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Record W2899670911 · doi:10.1161/circ.133.suppl_1.mp83

Abstract MP83: Exomechip Meta-analysis of 526,508 Individuals From Five Ancestries Identifies Coding Variation in <i>MC4R</i> and <i>KSR2</i> Associated with Body Mass Index

2016· article· en· W2899670911 on OpenAlexaff
Heather M. Highland, Valérie Turcot, Yingchang Lu, Claudia Schurmann, Anne E. Justice, Kristin L. Young, Mariaelisa Graff, Adam E. Locke, Luyu Wang, Petra Lenzini, L. Adrienne Cupples, Timothy M. Frayling, Joel N. Hirschhorn, Guillaume Lettre, Cecilia M. Lindgren, Kari E. North, Ingrid B. Borecki, Ruth J. F. Loos

Bibliographic record

VenueCirculation · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsGenome-wide association studyAlleleGeneticsMedicineBody mass indexGenetic associationMissense mutationSingle-nucleotide polymorphismGeneLocus (genetics)Meta-analysisInternal medicineBiologyGenotypeMutation

Abstract

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Increased body mass index (BMI) increases risk of chronic diseases including heart disease, stroke, and type 2 diabetes (T2D). Through genome-wide association studies (GWAS), 97 genetic variants, mostly common (MAF>5%) and non-coding, have been identified for BMI. To investigate the role of coding variants with putative functional effects (missense, nonsense, splicing, stop gain), we meta-analyzed ExomeChip data of 526,508 individuals from over 110 studies, predominantly of European ancestry. Individual studies performed association analyses using Rvtest or RareMetalWorker; results were subsequently combined in single variant meta-analyses and gene-based tests (SKAT, VT) stratified by ancestry using RareMETALS. Gene-based tests were grouped based on functional annotation and in silico predicted impact on proteins for variants with a MAF<5%. Among the 245,497 variants analyzed, of the 93 loci that reached array-wide significance (P<2E-07); 56 were novel or independent of previously identified BMI loci. This includes low frequency variants in ACHE (rs1799805, p.H353N, p=8.01E-10, EAF=4%, β(SE)=0.032(0.005) SD/allele), HIP1R (rs34149579, p.V67F, p=1.88E-08, EAF=4%, β(SE)=-0.027(0.005) SD/allele) and MC4R (rs13447324, p.Y35X, p=2.37e-11, EAF=0.01%, β(SE)=0.64(0.09) SD/allele). Eight gene-based associations were significant (p<2.5E-06), including GIPR (p=7.17E-09), whose effects were independent of the common GWAS proxy in the gene (rs1800437, p. E354Q, p=7.91E-30, MAF=20%, β(SE)=-0.029(0.003) SD/allele). GIPR is part of the GLP1 pathway responsible for the secretion of postprandial insulin. Other gene-based associations were largely driven by a single variant, such as for KSR2 (p=7.15E-09), RAPGEF3 (p=8.91E-15) and PRKAG1 (p=2.75E-12). Ksr2 knockout mice are obese. Multiple variants in KSR2 have been shown to associate with severe early onset obesity. Mutations in KSR2 disrupt the Raf-MEK-ERK pathway, resulting in impaired fatty acid oxidation and glucose oxidation. RAPGEF3 is involved in the GLP1 pathway and regulates glucose sensitivity of the K ATP channel, which regulates insulin secretion. PRKAG1 is involved in AMPK signaling and has previously been associated with T2D and weight gain on antipsychotic medication. Taken together, by interrogating coding variants in a large sample set, we have identified both additional genes and variants associated with BMI, some of which may be causal.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.012
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.251
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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