Skip to content
2000
image of Causal Mediation Analysis of the Effect of Dietary Habits on Sleep Apnea Risk

Abstract

Objective

Diet is a modifiable factor that influences several chronic diseases, making lifelong dietary interventions critically important for reducing disease risk. Hence, this study aims to assess the potential causal relationship between diet and sleep apnea (SA).

Methods

We analyzed genome-wide association study (GWAS) data from approximately 450,000 individuals, focusing on 8 dietary intakes and GWAS statistics for 249 metabolites from the UK Biobank. Sleep apnea-related phenotypic data from 16,761 participants were sourced from the FinnGen Biobank. Furthermore, we conducted a series of two-sample Mendelian Randomization (two-sample MR) to explore the causality between diet and SA. Sensitivity analyses were conducted to assess the robustness of the two-sample MR results, and reverse MR analysis was performed to examine potential reverse causality. Multivariate MR (MVMR) analysis and mediation effect estimation were employed to evaluate the mediating roles of metabolites.

Results

Two-sample MR analyses revealed significant causal associations between bread intake (OR=0.56, 95% CI 0.35–0.89, =0.014), cheese intake (OR=0.67, 95% CI 0.50–0.89, =0.006), and dried fruit intake (OR=0.61, 95% CI 0.39–0.95, =0.029) with SA. Reverse MR analysis indicated a causal effect of SA on dried fruit intake ( < 0.05). Univariate MR analyses further identified significant causal effects of bread and cheese intakes on 2 and 32 metabolites, respectively ( < 0.05). Subsequent MVMR analysis demonstrated direct causal effects of bread and cheese intake on SA, independent of metabolite mediation ( < 0.05). Furthermore, the mediating effect of cheese intake on SA through glucose was estimated at 0.023 (90% CI 0.01–0.046), whereas other modeled mediation effects were not statistically significant.

Conclusion

The MR analysis in this study offers genetic evidence indicating that heightened genetic susceptibility to cheese and bread intake potentially reduces SA risk. These findings underscore and validate the significance of diet in preventing SA.

Loading

Article metrics loading...

/content/journals/cchts/10.2174/0113862073348527250124113458
2025-02-06
2025-09-14
Loading full text...

Full text loading...

