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Diabetologia

Erschienen in:

20.05.2022 | Review

Precision nutrition in diabetes: when population-based dietary advice gets personal

verfasst von: Jordi Merino

Erschienen in: Diabetologia | Ausgabe 11/2022

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Abstract

Diet plays a fundamental role in maintaining long-term health, with healthful diets being endorsed by current dietary guidelines for the prevention and management of type 2 diabetes. However, the response to dietary interventions varies widely, highlighting the need for refinement and personalisation beyond population-based ‘one size fits all’. This article reviews the clinical evidence supporting precision nutrition as a fundamental approach for dietary advice in diabetes. Further, it proposes a framework for the eventual implementation of precision nutrition and discusses key challenges for the application of this approach in the prevention of diabetes. One implication of this approach is that precision nutrition would not exclude the parallel goal of population-based healthy dietary advice. Nevertheless, the shift in prioritising precision nutrition is needed to reflect the dynamic nature of responses to dietary interventions that vary among individuals and change over the life course.

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U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy People 2030: Social Determinants of Health. Available at https://health.gov/healthypeople/objectives-and-data/social-determinants-health. Accessed 14 Feb 2022

Gillies CL, Abrams KR, Lambert PC et al (2007) Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. BMJ 334(7588):299. https://doi.org/10.1136/bmj.39063.689375.55CrossRefPubMedPubMedCentral

Unwin N, Whiting D, Roglic G (2010) Social determinants of diabetes and challenges of prevention. Lancet 375(9733):2204–2205. https://doi.org/10.1016/S0140-6736(10)60840-9CrossRefPubMed

White M (2016) Population approaches to prevention of type 2 diabetes. PLoS Med 13(7):e1002080. https://doi.org/10.1371/journal.pmed.1002080CrossRefPubMedPubMedCentral

Chung WK, Erion K, Florez JC et al (2020) Precision medicine in diabetes: a consensus report from the American Diabetes Association (ADA) and the European Association for the Study of diabetes (EASD). Diabetologia 63(9):1671–1693. https://doi.org/10.1007/S00125-020-05181-WCrossRefPubMedPubMedCentral

Zeevi D, Korem T, Zmora N et al (2015) Personalised nutrition by prediction of glycemic responses. Cell 163(5):1079–1094. https://doi.org/10.1016/j.cell.2015.11.001CrossRefPubMed

Thaiss CA, Itav S, Rothschild D et al (2016) Persistent microbiome alterations modulate the rate of post-dieting weight regain. Nature 540(7634):544–551. https://doi.org/10.1038/nature20796CrossRefPubMed

Korem T, Zeevi D, Zmora N et al (2017) Bread affects clinical parameters and induces gut microbiome-associated personal glycemic responses. Cell Metab 25(6):1243–1253.e5. https://doi.org/10.1016/j.cmet.2017.05.002CrossRefPubMed

Mendes-Soares H, Raveh-Sadka T, Azulay S et al (2019) Assessment of a personalized approach to predicting postprandial glycemic responses to food among individuals without diabetes. JAMA Netw Open 2(2):e188102. https://doi.org/10.1001/jamanetworkopen.2018.8102CrossRefPubMedPubMedCentral

10.

Berry SE, Valdes AM, Drew DA et al (2020) Human postprandial responses to food and potential for precision nutrition. Nat Med 26(6):964–973. https://doi.org/10.1038/s41591-020-0934-0CrossRefPubMedPubMedCentral

11.

Wang DD, Hu FB (2018) Precision nutrition for prevention and management of type 2 diabetes. Lancet Diabetes Endocrinol 6(5):416–426. https://doi.org/10.1016/S2213-8587(18)30037-8CrossRefPubMed

12.

Bashiardes S, Godneva A, Elinav E, Segal E (2018) Towards utilization of the human genome and microbiome for personalized nutrition. Curr Opin Biotechnol 51:57–63. https://doi.org/10.1016/J.COPBIO.2017.11.013CrossRefPubMed

13.

de Toro-Martín J, Arsenault BJ, Després JP, Vohl MC (2017) Precision nutrition: a review of personalized nutritional approaches for the prevention and management of metabolic syndrome. Nutrients 9(8):913. https://doi.org/10.3390/NU9080913CrossRefPubMedCentral

14.

