dexlife final report - cordis · diabetes prevention project, which ran between 2012 and 2015 and...

PROJECT FINAL REPORT Grant Agreement number: 279228 Project acronym: DEXLIFE Project title: Mechanisms of prevention of type 2 diabetes by lifestyle intervention in subjects with pre-diabetes or at high-risk for progression. Funding Scheme: Collaborative Project Period covered: from 01 January 2012 to 31 December 2015

Name, title and organisation of the scientific representative of the project's coordinator: Prof. John Nolan, Steno Diabetes Center A/S, Copenhagen

Tel: +45 396 80800 E-mail: [email protected]

Project website address: http://dexlife.eu/

DEXLIFEFinalReport(ProjectNo.279228) 2

TableofContents

1. FINALPUBLISHABLESUMMARYREPORT..............................................................................................................41.1. EXECUTIVESUMMARY.................................................................................................................................................41.2. SUMMARYDESCRIPTIONOFPROJECTCONTEXTANDOBJECTIVES...........................................................................................5

1.2.1. Background....................................................................................................................................................51.2.2. DEXLIFEaimsandobjectives..........................................................................................................................51.2.3. DEXLIFEimpact..............................................................................................................................................61.2.4. TheDEXLIFEapproach....................................................................................................................................6

1.3. DESCRIPTIONOFTHEMAINS&TRESULTS/FOREGROUNDS..................................................................................................81.3.1. Introduction....................................................................................................................................................81.3.2. Personalisedmedicine....................................................................................................................................91.3.3. Metabolomicsofdiabetesandpre-diabetes................................................................................................101.3.4. Personalisedlifestyleinterventions..............................................................................................................111.3.5. Identificationofmetabolitesthattrackwiththedietandexerciseintervention.........................................131.3.6. Identificationofmethylomicandtranscriptomicalterationsinmusclesamples.........................................141.3.7. IdentificationandvalidationoflipidmolecularnetworksassociatedwithprogressionofT2D...................151.3.8. 10yearfollowupontheRISCcohort...........................................................................................................151.3.9. QuantoseImpairedglucosetolerance(IGT)test..........................................................................................161.3.10. NetworkofExcellenceandFutureCollaboration.......................................................................................161.3.11. Conclusion..................................................................................................................................................17

1.4. POTENTIALIMPACT,MAINDISSEMINATIONACTIVITIESANDEXPLOITATIONOFRESULTS...........................................................181.4.1. TheDEXLIFEimpactandfutureuse..............................................................................................................18

1.4.1.1. Introduction..............................................................................................................................................................181.4.1.2. Lessonslearnt-Diagnostickitstomeasurebiomarkers...........................................................................................181.4.1.3. Lessonslearnt-Personalisedinterventionregimensforfront-lineclinicalenvironments......................................181.4.1.4. Lessonslearnt-Automationandsimplificationofthebiomarkeranalysisprocess................................................191.4.1.5. Education-Diabetesmodulesforpersonalisedmedicine.......................................................................................191.4.1.6. Preventingdiabetes-usingDEXLIFEpersonalisedmedicinetomanagepatientsdiagnosedwithdiabetes..........191.4.1.7. Managingdiabetes-usingDEXLIFEpersonalisedmedicinetomanagepatientsdiagnosedwithdiabetes............191.4.1.8. Conclusion................................................................................................................................................................20

1.4.2. DEXLIFEdissemination.................................................................................................................................211.4.2.1. Websiteandonline...................................................................................................................................................211.4.2.2. ProjectMaterials......................................................................................................................................................221.4.2.3. Eventsandexhibitions..............................................................................................................................................241.4.2.4. DEXLIFEonEuronews...............................................................................................................................................241.4.2.5. DEXLIFEConference..................................................................................................................................................261.4.2.6. Publications..............................................................................................................................................................261.4.2.7. Presentations............................................................................................................................................................27


1.4.2.8. Other.........................................................................................................................................................................281.4.2.9. Conclusion................................................................................................................................................................28

1.5. PROJECTWEBSITEANDCONTACTDETAILS......................................................................................................................29


1. Finalpublishablesummaryreport

1.1. Executivesummary

Diabetes is a global pandemic, driven by many factors associated with modern living, not least an evenbiggerpandemicofobesity. Thereisapressingneedforbettermethodsofdetectionofthoseathighriskandmoreeffectivemethodsofselectionforpreventionandtreatment.

Despite scientific advances in the understanding of the pathophysiology of type 2 diabetes, it remains achallenge to effectively identify andmanage individuals in the general populationwho are at high risk ofdevelopingdiabetesorthosewhoalreadyhaveundiagnoseddiabetes.Therefore,thereisaneedtoidentifynovelearlymarkersofglucoseintolerancethatreflecttheunderlyingbiologyandtheoverallphysiological,metabolic,andclinicalcharacteristicsofprogressiontowardsdiabetes.