References

  1. Lyons M.M. Bhatt N.Y. Pack A.I. Magalang U.J. Global burden of sleep‐disordered breathing and its implications. Respirology 2020 25 7 690 702 10.1111/resp.13838 32436658
    [Google Scholar]
  2. Alchallah M.O. Safiah M.H. Belah Kajjoun M.M. Kalalib Al Ashabi K. Ataya S. Mohsen F. Bakdounes D. ElHomsi M.O. Alolabi H. Alistwani D. Alzein A. Ayash A. Youzbashi L. Darjazini Nahas L. Prevalence of childhood obstructive sleep apnoea syndrome and its role in daytime sleepiness in Syria: A large-scale school-based cross-sectional study. Ann. Med. Surg. (Lond.) 2023 85 6 2579 2586 10.1097/MS9.0000000000000820 37363593
    [Google Scholar]
  3. Benjafield A.V. Ayas N.T. Eastwood P.R. Heinzer R. Ip M.S.M. Morrell M.J. Nunez C.M. Patel S.R. Penzel T. Pépin J.L. Peppard P.E. Sinha S. Tufik S. Valentine K. Malhotra A. Estimation of the global prevalence and burden of obstructive sleep apnoea: A literature-based analysis. Lancet Respir. Med. 2019 7 8 687 698 10.1016/S2213‑2600(19)30198‑5 31300334
    [Google Scholar]
  4. Nieto F.J. Young T.B. Lind B.K. Shahar E. Samet J.M. Redline S. D’Agostino R.B. Newman A.B. Lebowitz M.D. Pickering T.G. Association of sleep-disordered breathing, sleep apnea, and hypertension in a large community-based study. Sleep Heart Health Study. JAMA 2000 283 14 1829 1836 10.1001/jama.283.14.1829 10770144
    [Google Scholar]
  5. Bradley T.D. Logan A.G. Floras J.S. Treating sleep disordered breathing for cardiovascular outcomes: Observational and randomised trial evidence. Eur. Respir. J. 2024 64 6 2401033 10.1183/13993003.01033‑2024 39638419
    [Google Scholar]
  6. Strausz S. Havulinna A.S. Tuomi T. Bachour A. Groop L. Mäkitie A. Koskinen S. Salomaa V. Palotie A. Ripatti S. Palotie T. Obstructive sleep apnoea and the risk for coronary heart disease and type 2 diabetes: A longitudinal population-based study in Finland. BMJ Open 2018 8 10 e022752 10.1136/bmjopen‑2018‑022752 30327404
    [Google Scholar]
  7. Chen B. Chen L. Dai Y. Wu J. Zheng D. Vgontzas A.N. Tang X. Li Y. The different roles of homocysteine metabolism in hypertension among normal-weight and obese patients with obstructive sleep apnea. Sleep Med. 2024 120 1 9 10.1016/j.sleep.2024.05.050 38824846
    [Google Scholar]
  8. Urbano G.L. Tablizo B.J. Moufarrej Y. Tablizo M.A. Chen M.L. Witmans M. The link between pediatric obstructive sleep apnea (OSA) and attention deficit hyperactivity disorder (ADHD). Children (Basel) 2021 8 9 824 10.3390/children8090824 34572256
    [Google Scholar]
  9. Kansagra S. Sleep disorders in adolescents. Pediatrics 2020 145 Suppl. 2 S204 S209 10.1542/peds.2019‑2056I 32358212
    [Google Scholar]
  10. Watson N.F. Health care savings: The economic value of diagnostic and therapeutic care for obstructive sleep apnea. J. Clin. Sleep Med. 2016 12 8 1075 1077 10.5664/jcsm.6034 27448424
    [Google Scholar]
  11. Watson N.F. Badr M.S. Belenky G. Bliwise D.L. Buxton O.M. Buysse D. Dinges D.F. Gangwisch J. Grandner M.A. Kushida C. Malhotra R.K. Martin J.L. Patel S.R. Quan S.F. Tasali E. Twery M. Croft J.B. Maher E. Barrett J.A. Thomas S.M. Heald J.L. Joint consensus statement of the american academy of sleep medicine and sleep research society on the recommended amount of sleep for a healthy adult: Methodology and discussion. Sleep 2015 38 8 1161 1183 10.5665/sleep.4886 26194576
