Written by: Adam Tzur
Updated: July 24, 2019 – Added West et al., 2012 | September 16, 2018 – Added Morton et al., 2018 | 20.05.2018 – Updated quotes | 16.05.2017 – Citation(s) added for cortisol
Acknowledgements: Greg Nuckols of Strengtheory.
Summary
Expand Table →
- Post-exercise hormone secretion will, per the research today, not predict gains. Even if the hormones secreted are anabolic.
- Designing training programs around testosterone maximization and cortisol minimization is most likely not a sound way to do programming.
- Intramuscular IGF-1 might be related to gains if measured properly.
Introduction to hormones
Our body uses hormones for sending “slow” long-range signals. Hormones act systemically, meaning they affect the body as a whole. This is in contrast to short-distance cell communication (Tortora & Derrickson, 2012). You have probably heard of hormones like cortisol and testosterone and associate these hormones with stress and growth, respectively.
In my experience, people commonly believe these hormones function in an independent, linear fashion. Meaning more testosterone equals more masculinity and growth, while more cortisol equals stress and catabolism. However, this point of view ignores the fact that hormones have a physiological range where they help the body function optimally (Tortora & Derrickson, 2012). By trying to minimise or maximise certain hormonal responses we ignore the whole-body context in which they exist. Indeed, hormones have many functions. For example, testosterone is a regulator of mental health (Celec et al., 2015). Trying to shoehorn a hormone into one role is overly reductionistic. We all know about hormones like insulin, growth hormone, adrenaline, and cortisol. We probably also have a general idea of their purpose in the body. But were you also aware that these hormones are linked to sleep regulation (McGinnis & Young., 2016)? People who inject hormones like insulin, GH, testosterone, etc. might be inadvertently altering organ functionality in their bodies. This could lead to unwanted and unintended consequences which could be detrimental to their overall health (Lamb, 1984; ACSM, 1987; Su et al., 1993; Sullivan et al., 1998; Hartgens & Kuipers, 2004; Maravelias et al., 2005; Achar et al., 2010; Piacentino et al., 2015; Frati et al., 2015; Grönbladh et al., 2016).
Trying to min-max your hormones like the stats of an RPG character is probably not a good idea given that hormones are essential regulators of homeostasis. By interfering with their natural balance you change a ton of homeostatic parameters, causing butterfly effects. But this review isn’t about the effects of steroids, so let’s get back on topic.
Research now shows that different, and perhaps unexpected, types of tissues can secrete hormones. For example, fat tissue can secrete inflammatory products 1 and hormones 2. In addition to fat, muscle tissue can secrete beneficial hormones (Egan and Zierath, 2013) called myokines 3. This means that muscles and fat can communicate messages to the whole body.
Can systemic hormones predict hypertrophy after exercise?
After challenging exercise, our body secretes various hormones like cortisol, testosterone, GH, and IGF-1 (Volek et al., 1997; Copeland et al., 2002; Leal-Cerro et al., 2003; Goto et al., 2005; Hill et al., 2008; Leite et al., 2011; Conceição et al., 2014; Rubin et al., 2015; Gonzalez, 2015; Kraemer and Castracane, 2015; Kraemer et al., 2016; Seifi-skishahr et al., 2016; González-Badillo et al., 2016; Hooper et al., 2017; Walker et al., 2017). Since several of these hormones are associated with hypertrophy, it makes intuitive sense that we improve our gains the higher our anabolic hormones spike after exercise (Goto et al., 2005; Villanueva et al., 2012). By accepting this hypothesis, we assume there is a positive relationship between acute post-exercise hormonal secretion and hypertrophy.
There is only one issue. Most studies and systematic reviews agree that temporary post-exercise increases in anabolic hormones do not predict hypertrophy (Wilkinson et al., 2006; Velloso, 2008; West et al., 2009; West et al., 2010; West et al., 2012; West and Phillips, 2010; Schroeder et al., 2013; Mitchell et al., 2013; Henselmans and Schoenfeld, 2014; Gonzalez et al., 2015a; Mangine et al., 2015; Morton et al, 2016; Fink et al., 2016; Mckendry et al., 2016; Hooper et al., 2017; Walker et al., 2017; Morton et al., 2018). Though some studies disagree when it comes to GH (McCall et al., 1999; Goto et al., 2005; West and Phillips, 2012) and cortisol being negatively associated with fat mass and LBM (Longland et al., 2016). GH might be indirectly tied to hypertrophy (Goto et al., 2005).
The figure shows the non-link between CSA (hypertrophy) and growth hormone secretion post-exercise by Fink et al., 2016
Several of the authors agree that local mechanisms are more important than systemic mechanisms 4. Others say there is not enough evidence to make conclusive statements about hormonal changes and gains (Schoenfeld, 2013; Kraemer et al., 2016). Schoenfeld speculates that “the purpose of post-exercise hormonal elevations is to mobilize fuel stores rather than promote tissue anabolism”, which is a hypothesis that fits with AMPK and the “energy crisis of the cell”. Additionally, Schoenfeld presents us with the idea that our genetics determine whether we respond to post-exercise increases in anabolic hormones 5. It’s possible that some people are genetically hardwired to react favourably with endogenous anabolic hormones, while others won’t.