TheDEXLIFEproject- ledbyJohnNolan,CEOandHeadofStenoDiabetesCenter inDenmark– isatype2diabetes prevention project, which ran between 2012 and 2015 and involved a wide range of Europeanpartners, including diabetes clinics, universities, and industry. The DEXLIFE project focuses on type 2diabetes, from its earliest stages in high risk, but otherwise healthy, individuals through to establisheddiabetes.Thecurrentapproachtodiabetesriskisbasedonclinicalassessmentincludingriskscoringsystemsalongwithsomeformofglucosemeasurement.Thecurrentapproachtothetreatmentoftype2diabetesfollowsgeneralisedalgorithms,applicabletoallpatients.DEXLIFEplacesmajorfocusonadeeperindividualphenotype both for people with pre-diabetes and for those with diabetes. Using newmethodologies inmetabolomicsandlipidomics,wehavecharacterisedbaselinerisk,progressionandresponsetointerventioninarangeofwellcharacterisedEuropeancohorts.

ThekeyworkundertakenandresultsachievedinDEXLIFEincludethefollowing:

• Identified novel biomarkers that anticipate and accurately forecast abnormal glucose tolerance inasymptomatic individuals. We have validated these biomarkers and investigated their mechanism ofactionanddeterminedtheextenttowhichthesebiomarkersareresponsivetolifestyleintervention.

• Developed a personalised model for intervention using a systems biology approach. The outputsanticipated from DEXLIFE can be used for large-scale screening programmes to identify high-riskindividualsandthosewithundiagnoseddiabetes.

• Ourworkhasresultedinninejournalpublicationstodate,withonemorearticleinpreparationforre-submission, and approximately 11morepublicationsplanned. Researchers alsopresentedonDEXLIFEandthedevelopmentofnoveldiagnosticsandpredicitvebiomarkersatseveralconferences.

In DEXLIFE, we have generated new knowledge about metabolomics, lipidomics, RNA-sequencing,methylation,interventionstudies,andbioinformatics.Webelievethatthisnewknowledgeprovideshealthcare providers and policy makers with a sound basis on which to shape future health policy, diabetessupportsandinterventions.Wehavealsoopenedupavenuesforfurtherresearchandstudy,particularlyintranslationalresearchandfurtherdevelopmentofdiagnosticinstrumentationallowinganalysisofbloodandothersamplesatanacceptablecostforclinicalpractice.

The ultimate legacy of DEXLIFE will be diagnostic kits to measure biomarkers, personalised interventionregimesforfront-lineclinicalenvironments,automationandsimplificationofbiomarkeranalysisprocess,aswellasfeedingintofuturepersonalisedmedicineeducation.Ourresultsandfindingshaverealpotentialtoimpactonhealthpolicyinthefutureandourpersonalisedlifestyleinterventionhasthepotentialtomakeasignificantcontributiontohelppreventprogressiontodiabetesinhigh-riskEuropeancitizen.WebelievetheultimatelegacyofDEXLIFEwillbetohelpimprovediabetesscreeningandinterventions,therebyimprovinghealth outcomes while reducing the burden on the health sector and delivering related social andsocioeconomicbenefits.


1.2. Summarydescriptionofprojectcontextandobjectives

1.2.1. Background

Large-scalediabetespreventionstudieshaveclearlyshownthattype2diabetescanbepreventedordelayedin people at high-risk by sustained changes in both diet and physical exercise. However, despite solidevidenceforpreventiveactions,itremainsachallengetoeffectivelyidentifyandmanageindividualsinthegeneral population who are at high risk of developing diabetes or those who already have undiagnoseddiabetes.Not only are theremultiple patterns of progression towards diabetes, there is also a significantvariation in individuals response to interventionsonexerciseanddiet.Thus,even ifpeopleareaccuratelyidentifiedashavingpre-diabetes,theirsubsequentresponsetopreventiveinterventionremainsdifficulttoforecastandisstillhighlyvariable.

DEXLIFE is tackling these problems by identifying novel markers of glucose intolerance that reflect theunderlying biology and the overall physiological, metabolic, and clinical characteristics of progressiontowardsdiabetes.Thesemarkersshouldideallybesensitivetosmallchangesinphysiologyanddemonstratechangewithdeterioratingglucosetoleranceaswellaswithimprovementsinglucosetoleranceinresponsetolifestyleintervention.Theidentificationofnewbiomarkersofthiskindcouldfacilitateacompletelynewapproach to disease prevention, based on accurate prognostic phenotyping of high-risk subjects andaccurateselectionoftheseindividualsfortheappropriatelymatchedinterventions.

TheDEXLIFEproject focuseson type2diabetes, from itsearliest stages inhigh riskbutotherwisehealthyindividuals through to established diabetes. The current approach to diabetes risk is based on clinicalassessment including risk scoring systems along with some form of glucose measurement. The currentapproachtothetreatmentoftype2diabetesfollowsgeneralisedalgorithms,applicabletoallpatients.

DEXLIFE placesmajor focus on a deeper individual phenotype both for peoplewith pre-diabetes and forthose with diabetes. Using new methodologies in metabolomics and lipidomics we have characterisedbaselinerisk,progression,andresponsetointervention,inarangeofwellcharacterisedEuropeancohorts.

