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Meta-analysis is the statistical combination of the results of multiple studies addressing a similar research question. An important part of this method involves computing an effect size across all of the studies; this involves extracting effect sizes and variance measures from various studies. Meta-analyses are integral in supporting research grant proposals, shaping treatment guidelines, and influencing health policies. They are also pivotal in summarizing existing research to guide future studies, thereby cementing their role as a fundamental methodology in metascience. Meta-analyses are often, but not always, important components of a systematic review procedure. For instance, a meta-analysis may be conducted on several clinical trials of a medical treatment, in an effort to obtain a better understanding of how well the treatment works.
Heritability is a statistic used in the fields of breeding and genetics that estimates the degree of variation in a phenotypic trait in a population that is due to genetic variation between individuals in that population. The concept of heritability can be expressed in the form of the following question: "What is the proportion of the variation in a given trait within a population that is not explained by the environment or random chance?"
Twin studies are studies conducted on identical or fraternal twins. They aim to reveal the importance of environmental and genetic influences for traits, phenotypes, and disorders. Twin research is considered a key tool in behavioral genetics and in related fields, from biology to psychology. Twin studies are part of the broader methodology used in behavior genetics, which uses all data that are genetically informative – siblings studies, adoption studies, pedigree, etc. These studies have been used to track traits ranging from personal behavior to the presentation of severe mental illnesses such as schizophrenia.
Genetic variation is the difference in DNA among individuals or the differences between populations among the same species. The multiple sources of genetic variation include mutation and genetic recombination. Mutations are the ultimate sources of genetic variation, but other mechanisms, such as genetic drift, contribute to it, as well.
Gene–environment interaction is when two different genotypes respond to environmental variation in different ways. A norm of reaction is a graph that shows the relationship between genes and environmental factors when phenotypic differences are continuous. They can help illustrate GxE interactions. When the norm of reaction is not parallel, as shown in the figure below, there is a gene by environment interaction. This indicates that each genotype responds to environmental variation in a different way. Environmental variation can be physical, chemical, biological, behavior patterns or life events.
The heritability of autism is the proportion of differences in expression of autism that can be explained by genetic variation; if the heritability of a condition is high, then the condition is considered to be primarily genetic. Autism has a strong genetic basis. Although the genetics of autism are complex, autism spectrum disorder (ASD) is explained more by multigene effects than by rare mutations with large effects.
Neil Risch is an American human geneticist and professor at the University of California, San Francisco (UCSF). Risch is the Lamond Family Foundation Distinguished Professor in Human Genetics, Founding Director of the Institute for Human Genetics, and Professor of Epidemiology and Biostatistics at UCSF. He specializes in statistical genetics, genetic epidemiology and population genetics.
The study of height and intelligence examines correlations between human height and human intelligence. Some epidemiological research on the subject has shown that there is a small but statistically significant positive correlation between height and intelligence after controlling for socioeconomic class and parental education. The cited study, however, does not draw any conclusions about height and intelligence, but rather suggests "a continuing effect of post-natal growth on childhood cognition beyond the age of 9 years." This correlation arises in both the developed and developing world and persists across age groups. An individual's taller stature has been attributed to higher economic status, which often translates to a higher quality of nutrition. This correlation, however, can be inverted to characterize one's socioeconomic status as a consequence of stature, where shorter stature can attract discrimination that affects many factors, among them employment, and treatment by educators. One such theory argues that since height strongly correlates with white and gray matter volume, it may act as a biomarker for cerebral development which itself mediates intelligence. Competing explanations include that certain genetic factors may influence both height and intelligence, or that both height and intelligence may be affected in similar ways by adverse environmental exposures during development. Measurements of the total surface area and mean thickness of the cortical grey matter using a magnetic resonance imaging (MRI) revealed that the height of individuals had a positive correlation with the total cortical surface area. This supports the idea that genes that influence height also influence total surface area of the brain, which in turn influences intelligence, resulting in the correlation. Other explanations further qualify the positive correlation between height and intelligence, suggesting that because the correlation becomes weaker with higher socioeconomic class and education level, environmental factors could partially override any genetic factors affecting both characteristics.
