Common disorders are quantitative traits
By Robert Plomin, C. Haworth, O. Davis. Nature reviews genetics, 2009
722 citations recorded by the source corpus.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/9d9f6f56a0f110c4f3771eda1822f8d08b1043cc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
- Terrie E. Moffitt
- Avshalom Caspi
- Elizabeth T. Cirulli
- Robert Plomin
- Ian J. Deary
- Mika Ala-Korpela
- David Houle
- Lourens J. Waldorp
In Molecular Biology
- Robert Plomin
- Ian J. Deary
- Terrie E. Moffitt
- Avshalom Caspi
- H.L.J. van der Maas
- Elizabeth T. Cirulli
- Lourens J. Waldorp
- Denny Borsboom
Citations in the corpus
- Comorbidity: A network perspective (2010, background): “Just as Cramer et al. highlight the difficulties of psychiatric diagnosis at a phenotypic level, we have argued that, at an etiological level, such common disorders are quantitative traits reflecting multiple underlying dimensions of genetic (and environmental) risk (Plomin et al. 2009).”
- Multiple New Loci Associated with Kidney Function and Chronic Kidney Disease: The CKDGen consortium (2010, neutral): “Common disorders such as CKD may be thought of as the extremes of underlying polygenic quantitative trait”
- Uncovering the roles of rare variants in common disease through whole-genome sequencing (2010, background): “Over the past several years, this view has become less popular, at least with some in the research community, than the theory that common diseases are more strongly influenced by many common gene variants with small effects on ris”
- Phenomics: the next challenge (2010, background): “Although phenotypes are sometimes truly categorical — such as dead or alive — in most cases, the underlying state is quantitativ”
- Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. (2015, background): “This is because of genetic and metabolic complexity, manifested by continuous biological processes and phenomena that neither allow for clear classifications nor accurate predictions with currently available information.(3,81) However, a recent Figure 1.”
- Development and Evaluation of a Genetic Risk Score for Obesity (2013, positive): “With respect to theory, our results are consistent with the hypothesis that genetic risk for obesity is quantitatively distributed and can be operationalized in a GRS (Plomin, Haworth, and Davis 2009).”
- Genetics and Intelligence Differences: Five Special Findings (2014, positive): “This implies that at the level of DNA variation there are no common disorders, only normally distributed quantitative traits 97 .”