Top

01-25-2017 | Lifestyle interventions | Review | Article

Lifestyle and precision diabetes medicine: will genomics help optimise the prediction, prevention and treatment of type 2 diabetes through lifestyle therapy?

Journal: Diabetologia

Authors: Paul W Franks, Alaitz Poveda

Publisher: Springer Berlin Heidelberg

Abstract

Precision diabetes medicine, the optimisation of therapy using patient-level biomarker data, has stimulated enormous interest throughout society as it provides hope of more effective, less costly and safer ways of preventing, treating, and perhaps even curing the disease. While precision diabetes medicine is often framed in the context of pharmacotherapy, using biomarkers to personalise lifestyle recommendations, intended to lower type 2 diabetes risk or to slow progression, is also conceivable. There are at least four ways in which this might work: (1) by helping to predict a person’s susceptibility to adverse lifestyle exposures; (2) by facilitating the stratification of type 2 diabetes into subclasses, some of which may be prevented or treated optimally with specific lifestyle interventions; (3) by aiding the discovery of prognostic biomarkers that help guide timing and intensity of lifestyle interventions; (4) by predicting treatment response. In this review we overview the rationale for precision diabetes medicine, specifically as it relates to lifestyle; we also scrutinise existing evidence, discuss the barriers germane to research in this field and consider how this work is likely to proceed.

National Research Council (US) Committee on A Framework for Developing a New Taxonomy of Disease (2011) Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease. National Academies Press, Washington, DC

Sturtevant AH (1917) Genetic factors affecting the strength of linkage in Drosophila. Proc Natl Acad Sci U S A 3:555–558CrossRefPubMedPubMedCentral

Watson JD, Crick FH (1953) Molecular structure of nucleic acids; a structure for deoxyribose nucleic acid. Nature 171:737–738CrossRefPubMed

Venter JC, Adams MD, Myers EW et al (2001) The sequence of the human genome. Science 291:1304–1351CrossRefPubMed

Lander ES, Linton LM, Birren B et al (2001) Initial sequencing and analysis of the human genome. Nature 409:860–921CrossRefPubMed

Crick F (1970) Central dogma of molecular biology. Nature 227:561–563CrossRefPubMed

Rutter GA, Chabosseau P, Bellomo EA et al (2016) Intracellular zinc in insulin secretion and action: a determinant of diabetes risk? Proc Nutr Soc 75:61–72CrossRefPubMed

Schoonjans K, Staels B, Auwerx J (1996) Role of the peroxisome proliferator-activated receptor (PPAR) in mediating the effects of fibrates and fatty acids on gene expression. J Lipid Res 37:907–925PubMed

Salas-Salvado J, Bullo M, Babio N et al (2011) Reduction in the incidence of type 2 diabetes with the Mediterranean diet: results of the PREDIMED-Reus nutrition intervention randomized trial. Diabetes Care 34:14–19CrossRefPubMed

10.

Yaghootkar H, Lotta LA, Tyrrell J et al (2016) Genetic evidence for a link between favorable adiposity and lower risk of type 2 diabetes, hypertension, and heart disease. Diabetes 65:2448–2460CrossRefPubMed

11.

Delahanty LM, Pan Q, Jablonski KA et al (2014) Effects of weight loss, weight cycling, and weight loss maintenance on diabetes incidence and change in cardiometabolic traits in the diabetes prevention program. Diabetes Care 37:2738–2745CrossRefPubMedPubMedCentral

12.

Loffler-Wirth H, Willscher E, Ahnert P et al (2016) Novel anthropometry based on 3D-Bodyscans applied to a large population based cohort. PLoS One 11, e0159887CrossRefPubMedPubMedCentral

13.

Herman WH, Edelstein SL, Ratner RE et al (2013) Effectiveness and cost-effectiveness of diabetes prevention among adherent participants. Am J Manag Care 19:194–202PubMedPubMedCentral

14.

McTigue KM, Conroy MB, Bigi L, Murphy C, McNeil M (2009) Weight loss through living well: translating an effective lifestyle intervention into clinical practice. Diabetes Educ 35:199–208CrossRefPubMed

15.

Li L, Cheng WY, Glicksberg BS et al (2015) Identification of type 2 diabetes subgroups through topological analysis of patient similarity. Sci Transl Med 7:311ra174CrossRefPubMedPubMedCentral

16.

Baier LJ, Muller YL, Remedi MS et al (2015) ABCC8 R1420H loss-of-function variant in a Southwest American Indian community: association with increased birth weight and doubled risk of type 2 diabetes. Diabetes 64:4322–4332CrossRefPubMedPubMedCentral

17.

Druker BJ, Guilhot F, O'Brien SG et al (2006) Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. N Engl J Med 355:2408–2417CrossRefPubMed

18.

Kwak EL, Bang YJ, Camidge DR et al (2010) Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med 363:1693–1703CrossRefPubMedPubMedCentral

19.

Tang Y, Axelsson AS, Spegel P et al (2014) Genotype-based treatment of type 2 diabetes with an α2A-adrenergic receptor antagonist. Sci Transl Med 6:257ra139CrossRefPubMed

20.

Boule NG, Weisnagel SJ, Lakka TA et al (2005) Effects of exercise training on glucose homeostasis: the HERITAGE family study. Diabetes Care 28:108–114CrossRefPubMed

21.

Bohm A, Weigert C, Staiger H, Haring HU (2016) Exercise and diabetes: relevance and causes for response variability. Endocrine 51:390–401CrossRefPubMed

22.

Bouchard C, Blair SN, Church TS et al (2012) Adverse metabolic response to regular exercise: is it a rare or common occurrence? PLoS One 7, e37887CrossRefPubMedPubMedCentral

23.