U.S. Department of Agriculture and U.S. Department of Health and Human Services. Dietary Guidelines for Americans, 2020–2025. 9th Edition. December 2020. Available at http://www.dietaryguidelines.gov. Accessed 28 Jan 2022

15.

Ley SH, Hamdy O, Mohan V, Hu FB (2014) Prevention and management of type 2 diabetes: dietary components and nutritional strategies. Lancet 383(9933):1999–2007. https://doi.org/10.1016/S0140-6736(14)60613-9CrossRefPubMedPubMedCentral

16.

Mozaffarian D (2016) Dietary and policy priorities for cardiovascular disease, diabetes, and obesity: a comprehensive review. Circulation 133(2):187–225. https://doi.org/10.1161/CIRCULATIONAHA.115.018585CrossRefPubMedPubMedCentral

17.

Evert AB, Dennison M, Gardner CD et al (2019) Nutrition therapy for adults with diabetes or prediabetes: a consensus report. Diabetes Care 42(5):731–754. https://doi.org/10.2337/dci19-0014CrossRefPubMedPubMedCentral

18.

Forouhi NG, Krauss RM, Taubes G, Willett W (2018) Dietary fat and cardiometabolic health: evidence, controversies, and consensus for guidance. BMJ 361:k2139CrossRef

19.

Trepanowski JF, Kroeger CM, Barnosky A et al (2017) Effect of alternate-day fasting on weight loss, weight maintenance, and cardioprotection among metabolically healthy obese adults: a randomized clinical trial. JAMA Intern Med 177(7):930–938. https://doi.org/10.1001/JAMAINTERNMED.2017.0936CrossRefPubMedPubMedCentral

20.

Schulze MB, Martínez-González MA, Fung TT, Lichtenstein AH, Forouhi NG (2018) Food based dietary patterns and chronic disease prevention. BMJ 361:k239. https://doi.org/10.1136/bmj.k2396CrossRef

21.

Spector TD, Gardner CD (2020) Challenges and opportunities for better nutrition science-an essay by Tim Spector and Christopher Gardner. BMJ 369:m2470. https://doi.org/10.1136/BMJ.M2470CrossRefPubMedPubMedCentral

22.

Johnston BC, Kanters S, Bandayrel K et al (2014) Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA 312(9):923–933. https://doi.org/10.1001/jama.2014.10397CrossRefPubMed

23.

Ge L, Sadeghirad B, Ball GDC et al (2020) Comparison of dietary macronutrient patterns of 14 popular named dietary programmes for weight and cardiovascular risk factor reduction in adults: systematic review and network meta-analysis of randomised trials. BMJ 369:m696. https://doi.org/10.1136/BMJ.M696CrossRefPubMedPubMedCentral

24.

Martins C, Gower BA, Hill JO, Hunter GR (2020) Metabolic adaptation is not a major barrier to weight-loss maintenance. Am J Clin Nut 112(3):558–565. https://doi.org/10.1093/AJCN/NQAA086CrossRef

25.

Hall KD, Sacks G, Chandramohan D et al (2011) Quantification of the effect of energy imbalance on bodyweight. Lancet 378(9793):826–837. https://doi.org/10.1016/S0140-6736(11)60812-XCrossRefPubMed

26.

Guo J, Brager DC, Hall KD (2018) Simulating long-term human weight-loss dynamics in response to calorie restriction. Am J Clin Nut 107(4):558. https://doi.org/10.1093/AJCN/NQX080CrossRef

27.

Tuomi T, Santoro N, Caprio S, Cai M, Weng J, Groop L (2014) The many faces of diabetes: a disease with increasing heterogeneity. Lancet 383(9922):1084–1094. https://doi.org/10.1016/S0140-6736(13)62219-9CrossRefPubMed

28.

Ahlqvist E, Storm P, Käräjämäki A et al (2018) Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 6(5):361–369. https://doi.org/10.1016/S2213-8587(18)30051-2CrossRefPubMed

29.