A very recent study challenges these arguments, because it finds that acute post-exercise testosterone secretion is related to hypertrophy in 26 resistance trained men over an 8 week training period (Mangine et al., 2016). The authors criticize some of the aforementioned studies because some of them were underpowered (i.e. too few participants) and because they used non-optimal statistical procedures. These are valid arguments. However, I get a bit suspicious when Mangine et al. imply that the research is biased or erroneous 6. This is a bit odd since such a critique could apply to pretty much every study out there. There’s always the possibility of bias and error. If bias and error were present in the hormone studies, they would be interfering with the efforts of several independent research teams. Mangine et al’s findings are very interesting but until they are replicated and supported by other studies, we have to slow-pedal their conclusions.
Beyond hypertrophy, there are studies that suggest there is a link between testosterone secretion and strength gains (Beaven et al., 2008). Though the focus of this article is hypertrophy and not strength, so I won’t go in-depth on this.
With all the research taken into account, designing a training program around hormonal responses is not a good way to do programming or periodization (Gonzalez, 2015b; Mangine et al., 2015; Walker et al., 2017). Any program that promises maximal testosterone or GH secretion using (for example) very short rest periods (Goto et al., 2005; Willardson, 2006; Villanueva et al., 2012; Henselmans and Schoenfeld, 2014) probably won’t do more good than regular, intelligent programming (Henselmans and Schoenfeld, 2014; Walker et al., 2017). Intense training to failure can actually lead to T-levels that fall below baseline, 48 hours post-exercise (González-Badillo et al., 2016) 7. Though this reduction in testosterone might be a temporary overreaching-response. See table below for details.
With that said, we shouldn’t discount hormones completely. Just because temporary changes in hormonal secretion doesn’t predict gains, doesn’t mean your long-term hormonal profile is unimportant (Kvorning et al., 2006; Mouser et al., 2016; Mangine et al., 2016; Hooper et al., 2017; Bermon, 2017). For example, men have 10x more circulating testosterone than women, which is one of the reasons it might be easier for men to build and maintain muscle mass after puberty (Schroeder et al., 2013). Androgenic hormones seem to be important for performance (Kvorning et al., 2006; Bermon, 2017). Though some disagree that gender differences in performance and muscle mass are related to anabolic hormones (Healy et al., 2014).
Insulin
Atherton and Smith have described insulin as an anti-catabolic hormone that lowers MPB and thus “protects” the body from muscle wasting. Insulin could act synergistically with essential amino acids (EAA), where insulin decreases MPB while EAAs increase MPS (Atherton and Smith, 2012; Everman et al., 2016).
Many studies have measured post-exercise insulin concentrations, and haven’t found any connection to gains. However, their results might be affected by the fact that insulin responds strongly to protein and carbohydrates. In fact, insulin concentrations actually decrease (Schwarz et al., 2011; Mangine et al., 2015) or remain unchanged (Marliss et al., 2002) during exercise. So it makes little sense that insulin would predict hypertrophy when measured right after exercise. But, if exercise was combined with feeding, it’s possible insulin might be correlated with gains.
Insulin secretion is therefore part of the nutrient timing hypothesis which states that consuming carbohydrates and protein around the the exercise window (before, during, after), could lead to improved gains (Kerksick et al., 2008). This hypothesis has been thoroughly researched in the last twenty years. I will write a separate nutrient timing article on this topic specifically.
Can local hormones predict hypertrophy after exercise?
Local hormones can also be described as intramuscular hormones. They exist in contrast to circulating hormones which flow freely in the bloodstream. Some authors think local hormonal concentrations are better at predicting gains compared to circulating hormones.
Insulin-like Growth Factor 1 (IGF-1)
Like insulin, IGF-1 is a hormone that is an exception to the rule. We can measure “circulating” IGF-1 in the blood, or we can measure intramuscular IGF-1 (IMIGF-1). The studies that dismissed IGF-1 as a predictor of gains measured circulating IGF-1. IMIGF-1 is different because it functions locally in cell-to-cell communication (Adams, 2002; Velloso, 2008; Wang et al., 2013). It’s possible that IMIGF-1 levels predict strength gains (Kraemer et al., 2016) and hypertrophy better than circulating IGF-1 (Häkkinen et al., 2001; Adams, 2002; Velloso, 2008; Frystyk, 2010; Schoenfeld, 2013; Mangine et al., 2016; Fink et al., 2016). Sadly, there hasn’t been a ton of human studies on this question as of yet (Velloso, 2008).
Conclusion
As per the research presented in this article, there’s little reason to believe temporary changes in hormonal secretion predicts gains. Future research is needed to confirm or deny the hormone hypothesis.