    [Google Scholar]
  12. Mogavero M.P. DelRosso L.M. Fanfulla F. Bruni O. Ferri R. Sleep disorders and cancer: State of the art and future perspectives. Sleep Med. Rev. 2021 56 101409 10.1016/j.smrv.2020.101409 33333427
    [Google Scholar]
  13. Gupta A. Kaur J. Shukla G. Bhullar K.K. Lamo P. Kc B. Agarwal A. Srivastava A.K. Sharma G. Effect of yoga-based lifestyle and dietary modification in overweight individuals with sleep apnea: A randomized controlled trial (ELISA). Sleep Med. 2023 107 149 156 10.1016/j.sleep.2023.04.020 37178546
    [Google Scholar]
  14. Gaona-Pineda E.B. Martinez-Tapia B. Rodríguez-Ramírez S. Guerrero-Zúñiga S. Perez-Padilla R. Shamah-Levy T. Dietary patterns and sleep disorders in mexican adults from a national health and nutrition survey. J. Nutr. Sci. 2021 10 e34 10.1017/jns.2021.24 34094514
    [Google Scholar]
  15. Chuang H.H. Lin R.H. Hsu J.F. Chuang L.P. Li H.Y. Fang T.J. Huang Y.S. Yang A.C. Lee G.S. Kuo T.B.J. Yang C.C.H. Lee L.A. Dietary profile of pediatric obstructive sleep apnea patients, effects of routine educational counseling, and predictors for outcomes. Front. Publ. Heal. 2023 11 1160647 10.3389/fpubh.2023.1160647 37377550
    [Google Scholar]
  16. Shi Y. Xu J. Yi S. Xu C. Yu F. Gu W. Zhang J. Ye L. Effects of high dietary carbohydrate intake in patients with obstructive sleep apnea. Sleep Breath. 2025 29 1 20 10.1007/s11325‑024‑03188‑w 39607637
    [Google Scholar]
  17. Carratù P. Dragonieri S. Quaranta V.N. Resta O. Portincasa P. Palmieri V.O. Carpagnano G.E. One Year Follow-Up Assessment of Impact of Rigorous Diet Regimen and Adequate C-PAP Therapy on Obese Patients with Obstructive Sleep Apnea Syndrome: A Retrospective Study. J. Clin. Med. 2024 13 21 6360 10.3390/jcm13216360 39518499
    [Google Scholar]
  18. Sekula P. Del Greco M F. Pattaro C. Köttgen A. Mendelian Randomization as an Approach to Assess Causality Using Observational Data. J. Am. Soc. Nephrol. 2016 27 11 3253 3265 10.1681/ASN.2016010098 27486138
    [Google Scholar]
  19. chen Y. Luo Y. Long J. liu S. zhao L. chen B. mu Q. TOMM40 Correlates with Cholesterol and is Predictive of a Favorable Prognosis in Endometrial Carcinoma. Comb. Chem. High Throughput Screen. 2024 28 4 592 607 10.2174/0113862073270411240102060240 38231050
    [Google Scholar]
  20. Liu X. Yang W. Yang Y. Exploring Dietary Factors and Esophageal Adenocarcinoma: Insights From Mendelian Randomization Study. Food Sci. Nutr. 2024 12 11 9600 9606 10.1002/fsn3.4527 39620031
    [Google Scholar]
  21. Chen K. Wang X. Shang Z. Li Q. Yao W. Guo S. Guan Y. Exploring the Causal Effects of Gut Microbiota on Diabetic Nephropathy: A Two-Sample Mendelian Randomization Study. Comb. Chem. High Throughput Screen. 2024 28 6 1026 1038 10.2174/0113862073311197240425073859 38676512
    [Google Scholar]
  22. Zhang R. Luo L. Zhang L. Lin X. Wu C. Jiang F. Wang J. Genetically supported causality between brain structural connectome and sleep duration in children: A two-sample Mendelian randomization study. eNeuro 2024 11 12 ENEURO.0267-24.2024 10.1523/ENEURO.0267‑24.2024 39632091
    [Google Scholar]