Weyrich P, Stefan N, Haring HU, Laakso M, Fritsche A (2007) Effect of genotype on success of lifestyle intervention in subjects at risk for type 2 diabetes. J Mol Med 85:107–117CrossRefPubMed

24.

Perusse L, Rice T, Province MA et al (2000) Familial aggregation of amount and distribution of subcutaneous fat and their responses to exercise training in the HERITAGE family study. Obes Res 8:140–150CrossRefPubMed

25.

Bouchard C, Tremblay A, Despres JP et al (1994) The response to exercise with constant energy intake in identical twins. Obes Res 2:400–410CrossRefPubMed

26.

Bouchard C, Tremblay A, Despres JP et al (1990) The response to long-term overfeeding in identical twins. N Engl J Med 322:1477–1482CrossRefPubMed

27.

Ahmad S, Rukh G, Varga TV et al (2013) Gene × physical activity interactions in obesity: combined analysis of 111,421 individuals of European ancestry. PLoS Genet 9, e1003607CrossRefPubMedPubMedCentral

28.

Andreasen CH, Stender-Petersen KL, Mogensen MS et al (2008) Low physical activity accentuates the effect of the FTO rs9939609 polymorphism on body fat accumulation. Diabetes 57:95–101CrossRefPubMed

29.

Vimaleswaran KS, Li S, Zhao JH et al (2009) Physical activity attenuates the body mass index-increasing influence of genetic variation in the FTO gene. Am J Clin Nutr 90:425–428CrossRefPubMed

30.

Rampersaud E, Mitchell BD, Pollin TI et al (2008) Physical activity and the association of common FTO gene variants with body mass index and obesity. Arch Intern Med 168:1791–1797CrossRefPubMedPubMedCentral

31.

Franks PW, Jablonski KA, Delahanty LM et al (2008) Assessing gene-treatment interactions at the FTO and INSIG2 loci on obesity-related traits in the diabetes prevention program. Diabetologia 51:2214–2223CrossRefPubMedPubMedCentral

32.

Kilpeläinen TO, Qi L, Brage S et al (2011) Physical activity attenuates the influence of FTO variants on obesity risk: a meta-analysis of 218,166 adults and 19,268 children. PLoS Med 8, e1001116CrossRefPubMedPubMedCentral

33.

Young AI, Wauthier F, Donnelly P (2016) Multiple novel gene-by-environment interactions modify the effect of FTO variants on body mass index. Nat Commun 7:12724CrossRefPubMedPubMedCentral

34.

Gerken T, Girard CA, Tung YC et al (2007) The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science 318:1469–1472CrossRefPubMedPubMedCentral

35.

Grunnet LG, Brons C, Jacobsen S et al (2009) Increased recovery rates of phosphocreatine and inorganic phosphate after isometric contraction in oxidative muscle fibers and elevated hepatic insulin resistance in homozygous carriers of the A-allele of FTO rs9939609. J Clin Endocrinol Metab 94:596–602CrossRefPubMed

36.

Smemo S, Tena JJ, Kim KH et al (2014) Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 507:371–375

37.

Claussnitzer M, Dankel SN, Kim KH et al (2015) FTO obesity variant circuitry and adipocyte browning in humans. N Engl J Med 373:895–907CrossRefPubMedPubMedCentral

38.

Xiang L, Wu H, Pan A et al (2016) FTO genotype and weight loss in diet and lifestyle interventions: a systematic review and meta-analysis. Am J Clin Nutr 103:1162–1170

39.

Palla L, Higgins JP, Wareham NJ, Sharp SJ (2010) Challenges in the use of literature-based meta-analysis to examine gene-environment interactions. Am J Epidemiol 171:1225–1232CrossRefPubMed

40.

Livingstone KM, Celis-Morales C, Papandonatos GD et al (2016) FTO genotype and weight loss: systematic review and meta-analysis of 9563 individual participant data from eight randomised controlled trials. BMJ 354:i4707

41.

Papandonatos GD, Pan Q, Pajewski NM et al (2015) Genetic predisposition to weight loss and regain with lifestyle intervention: analyses from the diabetes prevention program and the look AHEAD randomized controlled trials. Diabetes 64:4312–4321CrossRefPubMedPubMedCentral

42.

Nettleton JA, Follis JL, Ngwa JS et al (2015) Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. Hum Mol Genet 24:4728–4738CrossRefPubMedPubMedCentral

43.

Goran MI, Poehlman ET (1992) Endurance training does not enhance total energy expenditure in healthy elderly persons. Am J Phys 263:E950–E957

44.

Shephard RJ (2003) Limits to the measurement of habitual physical activity by questionnaires. Br J Sports Med 37:197–206CrossRefPubMedPubMedCentral

45.

Lobelo F, Kelli HM, Tejedor SC et al (2016) The wild wild west: a framework to integrate mhealth software applications and wearables to support physical activity assessment, counseling and interventions for cardiovascular disease risk reduction. Prog Cardiovasc Dis 58:584–594CrossRefPubMedPubMedCentral

46.

Jakicic JM, Davis KK, Rogers RJ et al (2016) Effect of wearable technology combined with a lifestyle intervention on long-term weight loss: the IDEA randomized clinical trial. JAMA 316:1161–1171CrossRefPubMed

47.

Zeevi D, Korem T, Zmora N et al (2015) Personalized nutrition by prediction of glycemic responses. Cell 163:1079–1094CrossRefPubMed

Be confident that your patient care is up to date

Medicine Matters is being incorporated into Springer Medicine, our new medical education platform.

Alongside the news coverage and expert commentary you have come to expect from Medicine Matters diabetes, Springer Medicine's complimentary membership also provides access to articles from renowned journals and a broad range of Continuing Medical Education programs. Create your free account »

Medicine Matters Diabetes

Abstract

Be confident that your patient care is up to date