1.2.2. DEXLIFEaimsandobjectives

TheDEXLIFEprojectwasdevelopedtoidentifynoveldiagnosticandpredictivebiomarkers,basedonthecorepathophysiology, that underlie the progression from normal glucose tolerance through to pre-diabetesfollowedbytype2diabetes.Inparticular,theobjectiveswereto:

• Identify a ‘metabolic signature’ of circulating and tissue specific biomarkers that characterise thedevelopmentofabnormalbloodglucose.

• Betterdetecttheprogressiontowarddiabetesinhigh-riskindividualswithdifferentphenotypes.

• Evaluate the responsiveness of these biomarkers to a lifestyle intervention known to prevent type 2diabetes.

DEXLIFE will help to inform the development of new screening tests and interventions to help preventprogressiontodiabetesinhigh-riskEuropeancitizens.DEXLIFEuniquelyprovidesthefollowing:• Besidesidentifyingnovelbiomarkersthatpredictthedevelopmentoftype2diabetes,theaimofthe

DEXLIFEprojectwastoinvestigatehowmanyofthebiomarkersthatpredictedprogressiontodiabetesalsotrackintheoppositedirectionwhendiabetesriskisreduced.Thiswouldenabletheidentificationofthebiomarkersmoststronglyassociatedwithchangesinglucosetolerance.Healthcareproviderswillbeabletodeterminewhetherindividualswillberesponsivetolifestyleinterventionatanearlystageorwhethertheyrequireothertreatmentoptions.

• Alifestyleintervention,comprisingchangesinphysicalactivityanddiet,hasbeenshowntosignificantlyreducetheriskofdevelopingdiabetes.TheDEXLIFEapproachdifferedfromotherinterventionstudiesinthattheinterventionfocusedonprovidingparticipantswithchoicesofdifferenttypesandschedulesofexerciseandvarietiesofdietcontrol,sotheycouldselectthebestoptionforthem.Forthefirsttimeitwillbecomepossibletotailorapersonalisedtreatmentplanwiththehighestlikelihoodofefficacyforanindividualpatient.


1.2.3. DEXLIFEimpact

DEXLIFE will ultimately help prevent progression to diabetes in high-risk European citizens. This hashappened,onasmall scale,during the lifetimeofour researchproject(throughour lifestyle intervention)andourresultsandtoolsarenowbeingsharedforwideruptake.

TheimpactofDEXLIFEextendsbeyondEuropeanborders.Type2diabetesisnowaglobalepidemicwiththegreatestratesofincreaseinAsiaanddevelopingcountries.However,phenotypiccharacteristicsofpatientsinthesecountriesmaydifferfromthetypicalpatternofpatientsfromEuropeancountries.Forexample,BMIis significantly lower in Asian patients diagnosed with type 2 diabetes. Nonetheless, the underlyingbiochemistryandphysiologyaresimilar.Whatthesecountriesmosturgentlyrequireisaninexpensive,easyto administer, widely available screening test to identify high-risk individuals. The screening capabilitiesresultingfromDEXLIFEcanthereforebenefitcitizensthatareatriskworldwide.

Theprojectresultswillalsoenablehealthcareproviders,includinggovernments,topredicttheprogressiontodiabetesandassistwithpreventionstrategies.Healthcareproviderswillbeabletodeterminewhetherindividuals will be responsive to lifestyle intervention at an early stage or whether they require othertreatment options. At present, diet and exercise modifications are recommended for all patients withdiabetesand, if theyarenot responsiveorcompliant,a seriesofpharmaceuticalagentsareprescribed tocontrol glucose and lipidmetabolism. Our consortium has challenged the assumption that all individualsrespondtolifestyleintervention,andhasshowthat,aswithpharmaceuticaltreatment,somearemore,orless responsive. Thanks to DEXLIFE, it is now, for the first time become possible to tailor apersonalisedtreatmentplanwiththehighestlikelihoodofefficacyforanindividualpatient.

Eventhoughthisdirectbenefitmakestheprojectworthwhile,therealvalueofDEXLIFEistacklingthefourmajorproblemsthatexistintheidentificationofhigh-riskindividuals:• Glucose istheonlyacceptedbiomarkerfordiabetes;unfortunatelythismetabolitechangestoo late in

thephysiologicalprogressiontodisease,sothatglucose-baseddiagnosisisoftentoolate.• Thereisahighdegreeofinter-individualvariationintheprogressiontodiabetes.• Thereisahighdegreeofvariabilityinresponsivenesstovarioustreatmentmodalities,includinglifestyle

changes.• Themajorityofpeoplewithabnormalglucose toleranceandtype2diabetes remainundiagnosedand

asymptomaticforanumberofyears.These problems require tools for population-based screening that can be easily distributed and are costeffective.Inthelifetimeoftheproject,DEXLIFEhas:

• Identified novel biomarkers that anticipate and accurately forecast abnormal glucose tolerance inasymptomaticindividuals.

• ValidatedtheDEXLIFEbiomarkersandinvestigatedtheirmechanismofaction.• Determinedtheextenttowhichthebiomarkersareresponsivetolifestyleintervention.• Developedapersonalisedmodelforinterventionusingasystemsbiologyapproach.

