Tag Archives: quantitative genetics

Five Fundamental Gaps In Nature-Nurture Science

Difficulties identifying causally relevant genetic variants underlying patterns of human variation have been given competing interpretations. The debate is illuminated in this article by drawing attention to the issue of underlying heterogeneity—the possibility that genetic and environmental factors or entities underlying a trait are heterogeneous—as well as four other fundamental gaps in the methods and interpretation of classical quantitative genetics:
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Heterogeneity, not randomness, sets challenges for quantitative genetics and epidemiology: A response to Davey Smith’s “gloomy prospect”

Social epidemiologist Davey Smith (2011) argues that epidemiologists should accept a gloomy prospect: considerable randomness at the individual level means that they should keep their focus on modifiable causes of disease at the population level. The difficulty epidemiology has had in moving from significant population-level risk factors to improved prediction of cases at an individual level is analogous to the lack of success in the search for systematic aspects of the non-shared environmental influences that human quantitative genetics claims overshadow common environmental influences (e.g., the family’s socioeconomic status which siblings have in common). This article responds to the argument and analogy, aiming to draw three audiences—social epidemiologists, human quantitative geneticists, and philosophers of science—into a shared discussion that centers not on randomness, but on heterogeneity in various forms.
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What to do if we think that researchers have overlooked a significant issue for 100 years?

Practice run of a talk to philosophers of biology & biologists, March 2016 Continue reading

Nature-Nurture? No (now available)

Almost every day we hear that some trait “has a strong genetic basis” or “of course it is a combination of genes and environment, but the hereditary component is sizeable.”  To say No to Nature-Nurture is to reject this relative weighting of heredity and environment.  This book shows that partitioning the variation observed for any trait into a heritability fraction and other components provides little clear or useful information about the genetic and environmental influences.

A key move this book makes is to distill the issues into eight conceptual and methodological gaps that need attention. Some gaps should be kept open; others should be bridged—or the difficulty of doing so should be conceded. Previous researchers and commentators have either not acknowledged all the gaps, not developed the appropriate responses, or not consistently sustained their responses.  Indeed, despite decades of contributions to nature-nurture debates, some fundamental problems in the relevant sciences have been overlooked.

When all the gaps are given proper attention, the limitations of human heritability studies become clear.  They do not provide a reliable basis for genetic research that seeks to identify the molecular variants associated with trait variation, for assertions that genetic differences in many traits come, over people’s lifetimes, to eclipse environmental differences and that the search for environmental influences and corresponding social policies is unwarranted, or for sociological research that focuses on differences in the experiences of members of the same family.

Saying No is saying Yes to interesting scientific and policy questions about heredity and variation.  To move beyond the gaps is to make space for fresh inquiries in a range of areas: in various sciences, from genetics and molecular biology to epidemiology and agricultural breeding; in history, philosophy, sociology, and politics of the life and social sciences; and in engagement of the public in discussion of developments in science.

Available as paperback through online retailers and as pdf

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The Pumping Station

Almost every day we hear that some trait “has a strong genetic basis” or “of course it is a combination of genes and environment, but the hereditary component is sizeable.”  To say No to Nature-Nurture is to reject this relative weighting of heredity and environment.  This book shows that partitioning the variation observed for any trait into a heritability fraction and other components provides little clear or useful information about the genetic and environmental influences.

A key move this book makes is to distill the issues into eight conceptual and methodological gaps that need attention. Some gaps should be kept open; others should be bridged—or the difficulty of doing so should be conceded. Previous researchers and commentators have either not acknowledged all the gaps, not developed the appropriate responses, or not consistently sustained their responses.  Indeed, despite decades of contributions to nature-nurture debates, some fundamental problems in the relevant…

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Implausible, given decades of debate among methodologically sophisticated scholars, that some fundamental problems in quantitative genetic estimation have been overlooked?

In recent publications (Taylor 2010, 2012) I show how the estimates made in human quantitative genetics are unreliable and typical interpretations, including interpretation of non-shared environmental influences, are unjustified.  Some readers may deem it implausible, given decades of debate among methodologically sophisticated scholars, that some fundamental problems in quantitative genetic estimation have been overlooked (Kendler 2005).  With a view to moving at least some skeptical readers to consider the full set of problems and conceptual themes I present, let me sketch the background that allows me to see the study of heredity and variation differently from most researchers and philosophers of science who have addressed quantitative genetics.