  23. BaHammam A. Jahrami H. Navigating Mendelian Randomization in Sleep Medicine: Challenges, Opportunities, and Best Practices. Nat. Sci. Sleep 2024 16 1811 1825 10.2147/NSS.S495411 39600493
    [Google Scholar]
  24. Cortese R. Inferring causality: Mendelian randomization in biomarker studies in obstructive sleep apnea. Sleep 2024 zsae274 10.1093/sleep/zsae274 39574248
    [Google Scholar]
  25. Ma Z. Zhao H. Zhao M. Zhang J. Qu N. Gut microbiotas, inflammatory factors, and mental-behavioral disorders: A mendelian randomization study. J. Affect. Disord. 2025 371 113 123 10.1016/j.jad.2024.11.049 39566744
    [Google Scholar]
  26. Skrivankova V.W. Richmond R.C. Woolf B.A.R. Yarmolinsky J. Davies N.M. Swanson S.A. VanderWeele T.J. Higgins J.P.T. Timpson N.J. Dimou N. Langenberg C. Golub R.M. Loder E.W. Gallo V. Tybjaerg-Hansen A. Davey Smith G. Egger M. Richards J.B. Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization. JAMA 2021 326 16 1614 1621 10.1001/jama.2021.18236 34698778
    [Google Scholar]
  27. Tang L. Next-generation peptide sequencing. Nat. Methods 2018 15 12 997 997 10.1038/s41592‑018‑0240‑7 30504869
    [Google Scholar]
  28. Kurki M.I. Karjalainen J. Palta P. Sipilä T.P. Kristiansson K. Donner K.M. Reeve M.P. Laivuori H. Aavikko M. Kaunisto M.A. Loukola A. Lahtela E. Mattsson H. Laiho P. Della Briotta Parolo P. Lehisto A.A. Kanai M. Mars N. Rämö J. Kiiskinen T. Heyne H.O. Veerapen K. Rüeger S. Lemmelä S. Zhou W. Ruotsalainen S. Pärn K. Hiekkalinna T. Koskelainen S. Paajanen T. Llorens V. Gracia-Tabuenca J. Siirtola H. Reis K. Elnahas A.G. Sun B. Foley C.N. Aalto-Setälä K. Alasoo K. Arvas M. Auro K. Biswas S. Bizaki-Vallaskangas A. Carpen O. Chen C.Y. Dada O.A. Ding Z. Ehm M.G. Eklund K. Färkkilä M. Finucane H. Ganna A. Ghazal A. Graham R.R. Green E.M. Hakanen A. Hautalahti M. Hedman Å.K. Hiltunen M. Hinttala R. Hovatta I. Hu X. Huertas-Vazquez A. Huilaja L. Hunkapiller J. Jacob H. Jensen J.N. Joensuu H. John S. Julkunen V. Jung M. Junttila J. Kaarniranta K. Kähönen M. Kajanne R. Kallio L. Kälviäinen R. Kaprio J. Kerimov N. Kettunen J. Kilpeläinen E. Kilpi T. Klinger K. Kosma V.M. Kuopio T. Kurra V. Laisk T. Laukkanen J. Lawless N. Liu A. Longerich S. Mägi R. Mäkelä J. Mäkitie A. Malarstig A. Mannermaa A. Maranville J. Matakidou A. Meretoja T. Mozaffari S.V. Niemi M.E.K. Niemi M. Niiranen T. O´Donnell C.J. Obeidat M. Okafo G. Ollila H.M. Palomäki A. Palotie T. Partanen J. Paul D.S. Pelkonen M. Pendergrass R.K. Petrovski S. Pitkäranta A. Platt A. Pulford D. Punkka E. Pussinen P. Raghavan N. Rahimov F. Rajpal D. Renaud N.A. Riley-Gillis B. Rodosthenous R. Saarentaus E. Salminen A. Salminen E. Salomaa V. Schleutker J. Serpi R. Shen H. Siegel R. Silander K. Siltanen S. Soini S. Soininen H. Sul J.H. Tachmazidou I. Tasanen K. Tienari P. Toppila-Salmi S. Tukiainen T. Tuomi T. Turunen J.A. Ulirsch J.C. Vaura F. Virolainen P. Waring J. Waterworth D. Yang R. Nelis M. Reigo A. Metspalu A. Milani L. Esko T. Fox C. Havulinna A.S. Perola M. Ripatti S. Jalanko A. Laitinen T. Mäkelä T.P. Plenge R. McCarthy M. Runz H. Daly M.J. Palotie A. FinnGen FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 2023 613 7944 508 518 10.1038/s41586‑022‑05473‑8 36653562
    [Google Scholar]
