ArticleNature communications2021
The impact of non-additive genetic associations on age-related complex diseases.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 6 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
82 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Meta-analysis across six global biobanks identifies recessive coding associations with complex traits and diseases.American journal of human genetics · 2026Pooled it
- Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk.Genome medicine · 2024Pooled it
- X-linked genetic associations in sporadic thoracic aortic dissection.American journal of medical genetics. Part A · 2024Pooled it
- Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.Translational psychiatry · 2024Pooled it
- Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes.Diabetes · 2022Pooled it
- TIGER: The gene expression regulatory variation landscape of human pancreatic islets.Cell reports · 2021Pooled it
- Causal links between gut microbiota, plasma metabolites, and insomnia: Insights from Mendelian randomization.Dialogues in clinical neuroscience · 2026Article
- Different genetic associations of chronic lung diseases and lung cancer risk in European and East Asian populations.Chinese medical journal · 2026Article
- Genetic evidence for a causal role of depression in late-onset Alzheimer disease: A Mendelian randomization study.Medicine · 2026Article
- Exploring the use of machine and deep learning in genome-wide association studies: a comprehensive review.BioData mining · 2026Review
- Investigations on transferability of polygenic risk scores depending on demography and dominance coefficients.HGG advances · 2026Article
- Causal effects among hypertension, osteoporosis, and metabolites: A Mendelian randomization study.Journal of the Chinese Medical Association : JCMA · 2026Article
- Multidimensional analysis of depression and diabetic kidney disease using GBD, NHANES, and MR.iScience · 2026Article
- Identifying genome-by-childhood trauma interactions for depression using a forest-based approach in the UK Biobank and Adolescent Brain Cognitive Development Study.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Heterogeneity in the association of genetic risk for RA and resultant RA phenotypes.Rheumatology (Oxford, England) · 2026Article
- Age-Related Genetic Causal Association Between Asthma and Delirium: A Bidirectional Two-Sample Mendelian Randomization.Brain and behavior · 2026Article
- Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference.Statistics in medicine · 2026Review
- Cost-effective non-additive GWAS across 2329 diseases in 500,349 individuals.Nature communications · 2025Article
- HTRA1/lncRNA HTRA1-AS1 dominates in age-related macular degeneration reticular pseudodrusen genetic risk with no complement involvement.Nature communications · 2025Article
- Exploring Random Forest in Genetic Risk Score Construction.Genetic epidemiology · 2025Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
22 authors.
Funding
Abstract
Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.
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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.