1.2.4. TheDEXLIFEapproach

DEXLIFEaddresses the corephysiologicalparametersunderlying the currentpandemicof type2diabetes,drivenbymodern trends indietandphysicalactivity.Central toDEXLIFEhasbeentheexaminationof theprogression from a state of normalmetabolismwith normal glucose tolerance through to pre-diabetesfollowedby type2diabetes.The rangeofcohortsavailable toDEXLIFEmeans thatwehavebeenable tomap the natural background progression to diabetes in certain groups. While mapping and analysingbackgroundprogressiontodiabetesisimportant,wechoseinadditiontoanalysetheresponsestolifestyle(dietandexercise)intervention.Thus,ourresearchsoughttomapascompletelyaspossiblethefullrangeoftheprocessoftheevolutionofdiabetes inthepopulation, fromyoungadultsthroughtomiddle-agedandolder subjects at various stages of progression of metabolic disease. By achieving this degree of clinical‘coverage’ of the phenotypes represented in the community, the project has provided its basic


science/mechanisticpartnerswithanappropriatelybroadrangeofclinicalsettingsfromwhichtoderivetherangeofcell,tissueandcirculatingbiomarkersneededtoclassifyandpredicttherelevantclinicalendpointsunderconsideration.Theoverallresearchstrategywasatop-downanditerativeevaluationofcombinationsofestablishedandnovelbiomarkers,leadingtonewinsightsintodiabetesriskandprogression.Thisincludedexaminationofclinicalphenotypes,metabolome/lipidomics,proteinexpression,transcriptomics,epigeneticsand genetics at a baseline, over the natural progression of type 2 diabetes and in response to activeintervention.

The DEXLIFE project encompasses a uniquely broad and deep research population. In DEXLIFE, severalunique and specially selected clinical cohorts provided the basis for a series of clinical, physiological andmechanisticinvestigations.Theseinvestigationswerecombinedwitharangeofthenew‘omictechnologiestoconstructadetailedprofileof thespectrumofprogressors/non-progressorsacrossmultiplecohorts. Inaddition, an exercise and dietary intervention study was conducted, enabling us to assess the impact ofpersonalised interventionsonbothbiomarkersand specific functional tissue-basedmarkers.Thesegroupsinclude:

• METSIM(MetabolicSyndromeinMen)cohort(alongitudinalstudyfollowing10,197menaged45to73fromthecityofKuopioinFinland);

• VHIDiabetesMellitusandVascularHealthInitiative(DMVhi)cohort(theVHIscreeningstudyidentified700participantsoutofthe30,000VHIpolicyholderswhoparticipatedinthisfirstlarge-scalescreeningstudy);

• YT2 (135 Young Type 2 participantswere recruited from the outpatients clinics at St. James’HospitalDublin)cohort;and

• The longitudinalmulticentreRISCcohort (1,500Europeans, recruited in2003and followed-up in2008and2013).

• The interventionstudyalsocomprisedof373participants from Irelandwhohavea sedentary lifestyleandaredeemedathigherriskfordevelopingtype2diabetes.

Figure1DEXLIFE:DuringthecourseofDEXLIFEmorethan7600bloodandmusclesampleshavebeenanalysedforamultitudeofdifferentmetabolitelevels.Thecomparisonofthesamples

allowedustodevelopnovelpredictivediagnosticbiomarkers.YT2(youngtype2),OT2(Oldtype2)


1.3. DescriptionofthemainS&Tresults/foregrounds

1.3.1. Introduction

TheDEXLIFEproject focuseson type2diabetes, from itsearliest stages inhigh riskbutotherwisehealthyindividuals through to established diabetes. Type 2 diabetes develops gradually over the course ofmanyyears. The prodromal stage of disease is clinically silent, andwithout symptoms. Previous approaches todiabetes risk are based on clinical assessment, including risk scoring systems along with some form ofglucosemeasurement.Treatmentoftype2diabetesfollowsgeneralisedalgorithmswhichareappliedtoallpatients.

Progressiontotype2diabeteshasbeenthemajor focusofDEXLIFE.Thisprogression is thought toresultfrom twomajor pathologies: (i) gradual loss of insulin secretion along with (ii) persistent and increasinginsulin resistance, with ongoing demand for compensatory increased insulin secretion. Vulnerability todiabetes isnotsimpleandmay includefactorsthatarenotobviousfromasimpleclinicalriskassessment.There is increasing interest in mapping trajectories of progression prior to the diagnosis of diabetes incarefully phenotyped cohorts. The DEXLIFE approach is novel because it placesmajor focus on a deeperindividual phenotype both for people with pre-diabetes and for those with diabetes. Using newmethodologies in metabolomics and lipidomics we have characterised baseline risk, progression, andresponsetointervention,inarangeofwellcharacterisedEuropeancohorts.

Thescientificworkoftheprojectwasdividedintothefollowingworkpackages:

• WP1:CohortManagement.ThemainobjectiveofWP1was toassemble, coordinateandmanage thevariouslargecohortsofhumansubjects.

• WP2:CirculatingBiomarkersand*omics.WP2studiedchangesincirculatingmetabolitesandlipidsthatcharacterise the progression from normal glucose tolerance through the intermediate prediabetic,dysglycemicstagesofimpairedfastingglucose(IFG)and/orimpairedglucosetolerance(IGT)and,finally,ontooverttype2diabetes(T2D).