  29. Lawlor D.A. Harbord R.M. Sterne J.A.C. Timpson N. Davey Smith G. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology. Stat. Med. 2008 27 8 1133 1163 10.1002/sim.3034 17886233
    [Google Scholar]
  30. Kamat M.A. Blackshaw J.A. Young R. Surendran P. Burgess S. Danesh J. Butterworth A.S. Staley J.R. PhenoScanner V2: An expanded tool for searching human genotype–phenotype associations. Bioinformatics 2019 35 22 4851 4853 10.1093/bioinformatics/btz469 31233103
    [Google Scholar]
  31. Pierce B.L. Ahsan H. VanderWeele T.J. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int. J. Epidemiol. 2011 40 3 740 752 10.1093/ije/dyq151 20813862
    [Google Scholar]
  32. Bowden J. Davey Smith G. Haycock P.C. Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet. Epidemiol. 2016 40 4 304 314 10.1002/gepi.21965 27061298
    [Google Scholar]
  33. Bowden J. Davey Smith G. Burgess S. Mendelian randomization with invalid instruments: Effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 2015 44 2 512 525 10.1093/ije/dyv080 26050253
    [Google Scholar]
  34. Li J. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 2017 13 11 29131815
    [Google Scholar]
  35. Huang Z. Zheng Z. Pang L. Fu K. Cheng J. Zhong M. Song L. Guo D. Chen Q. Li Y. Lv Y. Chen R. Sun X. The Association between Obstructive Sleep Apnea and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study. Thromb. Haemost. 2024 124 11 1061 1074 10.1055/a‑2308‑2290 38631385
    [Google Scholar]
  36. Weng H. Li H. Zhang Z. Zhang Y. Xi L. Zhang D. Deng C. Wang D. Chen R. Chen G. Tang S. Zuo X. Yang P. Zhai Z. Wang C. Association between uric acid and risk of venous thromboembolism in East Asian populations: A cohort and Mendelian randomization study. Lancet Reg. Health West. Pac. 2023 39 100848 10.1016/j.lanwpc.2023.100848 37565068
    [Google Scholar]
  37. Lazzeroni L.C. Lu Y. Belitskaya-Lévy I. Solutions for quantifying P-value uncertainty and replication power. Nat. Methods 2016 13 2 107 108 10.1038/nmeth.3741 26820540
    [Google Scholar]
  38. Huang S. He Q. Wang X. Choi S. Gong H. Associations of the planetary health diet index (PHDI) with asthma: The mediating role of body mass index. BMC Publ. Heal. 2024 24 1 2305 10.1186/s12889‑024‑19856‑1 39187832
    [Google Scholar]
  39. Tang M. Song X. Zhong W. Xie Y. Liu Y. Zhang X. Dietary fiber ameliorates sleep disturbance connected to the gut–brain axis. Food Funct. 2022 13 23 12011 12020 10.1039/D2FO01178F 36373848
    [Google Scholar]
  40. Zhao M. Tuo H. Wang S. Zhao L. The effects of dietary nutrition on sleep and sleep disorders. Mediators Inflamm. 2020 2020 1 7 10.1155/2020/3142874 32684833
    [Google Scholar]
  41. Meszaros M. Tarnoki A.D. Tarnoki D.L. Kovacs D.T. Forgo B. Lee J. Sung J. Vestbo J. Müller V. Kunos L. Bikov A. Obstructive sleep apnea and hypertriglyceridaemia share common genetic background: Results of a twin study. J. Sleep Res. 2020 29 4 e12979 10.1111/jsr.12979 31908118
    [Google Scholar]
  42. Martínez-Cerón E. Casitas R. Galera R. Sánchez-Sánchez B. Zamarrón E. Garcia-Sanchez A. Jaureguizar A. Cubillos-Zapata C. Garcia-Rio F. Contribution of sleep characteristics to the association between obstructive sleep apnea and dyslipidemia. Sleep Med. 2021 84 8 63 72 10.1016/j.sleep.2021.05.012 34111805
    [Google Scholar]
