Ingrid B %A Rotter, Jerome I %A März, Winfried %A Wild, Philipp S %A Lokki, Marja-Liisa %A Boyle, Michael %A Salomaa, Veikko %A Melbye, Mads %A Eriksson, Johan G %A Wilson, James F %A Penninx, Brenda W J H %A Becker, Diane M %A Worrall, Bradford B %A Gibson, Greg %A Krauss, Ronald M %A Ciullo, Marina %A Zaza, Gianluigi %A Wareham, Nicholas J %A Oldehinkel, Albertine J %A Palmer, Lyle J %A Murray, Sarah S %A Pramstaller, Peter P %A Bandinelli, Stefania %A Heinrich, Joachim %A Ingelsson, Erik %A Deary, Ian J %A Mägi, Reedik %A Vandenput, Liesbeth %A van der Harst, Pim %A Desch, Karl C %A Kooner, Jaspal S %A Ohlsson, Claes %A Hayward, Caroline %A Lehtimäki, Terho %A Shuldiner, Alan R %A Arnett, Donna K %A Beilin, Lawrence J %A Robino, Antonietta %A Froguel, Philippe %A Pirastu, Mario %A Jess, Tine %A Koenig, Wolfgang %A Loos, Ruth J F %A Evans, Denis A %A Schmidt, Helena %A Smith, George Davey %A Slagboom, P Eline %A Eiriksdottir, Gudny %A Morris, Andrew P %A Psaty, Bruce M %A Tracy, Russell P %A Nolte, Ilja M %A Boerwinkle, Eric %A Visvikis-Siest, Sophie %A Reiner, Alex P %A Gross, Myron %A Bis, Joshua C %A Franke, Lude %A Franco, Oscar H %A Benjamin, Emelia J %A Chasman, Daniel I %A Dupuis, Josée %A Snieder, Harold %A Dehghan, Abbas %A Alizadeh, Behrooz Z %X

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

%B Am J Hum Genet %V 103 %P 691-706 %8 2018 Nov 01 %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/30388399?dopt=Abstract %R 10.1016/j.ajhg.2018.09.009 %0 Journal Article %J Am J Hum Genet %D 2017 %T Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits. %A Tachmazidou, Ioanna %A Süveges, Dániel %A Min, Josine L %A Ritchie, Graham R S %A Steinberg, Julia %A Walter, Klaudia %A Iotchkova, Valentina %A Schwartzentruber, Jeremy %A Huang, Jie %A Memari, Yasin %A McCarthy, Shane %A Crawford, Andrew A %A Bombieri, Cristina %A Cocca, Massimiliano %A Farmaki, Aliki-Eleni %A Gaunt, Tom R %A Jousilahti, Pekka %A Kooijman, Marjolein N %A Lehne, Benjamin %A Malerba, Giovanni %A Männistö, Satu %A Matchan, Angela %A Medina-Gomez, Carolina %A Metrustry, Sarah J %A Nag, Abhishek %A Ntalla, Ioanna %A Paternoster, Lavinia %A Rayner, Nigel W %A Sala, Cinzia %A Scott, William R %A Shihab, Hashem A %A Southam, Lorraine %A St Pourcain, Beate %A Traglia, Michela %A Trajanoska, Katerina %A Zaza, Gialuigi %A Zhang, Weihua %A Artigas, María S %A Bansal, Narinder %A Benn, Marianne %A Chen, Zhongsheng %A Danecek, Petr %A Lin, Wei-Yu %A Locke, Adam %A Luan, Jian'an %A Manning, Alisa K %A Mulas, Antonella %A Sidore, Carlo %A Tybjaerg-Hansen, Anne %A Varbo, Anette %A Zoledziewska, Magdalena %A Finan, Chris %A Hatzikotoulas, Konstantinos %A Hendricks, Audrey E %A Kemp, John P %A Moayyeri, Alireza %A Panoutsopoulou, Kalliope %A Szpak, Michal %A Wilson, Scott G %A Boehnke, Michael %A Cucca, Francesco %A Di Angelantonio, Emanuele %A Langenberg, Claudia %A Lindgren, Cecilia %A McCarthy, Mark I %A Morris, Andrew P %A Nordestgaard, Børge G %A Scott, Robert A %A Tobin, Martin D %A Wareham, Nicholas J %A Burton, Paul %A Chambers, John C %A Smith, George Davey %A Dedoussis, George %A Felix, Janine F %A Franco, Oscar H %A Gambaro, Giovanni %A Gasparini, Paolo %A Hammond, Christopher J %A Hofman, Albert %A Jaddoe, Vincent W V %A Kleber, Marcus %A Kooner, Jaspal S %A Perola, Markus %A Relton, Caroline %A Ring, Susan M %A Rivadeneira, Fernando %A Salomaa, Veikko %A Spector, Timothy D %A Stegle, Oliver %A Toniolo, Daniela %A Uitterlinden, André G %A Barroso, Inês %A Greenwood, Celia M T %A Perry, John R B %A Walker, Brian R %A Butterworth, Adam S %A Xue, Yali %A Durbin, Richard %A Small, Kerrin S %A Soranzo, Nicole %A Timpson, Nicholas J %A Zeggini, Eleftheria %K Anthropometry %K Body Height %K Cohort Studies %K Databases, Genetic %K DNA Methylation %K Female %K Genetic Variation %K Genome, Human %K Genome-Wide Association Study %K Humans %K Lipodystrophy %K Male %K Meta-Analysis as Topic %K Obesity %K Physical Chromosome Mapping %K Quantitative Trait Loci %K Sequence Analysis, DNA %K Sex Characteristics %K Syndrome %K United Kingdom %X