Udler MS, Kim J, von Grotthuss M et al (2018) Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis. PLoS Med 15(9):e1002654. https://doi.org/10.1371/journal.pmed.1002654CrossRefPubMedPubMedCentral

30.

Mahajan A, Wessel J, Willems SM et al (2018) Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat Gen 50(4):559–571. https://doi.org/10.1038/S41588-018-0084-1CrossRef

31.

Lingvay I, Sumithran P, Cohen RV, le Roux CW (2022) Obesity management as a primary treatment goal for type 2 diabetes: time to reframe the conversation. Lancet 399(10322):394–405. https://doi.org/10.1016/S0140-6736(21)01919-XCrossRefPubMed

32.

Knowler WC, Barrett-Connor E, Fowler SE et al (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346(6):393–403. https://doi.org/10.1056/NEJMoa012512CrossRefPubMed

33.

Gregg EW, Jakicic JM, Blackburn G et al (2016) Association of the magnitude of weight loss and changes in physical fitness with long-term cardiovascular disease outcomes in overweight or obese people with type 2 diabetes: a post-hoc analysis of the look AHEAD randomised clinical trial. Lancet Diabetes Endocrinol 4(11):913–921. https://doi.org/10.1016/S2213-8587(16)30162-0CrossRefPubMedPubMedCentral

34.

Ma C, Avenell A, Bolland M et al (2017) Effects of weight loss interventions for adults who are obese on mortality, cardiovascular disease, and cancer: systematic review and meta-analysis. BMJ 359:j4849. https://doi.org/10.1136/BMJ.J4849CrossRefPubMedPubMedCentral

35.

Lean MEJ, Leslie WS, Barnes AC et al (2019) Durability of a primary care-led weight-management intervention for remission of type 2 diabetes: 2-year results of the DiRECT open-label, cluster-randomised trial. Lancet Diabetes Endocrinol 7(5):344–355. https://doi.org/10.1016/S2213-8587(19)30068-3CrossRefPubMed

36.

Gardner CD, Trepanowski JF, Del Gobbo LC et al (2018) Effect of low-fat vs low-carbohydrate diet on 12-month weight loss in overweight adults and the association with genotype pattern or insulin secretion: the DIETFITS randomized clinical trial. JAMA 319(7):667–679. https://doi.org/10.1001/JAMA.2018.0245CrossRefPubMedPubMedCentral

37.

Apolzan JW, Venditti EM, Edelstein SL et al (2019) Long-term weight loss with metformin or lifestyle intervention in the diabetes prevention program outcomes study. Ann Inter Med 170(10):682–690. https://doi.org/10.7326/M18-1605CrossRef

38.

Fan S, Hansen ME, Lo Y, Tishkoff SA (2016) Going global by adapting local: a review of recent human adaptation. Science 354(6308):54–59. https://doi.org/10.1126/SCIENCE.AAF5098CrossRefPubMedPubMedCentral

39.

The SIGMA Type 2 Diabetes Consortium, Williams AL, Jacobs SBR et al (2014) Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico. Nature 506(7486):97–101. https://doi.org/10.1038/nature12828CrossRef

40.

Ainbinder A, Zhao L, Glover P et al (2021) Mct11 deficiency alters hepatic glucose metabolism and energy homeostasis. bioRxiv 2021.09.08.459307. https://doi.org/10.1101/2021.09.08.459307

41.

Qi L, Cornelis MC, Zhang C, van Dam RM, Hu FB (2009) Genetic predisposition, Western dietary pattern, and the risk of type 2 diabetes in men. Am J Clin Nut 89(5):1453–1458. https://doi.org/10.3945/ajcn.2008.27249CrossRef

42.

Langenberg C, Sharp SJ, Franks PW et al (2014) Gene-lifestyle interaction and type 2 diabetes: the EPIC InterAct case-cohort study. PLoS Med 11(5):e1001647. https://doi.org/10.1371/journal.pmed.1001647CrossRefPubMedPubMedCentral

43.

Merino J, Guasch-Ferre M, Ellervik C et al (2019) Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis. BMJ 366:l4392. https://doi.org/10.1136/bmj.l4292CrossRef

44.

