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Record W4382798403 · doi:10.1093/sleep/zsad174

Sleep apnea and diet-induced obesity—the female advantage on the spotlight

2023· letter· en· W4382798403 on OpenAlexaff
Mohammad Badran, Vincent Joseph

Bibliographic record

VenueSLEEP · 2023
Typeletter
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsObesitySleep apneaSleep (system call)MedicineObstructive sleep apneaApneaInternal medicinePediatricsPsychologyCardiologyComputer science

Abstract

fetched live from OpenAlex

The scientific journey that established the association between sleep-disordered breathing (SDB) and obesity started during the late 19th century, as medical practitioners sought to address whether obese patients with extreme daytime sleepiness had altered sleep patterns (see [1] for historical account). Cessations of breathing during sleep in these patients were reported, and anecdotical evidence that weight loss could resolve the daytime sleepiness was highlighted. One aspect of this history is the association of the typical figure of a middle-aged, obese, male patient, that characterized the “Pickwickian syndrome,” based on one of the characters of the “Posthumous Papers of the Pickwick Club,” a famous Charles Dickens novel. There was a hint of truth in this male-centered popular description, and the view that a “strong male predominance” of sleep apnea syndrome persisted in the literature during the late 20th century [2]. Current epidemiological data nonetheless indicate that the ratio of male to female in sleep apnea patients is around 2:1 to 3:1 [3, 4] and given the high prevalence of sleep apnea in the general population [3, 5], this indicates that a considerable number of women suffer from sleep apnea worldwide. Yet, as for most research on sleep apnea [6], the association with obesity remains far less studied in females than in males despite strong evidence that metabolic phenotypes largely differ in males and females [7, 8], and that across a large range of body mass index, the prevalence of sleep apnea remains lower in women [9]. The main objective of the study by Kim et al. was to investigate the effects of diet-induced obesity (DIO) on breathing and sleep in female mice [10], and to compare them to previously observed effects in male mice [11, 12]. Remarkably, they found that, unlike male mice, DIO did not lead to SDB in female mice. The study had four main findings. Firstly, obese female mice had reduced metabolism and showed decreased respiratory sensitivity to carbon dioxide (CO2) during wakefulness. Secondly, unlike males, DIO did not increase arousal frequency in females. However, sleep fragmentation in obese females was higher than previously reported in males, and mainly attributed to non-respiratory arousals (characterized by simultaneous respiratory and EEG/EMG recordings in freely behaving mice) suggesting that the primary cause of sleep disruption was not related to breathing abnormalities. Thirdly, compared to lean females, obese females were able to protect their ventilation, resulting in decreased severity of apnea, and more stable breathing during sleep. This was unexpected, as obesity is generally associated with breathing problems during sleep as highlighted above. Finally, obesity attenuated the ventilatory response to arousals, suggesting that the reduced severity of SDB in female mice with obesity could be due to this attenuated response. Sex differences in the effects of DIO have been previously observed, with female mice showing a delay in weight gain and resistance to metabolic dysfunctions associated with obesity [7, 8]. However, chronic high-fat feeding eventually leads to obesity in female mice. In this study, about 60% of female mice showed significant weight gain on a high-fat diet, reaching similar levels of obesity as male mice with DIO. Female DIO mice also exhibited increased body fat mass and severe hyperleptinemia, which are key features of human obesity. Metabolism (measures as whole body O2 consumption and CO2 production rates—corrected to body mass) in female DIO mice decreased, and this was related to the increased fat mass, but overall remained higher than previously reported in males with DIO, which corresponds to previous sex-specific findings [7]. This suggests that females may be relatively protected from the detrimental effects of obesity on metabolism compared to males. The study acknowledges several limitations that should be taken into consideration. Firstly, the analysis only focused on female mice, which limited the assessment of sex differences in DIO-induced SDB and sleep fragmentation. Previous data on male DIO mice were used for comparison, but direct analysis of sex differences was not performed. Secondly, the effects of the estrous cycle on sleep and SDB in obese mice could not be fully examined due to the limited number of mice that developed DIO. However, most mice in lean and DIO groups were in the proestrus and estrus phases, and the exclusion of mice in diestrus and metestrus did not affect the outcomes. It should be noted that chronic high-fat feeding can disrupt the female reproductive cycle, potentially compromising the analysis of the estrous cycle in the context of DIO [13, 14]. Thirdly, the study did not measure ovarian hormone levels in obese and lean females. While it is known that DIO increases estrogen levels in female mice [14], the interactions between ovarian hormones, CO2 sensitivity, arousal reflexes, and SDB are not sufficiently understood to explain the differences observed in this study. It should nonetheless be emphasized that reports from the literature show that variability of physiological or biological parameters in female mice is not different than what is observed in males, and sometimes even lower, across a wide range of variables [15, 16], and ignoring potential variability associated with the estrous cycle is perfectly acceptable in preclinical studies. While repeating the experiments in ovariectomized female mice is warranted to understand the roles of ovarian hormones and their interaction with DIO, the roles of testosterone in males on respiratory and metabolic responses in SDB should not be overlooked [17, 18]. Fourthly, sleep studies were conducted for only 6 hours during the light phase. Longer recordings could have provided a more comprehensive analysis of sleep architecture and sleep fragmentation in female mice. Lastly, the analysis of CO2 sensitivity was only performed during wakefulness. Measuring hypercapnic ventilatory response (HCVR) during sleep is challenging since mice are more likely to wake up with the 8% CO2 flush used in the experiment, and while the ventilatory response to arousal was carefully monitored, the arousal response to CO2 was not evaluated. These limitations highlight areas that could be addressed in future studies to further enhance our understanding of the effects of DIO on sleep and breathing, including the consideration of sex and age differences, the impact of the estrous cycle and gonadal hormones in males and females, and the comprehensive analysis of sleep architecture and CO2 sensitivity during sleep. As for clinical relevance, the study points towards a protective effect of female sex against sleep disruption and SDB in females compared to males, but also towards a protective effect in obese females compared to lean ones, which seems rather counterintuitive. Despite the controversial role of obesity in women and its effects on ventilatory responses to SDB, the findings of the current study should be interpreted with caution, since the detrimental effects on obesity, in general, outweigh any protective effects it may offer against SDB. Overall, this study provides insights into the complex relationship between obesity, breathing, and sleep, highlighting sex differences in the response to obesity. The findings of the study are descriptive in nature, but essential, nonetheless. The study contributes to our understanding of how obesity affects sleep-related health issues and the potential protective effects of female sex. Further research is needed to elucidate the underlying mechanisms driving these sex differences and their implications for human health. Financial disclosure: The authors have nothing to disclose. Nonfinancial disclosure: The authors have nothing to disclose.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.045
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0450.034
Insufficient payload (model declined to judge)0.0080.004

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.

Opus teacher head0.034
GPT teacher head0.295
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations2
Published2023
Admission routes1
Has abstractno

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