My initial research work in the mid-1970s involved the statistical analysis of large plant breeding trials, in which many cultivated varieties would be tested in each of many locations around the world.  A first step in the analysis was to partition the variation in a given trait, say, yield of wheat plants, into components related to the averages or means of the varieties (across all locations), the means of the locations (across all varieties), and so on.  (Indeed, agricultural breeding was where partitioning of variation and measuring heritability originated.)  The challenge for the plant breeders with whom I worked was to go beyond the partitioning and hypothesize what it was about any variety that led to its pattern of response across locations and what it was about any location that led to the varieties’ responses in that location compared to others.  Knowing what aspects of, say, the pedigree of the variety or of the environment conditions in the location could inform subsequent breeding or cultivation decisions.  Yet, hypothesis generation was not easy even though we had large and complete data sets to work from.  A lesson from that experience was that the limits to hypothesizing about genetic and environmental factors must be even greater when researchers partition variation for human traits.  In human studies any genetically-defined type is, at best, replicated twice—as identical twins—and different genetic types cannot be systematically raised across the same range of “locations”—families, socio-economic conditions, and so on.

Fast forward to a decade ago: I was learning about three disparate areas of quantitative research that attempt to make sense of the complexity of biological and social factors that build on each other in the development of the given trait over the life course (Taylor 2004).  I was impressed by what had been accomplished, but had some reservations about the models used in one of the areas, namely, Dickens and Flynn’s (2001) attempt to resolve the IQ paradox, in which researchers find large generation-to-generation advances in IQ test scores even though the trait is held to have high heritability.  I explained my reservations to Dickens, digested his responses, and explained my reservations about his subsequent responses.  In the course of this I found myself digger deeper into the conceptual foundations of heritability estimation and partitioning of variation.  In order to present a picture that differed from what Dickens, Flynn, and others accepted without second thought, I was explicating first principles, not disputing specialized models or mathematics. Making extensive use of perspectives and examples from the earlier plant breeding research, my exposition took a pedagogical style (Taylor 2006, 2007, 2010).

Meanwhile, my investigation continued of the other two areas—life events and difficulties research (Brown and Harris 1989) and developmental origins of chronic diseases (Barker 1998).  Barker’s work led me to life-course epidemiology (Kuh and Ben-Shlomo 2004), so I spent time with Ben-Shlomo and the active social epidemiology research group at Bristol University.  Davey Smith is a leading figure in that group and co-edits the International Journal of Epidemiology based at Bristol.  While visiting in 2007 I gave a talk on “new and old debates about genes and environment,” which touched on some of the questions about heterogeneity raised in this article.  Davey Smith’s spoken response was along the lines of his subsequent “gloomy prospect” article: epidemiologists have to accept considerable randomness at the individual level and keep the focus on modifiable causes of disease at the population level.  In his ensuing article, Davey Smith (2011) links this perspective to claims from quantitative genetics, thus providing me an opportunity to address social epidemiologists and human quantitative geneticists at the same time as I respond to his account.  In an as-yet-unpublished article bringing my interest in heterogeneity to the attention of those audiences, I extend the pedagogical style and first-principles emphasis of the other recent work and thereby speaks to philosophers of science.  My contribution to philosophy takes the form, however, of articulating conceptual themes, not dissecting specific cases on empirical, analytical, bioethical or policy grounds.  The expository approach reflects the background reviewed here, with its roots in plant breeding trials, as well as the idea that contributing to the conceptual toolbox of readers will prepare them to make their own contributions to wider discussion of heredity, variation, and heterogeneity.

References

Barker, D. J. P. (1998). Mothers, Babies, and Health in Later Life. Edinburgh: Churchill Livingstone.

Brown, G. W., & Harris, T. O. (Eds.) (1989). Life Events and Illness. New York: Guilford Press.

Davey Smith, G. (2011). Epidemiology, epigenetics and the ‘Gloomy Prospect’: embracing randomness in population health research and practice. International Journal of  Epidemiology, 40, 537-562.

Dickens, W. T., & Flynn, J. R. (2001). Heritability estimates versus large environmental effects: The IQ paradox resolved. Psychological review, 108, 346-369.

Kendler, K. S. (2005). Reply to J. Joseph, Research Paradigms of Psychiatric Genetics. American Journal of Psychiatry, 162, 1985-1986.

Kuh, D., & Ben-Shlomo, Y. (Eds.) (2004). A Life Course Approach to Chronic Disease Epidemiology. Oxford: Oxford University Press.

Taylor, P. J. (2004). What can we do? — Moving debates over genetic determinism in new directions. Science as Culture, 13, 331-355.

Taylor, P. J. (2006). Heritability and heterogeneity: On the limited relevance of heritability in investigating genetic and environmental factors. Biological Theory: Integrating Development, Evolution and Cognition, 1, 150-164.

Taylor, P. J. (2007). The Unreliability of High Human Heritability Estimates and Small Shared Effects of Growing Up in the Same Family Biological Theory: Integrating Development, Evolution and Cognition, 2, 387-397.

Taylor, P. J. (2010). Three puzzles and eight gaps:  What heritability studies and critical commentaries have not paid enough attention to. Biology & Philosophy, 25, 1-31.

Taylor, P. J. (2012). A gene-free formulation of classical quantitative genetics used to examine results and interpretations under three standard assumptions. Acta Biotheoretica, 60, 357-378.

