ArticleAmerican journal of human genetics2019
Making the Most of Clumping and Thresholding for Polygenic Scores.
Article in American journal of human genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06529744 (Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling), which is not on this map. Cited by 137 papers, 3 of them syntheses that pooled it.
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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.
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.
Improving Prognostic Confidence in Neurodegenerative Diseases Causing Dementia Using Peripheral Biomarkers and Integrative Modeling
Who cites it
137 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Discovery and prioritization of genetic determinants of kidney function in 297,355 individuals from Taiwan and Japan.Nature communications · 2024Pooled it
- Genome-wide association study identifies four pan-ancestry loci for suicidal ideation in the Million Veteran Program.PLoS genetics · 2023Pooled it
- Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans.JAMA psychiatry · 2023Pooled it
- Longitudinal infection trajectories and biological aging acceleration in adults: a prospective cohort study.GeroScience · 2026Article
- The Relationship Between Polygenic Risk of Depression and Regional Brain Atrophy in Older Adults.International journal of geriatric psychiatry · 2026Article
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- Identifying sex-specific genetic effects across 733 traits in UK biobank.BMC genomics · 2026Article
- An efficient LASSO framework for admixture-aware polygenic scores.HGG advances · 2026Article
- Selphi, a tool for improving genotype imputation accuracy.Scientific reports · 2026Article
- Simultaneous Assessment of Genetic and Epigenetic Contributions to the Plasma Lipid Levels with Respect to Cardiovascular Risk.Journal of atherosclerosis and thrombosis · 2026Article
- Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.Chinese medical journal · 2026Article
- Widespread and Biologically Driven Sex Disparities in Polygenic Risk Prediction Across Complex Traits.Research square · 2026Article
- Integrating common and rare variants improves polygenic risk prediction across diverse populations.Nature communications · 2026Article
- Evaluating Individual Level Performance of Polygenic Risk Scores Using Early Onset High Genetic Risk Coronary Artery Disease as a Benchmark.medRxiv : the preprint server for health sciences · 2026Article
- Age-stratified genomic analyses reveal population-specific genetic determinants of exceptional longevity in Taiwan.GeroScience · 2026Article
- Genetically Simulated GLP-1 Receptor Agonism and Cerebral Small Vessel Disease.Neurology. Genetics · 2026Article
- Improved polygenic risk prediction for alzheimer's disease and related dementias using deep learning: age and APOE-stratified analysis.Alzheimer's research & therapy · 2026Article
- Cross-trait genomic modeling reveals the polygenic architecture and systemic impact of MASLD.Science advances · 2026Article
- Performance of different polygenic risk scores for breast cancer risk prediction: in-depth evaluations across large UK and Australian cohorts.European journal of human genetics : EJHG · 2026Article
77 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
Abstract
Polygenic prediction has the potential to contribute to precision medicine. Clumping and thresholding (C+T) is a widely used method to derive polygenic scores. When using C+T, several p value thresholds are tested to maximize predictive ability of the derived polygenic scores. Along with this p value threshold, we propose to tune three other hyper-parameters for C+T. We implement an efficient way to derive thousands of different C+T scores corresponding to a grid over four hyper-parameters. For example, it takes a few hours to derive 123K different C+T scores for 300K individuals and 1M variants using 16 physical cores. We find that optimizing over these four hyper-parameters improves the predictive performance of C+T in both simulations and real data applications as compared to tuning only the p value threshold. A particularly large increase can be noted when predicting depression status, from an AUC of 0.557 (95% CI: [0.544-0.569]) when tuning only the p value threshold to an AUC of 0.592 (95% CI: [0.580-0.604]) when tuning all four hyper-parameters we propose for C+T. We further propose stacked clumping and thresholding (SCT), a polygenic score that results from stacking all derived C+T scores. Instead of choosing one set of hyper-parameters that maximizes prediction in some training set, SCT learns an optimal linear combination of all C+T scores by using an efficient penalized regression. We apply SCT to eight different case-control diseases in the UK biobank data and find that SCT substantially improves prediction accuracy with an average AUC increase of 0.035 over standard C+T.
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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.