Changing Science in Heterogeneous Environments

Levins’ career was a series of explorations of complexity in many and diverse settings. One aspect of complexity, heterogeneity, is explored through two vignettes (about heritability and differences among means), a taxonomy of eleven kinds of heterogeneity, and a contention connecting heterogeneity, control of populations, and possibilities for participation.

“Changing Science in Heterogeneous Environments,” pp. 87-101 in T. Awerbuch, M. Clark, P. Taylor (eds.), The Truth is the Whole: Essays in Honor of Richard Levins, Arlington MA: The Pumping Station, 2018.

Working papers on heterogeneity and other matters

Four recently uploaded working papers from years past:

Making sense of Genotype-Phenotype Distinction, another version (7)

Comments welcome by anyone interested to read the revised draft, which begins:

The predominant current-day meaning of genotype is some relevant part of the DNA passed to the organism by its parents. The phenotype is the physical and behavioral traits of the organism, for example, size and shape, metabolic activities, and patterns of movement. The distinction between them is especially important in evolutionary theory, where the survival and mating of organisms depends on their traits, but it is the DNA, held to be unaffected by the development of the traits over the life course, that is transmitted to the next generation.

Making sense of Genotype-Phenotype Distinction, another version 6

The revised draft begins:

The predominant current-day meaning of genotype is some relevant part of the whole genome, the DNA passed to the organism by its parents. The phenotype is the physical and behavioral characteristics of the organism, for example, size and shape, metabolic activities, and patterns of movement.   The distinction is especially important in evolutionary theory, where the survival and mating of organisms depends on their traits, but it is the DNA, held to be unaffected by the development of the traits over the life course, that is transmitted to the next generation.

However:

Troubled by Heterogeneity?: A simple example to illustrate why we might or might not be

Fresh perspectives on modern understandings of heredity and development over the life course can be opened up by examining the ways that research and application of resulting knowledge address—or suppress—heterogeneity in a range of senses (including individual particularity and variation around a mean).  Let me illustrate why we might or might not be troubled by heterogeneity through a personal story that involves the simplest sense of heterogeneity, namely, a group made up of two distinguishable subgroups.

At my annual physical when I turned 50 my doctor recommended a regimen of half an aspirin a day to help prevent a stroke or heart attack.  Not long afterwards I learned that some fraction of the population is resistant to aspirin—it does not produce the desired anti-platelet effect.  This subgroup is, however, still subject to aspirin resulting in an increased risk of serious gastrointestinal bleeding.  Could I find out if I was in the resistant fraction?  My doctor informed me that health insurance companies do not consider testing to be a justified expense for healthy subjects.  It was, he advised, up to me to decide whether to take the daily aspirin.  Some Internet follow-up on my part revealed that testing for resistance is possible, but is undertaken only when patients under treatment for a cardiovascular attack do not seem to be showing the anti-platelet effects of aspirin intake.  Would I devote energy to find others with similar concerns about their aspirin-resistance status and agitate for access to testing?  No—I went along with the health insurance company’s determination and followed the doctor’s advice to make a personal choice, in this case, not to take the daily pill.

With hindsight, my decision was a good one—recent research indicates that in all healthy subjects the decreased average risk of a cardiovascular event might not outweigh the increased average risk of gastrointestinal bleeding (Seshasai et al. 2012).  Yet, these newer findings aside, consider my experience at the time.  In the doctor’s initial recommendation, aspirin-resistant and normal subgroups were treated as a single group of over-50s, all of us subject to the same positive trade-off between cardiovascular and gastrointestinal risks.  The doctor could have been troubled by the heterogeneity within this group, especially after I raised my concerns.  Instead he invoked the rhetoric of patient choice and the constraints of the health insurance system.  I entertained the possibility of joining with others to agitate for testing to determine which subgroup we belonged to.  In the end, I complied with my doctor’s framing of my position, namely, I should see myself as a member of an over-50s group subject to a degree of uncertainty about the positive trade-off.

In this story we can see the three parts of a broad contention—

•  Research and application of resulting knowledge are untroubled by heterogeneity to the extent that populations are well controlled—As the story conveys, I did not comply with my doctor’s initial recommendation, but accepted his subsequent advice.

•  Such control can be established and maintained, however, only with considerable effort or social infrastructure—The authority of medical professionals was not sufficient to achieve my compliance, but the rhetoric of patient choice and the reimbursement guidelines of the health insurance system eventually were.

•  The interplay of heterogeneity, control, and social infrastructure provides an opening to give more attention to possibilities for participation instead of control of human subjects—The Internet gave me a means to go beyond the consultation with my doctor.  It would have been my first port of call if I had embarked on a journey of finding whom to collaborate with to agitate for change in the guidelines for aspirin-resistance testing.