Nature-Nurture? No! (an overview of a book)

Nature-Nurture? No:  Moving the Sciences of Variation and Heredity Beyond the Gaps

Almost every day we hear that some trait “has a strong genetic basis” or “of course it is a combination of genes and environment, but the hereditary component is sizeable.” To say No to Nature-Nurture is to reject this relative weighting of heredity and environment. Continue reading

Heritability, heterogeneity, and group differences

Idea: As conventionally interpreted, heritability indicates the fraction of variation in a trait associated with “genetic differences.” A high value indicates a strong genetic contribution to the trait and “makes the trait a potentially worthwhile candidate for molecular research” that might identify the specific genetic factors involved. I contest the conventional interpretation and contend that there is nothing reliable that anyone can do on the basis of estimates of heritability for human traits. While some have moved their focus to cases in which measurable genetic and environmental factors are involved, others see the need to bring genetics into the explanation of differences among the averages for groups, especially racial groups.

a. Heritability & critique
Heritability is a quantity derived from analysis of variation in traits of humans, other animals, or plants in ways that take account of the genealogical relatedness of the individuals whose traits are observed. Such “quantitative genetic” analysis does not require any knowledge of the genes or “measurable genetic factors” involved.
Turkheimer is “on the left” of behavioral genetics, being much less gung ho about the implications of its findings. Here he gives a clear overview of what the field has shown.
Plomin articulates the confident consensus of behavior genetics, namely, that they’ve debunked the supposed environmentalist orthodoxy in social science that says that everything is social and have established a basis for connecting with molecular genetics to identify the actual genetic factors.
Rutter, a senior psychological researcher (who once worked with Brown on social determinants of mental illness), tries to moderate the “polarizing claims” and “unwarranted extrapolations.”
Taylor 2010 casts doubt on the findings that underlie both Turkheimer and Plomin’s articles by exposing problems with the concepts and methods used to arrive at those findings. Taylor ends with a nudge towards methods that use measured genetic factors as well as measured environmental factors (the latter being the staple of social epidemiology).

b. Interaction of measured genes and measured environments
Moffitt 2005 provides a review of what’s involved in trying to identify interactions between measured genetic and environmental factors. (Use Taylor 2010 to get clear about the difference between this kind of interaction and the classical genotype x environment interaction in quantitative genetics.) Caspi 2002 is one of two 2002 papers that caused a lot of splash. Davey-Smith picks up on the current consensus that the 2002 studies have been hard to replicate and invokes Mendelian randomization as a way to strengthen causal inference about interactions between measured genetic and environmental factors.

c. Data & models about heritability & change (or lack of it)
Dickens 2001 provides a resolution of the paradox that heritability of IQ test scores is reported to be high, but there has been a large increase in average IQ test scores from one generation to the next. We know that genes haven’t changed from one generation to the next, so Dickens’ account is also exposing a flaw in the logic that because heritability of IQ test scores is high within racially defined groups and because there is a large difference in average IQ test scores between whites and blacks, genetic factors are probably involved in that difference.
Rushton 2005 however thinks that 30 years of research has validated that idea.
Taylor 2010 refers to Dickens 2001, but gives a somewhat different spin on its implications.

(This post continues a series laying out a sequence of basic ideas in thinking like epidemiologists, especially epidemiologists who pay attention to possible social influences on the development and unequal distribution of diseases and behaviors in populations [see first post in series and contribute to open-source curriculum http://bit.ly/EpiContribute].)

References

Caspi, A., J. McClay, et al. (2002). “Role of Genotype in the Cycle of Violence in Maltreated Children.” Science 297(5582): 851-854.
Davey-Smith, G. (2009). “Mendelian randomization for strengthening causal inference in observational studies: Application to gene by environment interaction.” Perspectives on Psychological Science, in press.
Dickens, W. T. and J. R. Flynn (2001). “Heritability estimates versus large environmental effects: The IQ paradox resolved.” Psychological Review 108(2): 346-369.
Moffitt, T. E., A. Caspi, et al. (2005). “Strategy for investigating interactions between measured genes and measured environments.” Archives of General Psychiatry 62(5): 473-481.
Plomin, R. and K. Asbury (2006). “Nature and Nurture: Genetic and Environmental Influences on Behavior.” The Annals of the American Academy of Political and Social Science 600(1): 86-98.
Rushton, J. P. and A. R. Jensen (2005). “Thirty years of research on race differences in cognitive ability.” Psychology, Public Policy, and Law 11: 235-294.
Rutter, M. (2002). “Nature, nurture, and development: From evangelism through science toward policy and practice.” Child Development 73(1): 1-21.
Taylor, P. J. (2010). “Three puzzles and eight gaps: What heritability studies and critical commentaries have not paid enough attention to.” Biology & Philosophy, 25:1-31. (DOI 10.1007/s10539-009-9174-x).
Turkheimer, E. (2000). “Three laws of behavior genetics and what they mean.” Current Directions in Psychological Science 9(5): 160-164.