Said MA, Verweij N, van der Harst P (2018) Associations of combined genetic and lifestyle risks with incident cardiovascular disease and diabetes in the UK biobank study. JAMA Cardiol 3(8):693–702. https://doi.org/10.1001/JAMACARDIO.2018.1717CrossRefPubMedPubMedCentral

45.

Abdu-Ali GS, Mehta RS, Lloyd-Price J et al (2018) Metatranscriptome of human faecal microbial communities in a cohort of adult men. Nat Microbiol 3(3):356–366. https://doi.org/10.1038/S41564-017-0084-4CrossRef

46.

Tett A, Huang KD, Asnicar F et al (2019) The Prevotella copri complex comprises four distinct clades underrepresented in westernized populations. Cell Host Microbe 26(5):666–679.e7. https://doi.org/10.1016/J.CHOM.2019.08.018CrossRefPubMedPubMedCentral

47.

Li J, Li Y, Ivey KL et al (2022) Interplay between diet and gut microbiome, and circulating concentrations of trimethylamine N-oxide: findings from a longitudinal cohort of US men. Gut 71(4):724–733. https://doi.org/10.1136/GUTJNL-2020-322473CrossRefPubMed

48.

Qi Q, Li J, Yu B et al (2021) Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies. Gut. Online ahead of print. https://doi.org/10.1136/GUTJNL-2021-324053

49.

Ben-Yacov O, Godneva A, Rein M et al (2021) Personalised postprandial glucose response-targeting diet versus Mediterranean diet for glycemic control in prediabetes. Diabetes Care 44(9):1980–1991. https://doi.org/10.2337/DC21-0162CrossRefPubMed

50.

McCarthy MI (2017) Painting a new picture of personalised medicine for diabetes. Diabetologia 60(5):793–799. https://doi.org/10.1007/s00125-017-4210-xCrossRefPubMedPubMedCentral

51.

McCarthy M, Birney E (2021) Personalized profiles for disease risk must capture all facets of health. Nature 597(7875):175–177. https://doi.org/10.1038/D41586-021-02401-0CrossRefPubMed

52.

Bancks MP, Chen H, Balasubramanyam A et al (2021) Type 2 diabetes subgroups, risk for complications, and differential effects due to an intensive lifestyle intervention. Diabetes Care 44(5):1203–1210. https://doi.org/10.2337/DC20-2372CrossRefPubMedPubMedCentral

53.

Goodpaster BH, Sparks LM (2017) Metabolic flexibility in health and disease. Cell Metab 25(5):1027–1036. https://doi.org/10.1016/J.CMET.2017.04.015CrossRefPubMedPubMedCentral

54.

Wells JCK (2019) The diabesity epidemic in the light of evolution: insights from the capacity-load model. Diabetologia 62(10):1740–1750. https://doi.org/10.1007/S00125-019-4944-8CrossRefPubMedPubMedCentral

55.

Johnson JD (2021) On the causal relationships between hyperinsulinaemia, insulin resistance, obesity and dysglycaemia in type 2 diabetes. Diabetologia 64(10):2138–2146. https://doi.org/10.1007/S00125-021-05505-4CrossRefPubMed

56.

Kohnert KD, Augstein P, Zander E et al (2009) Glycemic variability correlates strongly with postprandial β-cell dysfunction in a segment of type 2 diabetic patients using oral hypoglycemic agents. Diabetes Care 32(6):1058–1062. https://doi.org/10.2337/DC08-1956CrossRefPubMedPubMedCentral

57.

Yoshino M, Kayser BD, Yoshino J et al (2020) Effects of diet versus gastric bypass on metabolic function in diabetes. N Engl J Med 383(8):721–732. https://doi.org/10.1056/NEJMOA2003697CrossRefPubMedPubMedCentral

58.

Greenway FL (2015) Physiological adaptations to weight loss and factors favouring weight regain. Int J Ob 39(8):1188–1196. https://doi.org/10.1038/IJO.2015.59CrossRef

59.

Wyatt P, Berry SE, Finlayson G et al (2021) Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nat Metab 3(4):523–529. https://doi.org/10.1038/S42255-021-00383-XCrossRefPubMedPubMedCentral

60.

