A recent series of papers in Nature Genetics described several combined Genome Wide Association Studies (GWAS) of height. Although height is a highly heritable trait that can be measured with near-perfect reliability, and the studies employed the latest SNP technology in massive samples numbering in the tens of thousands, only a handful of variants related to height were identified. The SNPs that were shown to be related to height collectively accounted for under 5% of the variation. The reasons for this surprising result are explored, focusing on the analogy between GWAS and the long-standing search for environmental causes of behavior, which I call EWAS, for Environment Wide Association Study. The problems of non-experimental causal inference faced by GWAS researchers were confronted long ago by mainstream social science, and were never fully overcome; they almost certainly cannot be fully overcome. Likewise, the statistical and methodological procedures that are employed in the genome project to control for multiple statistical tests and population stratification have been used in social science for decades. Understanding their successes and failures in that domain helps frame a reasonable set of expectations for the genomics of complex human characteristics.
- Propensity Score
- Genome Wide Association Study
- Delinquent Behavior
- Population Stratification
- Causal Process
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, access via your institution.
Tax calculation will be finalised at checkout
Purchases are for personal use onlyLearn about institutional subscriptions
In which the required significance level, usually p<.05, is divided by the total number of tests to be conducted in the experiment.
The greatest proponent of such ideas was the great theoretical psychologist Paul Meehl. The interested reader is directed to his many papers on the subject, most especially, Meehl, 1978, which should be required reading for GWAS researchers.
A latent variable is a hypothetical process that cannot be observed directly, but which serves to explain relationships that can be observed among actual measurements. If one observes that many aspects of deprived environments—crime, poor schools, inadequate nutrition, unstimulating surroundings—tend to co-occur, the latent variable poverty can be invoked to explain why. The relevant statistical procedure is known as factor analysis. See MacCorquodale and Meehl (1948), or for an accessible statistical treatment, Loehlin (1992).
As was the case for within-family studies of the environment, however, the existence of within sib-pair genetic associations still do not prove a causal relationship between the gene and the outcome. There still might be uncontrolled confounds within pairs (one member might be sent to a Japanese school where chopstick use is encouraged, while the other goes to an American school). The within-pair association controls for a class of confounds that vary between sibling pairs, which is a big help but not a panacea for the shortcomings of non-experimental science.
Angrist, J. D., Imbens, G. W. & Rubin, D. B. (1996): ‘Identification of causal effects using instrumental variables’. Journal of the American Statistical Association 91: 444–455.
Bouchard, T. J., Lykken, D. T., McGue, M. Segal, N. L. & Tellegen, A. (1990): ‘Sources of human psychological differences: the Minnesota study of twins reared apart’. Science 250: 223–228.
Campbell, D. T., Stanley, J. C. & Gage, N. L. (1963): Experimental and Quasi-Experimental Designs for Research. Chicago: Rand McNally.
Cardon, L. R. & Palmer, L. J. (2003): ‘Populations stratification and spurious allelic association’. The Lancet 361: 598–604.
Caspi, A., McClay, J., Moffitt, T. E., Mill, J., Martin, J., Craig, I. W., Taylor, A., Poulton, R. (2003): ‘Role of genotype in the cycle of violence in maltreated children’. Science 297: 851–854.
Cohen, J. (1994): ‘The world is round (p<.05)’. American Psychologist 49: 997–1003.
Dick, D.M., Johnson, J.K, Viken, R.J. & Rose, R.J. (2000): ‘Testing between-family Associations in within-family comparisons’. Psychological Science 11: 409–413.
Epstein, M. P., Allen, A. S., & Satten, G. A. (2007): ‘A simple and improved correction for population stratification in case-control studies’. The American Journal of Human Genetics 80: 921–930.
Fisher, R. A. (1918): ‘The correlation between relatives on the supposition of Mendelian inheritance’. Transactions of the Royal Society of Edinburgh 52: 399–433.
Gudbjartsson, D. F., Walters, D. F., Thorleifsson, H. S., Halldorsson, B. V., Zusmanovich, P. et al. (2008): ‘Many sequence variants affecting diversity of adult human height’. Nature Genetics 40: 609–615.
Hamer, D. & Sirota, L. (2000): ‘Beware the chopsticks gene’. Molecular Psychiatry 5: 11–13.
Harlow, L., Mulaik, S. A. & Steiger, J. H. (eds.) (1997): What If There Were No Significance Tests? Mahwah, NJ: Lawrence Erlbaum.