• WP3 Cell and Tissue Analyses. The major objective of WP3 was to study changes in the muscletranscriptome, metabolome (including lipidome), and methylome (promoter CpG methylation) as aresultoflifestyleinterventions(exerciseordiet).

• WP4Intervention.TheprimarypurposeofWP4wastodeliveralifestyleinterventionprogrammethatisexpectedtoimproveinsulinsensitivityanddecreasetheriskofprogressiontotype2diabetesinahighriskcohort.

• WP5 Integration & Translation.WP5 consisted of work on integrating data frommultiple cohorts inordertoobtainenvironmentalriskfactorsrelatedtodifferentstagesoftype2diabetes.Thedatafrommultiple cohort studies (WP1,WP2,WP3)was pooled and analysed inWP5. Biomarkers indicative ofhigherdiabetesriskand/orprediabeteswereidentified.TheseidentifiedbiomarkersweresubsequentlyevaluatedintheinterventionstudiesinWP4.

Figure2:TheDEXLIFEcohorts


The rangeof cohorts available toDEXLIFE (Figure 2) hasmade it possible tomap thenatural backgroundprogressiontodiabetesincertaingroups.ThemethodshavebeendescribedthoroughlyinarecentDEXLIFEpublication(Andersenetal.,2014).Themaincomponentsoftheprojectwere:

• Novelcirculatingmetabolomicand lipidomicprofilesofprogression todiabeteswere identified in twocohorts,theMETSIMstudyinFinlandandtheVhiHealthcarecohortinIreland.

• A small cohortof youngpeoplewith type2diabetes,matched controls andolderpeoplewith type2diabetes,wereusedtoidentifybiomarkersofearlyonsetdiabetes.

• Aprospectivelifestyleinterventionwasimplementedinahighriskgroupofindividualstodetermineifthenewcandidatebiomarkerstrackedwithimprovedglucosetolerance.

• ThenewcandidatebiomarkerswerevalidatedusingtheRISCcohortofhealthyEuropeanpeoplefromallover the continent and other samples from the Vhi Healthcare cohort that were not included in theoriginalanalysis.

1.3.2. Personalisedmedicine

Personalisedmedicine emerged as amedicalmodel using characterisation of individuals’ phenotypes andgenotypes (e.g. molecular profiling, medical imaging, lifestyle data) for tailoring the right therapeuticstrategyfortherightpersonattherighttime,todeterminethepredispositiontodisease,anddelivertimelyand targeted prevention. Essentially, personalised medicine relies on using biological markers to stratifypatientsintospecificsub-groups,whichmayrespondbesttospecificinterventionsandtherapies.Integratingthe biological and lifestyle components offers the best opportunity to stratify subgroups for personalisedpreventionortreatmentprogrammes.Thisapproachpromisestoreducetheburdenofdisease,bytargetingpreventionandtreatmentmoreeffectively.

InDEXLIFE,wehavetakenauniqueapproachbystratifyingboththebiologicalmarkersandtheresponsetolifestyleintervention.

• Biological markers: The success of personalised medicine requires the development of accurate andreliablediagnosticsandontheidentificationofpredictivebiomarkers.Fortheidentificationofsuitablebiomarkers,researchonearlydiseaseprocessesisimportantinordertoidentifywhichfactorstostudyaspotentialpredictorsofdiseaseandoftreatmentresponse.

• Lifestyle intervention: Stratifiedphenotypeswill be strengthened if they include responses to lifestyleintervention and are not solely based on biological progression. Individual responses to dietary andexerciseinterventionsarevariedandcanhaveamajorimpactonbiologicalbiomarkers.

Wheneffectivetherapycanbeselectedforagivenpatientbasedonindividualisedprofile,thetreatmentcanbe more effective and/or adverse effects can be avoided. This will in turn reduce healthcare costs byminimising costs associated with ineffective treatment and avoidable adverse events. The goal of thisapproach is also to focus healthcare resources on prevention,moving from illness towellness, and fromtreatingdiseasetomaintaininghealth.


1.3.3. Metabolomicsofdiabetesandpre-diabetes

Metabolitesaresmall,non-proteinmoleculeshavingmolecularweightsof lessthan1500Daltons. Severalthousandmetabolites can be detected in humanplasma, although considerably fewer aremeasured in atypical experiment. Circulating metabolites may result from a number of sources, including endogenousproduction, diet, gut microbes, drugs, and personal care products, and their levels can be affected byethnicity, age, BMI, and sex. Metabolite levels can change rapidly along with changes in flux throughmetabolicpathways(e.g.afterameal)andcanreflectthecurrentmetabolicstatusofanindividual.

DiscoverymetabolomicsandlipidomicswerecarriedoutusingtheDMVhi,YT2,andMETSIMcohorts–asaresult, 23 candidatemetabolite biomarkers were identified. In order to validate the 23metabolites thatwereshortlisted,anewMETSIMsubcohortwasused.1,293samplesfromnon-diabeticornewlydiagnoseddiabetic cases fromMETSIM baseline study (with gene expression data available) were selected for theMetabolondiscoveryplatform(alloftheseMetabolonnaïve).Modelstoidentifyimpairedglucosetolerance(IGT)usingfastingplasmaglucose(FPG)andourcandidatemetabolitesweregenerated-theQuantoseIGTmodel.Thismodelhasbeenfoundtobesensitiveandspecific,andmayserveasaconvenientalternativetotheoralglucosetolerancetest(OGTT)toidentifysubjectsathigh-riskstatefordevelopingtype2diabetes.Asecond, representative subset of METSIM samples, not used for discovery, and samples from the RISCcohort,arecurrentlyusedtovalidatethecandidatebiomarkers.

