Sports nutrition is a constantly evolving field with hundreds of research papers published annually. In the year 2017 alone, 2082 articles were published under the key words ‘sport nutrition’. Consequently, staying current with the relevant literature is often difficult. This paper is an ongoing update of the sports nutrition review article originally published as the lead paper to launch the Journal of the International Society of Sports Nutrition in 2004 and updated in 2010. It presents a well-referenced overview of the current state of the science related to optimization of training and performance enhancement through exercise training and nutrition. Notably, due to the accelerated pace and size at which the literature base in this research area grows, the topics discussed will focus on muscle hypertrophy and performance enhancement. As such, this paper provides an overview of: 1.) How ergogenic aids and dietary supplements are defined in terms of governmental regulation and oversight; 2.) How dietary supplements are legally regulated in the United States; 3.) How to evaluate the scientific merit of nutritional supplements; 4.) General nutritional strategies to optimize performance and enhance recovery; and, 5.) An overview of our current understanding of nutritional approaches to augment skeletal muscle hypertrophy and the potential ergogenic value of various dietary and supplemental approaches. This updated review is to provide ISSN members and individuals interested in sports nutrition with information that can be implemented in educational, research or practical settings and serve as a foundational basis for determining the efficacy and safety of many common sport nutrition products and their ingredients.

Human muscle fibers are generally classified by myosin heavy chain (MHC) isoforms characterized by slow to fast contractile speeds. Type I, or slow-twitch fibers, are seen in high abundance in elite endurance athletes, such as long-distance runners and cyclists. Alternatively, fast-twitch IIa and IIx fibers are abundant in elite power athletes, such as weightlifters and sprinters. While cross-sectional comparisons have shown marked differences between athletes, longitudinal data have not clearly converged on patterns in fiber type shifts over time, particularly between slow and fast fibers. However, not all fiber type identification techniques are created equal and, thus, may limit interpretation. Hybrid fibers, which express more than one MHC type (I/IIa, IIa/IIx, I/IIa/IIx), may make up a significant proportion of fibers. The measurement of the distribution of fibers would necessitate the ability to identify hybrid fibers, which is best done through single fiber analysis. Current evidence using the most appropriate techniques suggests a clear ability of fibers to shift between hybrid and pure fibers as well as between slow and fast fiber types. The context and extent to which this occurs, along with the limitations of current evidence, are discussed herein.

Mechanisms underlying mechanical overload-induced skeletal muscle hypertrophy have been extensively researched since the landmark report by Morpurgo (1897) of “work-induced hypertrophy” in dogs that were treadmill trained. Much of the preclinical rodent and human resistance training research to date supports that involved mechanisms include enhanced mammalian/mechanistic target of rapamycin complex 1 (mTORC1) signaling, an expansion in translational capacity through ribosome biogenesis, increased satellite cell abundance and myonuclear accretion, and postexercise elevations in muscle protein synthesis rates. However, several lines of past and emerging evidence suggest that additional mechanisms that feed into or are independent of these processes are also involved. This review first provides a historical account of how mechanistic research into skeletal muscle hypertrophy has progressed. A comprehensive list of mechanisms associated with skeletal muscle hypertrophy is then outlined, and areas of disagreement involving these mechanisms are presented. Finally, future research directions involving many of the discussed mechanisms are proposed.

Creatine (Cr) is a ubiquitous molecule that is synthesized mainly in the liver, kidneys, and pancreas. Most of the Cr pool is found in tissues with high-energy demands. Cr enters target cells through a specific symporter called Na⁺/Cl⁻-dependent Cr transporter (CRT). Once within cells, creatine kinase (CK) catalyzes the reversible transphosphorylation reaction between [Mg²⁺:ATP⁴⁻]²⁻ and Cr to produce phosphocreatine (PCr) and [Mg²⁺:ADP³⁻]⁻. We aimed to perform a comprehensive and bioinformatics-assisted review of the most recent research findings regarding Cr metabolism. Specifically, several public databases, repositories, and bioinformatics tools were utilized for this endeavor. Topics of biological complexity ranging from structural biology to cellular dynamics were addressed herein. In this sense, we sought to address certain pre-specified questions including: (i) What happens when creatine is transported into cells? (ii) How is the CK/PCr system involved in cellular bioenergetics? (iii) How is the CK/PCr system compartmentalized throughout the cell? (iv) What is the role of creatine amongst different tissues? and (v) What is the basis of creatine transport? Under the cellular allostasis paradigm, the CK/PCr system is physiologically essential for life (cell survival, growth, proliferation, differentiation, and migration/motility) by providing an evolutionary advantage for rapid, local, and temporal support of energy- and mechanical-dependent processes. Thus, we suggest the CK/PCr system acts as a dynamic biosensor based on chemo-mechanical energy transduction, which might explain why dysregulation in Cr metabolism contributes to a wide range of diseases besides the mitigating effect that Cr supplementation may have in some of these disease states.

