ArticleGenetics2015
Nonadditive Effects of Genes in Human Metabolomics.
Article in Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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
17 citing papers in PubMed, 32 citations in OpenAlex.
- Multi-environment GWAS uncovers markers associated to biotic stress response and genotype-by-environment interactions in stone fruit trees.Horticulture research · 2025Article
- DNA Damage Response Pharmacogenomic (DDR_PGx) Score Predicts Response to Chemotherapy Consisting of Gemtuzumab Ozogamicin in Pediatric AML: A Report from the Children's Oncology Group.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
- Causal relationships between serum metabolites and coronary heart disease risk: a mendelian randomization study.Frontiers in genetics · 2025Article
- Almond population genomics and non-additive GWAS reveal new insights into almond dissemination history and candidate genes for nut traits and blooming time.Horticulture research · 2023Article
- Population genomics identifies genetic signatures of carrot domestication and improvement and uncovers the origin of high-carotenoid orange carrots.Nature plants · 2023Article
- Deciphering the genetic basis of male fertility in Italian Brown Swiss dairy cattle.Scientific reports · 2022Article
- Genome-wide variants and polygenic risk scores for cognitive impairment following blood or marrow transplantation.Bone marrow transplantation · 2022Article
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- Disentangling Independent and Mediated Causal Relationships Between Blood Metabolites, Cognitive Factors, and Alzheimer's Disease.Biological psychiatry global open science · 2022Article
- Polygenic Ara-C Response Score Identifies Pediatric Patients With Acute Myeloid Leukemia in Need of Chemotherapy Augmentation.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022Article
- A Heterochromatic Knob Reducing the Flowering Time in Maize.Frontiers in genetics · 2021Article
- Heritability estimates for 361 blood metabolites across 40 genome-wide association studies.Nature communications · 2020Review
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- Article
- Whole-genome scan reveals significant non-additive effects for sire conception rate in Holstein cattle.BMC genetics · 2018Article
- Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018Article
- Genetics of human metabolism: an update.Human molecular genetics · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 6 institutions in 3 countries.
Funding
Abstract
Genome-wide association studies (GWAS) are widely applied to analyze the genetic effects on phenotypes. With the availability of high-throughput technologies for metabolite measurements, GWAS successfully identified loci that affect metabolite concentrations and underlying pathways. In most GWAS, the effect of each SNP on the phenotype is assumed to be additive. Other genetic models such as recessive, dominant, or overdominant were considered only by very few studies. In contrast to this, there are theories that emphasize the relevance of nonadditive effects as a consequence of physiologic mechanisms. This might be especially important for metabolites because these intermediate phenotypes are closer to the underlying pathways than other traits or diseases. In this study we analyzed systematically nonadditive effects on a large panel of serum metabolites and all possible ratios (22,801 total) in a population-based study [Cooperative Health Research in the Region of Augsburg (KORA) F4, N = 1,785]. We applied four different 1-degree-of-freedom (1-df) tests corresponding to an additive, dominant, recessive, and overdominant trait model as well as a genotypic model with two degree-of-freedom (2-df) that allows a more general consideration of genetic effects. Twenty-three loci were found to be genome-wide significantly associated (Bonferroni corrected P ≤ 2.19 × 10(-12)) with at least one metabolite or ratio. For five of them, we show the evidence of nonadditive effects. We replicated 17 loci, including 3 loci with nonadditive effects, in an independent study (TwinsUK, N = 846). In conclusion, we found that most genetic effects on metabolite concentrations and ratios were indeed additive, which verifies the practice of using the additive model for analyzing SNP effects on metabolites.
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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.