Abstract
The goal of this review article is to provide a conceptual based summary of how heritability estimates for complex traits such as obesity are determined and to explore the future directions of research in the heritability field. The target audience are researchers who use heritability data rather than those conducting heritability studies. The article provides an introduction to key concepts critical to understanding heritability studies including: i) definitions of heritability: broad sense versus narrow sense heritability; ii) how data for heritability studies are collected: twin, adoption, family and population- based studies; and iii) analytical techniques: path analysis, structural equations and mixed or regressive models of complex segregation analysis. For each section, a discussion of how the different definitions and methodologies influence heritability estimates is provided. The general limitations of heritability studies are discussed including the issue of “missing heritability” in which heritability estimates are significantly higher than the variance explained by known genetic variants. Potential causes of missing heritability include restriction of many genetic association studies to single nucleotide polymorphisms, gene by gene interactions, epigenetics, and gene by environment interactions. Innovative strategies of accounting for missing heritability including modeling techniques and improved software are discussed.
Keywords: Heritability, Complex traits, Twin studies, Family studies, Path analysis, Missing heritability.
Graphical Abstract
Call for Papers in Thematic Issues
Advanced Computational Algorithms and Artificial Intelligence in Clinical Pharmacogenomics
In the era of personalized medicine, understanding the relationship between genetics and drug response is crucial. This issue delves into innovative methodologies, leveraging deep computational analysis and artificial intelligence, to enhance the field of Clinical Pharmacogenomics. The interdisciplinary approach harnesses the power of advanced high-throughput genotyping technologies, sophisticated computational analysis, ...read more
Applications of Single-cell Sequencing Technology in Reproductive Medicine
Single cell sequencing (SCS) technology utilizes individual cells' genetic material to sequence their genome, transcriptome, and epigenetics at the molecular level. It offers insights into cell heterogeneity and enables the study of limited biological materials. Since its recognition as a valuable technique in 2011, single cell sequencing has yielded numerous ...read more
Big Data in Cancer Research
Cancer is a significant threat to human life and health, remaining a highly aggressive killer. It is a leading cause of death worldwide and represents a crucial medical issue for humanity. However, in the past decade, the effectiveness of new synthetic anticancer agents has not matched the current clinical speculation. ...read more
Current Genomics in Cardiovascular Research
Cardiovascular diseases are the main cause of death in the world, in recent years we have had important advances in the interaction between cardiovascular disease and genomics. In this Research Topic, we intend for researchers to present their results with a focus on basic, translational and clinical investigations associated with ...read more
Related Journals
Related Books
In Vitro Propagation and Secondary Metabolite Production from Medicinal Plants: Current Trends (Part 2)
Micropropagation of Medicinal Plants
Software and Programming Tools in Pharmaceutical Research
Biotechnology and Drug Development for Targeting Human Diseases
In Vitro Propagation and Secondary Metabolite Production from Medicinal Plants: Current Trends (Part 1)
Molecular and Physiological Insights into Plant Stress Tolerance and Applications in Agriculture- Part 2
Micropropagation of Medicinal Plants
Genome Editing in Bacteria (Part 1)
Data Science for Agricultural Innovation and Productivity
Animal Models In Experimental Medicine
22
1
1