Meta-analysis of Skeletal Muscle Response to Exercise
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MetaMEx
Meta-analysis of Skeletal Muscle Response to Exercise
The app to meta-analyse skeletal muscle transcriptomic response to inactivity and exercise.
Use MetaMEx to get a complete overview the behavior of a specific gene across
all published exercise and inactivity transcriptomic studies.
MetaMEx v3.2208, last update August 2022
The timeline plot is not reactive. All studies in healthy individuals are included by default, and differences (sex, age, protocol) are blocked for in the statistical model.
The timeline plot is not reactive. All studies in healthy individuals are included by default, and differences (sex, age, protocol) are blocked for in the statistical model.
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Click 'calculate' after changing selection criteria to update your analysis.
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This plot provides an overview of the meta-analysis for the selected gene.
The plot is reactive and updated based on the selection criteria used in all individual forest plots.
The data and meta-analysis calculation for the selected gene and population of interest can be downloaded here:
Find the legend used for the annotation of studies.
Find the references for all studies of acute exercise included in MetaMEx.
Find the references for all studies of exercise training included in MetaMEx.
Find the references for all studies of inactivity included in MetaMEx.
Find the legend used for the annotation of studies.
Find the references for all studies of acute exercise included in MetaMEx.
Find the references for all studies of exercise training included in MetaMEx.
Find the references for all studies of inactivity included in MetaMEx.
Welcome to MetaMEx
The online database of skeletal muscle
transcriptomic response to exercise and inactivity. On this website,
you will be able to explore how specific genes respond to acute exercise,
exercise training and inactivity in all available transcriptomic datasets.
This section summarizes and explains the main analyses available on MetaMEx.
Start typing the gene name and suggestions will appear in the scroll menu. MetaMEx works with official gene symbols, for instance the official gene name of PGC1α is PPARGC1A.
Genes are sometimes present in the forest plots but not in the timeline plots. This is because the timeline is calculated by including all datasets and applying specific inclusion/exclusion to balance the linear model. This results in genes being excluded if they are not detected in enough datasets at each time point.
In order to give a transparent overview of the currently available data, all studies are presented, even if genes are not detected. Older studies, or custom arrays often have a limited number of probes and therefore fewer detected genes. On the other hand, the more recent RNA sequencing datasets often have more depth and detect non-coding RNAs which are not present in gene arrays.
A forest plot is a graphical representation of results from several scientific studies and is typically used to plot meta-analyses. The left-hand columns list the names of the studies, followed by the fold-change (log2), false discovery rate (FDR) and sample size (n) for each individual study. The right-hand column is a plot of the fold-change (log2) represented by a square and the 95% confidence intervals represented by horizontal lines. The area of each square is proportional to the study's weight (sample size) in the meta-analysis. The overall meta-analysed score is represented by a diamond on the bottom line, the lateral points of which indicate confidence intervals.
MetaMEx compiles more than 90 studies which include volunteers of different age, sex, weight, fitness, weight and health. Studies can be included or excluded from the analysis by scrolling at the bottom of the page and checking the boxes. For instance, select males or females by checking the corresponding tick boxes.
Sex. Choose whether you want males (M) or females (F). Some studies have pooled males and females or did not provide sex information and are labelled as undefined (U).
Age. Studies in MetaMEx are split into three age groups: young (<35), middle age (35-60) and elderly (>60).
Fitness. Activity levels were determined based on the description of the cohorts available in the publications. Sedentary is defined as no formal exercise training. Individuals performing exercise for more than 150 min per week and/or having an average VO2max are considered active. Athletes are individuals engaged in formal and regular exercise training and exhibit good to excellent VO2max.
Weight. Body composition is based on body mass index provided in the publications and the actual definition of lean (BMI<25), overweight (25≤BMI<30), obese (30≤BMI<40) and morbidly obese (BMI≥40).
Muscle. Most studies do cycling exercise and therefore collect vastus lateralis (quadriceps) biopsies. However, a handful of studies used soleus or biceps biopsies. Sometimes the muscle biopsy is unknow and is therefore annotated as N.A.
Health. MetaMEx includes studies from healthy individuals with no history of disease as well as people diagnosed with metabolic diseases or other chronic conditions such as chronic kidney disease or frailty.
After selecting either acute exercise, exercise training or inactivity, a specific menu will appear on the right of the page. This menu includes parameters such as exercise duration or time of biopsy collection after exercise cessation. Another list will appear under the forest plot to select or unselect specific datasets.