Q #2: Some years ago there was a great deal of attention placed on myostatin-related muscle hypertrophy, animals with myostatin deletion animals being incredibly muscular, and many being convinced that was the magic bullet to muscularity. Of course a bunch of worthless ?myostatin inhibitor? supplements sprung up following that. I recall some pro bodybuilders being tested for alterations in the myostatin gene, but the results were inconsistent. While myostatin clearly plays an important role, it?s obviously not the magic bullet first thought. It seemed the focus on myostatin dropped off as data on the importance of mTOR and PI3K pathway‎ increased, and people then jumped on that as the new be-all-end-all of pathways and related genes for manipulating muscle mass and such. What area of genetic related research do you feel worthy of focus that might show what essential differences exist between super responders and the rest of us? It?s obviously an immensely complex topic.

Conrad: At this point in time, genetics can only point to a few genes that may influence strength performance. They are not (yet) the magic bullet because, as you have stated, genetics are complex and involve hundreds of genes. In my previous example, there are hundreds (probably more) of genes in involved in cardiovascular adaptations and no reason to think the same does not apply to strength.

Thus, hundreds of subjects will eventually need to be analyzed and then run through some fairly elaborate modeling ? perhaps machine modeling ? to ferret out the top candidate genes. Once we have a clue on those, they would further have to be aligned with muscle fiber content and potentially muscle architecture.

Jose: I?ve actually wrapped up a study on the ACTN3 gene (gene for ?speed?). A few things you can learn from it. One, you ain?t a slave to your genes. But two, your genes can limit you. If you ain?t got the ACTN3 gene, then forget about performing well at a speed sport. It would be like entering a math contest with just half a brain. Gene research is certainly the next frontier in exercise and sports science. I?ll be looking at genetic markers for ?fatness? (FTO gene) and others. So you may have super-responders (i.e., speed gene, ACTN3); but on the flip side, you might be a ?super-responder? for gaining fat. It?s really different sides of the same coin.

Q #3: To that end, do you feel it?s likely to be some combination of genes science is already aware of, or some yet to be discovered? Any pathways you?re currently looking at that might be a piece of this puzzle?

Alan: I?ll answer the previous two questions in one swoop here since they?re similar. Funny you should bring up myostatin inhibitors, Wilson et al have an abstract published in JISSN (PMC: 4271642) showing positive results from a follistatin derived from fertile chicken egg yolk isolate. 1.7 kg was gained in 8 weeks in recreationally trained subjects ? not nearly as impressive as the gains seen from HMB-FA. Based on the current literature on molecular drivers of muscle hypertrophy, many of the areas are too disjointed and poorly understood to draw and firm conclusions or base future directions on. While it?s true that the PI3K/AKT/mTORc1 (collectively abbreviated to mTOR) pathway has received a ton of study and recognition for its role in muscle anabolism, it was also relatively recently found by Phillips et al (PMID: 23555298) that subjects with the greatest degree of hypertrophy showed an inhibited mTOR activation signature, including the down-regulation of 70 rRNAs. A bit of a head-scratcher there. I think the areas of focus that we might more fruitfully sink our teeth into are the activation and incorporation of satellite cells, and what agents or protocols might be most potent at achieving this. For those unaware, satellite cells are precursors to full-blown skeletal muscle cells; they?ve been referred to as the most abundant myogenic stem cells. They are capable of providing additional myonuclei for augmenting muscle fiber growth. The implications here are potentially profound, since the ceiling of muscle growth is thought to be influenced by the number of myonuclei within the fibers. Creatine is widely considered to be the most effective supplement for muscle hypertrophy, and one of its mechanisms of action is the proliferation of satellite cells & myonuclei (PMID: 16581862). Another area of interest where the findings have been a bit more concrete is muscle protein synthesis (MPS), and which agents or protocols most potently increase it over the short- and longer-term. As for nutritionally mediated gainz, gene expression of cyclin-dependent kinase 2 (cdk2) ? a factor that increases cell proliferation and body mass ? has been shown to increase both acutely and chronically as a result of resistance training, but only after the ingestion of whey protein near the training bouts (PMID:18661258).

Conrad: Definitely a combination of genes as they relate to fiber type.

Q #4: During your own research, be it exercise training of various types, supplements etc, have you found super responders once the data came in? When you saw it, did you put it down to some statistical anomaly? Voodoo? Or, did you wonder how and why a small portion of your study participants were so genetically gifted? It would seem until very recently, the small fraction of people who fell well outside the statistical norms, the non-responders and super responders where viewed as more a curiosity of unknown origin and essentially ignored. At least in the non-responder side, that appears to be changing. Thoughts?

Alan: In the research I?ve collaborated on thus far, I unfortunately can?t report anything spectacular. In fact, it?s some of the most anticlimactic/unsexy results in the literature (LOL). However, in the most recent RCT of ours that?s in publication (PMID: 28070459), we did report individual data, and one of the subjects showed approximately an 18 mm gain in biceps thickness (0.71 inches), measured via ultrasound, over an 10-week period. The rest of the subjects ? all of whom were resistance-trained ? stayed pretty much the same, which was not surprising since they were in hypocaloric conditions. It?s interesting to imagine what type of response this high responder would have if conditions were optimized for muscle growth, and/or supplementation was implemented. On the poor responder side, one of the subjects experienced a huge drop in quadriceps thickness (25 mm; about 1 inch) during this study. Interindividual response variability is just the nature of the beast, and a very poignant example of this is work by Ahtiainen et al (PMID: 26767377), who demonstrated vast heterogeneity in subjects? responses to resistance training. Their study is openly accessible, have a look at this figure showing the full range of differences in strength & size gains (and losses): https://www.ncbi.nlm.nih.gov/pmc/art...7/figure/Fig4/. 
High responders gained 4-5 times the muscle mass of average responders. Of course there are the unfortunate subjects (2% of the subjects were classified as low responders) who included those who experienced losses in size and strength as a result of resistance training (and in my speculation, other factors as well).

Conrad: Not really, no. It?s a great question. From a statistical point of view one has to separate out potential outliers who may over or under respond vs. a ?super responder.? Outliers are more times than not a matter of study variance (typically unintended) where participants might not have been fully compliant to a protocol.

For example, a few years a go I performed a study looking at the effects of Astaxanthin on cycling time trial performance and found one person who responded amazingly well. Too well and outside the realm of reason. I also found one person to under-respond in a similar fashion. Everyone else fit neatly within the bounds of the average change and confidence intervals of the study. Some a bit better than average, some less so.(3)

Jose: to me, the outliers have always been fascinating (especially the ones who respond well, not those who barely respond). The nature of my research can?t pin down specific mechanisms. For instance, the graph below is from one of my high protein diet studies. You will note that in general, higher protein intakes promote a loss of fat mass. But look at the individual variability (NP is normal protein; HP is high protein). Perhaps it is a mistake in logging food. Perhaps some people gain fat really easy while others lose it easily. I mean who knows? But the GENERAL effect is that eating lots of protein tends to produce a loss of fat. And that?s good enough for 75% of the population. The other 25% will respond in a manner that isn?t ?average.?
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