Mechanisms, Pathophysiology, and Management of Obesity
Bibliographic record
Abstract
The n e w e ng l a n d j o u r na l Hugh Calkins, M.D. Johns Hopkins Medical Institutions Baltimore, MD Since publication of their article, the authors report no fur- ther potential conflict of interest. 1. Rigato I, Bauce B, Rampazzo A, et al. Compound and di- genic heterozygosity predicts lifetime arrhythmic outcome and sudden cardiac death in desmosomal gene-related arrhythmo- genic right ventricular cardiomyopathy. Circ Cardiovasc Genet 2. Corrado D, Wichter T, Link MS, et al. Treatment of arrhythmo- of m e dic i n e genic right ventricular cardiomyopathy/dysplasia: an Internation- al Task Force consensus statement. Circulation 2015;132:441-53. 3. Hodgkinson KA, Howes AJ, Boland P, et al. Long-term clini- cal outcome of arrhythmogenic right ventricular cardiomyopa- thy in individuals with a p.S358L mutation in TMEM43 following implantable cardioverter defibrillator therapy. Circ Arrhythm Electrophysiol 2016;9(9):e003589. 4. Haywood AF, Merner ND, Hodgkinson KA, et al. Recurrent missense mutations in TMEM43 (ARVD5) due to founder effects cause arrhythmogenic cardiomyopathies in the UK and Canada. Eur Heart J 2013;34:1002-11. DOI: 10.1056/NEJMc1701400 Mechanisms, Pathophysiology, and Management of Obesity To the Editor: The review article by Heymsfield and Wadden (Jan. 19 issue) 1 is valuable with re- spect to the clinical management of obesity, but information about the contribution of mitochon- drial genes to obesity is not included. Mitochon- drial dysfunction is associated with an accumu- lation of fat that can occur during aging and in patients with obesity, the metabolic syndrome, or diabetes mellitus. 2 Zheng et al. 3 found that obese participants with a high metabolic syndrome score have in- creased DNA methylation in the mitochondrial genes MT-CO1 and MT-ND6 and in the mitochon- drion-related nuclear gene PPARGC1A. Flaquer et al. 4 conducted a study using samples obtained from 6528 participants in the KORA (Coopera- tive Health Research in the Region of Augsburg) studies and found that two mitochondrial single- nucleotide polymorphisms (SNPs) located in the cytochrome c oxidase subunit genes (MT-CO1 and MT-CO3) and three mitochondrial SNPs located in the NADH dehydrogenase subunit genes (MT-ND1, MT-ND2, and MT-ND4L) were significantly asso- ciated with a higher body-mass index (BMI). Latorre-Pellicer et al. 5 systematically character- ized conplastic mice (mice in which the nuclear genome of one mouse is backcrossed into the cy- toplasm of another, so that the nuclear genes and mitochondrial genes are from different parents) throughout their lifespan. They found that the mitochondrial DNA haplotype profoundly influ- ences mitochondrial proteostasis and generation of reactive oxygen species, insulin signaling, telo- mere shortening, the development of obesity, and mitochondrial dysfunction. These findings high- light the importance of the contribution of mito- chondrial genetic variants to the risk of a high BMI. Nai‑Wei Sheu, M.D. Yu‑Chih Lin, M.D. Kaohsiung Medical University Hospital Kaohsiung, Taiwan Chung‑Jen Chen, M.D. Kaohsiung Medical University College of Medicine Kaohsiung, Taiwan cjchen@kmu.edu.t w No potential conflict of interest relevant to this letter was re- ported. 1. Heymsfield SB, Wadden TA. Mechanisms, pathophysiology, and management of obesity. N Engl J Med 2017;376:254-66. 2. Lopez-Lluch G. Mitochondrial activity and dynamics changes regarding metabolism in ageing and obesity. Mech Ageing Dev 2016 December 16 (Epub ahead of print). 3. Zheng LD, Brooke J, Smith C, Almeida FA, Cheng Z. Mito- chondrial epigenetic changes and progression from metaboli- cally healthy obesity to metabolically unhealthy obesity: a cross- sectional study. Lancet Diabetes Endocrinol 2016;4:Suppl 1:S16. 4. Flaquer A, Baumbach C, Kriebel J, et al. Mitochondrial ge- netic variants identified to be associated with BMI in adults. PLoS One 2014;9(8):e105116. 5. Latorre-Pellicer A, Moreno-Loshuertos R, Lechuga-Vieco AV, et al. Mitochondrial and nuclear DNA matching shapes metabo- lism and healthy ageing. Nature 2016;535:561-5. DOI: 10.1056/NEJMc1701944 To the Editor: Heymsfield and Wadden iden- tify environmental and genetic factors as well as energy-balance dysregulation as the leading mech- anisms of obesity, and they describe therapeutic lifestyle changes, adjunctive pharmacotherapy, and bariatric surgery as the main treatment strate- gies for this condition. We would like to point out that emotional factors can influence overeat- ing that results in overweight and obesity. 1 Emerging data suggest that addictive overeat- ing is a common experience of obese persons. 1 In one randomized trial, mothers had significant and clinically important reductions in weight when their school-age children were taught about nutri- n engl j med 376;15 nejm.org April 13, 2017 The New England Journal of Medicine Downloaded from nejm.org by ROBERT LUSTIG on April 25, 2017. For personal use only. No other uses without permission. Copyright © 2017 Massachusetts Medical Society. All rights reserved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".