  43. Patel K. Lawson M. Cheung J. Whole-food plant-based diet reduces daytime sleepiness in patients with OSA. Sleep Med. 2023 107 327 329 10.1016/j.sleep.2023.05.007 37285791
    [Google Scholar]
  44. Tang H. Zhou Q. Zheng F. Wu T. Tang Y.D. Jiang J. The causal effects of lipid profiles on sleep apnea. Front. Nutr. 2022 9 910690 10.3389/fnut.2022.910690 35799595
    [Google Scholar]
  45. Kettunen J. Demirkan A. Würtz P. Draisma H.H.M. Haller T. Rawal R. Vaarhorst A. Kangas A.J. Lyytikäinen L.P. Pirinen M. Pool R. Sarin A.P. Soininen P. Tukiainen T. Wang Q. Tiainen M. Tynkkynen T. Amin N. Zeller T. Beekman M. Deelen J. van Dijk K.W. Esko T. Hottenga J.J. van Leeuwen E.M. Lehtimäki T. Mihailov E. Rose R.J. de Craen A.J.M. Gieger C. Kähönen M. Perola M. Blankenberg S. Savolainen M.J. Verhoeven A. Viikari J. Willemsen G. Boomsma D.I. van Duijn C.M. Eriksson J. Jula A. Järvelin M.R. Kaprio J. Metspalu A. Raitakari O. Salomaa V. Slagboom P.E. Waldenberger M. Ripatti S. Ala-Korpela M. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nat. Commun. 2016 7 1 11122 10.1038/ncomms11122 27005778
    [Google Scholar]
  46. Wu W.T. Tsai S.S. Shih T.S. Lin M.H. Chou T.C. Ting H. Wu T.N. Liou S.H. The association between obstructive sleep apnea and metabolic markers and lipid profiles. PLoS One 2015 10 6 e0130279 10.1371/journal.pone.0130279 26115005
    [Google Scholar]
  47. Shahavandi M. The association between dairy products consumption with risk of type 1 diabetes mellitus in children: A meta-analysis of observational studies. Int. J. Diabe. Develop. Countr. 2021 41 369 376 10.1007/s13410‑021‑00923‑x
    [Google Scholar]
  48. Vanderhout S.M. Aglipay M. Torabi N. Jüni P. da Costa B.R. Birken C.S. O’Connor D.L. Thorpe K.E. Maguire J.L. Whole milk compared with reduced-fat milk and childhood overweight: A systematic review and meta-analysis. Am. J. Clin. Nutr. 2020 111 2 266 279 10.1093/ajcn/nqz276
    [Google Scholar]
  49. Giosuè A. Calabrese I. Vitale M. Riccardi G. Vaccaro O. Consumption of dairy foods and cardiovascular disease: A systematic review. Nutrients 2022 14 4 831 10.3390/nu14040831 35215479
    [Google Scholar]
  50. Kechribari I. Kontogianni M.D. Fragopoulou E. Tenta R. Georgoulis M. Lamprou K. Vagiakis E. Yiannakouris N. Adherence to a “Western-type” dietary pattern is positively associated with the Apnea-Hypopnea Index in adults with obstructive sleep apnea. Nutr. Res. 2023 117 56 65 10.1016/j.nutres.2023.06.006 37480783
    [Google Scholar]
  51. Bove C. Jain V. Younes N. Hynes M. What you eat could affect your sleep: Dietary findings in patients with newly diagnosed obstructive sleep apnea. Am. J. Lifestyle Med. 2021 15 3 305 312 10.1177/1559827618765097 34025323
    [Google Scholar]
  52. Yang Y. Wang X. Yang W. A mendelian randomization study investigating the association between sleep apnea risk and cheese consumption through biomarker analysis. Sleep Med. 2024 124 737 744 10.1016/j.sleep.2024.10.029 39551000
    [Google Scholar]
  53. Gijsbers L. Ding E.L. Malik V.S. de Goede J. Geleijnse J.M. Soedamah-Muthu S.S. Consumption of dairy foods and diabetes incidence: A dose-response meta-analysis of observational studies. Am. J. Clin. Nutr. 2016 103 4 1111 1124 10.3945/ajcn.115.123216
    [Google Scholar]