Freedman LS, Schatzkin A, Midthune D, Kipnis V (2011) Dealing with dietary measurement error in nutritional cohort studies. J Natl Cancer Inst 103(14):1086–1092. https://doi.org/10.1093/JNCI/DJR189CrossRefPubMedPubMedCentral

61.

Howard R, Guo J, Hall KD (2020) Imprecision nutrition? Different simultaneous continuous glucose monitors provide discordant meal rankings for incremental postprandial glucose in subjects without diabetes. Am J Clin Nutr 112(4):1114–1119. https://doi.org/10.1093/ajcn/nqaa198CrossRefPubMedPubMedCentral

62.

Merino J, Linenberg I, Bermingham KM et al (2022) Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition. Am J Clin Nutr. Online ahead of print. https://doi.org/10.1093/AJCN/NQAC026

63.

Potter T, Vieira R, de Roos B (2021) Perspective: application of N-of-1 methods in personalized nutrition research. Adv Nutr 12(3):579–589. https://doi.org/10.1093/ADVANCES/NMAA173CrossRefPubMedPubMedCentral

64.

Senn S (2018) Statistical pitfalls of personalised medicine. Nature 563(7733):619–621. https://doi.org/10.1038/D41586-018-07535-2CrossRefPubMed

65.

Schüssler-Fiorenza Rose SM, Contrepois K, Moneghetti KJ et al (2019) A longitudinal big data approach for precision health. Nat Med 25(5):792–804. https://doi.org/10.1038/s41591-019-0414-6CrossRefPubMed

66.

Zhou W, Sailani MR, Contrepois K et al (2019) Longitudinal multi-omics of host–microbe dynamics in prediabetes. Nature 569(7758):663–671. https://doi.org/10.1038/s41586-019-1236-xCrossRefPubMedPubMedCentral

67.

Hall H, Perelman D, Breschi A et al (2018) Glucotypes reveal new patterns of glucose dysregulation. PLoS Biol 16(7):e2005143. https://doi.org/10.1371/journal.pbio.2005143CrossRefPubMedPubMedCentral

68.

Diabetes Prevention Program Research Group (2012) The 10-year cost-effectiveness of lifestyle intervention or metformin for diabetes prevention: an intent-to-treat analysis of the DPP/DPPOS. Diabetes Care 35(4):723–730. https://doi.org/10.2337/dc11-1468CrossRef

69.

The Global Nutrition Report’s Independent Expert Group https://globalnutritionreport.org/reports/2020-global-nutrition-report/2020-global-nutrition-report-context-covid-19/. Accessed 6 Jan 2022

70.

International Diabetes Federation. IDF Diabetes Atlas. http://www.diabetesatlas.org. Accessed 14 Feb 2022

71.

Popkin BM, Barquera S, Corvalan C et al (2021) Towards unified and impactful policies to reduce ultra-processed food consumption and promote healthier eating. Lancet Diabetes Endocrinol 9(7):462–470. https://doi.org/10.1016/S2213-8587(21)00078-4CrossRefPubMedPubMedCentral

72.

Pell D, Mytton O, Penney TL et al (2021) Changes in soft drinks purchased by British households associated with the UK soft drinks industry levy: controlled interrupted time series analysis. BMJ 372:n254. https://doi.org/10.1136/bmj.n254CrossRefPubMedPubMedCentral

73.

Sánchez-Romero LM, Canto-Osorio F, González-Morales R et al (2020) Association between tax on sugar sweetened beverages and soft drink consumption in adults in Mexico: open cohort longitudinal analysis of health workers cohort study. BMJ 369:m1311. https://doi.org/10.1136/BMJ.M1311CrossRefPubMedPubMedCentral

Titel: Precision nutrition in diabetes: when population-based dietary advice gets personal
verfasst von: Jordi Merino
Publikationsdatum: 20.05.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Diabetologia / Ausgabe 11/2022
Print ISSN: 0012-186X
Elektronische ISSN: 1432-0428
DOI: https://doi.org/10.1007/s00125-022-05721-6

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