A Systematic Mapping Approach of 16q12.2/FTO and BMI in More Than 20,000 African Americans Narrows in on the Underlying Functional Variation: Results from the Population Architecture using Genomics and Epidemiology (PAGE) Study
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{"title"=>"A Systematic Mapping Approach of 16q12.2/FTO and BMI in More Than 20,000 African Americans Narrows in on the Underlying Functional Variation: Results from the Population Architecture using Genomics and Epidemiology (PAGE) Study", "type"=>"journal", "authors"=>[{"first_name"=>"Ulrike", "last_name"=>"Peters", "scopus_author_id"=>"7101680952"}, {"first_name"=>"Kari E.", "last_name"=>"North", "scopus_author_id"=>"7006800602"}, {"first_name"=>"Praveen", "last_name"=>"Sethupathy", "scopus_author_id"=>"11738969200"}, {"first_name"=>"Steve", "last_name"=>"Buyske", "scopus_author_id"=>"6602253579"}, {"first_name"=>"Jeff", "last_name"=>"Haessler", "scopus_author_id"=>"16318526900"}, {"first_name"=>"Shuo", "last_name"=>"Jiao", "scopus_author_id"=>"42661544000"}, {"first_name"=>"Megan D.", "last_name"=>"Fesinmeyer", "scopus_author_id"=>"8529960600"}, {"first_name"=>"Rebecca D.", "last_name"=>"Jackson", "scopus_author_id"=>"7404310087"}, {"first_name"=>"Lew H.", "last_name"=>"Kuller", "scopus_author_id"=>"57200682268"}, {"first_name"=>"Aleksandar", "last_name"=>"Rajkovic", "scopus_author_id"=>"6603842643"}, {"first_name"=>"Unhee", "last_name"=>"Lim", "scopus_author_id"=>"14031811900"}, {"first_name"=>"Iona", "last_name"=>"Cheng", "scopus_author_id"=>"8646125400"}, {"first_name"=>"Fred", "last_name"=>"Schumacher", "scopus_author_id"=>"56386979100"}, {"first_name"=>"Lynne", "last_name"=>"Wilkens", "scopus_author_id"=>"7007036544"}, {"first_name"=>"Rongling", "last_name"=>"Li", "scopus_author_id"=>"55491283700"}, {"first_name"=>"Keri", "last_name"=>"Monda", "scopus_author_id"=>"57194729439"}, {"first_name"=>"Georg", "last_name"=>"Ehret", "scopus_author_id"=>"14029825300"}, {"first_name"=>"Khanh Dung H.", "last_name"=>"Nguyen", "scopus_author_id"=>"55568535400"}, {"first_name"=>"Richard", "last_name"=>"Cooper", "scopus_author_id"=>"56662407500"}, {"first_name"=>"Cora E.", "last_name"=>"Lewis", "scopus_author_id"=>"35372126200"}, {"first_name"=>"Mark", "last_name"=>"Leppert", "scopus_author_id"=>"35351313000"}, {"first_name"=>"Marguerite R.", "last_name"=>"Irvin", "scopus_author_id"=>"28567762900"}, {"first_name"=>"C. Charles", "last_name"=>"Gu", "scopus_author_id"=>"24775504800"}, {"first_name"=>"Denise", "last_name"=>"Houston", "scopus_author_id"=>"8322975400"}, {"first_name"=>"Petra", "last_name"=>"Buzkova", "scopus_author_id"=>"23093239700"}, {"first_name"=>"Marylyn", "last_name"=>"Ritchie", "scopus_author_id"=>"7102927061"}, {"first_name"=>"Tara C.", "last_name"=>"Matise", "scopus_author_id"=>"7003415423"}, {"first_name"=>"Loic", "last_name"=>"Le Marchand", "scopus_author_id"=>"7006229986"}, {"first_name"=>"Lucia A.", "last_name"=>"Hindorff", "scopus_author_id"=>"6602543812"}, {"first_name"=>"Dana C.", "last_name"=>"Crawford", "scopus_author_id"=>"7403085570"}, {"first_name"=>"Christopher A.", "last_name"=>"Haiman", "scopus_author_id"=>"6701722861"}, {"first_name"=>"Charles", "last_name"=>"Kooperberg", "scopus_author_id"=>"56758746100"}], "year"=>2013, "source"=>"PLoS Genetics", "identifiers"=>{"issn"=>"15537390", "isbn"=>"1553-7404 (Electronic)\\r1553-7390 (Linking)", "pmid"=>"23341774", "scopus"=>"2-s2.0-84873504695", "doi"=>"10.1371/journal.pgen.1003171", "sgr"=>"84873504695", "pui"=>"368295362"}, "id"=>"01c089e5-076f-3739-aed5-c0abb2f7b277", "abstract"=>"Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 × 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.", "link"=>"http://www.mendeley.com/research/systematic-mapping-approach-16q122fto-bmi-more-20000-african-americans-narrows-underlying-functional", "reader_count"=>47, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Researcher"=>18, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>1, "Other"=>4, "Student > Master"=>5, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Researcher"=>18, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>1, "Other"=>4, "Student > Master"=>5, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Medicine and Dentistry"=>9, "Agricultural and Biological Sciences"=>25, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Psychology"=>1, "Social Sciences"=>1, "Computer Science"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>25}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"Republic of Singapore"=>1, "United States"=>2, "Egypt"=>1, "Brazil"=>1, "South Africa"=>1, "Portugal"=>1, "Russia"=>1}, "group_count"=>3}

Scopus | Further Information

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  • {"files"=>["https://ndownloader.figshare.com/files/276073", "https://ndownloader.figshare.com/files/276113", "https://ndownloader.figshare.com/files/276214", "https://ndownloader.figshare.com/files/276307", "https://ndownloader.figshare.com/files/276365", "https://ndownloader.figshare.com/files/276423"], "description"=>"<div><p>Genetic variants in intron 1 of the fat mass– and obesity-associated (<em>FTO</em>) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI–associated <em>FTO</em> index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/<em>FTO</em> locus and to search for second independent signals in the broader region, we fine-mapped a 646–kb region, encompassing the large <em>FTO</em> gene and the flanking gene <em>RPGRIP1L</em> by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known <em>FTO</em> intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3×10<sup>−6</sup>) had not been highlighted in previous studies. While rs56137030was correlated at r<sup>2</sup>>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor <em>CUX1</em>, which has recently been implicated in the regulation of <em>FTO</em>. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known <em>FTO</em> locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.</p> </div>", "links"=>[], "tags"=>["systematic", "bmi", "african", "americans", "narrows", "results", "genomics", "epidemiology", "study"], "article_id"=>114378, "categories"=>["Genetics", "Biotechnology"], "users"=>["Ulrike Peters", "Kari E. North", "Praveen Sethupathy", "Steve Buyske", "Jeff Haessler", "Shuo Jiao", "Megan D. Fesinmeyer", "Rebecca D. Jackson", "Lew H. Kuller", "Aleksandar Rajkovic", "Unhee Lim", "Iona Cheng", "Fred Schumacher", "Lynne Wilkens", "Rongling Li", "Keri Monda", "Georg Ehret", "Khanh-Dung H. Nguyen", "Richard Cooper", "Cora E. Lewis", "Mark Leppert", "Marguerite R. Irvin", "C. Charles Gu", "Denise Houston", "Petra Buzkova", "Marylyn Ritchie", "Tara C. Matise", "Loic Le Marchand", "Lucia A. Hindorff", "Dana C. Crawford", "Christopher A. Haiman", "Charles Kooperberg"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1003171.s001", "https://dx.doi.org/10.1371/journal.pgen.1003171.s002", "https://dx.doi.org/10.1371/journal.pgen.1003171.s003", "https://dx.doi.org/10.1371/journal.pgen.1003171.s004", "https://dx.doi.org/10.1371/journal.pgen.1003171.s005", "https://dx.doi.org/10.1371/journal.pgen.1003171.s006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Systematic_Mapping_Approach_of_16q12_2_FTO_and_BMI_in_More_Than_20_000_African_Americans_Narrows_in_on_the_Underlying_Functional_Variation_Results_from_the_Population_Architecture_using_Genomics_and_Epidemiology_PAGE_Study__/114378", "title"=>"A