Figure 1. Schema that summarizes the contention in the text.  The contention applies both to the modern understandings of heredity and to interpretations of science in Science and Technology Studies (STS). (Colored text narrates the connection between terms linked by the curves. Zigzag lines indicate a tension or contrast, e.g, populations are harder to control if members of the population are able to participate in ways that draw attention to heterogeneity within the population.)

Heterogeneity and Data Analysis: Coda: Heterogeneity and Control

CODA: HETEROGENEITY AND CONTROL

Several of the vignettes speak to a broad contention I would make about heterogeneity and control:  In relation to modern understandings of heredity and development over the life course, research and application of resulting knowledge are untroubled by heterogeneity to the extent that populations are well controlled.  Such control can be established and maintained, however, only with considerable effort or social infrastructure, which invites more attention to possibilities for participation instead of control of human subjects.  On the control side, people can be made to fit types in many ways: through stereotyping, screening and surveillance, population health measures, diagnostic manuals in psychology, reassignment surgery, ignoring non-conformers, and so on.  On the participation side, Taylor (2005) describes diagramming of intersecting processes to expose multiple points of engagement, “mapping” by researchers of the complex situations they study and their own complex situatedness, and well-facilitated participatory processes.

Does the contention about heterogeneity and control make sense in data analysis?  Does it have relevance beyond heredity and life course development?

—

(completing a series of posts—see first post)

Underlying heterogeneity and heritability II: What can researchers do on the basis of knowing a trait’s heritability if the genetic and environmental factors underlying the observed trait are heterogeneous?

What can researchers do on the basis of knowing a trait’s heritability if the genetic and environmental factors underlying the observed trait are heterogeneous, or if the method of data analysis does not allow researchers to rule out the possibility of underlying heterogeneity?  What steps and conditions are needed for researchers to bridge or circumvent the knowledge that underlying factors may be heterogeneous?  There seem to be six directions that researchers might pursue:

a. Undertake research to identify the specific, measurable genetic and environmental factors without reference to the trait’s heritability or the other fractions of the total variance (e.g., Moffitt et al. 2005, Davey Smith and Ebrahim 2007, Khoury et al. 2007).  Discussion of this direction of research takes us beyond heritability studies.

b. Use high heritability to guide molecular research to identify the specific genetic factors involved.  There may be traits for which the underlying factors are not heterogeneous.  These might be worth finding even if researchers do not know in advance the proportion of fruitful investigations compared with those confounded by the underlying heterogeneity.   The search here is not for high penetrance major genes; these can be detected through examination of family trees; heritability analysis need not be involved.  Rather, researchers need to find traits in which many underlying genetic factors each of small influence turn out to be similar for all individuals who show the same value for the trait within some defined population.

c.  Restrict attention to within a set of relatives.  Even if the underlying factors are not yet known, high heritability still means that if one twin develops the trait (e.g., type 1 diabetes), the other twin is more likely to as well.  This information might stimulate the second twin to take measures to reduce the health impact if and when the disease starts to appear.  However, notice that this scenario assumes that the timing of getting the condition differs from the first twin to the second.  Researchers might well ask: What factors influence the timing?  How changeable are these?  How much reduction in risk comes from changing them?  To address these issues researchers have to identify the genetic and environmental factors involved in the development of the trait and to secure larger sample sizes than any single set of relatives allows.  The question then arises whether the results can be extrapolated from one set of relatives to others.  The possibility of underlying heterogeneity has not, therefore, gone away as an issue.  The answer to the question of extrapolation is an empirical one; there is a risk, as before, that the proportion of fruitful investigations will be low compared to those confounded by factors not extrapolating well from the initial set of relatives.

d. Put aside the search for measurable factors.  Instead, focus on heritability as a fraction of the variation among measurements.  This focus is useful in agricultural and laboratory breeding.  If the actual advance under selective breeding is less than predicted, one source of the discrepancy might be the underlying heterogeneity of genetic factors and their reassortment through mating.  Again, this matters little for breeders because they can always compensate for discrepancies: they discard the undesired offspring, breed the desired ones, and continue.  Of course, selective breeding is not an acceptable option for humans.  What is left is the intuition that genetic factors have a larger influence than environmental factors for high heritability traits.  This is problematic (Taylor 2010, p. 13ff), even more so when researchers consider models that allow for heterogeneous factors to underlie the trait.