Metabolite Classification

α-Hydroxybutyric acid (AHB) Methionine/Threonine metabolism

β-Hydroxybutyric acid (BHB) Ketone body

2-Aminoadipic acid (2AAA) Lysine metabolism

3-Hydroxyisobutyric acid (3HIB) Valine metabolism

3-Methyl-2-oxobutyric acid (3MOB) Valine metabolism

3-Methyl-2-oxopentanoic acid (3MOP) Isoleucine metabolism

4-Methyl-2-oxopentanoic acid (4MOP) Leucine metabolism

α-Ketobutyric acid (AKB) Methionine/Threonine metabolism

α-Ketoglutaric acid (AKG) Krebs cycle intermediate

Creatine Creatine metabolism

Glycine Amino acid

Hydroxyisovaleroyl carnitine Leucine metabolism

Isoleucine Branched-chain amino acid

Leucine Branched-chain amino acid

lysoPC(18:2(9Z,12Z)); also known as LGPC Lysophosphatidylcholine

Oleic acid Fatty acid

Phenylalanine Aromatic amino acid

Serine Amino acid

Trigonelline (N’-methylnicotinate) Nicotinate metabolism;

Tyrosine Aromatic amino acid

Valine Branched-chain amino acid

Vitamin B5 (pantothenic acid) Vitamin; precursor to CoA

X-12063 Unknown

Table 1 Quantitative Assay List – Panel of 23 Metabolites identified and validated by the DEXLIFE project.


Thepanelofquantitativeassayswasusedtovalidatethemetabolites in1,620diabetes-freesubjectsfromthe RISC cohort and the Vhi Healthcare cohort not used in the original discovery phase. A set of 23metabolitesthatpredictprogressiontotype2diabeteshavebeen identifiedandvalidatedbytheDEXLIFEproject.Inmostcases,themetabolitechangeswerepresentinpre-diabetes, indicatingtheycouldbeusedasearlyindicatorsofdiabetesrisk.

Stenoscientistswillcontinueresearchinbiomarkersthatpredictthedevelopmentofdiabetes.TheresearchwillbeextendedtobiomarkersthatcanpredictcomplicationsinbothT1DandT2Dpatients.ThePOPSstudy(currently ongoing at Steno) will examine the hypothesis that: a patient profile includingpsychosocial/demographic data and physical tests, complimented by metabolomics, lipidomics, andproteomicsdataonbiologicalsamplesmaybeusedtoobtainamoreeffectivetreatmentrecommendation.Theresultswillbedirectlytranslatedintobetterpersonalisedtreatmentandclinicalcare.

1.3.4. Personalisedlifestyleinterventions

The DEXLIFE lifestyle intervention was a 12-week, partially supervised, exercise training programmeaccompaniedwithdietaryadvice,toimproveinsulinsensitivityandassistwithbodyfatreduction.Lifestyleinterventions,comprisingchangesinphysicalactivityanddiet,havebeenshowntosignificantlyreducetheincidenceofdiabetes.

Theaimofourprogrammewastodecreasetheriskofprogressingtodiabetesby improvingfitness levels,changingdietaryintakeanddecreasingbodyfatlevels.Insodoingwehypothesisedthatbloodglucoselevelswoulddecreaseand that someof thebiomarkers thatpredictprogression todiabeteswouldmove in theexpecteddirectionofchange.Wewantedtoseehowmanyofthebiomarkersthatpredictedprogressiontodiabetesalsotrack intheoppositedirectionwhendiabetesrisk isreduced.Thiswouldhelpus identifythebiomarkersmoststronglyassociatedwithchangesinglucosetolerance.

Participantswere recruited from theVhiHealthcare cohort and the general public,whomeet one of thefollowing criteria: (i) impaired fasting glucoseor impaired glucose tolerance; (ii) normal glucose tolerancebutascore>12ontheFINDRISCquestionnaire(suggestinga1in6chanceofdevelopingtype2diabetesinthe next 10 yrs.). Participants who provided consent were invited to attend for medical screening andbaseline measures of aerobic capacity with ECG monitoring, an oral glucose tolerance test, heart ratevariability and body composition (DEXA and abdominal ultrasound). They completed a series ofquestionnairestoassessqualityoflife,physicalactivity,health&lifestyle.Asub-groupofthecontrol(n=40)andintervention(n=100)participantshadaskeletalmusclebiopsyfromthevastuslateralis.Wefocusedontwokeycomponentstomodifylifestyleandachieveouraim:

• Exercise:Wesetatargetof4-hrsofexerciseperweekandencouragedparticipantstojoingroupclassesthatwerespeciallydesigned intheUniversity (DCU)sportscomplex.Wealsodevelopedaspecialwebdiarythatallowedustrackalloftheexercisesessions,evenforthosethatcouldnotcometothesportscomplex.

