The Response to Long-Term Overfeeding in Identical Twins
Open accessAbstract
We undertook this study to determine whether there are differences in the responses of different persons to long-term overfeeding and to assess the possibility that genotypes are involved in such differences. After a two-week base-line period, 12 pairs of young adult male monozygotic twins were overfed by 4.2 MJ (1000 kcal) per day, 6 days a week, for a total of 84 days during a 100-day period. The total excess amount each man consumed was 353 MJ (84,000 kcal). During overfeeding, individual changes in body composition and topography of fat deposition varied considerably. The mean weight gain was 8.1 kg, but the range was 4.3 to 13.3 kg. The similarity within each pair in the response to overfeeding was significant (P less than 0.05) with respect to body weight, percentage of fat, fat mass, and estimated subcutaneous fat, with about three times more variance among pairs than within pairs (r approximately 0.5). After adjustment for the gains in fat mass, the within-pair similarity was particularly evident with respect to the changes in regional fat distribution and amount of abdominal visceral fat (P less than 0.01), with about six times as much variance among pairs as within pairs (r approximately 0.7). We conclude that the most likely explanation for the intrapair similarity in the adaptation to long-term overfeeding and for the variations in weight gain and fat distribution among the pairs of twins is that genetic factors are involved. These may govern the tendency to store energy as either fat or lean tissue and the various determinants of the resting expenditure of energy.
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Multiple lines of evidence from evolutionary history, genetic and twin studies support a genetic basis for obesity and differences in obese and lean phenotypes in women with PCOS.
“Multiple lines of evidence from evolutionary history, genetic and twin studies, support a genetic basis for obesity and differences in obese and lean phenotypes in women with PCOS [183,184,185,186].”
From Polycystic Ovary Syndrome: An Evolutionary Adaptation to Lifestyle and the Environment (2022) · cites this paper as [185]
In the Quebec feeding study on monozygotic twins, although members of the twin pairs were equally overfed, the variation in weight gained between pairs of twins was large, whereas the variation within any pair of twins was small.
“Although members of the twin pairs were equally overfed, the variation in weight gained between pairs of twins was large (whereas the variation within any pair of twins was small).”
From Appetite control and energy balance: Impact of exercise (2015) · cites this paper as [51]
Identical twin studies suggest that genetic factors account for 50-90% of the variance in weight gain.
“Identical twin studies suggest that genetic factors account for 50–90% of the variance in weight gain 39,40.”
From Cellular bioenergetics as a target for obesity therapy (2010) · cites this paper as [39]
>3-fold variations in energy expenditure and weight gain have been observed in response to overfeeding in normal lean individuals.
“Indeed, >3-fold variations in energy expenditure and weight gain have been observed in response to overfeeding in normal lean individuals 39.”
From Cellular bioenergetics as a target for obesity therapy (2010) · cites this paper as [39]
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Pileggi, C. A., Hooks, B. G., McPherson, R., Dent, R. R. M., & Harper, M.-E. (2022) · Clinical Science · doi:10.1042/cs20210506 · Cited by 21 · see citing works
Can your microbiome tell you what to eat?
Vanamala, J. K. P., Knight, R., & Spector, T. D. (2015) · Cell Metabolism · doi:10.1016/j.cmet.2015.11.009 · Cited by 20 · see citing works
Heritability of running economy: a study made on twin brothers
Rodas, G., Calvo, M., Estruch, A., Garrido, E., Ercilla, G., Arcas, A., Segura, R., & Ventura, J. L. (1998) · European Journal of Applied Physiology · doi:10.1007/s004210050368 · Cited by 17 · see citing works
Lakka, H.-M., Tremblay, A., Després, J.-P., & Bouchard, C. (2004) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2003.09.012 · Cited by 17 · see citing works
Self-citationBiology or Behavior: Which Is the Strongest Contributor to Weight Gain?
Byrne, N. M., & Hills, A. P. (2013) · Current Obesity Reports · doi:10.1007/s13679-012-0040-9 · Cited by 13 · see citing works
- Authors
- Bouchard, C., Tremblay, A., Després, J.-P., Nadeau, A., Lupien, P. J., Thériault, G., Dussault, J., Moorjani, S., Pinault, S., & Fournier, G.
- Affiliations
- Université Laval (CA)
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 1990-05-24
- Volume
- 322
- Issue
- 21
- Pages
- 1477-1482
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2319231450
- Cited by
- 1,278
- References
- 20
- Citations by year
- 2026: 13 · 2025: 5 · 2024: 11 · 2023: 32 · 2022: 21 · 2021: 17 · 2020: 31 · 2019: 26 · 2018: 26 · 2017: 45 · 2016: 38 · 2015: 38 · 2014: 41 · 2013: 48 · 2012: 67
- FWCI
- 21.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK034624, DK34624)
- Topics
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Regulation of Appetite and Obesity
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Keywords
- monozygotic twins, genetic factors, weight gain, body composition, fat mass, regional fat distribution, visceral fat, subcutaneous adipose tissue, energy expenditure, energy storage
- MeSH terms
- Adult, Body Composition, Energy Intake, Humans, Hyperphagia, Male, Obesity, Twins, Twins, Monozygotic, Weight Gain
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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