ArticleGenetic epidemiology2011
Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.
Article in Genetic epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
77 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Pooled it
- Meta-analysis and field synopsis of genetic variants associated with the risk and severity of acute pancreatitis.BJS open · 2020Pooled it
- Testing of candidate single nucleotide variants associated with paclitaxel neuropathy in the trial NCCTG N08C1 (Alliance).Cancer medicine · 2016Pooled it
- Charting the Phenotypic Landscape of FBN1 Variants in Marfan Syndrome With Ectopia Lentis Through Extreme Phenotype Sampling.Investigative ophthalmology & visual science · 2026Article
- High-Penetrance Rare Variants Underlying Familial Lung Cancer Risk: Insights From Genetic Epidemiology of Lung Cancer Consortium.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026Article
- The biomedical landscape of genomic structural variation in the qatari population.Nature communications · 2026Article
- Identifying Rare Germline Variants Associated with Metastatic Prostate Cancer Through an Extreme Phenotype Study.medRxiv : the preprint server for health sciences · 2025Article
- Perturbations in the neuroactive ligand-receptor interaction and renin angiotensin system pathways are associated with cancer-related cognitive impairment.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025Article
- Article
- Whole Exome-Trio Analysis Reveals Rare Variants Associated with Congenital Pouch Colon.Children (Basel, Switzerland) · 2023Article
- Genome-wide DNA methylation analysis of extreme phenotypes in the identification of novel epigenetic modifications in diabetic retinopathy.Clinical epigenetics · 2022Article
- The heart-brain axis: A proteomics study of meditation on the cardiovascular system of Tibetan Monks.EBioMedicine · 2022Article
- Identification of heritable rare variants associated with early-stage lung adenocarcinoma risk.Translational lung cancer research · 2022Article
- Genomic architecture of phenotypic extremes in a wild cervid.BMC genomics · 2022Article
- Genetic susceptibility loci forFrontiers in immunology · 2022Article
- Combined Effect of a Polygenic Risk Score and Rare Genetic Variants on Prostate Cancer Risk.European urology · 2021Article
- Assessing the relationship between the rumen microbiota and feed efficiency in Nellore steers.Journal of animal science and biotechnology · 2021Article
- Genome-wide association study of patients with a severe major depressive episode treated with electroconvulsive therapy.Molecular psychiatry · 2021Article
- PHACTR1 genetic variability is not critical in small vessel ischemic disease patients and PcomA recruitment in C57BL/6J mice.Scientific reports · 2021Article
- Rare deleterious germline variants and risk of lung cancer.NPJ precision oncology · 2021Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.