Skeletal muscle is highly adaptable and has consistently been shown to morphologically respond to exercise training. Skeletal muscle growth during periods of resistance training has traditionally been referred to as skeletal muscle hypertrophy, and this manifests as increases in muscle mass, muscle thickness, muscle area, muscle volume, and muscle fiber cross-sectional area (fCSA). Delicate electron microscopy and biochemical techniques have also been used to demonstrate that resistance exercise promotes ultrastructural adaptations within muscle fibers. Decades of research in this area of exercise physiology have promulgated a widespread hypothetical model of training-induced skeletal muscle hypertrophy; specifically, fCSA increases are accompanied by proportional increases in myofibrillar protein, leading to an expansion in the number of sarcomeres in parallel and/or an increase in myofibril number. However, there is ample evidence to suggest that myofibrillar protein concentration may be diluted through sarcoplasmic expansion as fCSA increases occur. Furthermore, and perhaps more problematic, are numerous investigations reporting that pre-to-post training change scores in macroscopic, microscopic, and molecular variables supporting this model are often poorly associated with one another. The current review first provides a brief description of skeletal muscle composition and structure. We then provide a historical overview of muscle hypertrophy assessment. Next, current-day methods commonly used to assess skeletal muscle hypertrophy at the biochemical, ultramicroscopic, microscopic, macroscopic, and whole-body levels in response to training are examined. Data from our laboratory, and others, demonstrating correlations (or the lack thereof) between these variables are also presented, and reasons for comparative discrepancies are discussed with particular attention directed to studies reporting ultrastructural and muscle protein concentration alterations. Finally, we critically evaluate the biological construct of skeletal muscle hypertrophy, propose potential operational definitions, and provide suggestions for consideration in hopes of guiding future research in this area.

We sought to identify biomarkers which delineated individual hypertrophic responses to resistance training. Untrained, college-aged males engaged in full-body resistance training (3 d/wk) for 12 weeks. Body composition via dual x-ray absorptiometry (DXA), vastus lateralis (VL) thickness via ultrasound, blood, VL muscle biopsies, and three-repetition maximum (3-RM) squat strength were obtained prior to (PRE) and following (POST) 12 weeks of training. K-means cluster analysis based on VL thickness changes identified LOW [n = 17; change (mean±SD) = +0.11±0.14 cm], modest (MOD; n = 29, +0.40±0.06 cm), and high (HI; n = 21, +0.69±0.14 cm) responders. Biomarkers related to histology, ribosome biogenesis, proteolysis, inflammation, and androgen signaling were analyzed between clusters. There were main effects of time (POST>PRE, p<0.05) but no cluster×time interactions for increases in DXA lean body mass, type I and II muscle fiber cross sectional area and myonuclear number, satellite cell number, and macronutrients consumed. Interestingly, PRE VL thickness was ~12% greater in LOW versus HI (p = 0.021), despite POST values being ~12% greater in HI versus LOW (p = 0.006). However there was only a weak correlation between PRE VL thickness scores and change in VL thickness (r² = 0.114, p = 0.005). Forced post hoc analysis indicated that muscle total RNA levels (i.e., ribosome density) did not significantly increase in the LOW cluster (351±70 ng/mg to 380±62, p = 0.253), but increased in the MOD (369±115 to 429±92, p = 0.009) and HI clusters (356±77 to 470±134, pPOST LOW, p = 0.013). Nonetheless, there was only a weak association between change in muscle total RNA and VL thickness (r² = 0.079, p = 0.026). IL-1β mRNA levels decreased in the MOD and HI clusters following training (p<0.05), although associations between this marker and VL thickness changes were not significant (r² = 0.0002, p = 0.919). In conclusion, individuals with lower pre-training VL thickness values and greater increases muscle total RNA levels following 12 weeks of resistance training experienced greater VL muscle growth, although these biomarkers individually explained only ~8–11% of the variance in hypertrophy.