  54. Fathi S. Vahdat M. Saeedirad Z. Hassanpour Ardekanizadeh N. Mousavi Mele M. Shekari S. Mobarakeh K.A. Shafaei H. Mosavi Jarrahi A. Rajabi Harsini A. Khoshdooz S. Gholamalizadeh M. YazdiMoghaddam H. Doaei S. The association between consumption of dairy products and risk of type 2 diabetes. Cardiovasc. Endocrinol. Metab. 2024 14 1 e00318 10.1097/XCE.0000000000000318 39649678
    [Google Scholar]
  55. Flores-Hernández M.N. Martínez-Coria H. López-Valdés H.E. Arteaga-Silva M. Arrieta-Cruz I. Gutiérrez-Juárez R. Efficacy of a high-protein diet to lower glycemic levels in type 2 diabetes mellitus: A systematic review. Int. J. Mol. Sci. 2024 25 20 10959 10.3390/ijms252010959 39456742
    [Google Scholar]
  56. Santiago-López L. Aguilar-Toalá J.E. Hernández-Mendoza A. Vallejo-Cordoba B. Liceaga A.M. González-Córdova A.F. Bioactive compounds produced during cheese ripening and health effects associated with aged cheese consumption. J. Dai. Sci. 2018 101 5 3742 3757 10.3168/jds.2017‑13465 29477517
    [Google Scholar]
  57. Mayneris-Perxachs J. Castells-Nobau A. Arnoriaga-Rodríguez M. Martin M. de la Vega-Correa L. Zapata C. Burokas A. Blasco G. Coll C. Escrichs A. Biarnés C. Moreno-Navarrete J.M. Puig J. Garre-Olmo J. Ramos R. Pedraza S. Brugada R. Vilanova J.C. Serena J. Gich J. Ramió-Torrentà L. Pérez-Brocal V. Moya A. Pamplona R. Sol J. Jové M. Ricart W. Portero-Otin M. Deco G. Maldonado R. Fernández-Real J.M. Microbiota alterations in proline metabolism impact depression. Cell Metab. 2022 34 5 681 701.e10 10.1016/j.cmet.2022.04.001 35508109
    [Google Scholar]
  58. Ayakdaş G. Ağagündüz D. Microbiota-accessible carbohydrates (MACs) as novel gut microbiome modulators in noncommunicable diseases. Heliyon 2023 9 9 e19888 10.1016/j.heliyon.2023.e19888 37809641
    [Google Scholar]
  59. Zhao Y. Liu J. Sun S. Zheng M. Liu M. Liu J. Liu H. Grain actives modulate gut microbiota to improve obesity-related metabolic diseases: A review. Food Res. Int. 2025 199 115367 10.1016/j.foodres.2024.115367 39658187
    [Google Scholar]
  60. Sen P. Molinero-Perez A. O’Riordan K.J. McCafferty C.P. O’Halloran K.D. Cryan J.F. Microbiota and sleep: Awakening the gut feeling. Trends Mol. Med. 2021 27 10 935 945 10.1016/j.molmed.2021.07.004 34364787
    [Google Scholar]
  61. Yan W. Jiang M. Hu W. Zhan X. Liu Y. Zhou J. Ji J. Wang S. Tai J. Causality investigation between gut microbiota, derived metabolites, and obstructive sleep apnea: A bidirectional mendelian randomization study. Nutrients 2023 15 21 4544 10.3390/nu15214544 37960197
    [Google Scholar]
  62. Ogawa Y. Miyoshi C. Obana N. Yajima K. Hotta-Hirashima N. Ikkyu A. Kanno S. Soga T. Fukuda S. Yanagisawa M. Gut microbiota depletion by chronic antibiotic treatment alters the sleep/wake architecture and sleep EEG power spectra in mice. Sci. Rep. 2020 10 1 19554 10.1038/s41598‑020‑76562‑9 33177599
    [Google Scholar]
  63. Smith C. Van Haute M.J. Rose D.J. Processing has differential effects on microbiota-accessible carbohydrates in whole grains during in vitro fermentation. Appl. Environ. Microbiol. 2020 86 21 e01705-20 10.1128/AEM.01705‑20 32859598
    [Google Scholar]
