The Pervasive Myth of Variability in Female Subjects
By Claire Deckers
Longstanding societal stereotypes paint women as being emotional and irrational creatures that are largely controlled by hormonal impulses. These stereotypes are seemingly ubiquitous in nature, affecting the paradigms by which scientific research subjects are selected and utilized. Until 2016, the National Institute of Health did not require scientists conducting research with animal subjects to consider sex as a biological variable, leaving female subjects completely out of the picture except in select scenarios1. When these requirements ultimately changed, major pushback was encountered.
The first (and primary) reason for this pushback comes from the pervasive idea that utilizing female subjects produces data that is too variable and inconsistent to be of any use. Those who prescribe to this idea believe that fluctuating hormonal levels during estrous cycles result in similarly fluctuating data, will be too confusing to make sense of. The purportedly complicated nature of the data is seen as statistically problematic, and if any results are found, the impact of the findings will be diminished2. In order to combat this variability, traditional scientific paradigms held that researchers would need to keep four times the number of female animals than males, allowing them to analyze data in each phase of the estrous cycle and account for hormonal changes 1 2 3 4 5. This alleged need for estrous phase monitoring and large groups of animals represents both a significant time and monetary investment, leading investigators to be largely discouraged from pursuing research in females.
Despite the persistence of these two issues within the general scientific mindset, neither assumption is empirically supported. Multiple data meta-analyses of studies including male and female subjects found that across all analyzed traits (behavioral, electrophysiological, neurochemical, and histological), there were no sex differences in variability4 5 6. According to this analysis, female subjects are not more variable at any stage of the estrous cycle than males. Therefore, testing can occur without monitoring the estrous phase, unless there is a specific reason to test a hormonal interaction. Ironically, additional studies have actually found significantly greater mean genetic and phenotypic variability in male subjects2 7.
Essentially, the findings of these meta-data analyses eliminate the argument against utilizing female subjects in scientific studies. So how should studies with heterogenous male and female subjects be conducted? One suggestion is to set up a factorial experiment, a design that allows the researcher to examine effects of multiple factors and their interactions within their results2. In this manner, researchers can determine overall experimental findings and elucidate if sex differences are present. An additional, simpler experimental design would be to utilize female and male subjects in equal proportions and directly compare them4.
Utilizing female subjects is essential to the understanding of underlying biological functioning at its most basic level. Studies that only involve the examination of a single sex do not have the ability to generate a complete understanding of biological mechanisms. As a scientist, one has an unspoken and under-recognized ethical duty to find whether sex differences are, or are not present. Either can provide valuable and important information. Ignoring biological sex within scientific studies presents a failing and an irresponsibility in producing a complete portrait of biological systems within the general, heterogenous population. The use of female subjects is incredibly important in the generation of results that hold external validity and applicability within general populations3. With today’s scientific literature backing this assertion, female subjects must be used in research in order for results to be relevant to a wider populace.
Shansky, R.M. and Woolley, C.S. (2016). Considering sex as a biological variable will be valuable for neuroscience research. Journal of Neuroscience, 36(47): 11817-11822.
2 Beery, A. K. (2018). Inclusion of females does not increase variability in rodent research studies. Current Opinion in Behavioral Sciences, 23: 143-149.
3 Wald, C. and Wu, C. (2010). Of mice and women: the bias in animal models. Science, 327: 1571-1572
4 Prendergast, B.J.; Onishi, K. G.; Zucker, I. (2014). Female mice liberated for inclusion in neuroscience and biomedical research. Neuroscience and Biobehavioral Reviews, 40: 1-5.
5 Beery, A. K. and Zucker, I. (2011). Sex bias in neuroscience and biomedical research. Neuroscience and Biobehavioral Review 35(3): 565-572.
6 Becker, J. B.; Prendergast, B. J.; Liang, J. W. (2016). Female rats are not more variable than male rats: a meta-analysis of neuroscience studies. Biology of Sex Differences, 7(34).
7 Itoh, Y. and Arnold, A. P. (2015). Are females more variable than males in gene expression? Meta-analysis of microarray datasets. Biology of Sex Differences, 6(18).