• Diet:Ouraimwastodevelopaself-selectedhealthyeatingfoodplanbasedonparticipant’s(estimated3-day) food diaries. The dietician assisted in identifying food choices that were unhealthy, offeringalternative healthy options and advice on reducing intake by 600 kcal per day. Each participant wascontactedeveryfourweekstoensurethattheywerefollowingtheirdietaryplan.

Theinterventionfocusedonprovidingchoicesforparticipantssotheycouldselectthebestoptionforthem.

• Therewereover50exerciseclassesavailableeachweek,atalltimesoftheday,andtosuitallactivities.The group classeswere specially designed for chronic diseasemanagement and based on a circuit ofexercise stations that worked the upper and lower body. Other options included yoga, pilates andspinningclassesorparticipantscouldexercisethemselvesusingthegymequipment.

• Thedietaryinterventionwasminimallyinvasiveandfocusedonofferingalternativestounhealthyfoodchoicesthatwerehealthierandhadalowercaloriecontent.


• Theonlinediarywasused to recordexercise sessionsand tomonitorbodyweight.Thiswas regularlymonitoredandparticipantswere contacted if theyhadnotentereda recentexercise sessionorbodyweighthadnotchanged.

Whatdidwemeasurebeforeandaftertheintervention?

• Bodysizeandshape:Wemeasuredchangesinbodyweight,shapeandcomposition.Wemeasuredthecircumferenceof thewaist andhip using standard protocols.Using aDEXA scanner,wewere able todetectchangesintheamountoffatandmuscleinthebody,andwealsomeasuredthethicknessoffatintheabdomenusingultrasound.

• Physical fitness: Participants walked on a treadmill until they could no longer keep going, using astandardexercisestresstestprotocol(Figure3).TheyhadECG,bloodpressureandoxygenconsumptionmeasured during the test. A higher amount of oxygen consumed is associated with better aerobicfitness.PriortothetesttheyalsohadheartratevariabilitymeasuredusingtheVagussystem.

• Glucosetolerance:Afteranovernightfast,participantsweregivenastandard75goralglucosetolerancetest.Bloodsamplesweretakenbeforeglucoseingestionandat30-,60-,90-,120-and180-minspost.

• Questionnaires: Each participant completed a series of questionnaires to assess quality of life andseveralindicatorsofhealthandwellbeing.

Significantdifferenceswerefoundbetweentheinterventionandcontrolgroups.Overall,participantsintheinterventiongroupdecreasedtheirbodymassindex,waistcircumference,andbodyfat,aswellasincreasedtheir aerobic fitness. Blood glucose levels were significantly lower in the intervention group and healthrelatedqualityof lifeanddietary intake improvedsignificantly. Itwasalsoconcludedthat individualswhoexercisedinthegymdidbetterthanindividualswhomainlyexercisedathome.

Figure3.Testingthephysicalfitnessofparticipantsinthelifestyleintervention.


MainResults:

Physicalcharacteristics:Aftercompletingthe12-weekprogrammetheintervention,butnotcontrol,grouphadasignificantreductioninbodyweight,BMI,waistcircumference,subcutaneousfatthickness,andwholebody fat percentage. There was no difference in the visceral fat thickness in either the control ofintervention groups. The intervention group also significantly improved their aerobic fitness while thecontrolgroupdidnotchangefrombaseline.

Glucose tolerance: Fasting blood glucose and 2-hr blood glucose, following the OGTT, were significantlylower in the intervention group following the intervention programme. Therewere no differences in thecontrolgroup.

Qualityoflife:Theoverallqualityoflifescoresignificantlyimprovedintheinterventiongroupfollowingthe12-weekintervention.Thesignificantimprovementsinphysicalfunctioning,generalhealthandvitalityseemtocontributemosttothechangeinqualityoflife.Thecontrolgrouphadnochangeinqualityoflifeoranyoftheindividualcomponents.

1.3.5. Identificationofmetabolitesthattrackwiththedietandexerciseintervention

OurDEXLIFEprospectivelifestyleinterventionhelpedtodetermineifthenewcandidatebiomarkerstrackedwith improved glucose tolerance. Analysis of intervention study samples showed that ten of the 23metabolites changed significantlywith the intervention. The 23metabolite panelwasmeasured pre- andpost-interventionforasub-groupofsubjectsthatcompletedthe12-weekintervention.ThenewcandidatebiomarkerswerevalidatedusingtheRISCcohortofhealthyEuropeanpeoplefromalloverthecontinentandothersamplesfromtheVhiHealthcarecohortthatwerenotincludedintheoriginalanalysis.

We identified twopotentialbiomarkers for trackingdiet andexercise interventioneffectiveness. Thebestoverall biomarker to track responses in the diet and exercise intervention is tyrosine, which is alreadymeasured in standard amino acid clinical panels. Changes in tyrosine correlated bestwith change in FPGwhile changes in an unidentified metabolite correlated best with change in body weight. Metabolon iscurrentlyworkingonelucidatingthestructureoftheunidentifiedmetabolite.