e. Reduce the possibility of underlying heterogeneity by restricting the range of varieties or locations.  Agricultural researchers can reduce the possibility of underlying heterogeneity by restricting the range of locations in which a variety is raised or grown.  They can also control environmental conditions, such as, for animals, the regimes of feeding and husbandry or, for plants, the application of fertilizer and irrigated water.  Agricultural breeders can also produce inbred lines and thereby eliminate the heterogeneity of genetic factors that exists within outbred varieties.  However, to envisage taking action on the basis of research conducted under restrictive conditions is to presume that the restrictive conditions can be replicated.  This presumption is most apparent when plant breeders recommend varieties to be grown only in defined regions and under prescribed techniques of cultivation, or when animal breeders specify the optimal feeding and husbandry for each variety.  In the study of human traits, however, it is not feasible to control the full range of relevant environmental conditions or to breed for genetic uniformity.  It may be possible to restrict the locations included in a human study (e.g., to include only families of low socioeconomic status; Turkheimer et al. 2003).  The heritability estimates would be reliable to the extent that these restrictions were replicated in subsequent research or policy.  That is, the research could be applied even though the environmental factors underlying those locations had not been identified.

f. Reduce the possibility of underlying heterogeneity by grouping varieties that are similar in responses across locations. (Note that when analyzing measurements from studies of human twins because such studies have only two replicates [twins] in one or at most two locations [families], so this is not a feasible direction by which research on human variation can bridge or circumvent the knowledge that underlying factors may be heterogeneous.)  In agricultural trials, where a number of varieties or animals or plants can be raised or grown in multiple replicates in many locations, varieties can be grouped by similarity in responses across all locations (using techniques of cluster analysis; Byth et al. 1976).  (Similarly, locations can be grouped by similarity in responses elicited from varieties grown across those locations.)  Varieties in any resulting group tend to be above average for a location in the same locations and below average in the same location (Taylor 2010).  The wider the range of locations in the measurements on which the grouping is based, the more likely it is that the ups and downs shared by varieties in a group are produced by the same conjunctions of underlying measurable factors.  This gives researchers more license to discount the possibility of underlying heterogeneity within a group.  If the underlying factors are assumed to be homogeneous within each of the groups, researchers can hypothesize about the group averages—about what factors in the locations elicited basically the same response from varieties in a particular variety group that distinguishes them from other groups.  (It should be noted that knowledge from sources other than the data analysis is always needed to help researchers generate any hypotheses about genetic and environmental factors.)

In summary, unless you can think of directions of research other than the six above, there is very little that researchers on human variation can do that is reliable on the basis of knowing a trait’s heritability if the genetic and environmental factors underlying the observed trait are heterogeneous.  Agricultural researchers can do more because they have greater control of their varieties and conditions in test locations.

Adapted from Taylor (2010) and Nature-Nurture? No… A Short, but Expanding Guide to Variation and Heredity (work in progress)

References

Byth, D.E., Eisemann, R.L. and DeLacy, I.H.: 1976, Two-Way Pattern Analysis of a Large Data Set to Evaluate Genotypic Adaptation. Heredity 37(2), 215-230.

Davey-Smith, G. and Ebrahim, S.: 2007, Mendelian randomization: Genetic variants as instruments for strengthening causal influences in observational studies, in Weinstein, M., Vaupel, J. W., Wachter, K.W. (eds.) Biosocial Surveys. Washington, DC, National Academies Press, pp. 336-366.

Khoury, M.J., Little, J., Gwinn, M. and Ioannidis, J.P.: 2007, On the Synthesis and Interpretation of Consistent but Weak Gene-Disease Associations in the Era of Genome-Wide Association Studies. International Journal of Epidemiology, 36, 439-445.

Moffitt, T.E., Caspi, A. and Rutter, M.: 2005, Strategy for Investigating Interactions between Measured Genes and Measured Environments. Archives of General Psychiatry, 62(5), 473-481.

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

Turkheimer, E., Haley, A., Waldron, M., D’Onofrio, B. and Gottesman, I.I.: 2003, Socioeconomic Status Modifies Heritability of IQ in Young Children, Psychological Science 16(6), 623-628

Control and the foundational theories of modern life sciences

The original theories of evolution by natural selection and the genetic basis of heredity were built from language, arguments, evidence, and practices of controlled breeding in agriculture and the laboratory.  What does it mean that understandings of the diversity of life—its changes and its continuities—were formed in a crucible of human control of biological materials?  What does it mean that this question has not been given much attention in the history and philosophy of the life sciences?

Of course, there are innumerable episodes and currents in the history and philosophy of heredity that invite further inquiry.  One response to the two questions above would be for me to get to work, to research and write on them myself.  Another response would be to try to stimulate others to explore assumptions about control built into analyses and models of variation and change and to make their own contributions.  On both fronts, stay tuned…