| Title: | Improving accuracy in genome-wide association studies: a two-step approach for handling below limit of detection biomarker measurements |
| Journal: | NAR Genomics and Bioinformatics |
| Published: | 7 Oct 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41480591/ |
| DOI: | https://doi.org/10.1093/nargab/lqaf201 |
Publication 19262
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Abstract
Advances in high-throughput technologies enable large-scale studies on genomics and molecular phenotypes. However, the trade-off between quality and quantity reduces assay sensitivity, and several measurements in large-scale proteomics and metabolomics analytes fall below the limit of detection (LOD). If not properly addressed, this may introduce bias in effect estimates. To address this, we conducted a simulation study to evaluate the performance of linear, Tobit, Cox, and logistic modeling in the presence of below-LOD measurements in genome-wide association studies. We identified the optimal strategy as a two-step Linear-Tobit scheme, including rapid screening with linear regression followed by refinement with Tobit regression to retrieve accurate effect estimates. This higher accuracy helps mitigate a 1.3-fold and 2.7-fold inflation in causal estimates in a Mendelian randomization (MR) study, which would otherwise be present with 50% and 90% values below LOD. Validation through case studies on estradiol and testosterone levels in the UK Biobank confirmed the simulation results across subgroups with varying proportions of below-LOD measurements. The Linear-Tobit scheme offers optimal detection power and efficiency, with a focus on its applicability to biobank-scale datasets and accuracy in effect estimates to mitigate bias in downstream applications such as MR and polygenic risk scores.</p>
9 Keywords
- Biomarkers
- Computer Simulation
- Estradiol
- Genome-Wide Association Study
- Humans
- Limit of Detection
- Linear Models
- Mendelian Randomization Analysis
- Testosterone
3 Authors
- Yaqi A Deng
- Torgny Karlsson
- Åsa Johansson
1 Application
| Application ID | Title |
|---|---|
| 41143 | Effects of diet and lifestyle, and their interactions with genetic variants, on our health |
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