Hutchison, K. E., Stallings, M., McGeary, J. & Bryan, A. (2004): ‘Population stratification in the candidate gene study: Fatal threat or red herring?’ Psychological Bulletin 130: 66–79.
Lawlor, D. A., Harbord, R. M., Sterne, J. A., Timpson, N. & Davey Smith, G. (2008): ‘Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology’. Statistics in Medicine 27: 1133–1163.
Lettre, G., Jackson, A. U., Gieger, C., Schumacher, F. R., Berndt, S. I. et al. (2008): ‘Identification of ten loci associated with height highlights new biological pathways in human growth’. Nature Genetics 5: 584–591.
Loehlin, J. C. (1992): Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis. Lawrence Erlbaum Associates.
MacCorquodale, K. & Meehl, P. E. (1948): ‘On a distinction between hypothetical constructs and intervening variables’. Psychological Review 55: 95–107.
Meehl, P. E. (1978): ‘Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology’. Journal of Consulting and Clinical Psychology 46: 806–834.
Plaisance, K. S. (2006): Behavioral Genetics and the Environment: The Generation and Exportation of Scientific Claims, unpublished dissertation, University of Minnesota.
Plomin, R. & Crabbe, J. (2000): ‘DNA’. Psychological Bulletin 126: 806–828.
Plomin, R. & Daniels, D. (1987): ‘Why are children in the same family so different from one another?’ Behavioral and Brain Sciences 10: 1–16.
Price, A.L., Patterson, N.J, Plenge, R.M., Weinblatt, M.E, Shadick, N.A. & Reich, D. (2006): ‘Principle components analysis corrects for stratification in genome-wide association studies’. Nature Genetics 38: 904–909.
Rodgers, J. L., Cleveland, H. H., van den Oord, E. & Rowe, D. C. (2000): ‘Resolving the debate over birth order, family size, and intelligence’. American Psychologist 55: 599–612.
Rosenbaum, P. R, & Rubin, D. B. (1983): ‘The central role of the propensity score in observational studies for causal effects’. Biometrika 70: 41–55.
Rutter, M., Pickles, A., Murray, R,. & Eaves, L. (2001): ‘Testing hypotheses on specific environmental causal effects on behavior’. Psychological Bulletin 127: 291–324.
Schmidt, F. L. (1996): ‘Statistical significance testing and cumulative knowledge in psychology: Implications for training of researchers’. Psychological Methods 1: 115–129.
Silventoinen et al. (2003): ‘Heritability of adult body height: A comparative study of twin cohorts in eight countries’. Twin Research and Human Genetics 6: 399–408.
Tabery, J. (2009): ‘Difference mechanisms: Explaining variation with mechanisms’. Biology & Philosophy 24: 645–664.
Turkheimer, E. (1998): ‘Heritability and biological explanation’. Psychological Review 105: 782–791.
Turkheimer, E. (2000): ‘Three laws of behavior genetics and what they mean’. Current Directions in Psychological Science 9: 160–164.
Turkheimer, E. (2004): ‘Spinach and ice cream: Why social science is so difficult’. In. L. DiLalla (ed.): Behavior Genetics Principles: Perspectives in Development, Personality, and Psychopathology. Washington, DC, US: American Psychological Association, pp. 161–189.
Turkheimer, E. (2006): ‘Interaction and play’. PsycCRITIQUES 51: 43.
Turkheimer, E. & Waldron, M. C. (2000): ‘Nonshared environment: A theoretical, methodological and quantitative review’. Psychological Bulletin 126: 78–108.
Visscher, P. M. (2008): ‘Sizing up human height variation’. Nature Genetics 40: 489–490.
Weedon, M. N., Lango, H., Lindgren, C. M., Wallace, C., Evans, D. M. et al. (2008): ‘Genome-wide association analysis identifies 20 loci that influence adult height’. Nature Genetics 40: 575–583.
Wimsatt, W. (1997): Transcripts from “modularity of animal form”. Proceedings of the evolvability of developmental mechanisms short course, http://celldynamics.org/evolvacourse/transcripts/BillWimsatt.html
Editors and Affiliations
© 2012 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Turkheimer, E. (2012). Genome Wide Association Studies of Behavior are Social Science. In: Plaisance, K., Reydon, T. (eds) Philosophy of Behavioral Biology. Boston Studies in the Philosophy of Science, vol 282. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1951-4_3
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-1950-7
Online ISBN: 978-94-007-1951-4