Article in PLoS genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literature
Who cites it
15 citing papers in PubMed, 21 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
25 authors at 7 institutions in 3 countries.
Cassandra N SpracklenDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0003-3590-7182
Apoorva K IyengarDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0001-8465-333X
Swarooparani VadlamudiDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0001-9650-768X
Chelsea K RaulersonDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0001-5888-5196
Anne U JacksonDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-9672-2547
Sarah M BrotmanDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-7566-8895
Ying WuDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Maren E CannonDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.
James P DavisDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-8715-7857
Aaron T CrainDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-2425-5695
Kevin W CurrinDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.
Hannah J PerrinDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-3204-859X
Narisu NarisuNational Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America.ORCID 0000-0002-8483-1156
Heather M StringhamDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-2991-6392
Christian FuchsbergerDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.
Adam E LockeDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0001-6227-198X
Ryan P WelchDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0001-6378-1295
Johanna K KuusistoDepartment of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.
Päivi PajukantaDepartment of Human Genetics, University of California, Los Angeles, California, United States of America.ORCID 0000-0002-6423-8056
Laura J ScottDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-4886-5084
Yun LiDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0002-9275-4189
Francis S CollinsNational Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America.ORCID 0000-0002-1023-7410
Michael BoehnkeDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-6442-7754
Markku LaaksoDepartment of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland.
Karen L MohlkeDepartment of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID 0000-0001-6721-153X
University of North Carolina at Chapel Hill · USUniversity of Michigan · USNational Institutes of Health · USUniversity of Eastern Finland · FIEurac Research · ITJames S. McDonnell Foundation · USUniversity of California, Los Angeles · US
Funding
Systems genomics of metabolic syndrome traitsP01HL028481 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUSIS, ALDONS JAKE · 1985 to 2019
$50.2M
Genetic analysis of type II diabetes in Finnish populationZIAHG000024 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI ERDOS, MICHAEL · 2009 to 2025
$38.2M
Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
UNC Initiative for Maximizing Student DevelopmentR25GM055336 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI COOK, JEANETTE GOWEN, KASH, THOMAS L. · 1996 to 2023
$12.1M
Identifying Genes for Type 2 Diabetes: FUSIONU01DK062370 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L, SCOTT, LAURA J. · 2009 to 2021
$11.6M
Targeted Genetic Analysis of T2D and Quantitative TraitsR01DK072193 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN L. MOHLKE · 2005 to 2026
$11.3M
Pre-doctoral Training Program in Integrative Vascular BiologyT32HL069768 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Christopher P. Mack · 2002 to 2026
$9.7M
Genetic epidemiology of rare and regulatory variants for metabolic traitsR01DK093757 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN L. MOHLKE · 2011 to 2026
$8.2M
Identifying Genes for Type 2 Diabetes:FUSIONR01DK062370 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L, SCOTT, LAURA J. · 2003 to 2025
$6.7M
GENETIC ANALYSIS OF TYPE II DIABETES IN FINNISH POPULATIONZ01HG000024 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI COLLINS, FRANCIS S. · 1995 to 2008
$6.2M
NRSA IN GENETICST32GM007092 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SEKELSKY, JEFF J. · 1985 to 2019
$5.9M
The Genetic Epidemiology of Heart, Lung, and Blood TraitsTraining Grant (GenHLB)T32HL129982 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Christy Leigh Avery, KAREN L. MOHLKE · 2016 to 2026
Loci identified in genome-wide association studies (GWAS) can include multiple distinct association signals. We sought to identify the molecular basis of multiple association signals for adiponectin, a hormone involved in glucose regulation secreted almost exclusively from adipose tissue, identified in the Metabolic Syndrome in Men (METSIM) study. With GWAS data for 9,262 men, four loci were significantly associated with adiponectin: ADIPOQ, CDH13, IRS1, and PBRM1. We performed stepwise conditional analyses to identify distinct association signals, a subset of which are also nearly independent (lead variant pairwise r2<0.01). Two loci exhibited allelic heterogeneity, ADIPOQ and CDH13. Of seven association signals at the ADIPOQ locus, two signals colocalized with adipose tissue expression quantitative trait loci (eQTLs) for three transcripts: trait-increasing alleles at one signal were associated with increased ADIPOQ and LINC02043, while trait-increasing alleles at the other signal were associated with decreased ADIPOQ-AS1. In reporter assays, adiponectin-increasing alleles at two signals showed corresponding directions of effect on transcriptional activity. Putative mechanisms for the seven ADIPOQ signals include a missense variant (ADIPOQ G90S), a splice variant, a promoter variant, and four enhancer variants. Of two association signals at the CDH13 locus, the first signal consisted of promoter variants, including the lead adipose tissue eQTL variant for CDH13, while a second signal included a distal intron 1 enhancer variant that showed ~2-fold allelic differences in transcriptional reporter activity. Fine-mapping and experimental validation demonstrated that multiple, distinct association signals at these loci can influence multiple transcripts through multiple molecular mechanisms.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Adiponectin GWAS loci harboring extensive allelic heterogeneity exhibit distinct molecular consequences. · full record | OpenQuestion