Heritability is the proportion of variance caused by genetic factors of a specific trait in a population. Falconer's formula is a mathematical formula that is used in twin studies to estimate the relative contribution of genetic vs. environmental factors to variation in a particular trait based on the difference between twin correlations. Statistical models for heritability commonly include an error that will absorb phenotypic variation that cannot be described by genetics when analyzed. These are unique subject-specific influences on a trait. Falconer's formula was first proposed by the Scottish geneticist Douglas Falconer.
In multivariate quantitative genetics, a genetic correlation is the proportion of variance that two traits share due to genetic causes, the correlation between the genetic influences on a trait and the genetic influences on a different trait estimating the degree of pleiotropy or causal overlap. A genetic correlation of 0 implies that the genetic effects on one trait are independent of the other, while a correlation of 1 implies that all of the genetic influences on the two traits are identical. The bivariate genetic correlation can be generalized to inferring genetic latent variable factors across > 2 traits using factor analysis. Genetic correlation models were introduced into behavioral genetics in the 1970s–1980s.
Behavioural genetics, also referred to as behaviour genetics, is a field of scientific research that uses genetic methods to investigate the nature and origins of individual differences in behaviour. While the name "behavioural genetics" connotes a focus on genetic influences, the field broadly investigates the extent to which genetic and environmental factors influence individual differences, and the development of research designs that can remove the confounding of genes and environment. Behavioural genetics was founded as a scientific discipline by Francis Galton in the late 19th century, only to be discredited through association with eugenics movements before and during World War II. In the latter half of the 20th century, the field saw renewed prominence with research on inheritance of behaviour and mental illness in humans, as well as research on genetically informative model organisms through selective breeding and crosses. In the late 20th and early 21st centuries, technological advances in molecular genetics made it possible to measure and modify the genome directly. This led to major advances in model organism research and in human studies, leading to new scientific discoveries.
In statistical genetics, inclusive composite interval mapping (ICIM) has been proposed as an approach to QTL mapping for populations derived from bi-parental crosses. QTL mapping is based on genetic linkage map and phenotypic data to attempt to locate individual genetic factors on chromosomes and to estimate their genetic effects.
The missing heritability problem is the fact that single genetic variations cannot account for much of the heritability of diseases, behaviors, and other phenotypes. This is a problem that has significant implications for medicine, since a person's susceptibility to disease may depend more on the combined effect of all the genes in the background than on the disease genes in the foreground, or the role of genes may have been severely overestimated.
"Envirome" is a concept that relates the core of environmental conditions with the successful biological performance of living beings. This concept was created in genetic epidemiology, in which an envirome is defined as the total set of environmental factors, both present, and past, that affect the state, and in particular the disease state, of an organism. The study of the envirome and its effects is termed enviromics. The term was first coined in the field of psychiatric epidemiology by J.C. Anthony in 1995. More recently, use of the term has been extended to the cellular domain, where cell functional enviromics studies both the genome and envirome from a systems biology perspective. In plants, enviromics is directly related to complex ecophysiology, in which the wide environment of the plants, into an omics scale, can be dissected and understood as a mosaic of possible growing factors and the balance of diverse resources available. In ecology, this concept can be related to the Shelford's law of tolerance. The enviromics is conceived as a pillar of the Modern Plant Breeding, capable to connect the design and development of breeding goals concealing it with the agronomic targets for a climate-smart agriculture. It also has the ability to bridge the knowledge gaps between the different levels of systems biology and phenomics in the context of Gene–environment interaction.
Genetic variance is a concept outlined by the English biologist and statistician Ronald Fisher in his fundamental theorem of natural selection. In his 1930 book The Genetical Theory of Natural Selection, Fisher postulates that the rate of change of biological fitness can be calculated by the genetic variance of the fitness itself. Fisher tried to give a statistical formula about how the change of fitness in a population can be attributed to changes in the allele frequency. Fisher made no restrictive assumptions in his formula concerning fitness parameters, mate choices or the number of alleles and loci involved.
Family resemblance refers to physical similarities shared between close relatives, especially between parents and children and between siblings. In psychology, the similarities of personality are also observed.