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

%B Am J Hum Genet %V 100 %P 865-884 %8 2017 Jun 01 %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/28552196?dopt=Abstract %R 10.1016/j.ajhg.2017.04.014 %0 Journal Article %J Nat Genet %D 2015 %T Genome sequencing elucidates Sardinian genetic architecture and augments association analyses for lipid and blood inflammatory markers. %A Sidore, Carlo %A Busonero, Fabio %A Maschio, Andrea %A Porcu, Eleonora %A Naitza, Silvia %A Zoledziewska, Magdalena %A Mulas, Antonella %A Pistis, Giorgio %A Steri, Maristella %A Danjou, Fabrice %A Kwong, Alan %A Ortega Del Vecchyo, Vicente Diego %A Chiang, Charleston W K %A Bragg-Gresham, Jennifer %A Pitzalis, Maristella %A Nagaraja, Ramaiah %A Tarrier, Brendan %A Brennan, Christine %A Uzzau, Sergio %A Fuchsberger, Christian %A Atzeni, Rossano %A Reinier, Frederic %A Berutti, Riccardo %A Huang, Jie %A Timpson, Nicholas J %A Toniolo, Daniela %A Gasparini, Paolo %A Malerba, Giovanni %A Dedoussis, George %A Zeggini, Eleftheria %A Soranzo, Nicole %A Jones, Chris %A Lyons, Robert %A Angius, Andrea %A Kang, Hyun M %A Novembre, John %A Sanna, Serena %A Schlessinger, David %A Cucca, Francesco %A Abecasis, Goncalo R %X

We report ∼17.6 million genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from previous sequencing-based compilations and are enriched for predicted functional consequences. Furthermore, ∼76,000 variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. We observe 14 signals, including 2 major new loci, for lipid levels and 19 signals, including 2 new loci, for inflammatory markers. The new associations would have been missed in analyses based on 1000 Genomes Project data, underlining the advantages of large-scale sequencing in this founder population.

%B Nat Genet %V 47 %P 1272-81 %8 2015 Nov %G eng %N 11 %1 http://www.ncbi.nlm.nih.gov/pubmed/26366554?dopt=Abstract %R 10.1038/ng.3368 %0 Journal Article %J Nat Commun %D 2015 %T Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel. %A Huang, Jie %A Howie, Bryan %A McCarthy, Shane %A Memari, Yasin %A Walter, Klaudia %A Min, Josine L %A Danecek, Petr %A Malerba, Giovanni %A Trabetti, Elisabetta %A Zheng, Hou-Feng %A Gambaro, Giovanni %A Richards, J Brent %A Durbin, Richard %A Timpson, Nicholas J %A Marchini, Jonathan %A Soranzo, Nicole %X

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.

%B Nat Commun %V 6 %P 8111 %8 2015 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/26368830?dopt=Abstract %R 10.1038/ncomms9111 %0 Journal Article %J PLoS Genet %D 2014 %T A general approach for haplotype phasing across the full spectrum of relatedness. %A O'Connell, Jared %A Gurdasani, Deepti %A Delaneau, Olivier %A Pirastu, Nicola %A Ulivi, Sheila %A Cocca, Massimiliano %A Traglia, Michela %A Huang, Jie %A Huffman, Jennifer E %A Rudan, Igor %A McQuillan, Ruth %A Fraser, Ross M %A Campbell, Harry %A Polasek, Ozren %A Asiki, Gershim %A Ekoru, Kenneth %A Hayward, Caroline %A Wright, Alan F %A Vitart, Veronique %A Navarro, Pau %A Zagury, Jean-Francois %A Wilson, James F %A Toniolo, Daniela %A Gasparini, Paolo %A Soranzo, Nicole %A Sandhu, Manjinder S %A Marchini, Jonathan %K Chromosome Mapping %K Cohort Effect %K Family %K Genotype %K Haplotypes %K Humans %K Models, Genetic %K Pedigree %K Phenotype %K Recombination, Genetic %X

Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.

%B PLoS Genet %V 10 %P e1004234 %8 2014 Apr %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/24743097?dopt=Abstract %R 10.1371/journal.pgen.1004234