  64. Xie J. Li L. Dai T. Qi X. Wang Y. Zheng T. Gao X. Zhang Y. Ai Y. Ma L. Chang S. Luo F. Tian Y. Sheng J. Short‐chain fatty acids produced by ruminococcaceae mediate α‐linolenic acid promote intestinal stem cells proliferation. Mol. Nutr. Food Res. 2022 66 1 2100408 10.1002/mnfr.202100408 34708542
    [Google Scholar]
  65. Xu B. Fu J. Qiao Y. Cao J. Deehan E.C. Li Z. Jin M. Wang X. Wang Y. Higher intake of microbiota-accessible carbohydrates and improved cardiometabolic risk factors: A meta-analysis and umbrella review of dietary management in patients with type 2 diabetes. Am. J. Clin. Nutr. 2021 113 6 1515 1530 10.1093/ajcn/nqaa435 33693499
    [Google Scholar]
  66. Martin-Gallausiaux C. Marinelli L. Blottière H.M. Larraufie P. Lapaque N. SCFA: Mechanisms and functional importance in the gut. Proc. Nutr. Soc. 2021 80 1 37 49 10.1017/S0029665120006916 32238208
    [Google Scholar]
  67. Mirhosseini S.M. Mahdavi A. Yarmohammadi H. Razavi A. Rezaei M. Soltanipur M. Karimi Nemch M. Jafari Naeini S. Siadat S.D. What is the link between the dietary inflammatory index and the gut microbiome? A systematic review. Eur. J. Nutr. 2024 63 7 2407 2419 10.1007/s00394‑024‑03470‑3 39069586
    [Google Scholar]
  68. Carter P. Troughton J. Khunti K. Davies M.J. Fruit and vegetable intake and incidence of type 2 diabetes mellitus: Systematic review and meta-analysis. BMJ 2010 341 C4229 10.1136/bmj.c4229 20724400
    [Google Scholar]
  69. Puchau B. Zulet M.A. de Echávarri A.G. Hermsdorff H.H.M. Martínez J.A. Dietary total antioxidant capacity is negatively associated with some metabolic syndrome features in healthy young adults. Nutrition 2010 26 5 534 541 10.1016/j.nut.2009.06.017 19783122
    [Google Scholar]
  70. Gariballa S. Al-Bluwi G.S.M. Yasin J. Increased fruit and vegetable consumption mitigates oxidative damage and associated inflammatory response in obese subjects independent of body weight change. Nutrients 2023 15 7 1638 10.3390/nu15071638 37049477
    [Google Scholar]
  71. Baldrick F.R. Elborn J.S. Woodside J.V. Treacy K. Bradley J.M. Patterson C.C. Schock B.C. Ennis M. Young I.S. McKinley M.C. Effect of fruit and vegetable intake on oxidative stress and inflammation in COPD: A randomised controlled trial. Eur. Respir. J. 2012 39 6 1377 1384 10.1183/09031936.00086011 22088966
    [Google Scholar]
  72. Mirmiran P. Bahadoran Z. Moslehi N. Bastan S. Azizi F. Colors of fruits and vegetables and 3-year changes of cardiometabolic risk factors in adults: Tehran lipid and glucose study. Eur. J. Clin. Nutr. 2015 69 11 1215 1219 10.1038/ejcn.2015.49 25852026
    [Google Scholar]
  73. Kechribari I. Kontogianni M.D. Georgoulis M. Lamprou K. Mourati I. Vagiakis E. Yiannakouris N. Associations between red meat intake and sleep parameters in patients with obstructive sleep apnea. J. Acad. Nutr. Diet. 2020 120 6 1042 1053 10.1016/j.jand.2019.10.016 31892502
    [Google Scholar]
  74. Reid M. Maras J.E. Shea S. Wood A.C. Castro-Diehl C. Johnson D.A. Huang T. Jacobs D.R. Jr Crawford A. St-Onge M.P. Redline S. Association between diet quality and sleep apnea in the multi-ethnic study of atherosclerosis. Sleep 2019 42 1 zsy194 10.1093/sleep/zsy194 30346597
    [Google Scholar]
/content/journals/cchts/10.2174/0113862073348527250124113458
Loading
/content/journals/cchts/10.2174/0113862073348527250124113458
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test