Systematic Mapping Approach of 16q12.2/<em>FTO</em> and BMI in More Than 20,000 African Americans Narrows in on the Underlying Functional Variation: Results from the Population Architecture using Genomics and Epidemiology (PAGE) Study", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-01-17 01:12:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/504849"], "description"=>"<p>The top half of each figure has physical position along the x axis, and the −log<sub>10</sub> of the meta-analysis p-value on the y-axis. Each dot on the plot represents the p-value of the association for one SNP with lnBMI across all studies. The most significant SNP (rs56137030) is marked as a purple diamond. The color scheme represents the pairwise correlation (r<sup>2</sup>) for the SNPs across the 16q12.2/<i>FTO</i> region with the most significant SNP (rs56137030). Gray squares indicate that correlation was missing for this p-value because the variant was monomorphic in EA. The bottom half of the figure shows the position of the genes across the region. A and B show the same region and results. The only difference between A and B is that in A correlation with the most significant SNP (rs56137030) was calculated based on EAs, specifically based on data from 65 European Americans (Utah residents with Northern and Western European ancestry from the CEPH collection, CEU) sequenced as part of the 1000 Genomes Project and B correlation was based on 61 African Americans from the South-west (ASW) and sequenced as part of the 1000 Genomes Project.</p>", "links"=>[], "tags"=>["snps", "lnbmi", "african", "americans", "rs56137030"], "article_id"=>175324, "categories"=>["Genetics", "Biotechnology"], "users"=>["Ulrike Peters", "Kari E. North", "Praveen Sethupathy", "Steve Buyske", "Jeff Haessler", "Shuo Jiao", "Megan D. Fesinmeyer", "Rebecca D. Jackson", "Lew H. Kuller", "Aleksandar Rajkovic", "Unhee Lim", "Iona Cheng", "Fred Schumacher", "Lynne Wilkens", "Rongling Li", "Keri Monda", "Georg Ehret", "Khanh-Dung H. Nguyen", "Richard Cooper", "Cora E. Lewis", "Mark Leppert", "Marguerite R. Irvin", "C. Charles Gu", "Denise Houston", "Petra Buzkova", "Marylyn Ritchie", "Tara C. Matise", "Loic Le Marchand", "Lucia A. Hindorff", "Dana C. Crawford", "Christopher A. Haiman", "Charles Kooperberg"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1003171.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_results_p_values_and_correlation_structure_for_all_SNPs_in_the_16q12_2_FTO_region_and_lnBMI_among_African_Americans_using_rs56137030_to_calculate_correlation_among_SNPs_LocusZoom_plots_/175324", "title"=>"Association results (p-values) and correlation structure for all SNPs in the 16q12.2/<i>FTO</i> region and lnBMI among African Americans using rs56137030 to calculate correlation among SNPs (LocusZoom plots).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-17 01:28:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/504976"], "description"=>"<p>Distribution of study characteristics by study and overall.</p>", "links"=>[], "tags"=>["characteristics"], "article_id"=>175459, "categories"=>["Genetics", "Biotechnology"], "users"=>["Ulrike Peters", "Kari E. North", "Praveen Sethupathy", "Steve Buyske", "Jeff Haessler", "Shuo Jiao", "Megan D. Fesinmeyer", "Rebecca D. Jackson", "Lew H. Kuller", "Aleksandar Rajkovic", "Unhee Lim", "Iona Cheng", "Fred Schumacher", "Lynne Wilkens", "Rongling Li", "Keri Monda", "Georg Ehret", "Khanh-Dung H. Nguyen", "Richard Cooper", "Cora E. Lewis", "Mark Leppert", "Marguerite R. Irvin", "C. Charles Gu", "Denise Houston", "Petra Buzkova", "Marylyn Ritchie", "Tara C. Matise", "Loic Le Marchand", "Lucia A. Hindorff", "Dana C. Crawford", "Christopher A. Haiman", "Charles Kooperberg"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1003171.