Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Testosterone: Functions and Regulation01:26

Testosterone: Functions and Regulation

676
The intricate hormonal interplay essential for male reproductive health begins with the release of gonadotropin-releasing hormone (GnRH) by the hypothalamus. This hormone prompts the pituitary gland to secrete follicle-stimulating hormone (FSH) and luteinizing hormone (LH). LH targets the Leydig cells in the testes, stimulating them to produce and release testosterone. In concert with testosterone, FSH acts on the Sertoli cells within the seminiferous tubules to facilitate the release of...
676
Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

43
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
43
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

225
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
225
Randomized Experiments01:13

Randomized Experiments

7.0K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
7.0K
Two-Way ANOVA01:17

Two-Way ANOVA

2.6K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Androgen Receptor Splice Variant-7 Expression Analysis in Circulating Tumor Cells: Methodology and Application of AdnaTest in Prostate Cancer Research.

Methods in molecular biology (Clifton, N.J.)·2026
Same author

Pain-centered symptom-language co-occurrence networks differ between interstitial cystitis/bladder pain syndrome and fibromyalgia in Reddit patient discourse.

Scientific reports·2026
Same author

Enhancing Continence Recovery After Robot-Assisted Radical Prostatectomy: A Novel Combined Approach Using Testosterone Therapy and Magnetic Stimulation.

The Prostate·2026
Same author

Nationwide epidemiological survey of autosomal dominant polycystic kidney disease in Japan in 2022.

Clinical and experimental nephrology·2026
Same author

In Older Men With Persistent Nocturia Due to Nocturnal Polyuria, Desmopressin Is Effective for Those With Higher Muscle Mass.

Lower urinary tract symptoms·2026
Same author

Prevalence and prognostic impact of cancer cachexia in patients with bladder cancer: a multicenter retrospective study.

International journal of clinical oncology·2026

Related Experiment Video

Updated: Jul 8, 2025

Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
11:51

Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making

Published on: March 2, 2011

15.1K

Body composition and testosterone in men: a Mendelian randomization study.

Yoshihiro Ikehata1, Tsuyoshi Hachiya2, Takuro Kobayashi1

  • 1Department of Urology, Juntendo University, Graduate School of Medicine, Tokyo, Japan.

Frontiers in Endocrinology
|December 13, 2023
PubMed
Summary

Reducing body fat mass may increase testosterone levels in men. This study used Mendelian randomization to explore the causal link between body composition and testosterone, finding a significant negative association with fat mass.

Keywords:
BMIMendelian randomizationbody compositionexercisefat massfat-free masstestosterone levels

More Related Videos

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies
06:27

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies

Published on: January 10, 2025

765
Skeletal Muscle Gender Dimorphism from Proteomics
09:29

Skeletal Muscle Gender Dimorphism from Proteomics

Published on: December 14, 2011

12.6K

Related Experiment Videos

Last Updated: Jul 8, 2025

Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
11:51

Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making

Published on: March 2, 2011

15.1K
Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies
06:27

Establishment of Rat Models Mimicking Gender-affirming Hormone Therapies

Published on: January 10, 2025

765
Skeletal Muscle Gender Dimorphism from Proteomics
09:29

Skeletal Muscle Gender Dimorphism from Proteomics

Published on: December 14, 2011

12.6K

Area of Science:

  • Endocrinology
  • Genetics
  • Human Physiology

Background:

  • Testosterone is a crucial male sex hormone impacting overall health and development.
  • While obesity is known to lower testosterone, the precise causal relationship with body composition remains unclear.

Purpose of the Study:

  • To investigate the causal associations between various body composition metrics and testosterone levels using Mendelian randomization.
  • To determine if specific body fat or fat-free mass distribution influences testosterone.

Main Methods:

  • Employed Mendelian randomization with genome-wide association study data from the UK Biobank.
  • Utilized genetic instruments for 13 body composition traits (fat mass, fat-free mass, BMI) as exposures.
  • Assessed total testosterone (TT), bioavailable testosterone (BT), and sex hormone-binding globulin (SHBG) as outcomes.

Main Results:

  • Genetically predicted whole body fat mass showed a significant negative association with TT, BT, and SHBG.
  • Genetically predicted whole body fat-free mass was negatively associated with BT, but not TT or SHBG.
  • The impact of fat mass on testosterone levels was more pronounced than that of fat-free mass, with no significant differences observed between body parts.

Conclusions:

  • Reducing body fat mass is suggested as a potential strategy to increase testosterone levels.
  • The findings provide causal evidence linking higher fat mass to lower testosterone in men.