Tackling missing heritability by use of an optimum curve: A systematic review and meta-analysis
Sleeswijk, Anneke Wegener; Heijungs, Reinout; Durston, Sarah
(2019) International journal of molecular sciences, volume 20, issue 20
(Article)
Abstract
Missing heritability is a common problem in psychiatry that impedes precision medicine approaches to autism and other heritable complex disorders. This proof-of-concept study uses a systematic review and meta-analysis of the association between variants of the serotonin transporter promoter (5-HTTLPR) and autism to explore the hypothesis that some missing heritability
... read more
can be explained using an optimum curve. A systematic literature search was performed to identify transmission disequilibrium tests on the short/long (S/L) 5-HTTLPR polymorphism in relation to autism. We analysed five American, seven European, four Asian and two American/European samples. We found no transmission preference in the joint samples and in Europe, preferential transmission of S in America and preferential transmission of L in Asia. Heritability will be underestimated or missed in genetic association studies if two alternative genetic variants are associated with the same disorder in different subsets of a sample. An optimum curve, relating a multifactorial biological variable that incorporates genes and environment to a score for a human trait, such as social competence, can explain this. We suggest that variants of functionally related genes will sometimes appear in fixed combinations at both sides of an optimum curve and propose that future association studies should account for such combinations.
show less
Download/Full Text
Keywords: 5-HTTLPR polymorphism, Autism, Context-dependent risk variants, Genetic association, Inverted U, Meta-analysis, Missing heritability, Multifactorial variable, Optimum curve, Systematic review, Catalysis, Molecular Biology, Spectroscopy, Computer Science Applications, Physical and Theoretical Chemistry, Organic Chemistry, Inorganic Chemistry
ISSN: 1661-6596
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Note: Funding Information: We thank Franca Guerini (IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy), Erik Mulder (GGZ Drenthe, Assen, The Netherlands), Astrid Vicente (University of Lisboa, Lisbon, Portugal), and Kenji Yamamoto (Tokai University, Kanagawa, Japan) for answering our questions an providing us with helpful information about their studies. Publisher Copyright: © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
(Peer reviewed)