The Effect of Creatine Supplementation on Resistance Training-Based Changes to Body Composition: A Systematic Review and Meta-analysis.

ABSTRACT: Desai, I, Wewege, MA, Jones, MD, Clifford, BK, Pandit, A, Kaakoush, NO, Simar, D, and Hagstrom, AD. The effect of creatine supplementation on resistance training-based changes to body composition: A systematic review and meta-analysis. J Strength Cond Res XX(X): 000-000, 2024-The purpose of this review was to determine the added effect of creatine supplementation on changes in body composition with resistance training in adults younger than 50 years. The review protocol was preregistered on the Open Science Framework (osf.io/x48a6/). Our primary outcome was lean body mass (LBM); secondary outcomes were body fat percentage (%) and body fat mass (kg). We performed a random-effects meta-analysis in R using the metafor package. Subgroup analyses were conducted to examine the effects of training status and use of a carbohydrate drink with creatine. We conducted a meta-regression to examine the moderating effect of total training volume. Statistical significance was set at p < 0.05. One thousand six hundred ninety-four records were screened, and 67 full-text articles were assessed for eligibility. Twelve studies were included in the meta-analysis. Fifty-two percentages of the studies had low risk, 41% some concerns, and 7% high risk of bias. Compared with resistance training (RT) alone, creatine supplementation increased LBM by 1.14 kg (95% CI 0.69 to 1.59), and reduced body fat percentage by -0.88% (95% CI -1.66 to -0.11) and body fat mass by -0.73 kg (95% CI -1.34 to -0.11). There were no differences between training status or carbohydrate subgroups. Training volume was not associated with effect size in all outcomes; 7 g or 0.3 g/kg of body mass of creatine per day is likely to increase LBM by 1 kg and reduce fat mass by 0.7 kg more than RT alone. Concurrent carbohydrate ingestion did not enhance the hypertrophy benefits of creatine.

Refining microbial community metabolic models derived from metagenomics using reference-based taxonomic profiling.

Characterization of microbial community metabolic output is crucial to understanding their functions. Construction of genome-scale metabolic models from metagenome-assembled genomes (MAG) has enabled prediction of metabolite production by microbial communities, yet little is known about their accuracy. Here, we examined the performance of two approaches for metabolite prediction from metagenomes, one that is MAG-guided and another that is taxonomic reference-guided. We applied both on shotgun metagenomics data from human and environmental samples, and validated findings in the human samples using untargeted metabolomics. We found that in human samples, where taxonomic profiling is optimized and reference genomes are readily available, when number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach. The two approaches showed significant overlap but each identified metabolites not predicted in the other. Pathway enrichment analyses identified significant differences in inferences derived from data based on the approach, highlighting the need for caution in interpretation. In environmental samples, when the number of input taxa was normalized, the reference-guided approach predicted more metabolites than the MAG-guided approach for total metabolites in both sample types and non-redundant metabolites in seawater samples. Nonetheless, as was observed for the human samples, the approaches overlapped substantially but also predicted metabolites not observed in the other. Our findings report on utility of a complementary input to genome-scale metabolic model construction that is less computationally intensive forgoing MAG assembly and refinement, and that can be applied on shallow shotgun sequencing where MAGs cannot be generated.IMPORTANCELittle is known about the accuracy of genome-scale metabolic models (GEMs) of microbial communities despite their influence on inferring community metabolic outputs and culture conditions. The performance of GEMs for metabolite prediction from metagenomes was assessed by applying two approaches on shotgun metagenomics data from human and environmental samples, and validating findings in the human samples using untargeted metabolomics. The performance of the approach was found to be dependent on sample type, but collectively, the reference-guided approach predicted more metabolites than the MAG-guided approach. Despite the differences, the predictions from the approaches overlapped substantially but each identified metabolites not predicted in the other. We found significant differences in biological inferences based on the approach, with some examples of uniquely enriched pathways in one group being invalidated when using the alternative approach, highlighting the need for caution in interpretation of GEMs.

Profiling the colonic mucosal response to fecal microbiota transplantation identifies a role for GBP5 in colitis in humans and mice.

Host molecular responses to fecal microbiota transplantation (FMT) in ulcerative colitis are not well understood. Here, we profile the human colonic mucosal transcriptome prior to and following FMT or placebo to identify molecules regulated during disease remission. FMT alters the transcriptome above the effect of placebo (n = 75 vs 3 genes, q < 0.05), including modulation of structural, metabolic and inflammatory pathways. This response is attributed to responders with no consistency observed in non-responders. Regulated pathways in responders include tight junctions, calcium signalling and xenobiotic metabolism. Genes significantly regulated longitudinally in responders post-FMT could discriminate them from responders and non-responders at baseline and non-responders post-FMT, with GBP5 and IRF4 downregulation being associated with remission. Female mice with a deletion of GBP5 are more resistant to developing colitis than their wild-type littermates, showing higher colonic IRF4 phosphorylation. The colonic mucosal response discriminates UC remission following FMT, with GBP5 playing a detrimental role in colitis.

Ku70 senses cytosolic DNA and assembles a tumor-suppressive signalosome.

The innate immune response contributes to the development or attenuation of acute and chronic diseases, including cancer. Microbial DNA and mislocalized DNA from damaged host cells can activate different host responses that shape disease outcomes. Here, we show that mice and humans lacking a single allele of the DNA repair protein Ku70 had increased susceptibility to the development of intestinal cancer. Mechanistically, Ku70 translocates from the nucleus into the cytoplasm where it binds to cytosolic DNA and interacts with the GTPase Ras and the kinase Raf, forming a tripartite protein complex and docking at Rab5+Rab7+ early-late endosomes. This Ku70-Ras-Raf signalosome activates the MEK-ERK pathways, leading to impaired activation of cell cycle proteins Cdc25A and CDK1, reducing cell proliferation and tumorigenesis. We also identified the domains of Ku70, Ras, and Raf involved in activating the Ku70 signaling pathway. Therapeutics targeting components of the Ku70 signalosome could improve the treatment outcomes in cancer.