Abstract 048: Association Analyses of up to ∼263,000 Individuals Provide New Insights into the Biology and Genetic Architecture of the Extremes of Anthropometric Traits
Bibliographic record
Abstract
Anthropometric traits have a strong genetic component with heritability estimates between 40–70% for body mass index (BMI) and ∼80% for height; however, established loci only account for a small fraction (1–10%) of the phenotypic variance of these complex traits. It has been hypothesized that the extremes of the distributions of these traits are enriched for genetic loci and may have a distinct genetic architecture compared to the general population. To explore the genetic contribution of the extremes (defined as the upper and lower 5th percentile) of BMI, height, and waist-hip ratio [WHR] adjusted for BMI and clinical classes of obesity (including overweight and obesity classes I, II, and III), we conducted meta-analyses of ∼2.8 million SNPs from 49 genome-wide association studies of European ancestry totaling from 4,774 cases and 5,481 controls (extreme WHR) to 93,015 cases and 65,840 controls (overweight) for these traits. The most promising loci from each meta-analysis (P<5 x 10 −6 ) were taken forward for replication into up to 65,332 cases and 39,294 controls. In meta-analyses of the combined stages, we observed genome-wide significant associations (P<5 x 10 −8 ) for 191 loci (extreme BMI, height and WHR: 10, 96 and 2 loci, respectively; overweight and obesity classes I, II, and III: 25, 33, 24 and 1 loci, respectively). Out of these 191 loci, we identified 9 novel loci that have not been previously associated with anthropometric traits when studying the whole distributions (P<5 x 10 −8 ), including three loci for extreme height ( ZNF36, H6PD , RSRC1 ), three for obesity class II ( OLFM4 , HS6ST3 , AK5/ZZZ3 ), two for obesity class I ( GNAI3/MIR197/GNAT2, HNF4G ), and two for overweight ( RPTOR, HNF4G ). Several loci for obesity were located near genes expressed primarily in the brain (e.g. CACNA1D, AK5 ), suggesting a neuronal influence, whereas the loci for overweight were near genes involved in other processes, such as mTOR signaling (e.g. RPTOR ). All of the novel loci discovered for the extremes and obesity classes were nominally associated with the trait as a continuous measure in the general population (N = 123,865) but at a lesser significance level (P range: 0.003 – 1.4x10 −5 ). A polygenetic risk score including all independent SNPs associated with BMI (at different P-value thresholds) revealed that significantly more of the variance was explained for the extremes of BMI and obesity class II, than for BMI as a continuous measure in the population (variance explained, 20%, 10% and 5%, respectively), suggesting a greater genetic influence on the extremes. Investigations are underway to evaluate haplotypes and additional signals at known BMI and height loci in the extreme samples to explore allelic heterogeneity. In conclusion, this study identifies additional loci and provides novel insights into the genetic architecture of the extremes of anthropometric traits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".