In behavioural genetics, DeFries–Fulker (DF) regression, also sometimes called DeFries–Fulker extremes analysis, is a type of multiple regression analysis designed for estimating the magnitude of genetic and environmental effects in twin studies. It is named after John C. DeFries and David Fulker, who first proposed it in 1985. It was originally developed to assess heritability of reading disability in twin studies, but it has since been used to assess the heritability of other cognitive traits, and has also been applied to non-twin methodologies.
The infinitesimal model, also known as the polygenic model, is a widely used statistical model in quantitative genetics and in genome-wide association studies. Originally developed in 1918 by Ronald Fisher, it is based on the idea that variation in a quantitative trait is influenced by an infinitely large number of genes, each of which makes an infinitely small (infinitesimal) contribution to the phenotype, as well as by environmental factors. In "The Correlation between Relatives on the Supposition of Mendelian Inheritance", the original 1918 paper introducing the model, Fisher showed that if a trait is polygenic, "then the random sampling of alleles at each gene produces a continuous, normally distributed phenotype in the population". However, the model does not necessarily imply that the trait must be normally distributed, only that its genetic component will be so around the average of that of the individual's parents. The model served to reconcile Mendelian genetics with the continuous distribution of quantitative traits documented by Francis Galton.
Personality traits are patterns of thoughts, feelings and behaviors that reflect the tendency to respond in certain ways under certain circumstances.
In quantitative genetics, QST is a statistic intended to measure the degree of genetic differentiation among populations with regard to a quantitative trait. It was developed by Ken Spitze in 1993. Its name reflects that QST was intended to be analogous to the fixation index for a single genetic locus (FST). QST is often compared with FST of neutral loci to test if variation in a quantitative trait is a result of divergent selection or genetic drift, an analysis known as QST–FST comparisons.
References
- ↑ Germine, Laura; Russell, Richard; Bronstad, P. Matthew; Blokland, Gabriëlla A.M.; Smoller, Jordan W.; Kwok, Holum; Anthony, Samuel E.; Nakayama, Ken; Rhodes, Gillian (October 2015). "Individual Aesthetic Preferences for Faces Are Shaped Mostly by Environments, Not Genes". Current Biology. 25 (20): 2684–2689. Bibcode:2015CBio...25.2684G. doi:10.1016/j.cub.2015.08.048. ISSN 0960-9822. PMC 4629915 . PMID 26441352.
- ↑ Maes, Hermine H. (2005-10-15). ACE Model. Chichester, UK: John Wiley & Sons, Ltd. doi:10.1002/0470013192.bsa002. ISBN 978-0470860809.
{{cite encyclopedia}}:|journal=ignored (help) - 1 2 3 Kohler, Hans-Peter; Behrman, Jere R.; Schnittker, Jason (2011). "Social science methods for twins data: integrating causality, endowments, and heritability". Biodemography and Social Biology. 57 (1): 88–141. doi:10.1080/19485565.2011.580619. ISSN 1948-5565. PMC 3158495 . PMID 21845929.
- ↑ Beauchamp, Jonathan P.; Cesarini, David; Johannesson, Magnus; Lindqvist, Erik; Apicella, Coren (2010-07-06). "On the sources of the height–intelligence correlation: New insights from a bivariate ACE model with assortative mating". Behavior Genetics. 41 (2): 242–252. doi:10.1007/s10519-010-9376-7. ISSN 0001-8244. PMC 3044837 . PMID 20603722.
- ↑ Lawlor, Debbie A.; Lawlor, Deborah A.; Mishra, Gita D. (2009-04-02). Family Matters: Designing, Analysing and Understanding Family Based Studies in Life Course Epidemiology. OUP Oxford. pp. 252–3. ISBN 9780199231034.
- ↑ Wang, Xueqin; Guo, Xiaobo; He, Mingguang; Zhang, Heping (2011-02-09). "Statistical Inference in Mixed Models and Analysis of Twin and Family Data". Biometrics. 67 (3): 987–995. doi:10.1111/j.1541-0420.2010.01548.x. ISSN 0006-341X. PMC 3129472 . PMID 21306354.