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_study_characteristics_by_study_and_overall_/175459", "title"=>"Distribution of study characteristics by study and overall.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-17 01:30:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/505048"], "description"=>"<p><b>a</b>SNPposition based on build 37.</p><p><b>b</b>Coding = coding allele, Base = baseline allele (risk estimates provide the log additive effect per copy of the coding allele).</p><p><b>c</b>CAF = coding allele frequency.</p><p><b>d</b>Rsq = measurement of imputation accuracy, ranging from 0 (low) to 1 (high).</p>", "links"=>[], "tags"=>["snps", "bmi", "studies"], "article_id"=>175528, "categories"=>["Genetics", "Biotechnology"], "users"=>["Ulrike Peters", "Kari E. North", "Praveen Sethupathy", "Steve Buyske", "Jeff Haessler", "Shuo Jiao", "Megan D. Fesinmeyer", "Rebecca D. Jackson", "Lew H. Kuller", "Aleksandar Rajkovic", "Unhee Lim", "Iona Cheng", "Fred Schumacher", "Lynne Wilkens", "Rongling Li", "Keri Monda", "Georg Ehret", "Khanh-Dung H. Nguyen", "Richard Cooper", "Cora E. Lewis", "Mark Leppert", "Marguerite R. Irvin", "C. Charles Gu", "Denise Houston", "Petra Buzkova", "Marylyn Ritchie", "Tara C. Matise", "Loic Le Marchand", "Lucia A. Hindorff", "Dana C. Crawford", "Christopher A. Haiman", "Charles Kooperberg"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1003171.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_SNPs_in_the_FTO_region_and_BMI_for_all_studies_combined_/175528", "title"=>"Association between SNPs in the <i>FTO</i> region and BMI for all studies combined.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-17 01:32:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/505115"], "description"=>"<p><b>a</b>Based o allele frequency for all AA participants in this study.</p><p><b>b</b>Based on data from the Exome Variation Server (<a href=\"http://snp.gs.washington.edu/EVS/\" target=\"_blank\">http://snp.gs.washington.edu/EVS/</a> accessed August 2012).</p>", "links"=>[], "tags"=>["allele", "snps", "fine-mapping"], "article_id"=>175595, "categories"=>["Genetics", "Biotechnology"], "users"=>["Ulrike Peters", "Kari E. North", "Praveen Sethupathy", "Steve Buyske", "Jeff Haessler", "Shuo Jiao", "Megan D. Fesinmeyer", "Rebecca D. Jackson", "Lew H. Kuller", "Aleksandar Rajkovic", "Unhee Lim", "Iona Cheng", "Fred Schumacher", "Lynne Wilkens", "Rongling Li", "Keri Monda", "Georg Ehret", "Khanh-Dung H. Nguyen", "Richard Cooper", "Cora E. Lewis", "Mark Leppert", "Marguerite R. Irvin", "C. Charles Gu", "Denise Houston", "Petra Buzkova", "Marylyn Ritchie", "Tara C. Matise", "Loic Le Marchand", "Lucia A. Hindorff", "Dana C. Crawford", "Christopher A. Haiman", "Charles Kooperberg"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1003171.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_allele_frequency_of_SNPs_in_the_FTO_fine_mapping_region_/175595", "title"=>"Distribution of allele frequency of SNPs in the <i>FTO</i> fine-mapping region.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-17 01:33:15"}

PMC Usage Stats | Further Information

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Relative Metric

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