δ-Metabolite δ-FPG δ-2hPG δ-Weight

Tyrosine 0.34 0 0.4

Alpha-ketoglutaric acid 0.22 0.13 0.1

3-Methyl-2-oxobutyric acid -0.03 0.16 -0.02

Phenylalanine 0.17 -0.01 0.26

2-Aminoadipic acid 0.29 0.03 0.14

Leucine 0.23 0.05 0.27

Isoleucine 0.25 0.08 0.15

alpha-ketobutyric acid 0.07 0.21 -0.2

Table 2 Pearson Correlations for Change in Metabolite Concentration Versus Change in Glucose

Theabovemetabolitechanges reflecta single timepoint (12weeks)after initiationofadietandexerciselifestyle modification. More research is needed to understand metabolite changes in both shorter andlonger timeframes for this intervention. In addition,metabolite changeswith exercise only and diet onlyinterventionsneedtobeinvestigatedaswellasresponsestodrugtherapy(e.g.metformin).

TheDEXLIFEprogrammehasgreatlyexpandedourknowledgeofmetabolitebiomarkersassociatedwiththepathophysiology of prediabetes and type 2 diabetes. Future work in this area should include theirincorporation intonewtests forthepredictionof incidentdiabetesandforuse inmonitoring interventionstudiesforthepreventionordelayofincidentdiabetes.

1.3.6. Identificationofmethylomicandtranscriptomicalterationsinmusclesamples

Alistofpossiblealteredgenepathwayshasbeengeneratedbasedonacomparisonoftypicaltype2diabeticpatients and BMI- and age-matched non-diabetic subjects. Although methylome has been shown to bedirectly altered by diets, such as those deficient in folate or methionine, epigenetic alterations of keymetabolic genes that may determine the molecular basis of diabetes development have not beencharacterisedindetailyet.

Analysis of the genome-wide methylation showed that the intervention program (diet and exercise)significantly alters theCpGmethylationprofiles at specific regulatory sequences.Controlsdonotdiffer intheir genome-wide methylation profiles. However, we could identify 158 CpGs that change after theintervention inall individuals.Most importantly,61of theseCpGswere located into the regulatorygenesand were selected as the panel to cross with the transcriptome – derived candidates. Gene ontologyanalysesrevealanenrichmentofgenesassociatedwithregulatoryfunctions(suchastranscriptionfactors),Apksignallingpathwayandimmunedefense(CD1,CD22,IL1RE).

Ultimately,wehave identifiednoveldifferentiallyexpressedgenepathways in skeletalmuscle inhigh riskindividualssubjectedtoalifestyleinterventionprogramme(WP4).Wereportgenepathwaysinvolvedintheoxidative phosphorylation, cellular respiration all enclosed in mitochondrial function as well as skeletalmuscleremodelling.RNAsequencingoftheskeletalmusclesamplesgaveusahigheroverviewofthegeneexpression inmuscle before and after lifestyle intervention programme.Moreover, RNA seq informationallows us to analyse not only the gene expression per se but also of the isoforms associated a particulargene. The successful sequencing of RNA allowed us to validate the benefit in quality of life linked to thelifestyleintervention.Methylationstudiesinthesamecohort,providedacompletelynewinformationoftheregulationofmitochondrialfunctionandskeletalmuscleremodellinggeneexpression.Allthesedataledtotheidentificationofspecificpathwaysthatcanbeinvestigatedinthefutureinamorespecificprogrammewhereexerciseanddietcanbeanalysedseparately.TheDEXLIFEprojecthasbeenusefulasaplatformforthegenerationofveryimportantdatabaseinthephysiologyofskeletalmuscleinthewayoftype2diabetesdevelopment.


1.3.7. IdentificationandvalidationoflipidmolecularnetworksassociatedwithprogressionofT2D

Lipids are a diverse group of metabolites that have many key biological functions, acting as structuralcomponents of cellmembranes, energy storage sources and intermediates in signaling pathways. Due totheir importance lipidsareunder tighthomeostatic control andexhibit spatial anddynamic complexity atmultiple levels. It is thus not surprising that altered lipid metabolism plays important roles in thepathogenesis of most of the common diseases including in diabetes. Lipidomics emerged as a disciplineclosely related tometabolomics,which is dedicated to global study of lipidomes, including pathways andnetworks of lipids in biological systems. Advanced analytical techniques, particularly mass spectrometry,haveplayedthecrucialroleintherecentprogressoflipidomics.

Lipidomic analysis identified several co-regulated clusters of lipids associated with progression of type 2diabetes.Usingnetworkanalysisandsub-sequentstepwiseregressionanalysis,asubsetofindividual lipidswas identified as a biomarker candidate panel to predict progression of type 2 diabetes. These lipidsincludedlysophosphatidylcholine(lysoPC(18:2)),oneetherphosphatidylcholineandthreetriacylglycerols.Inanindependentstudysetting,theselipidswerethenconfirmedaspredictivemarkersoftype2diabetes.Ithasalsobeenshownthislipidbiomarkerpanelisanindependentpredictoroftype2diabeteswhichaloneoutperformstheFINDRISKscore,aswellasimprovesthepredictionifcombinedwithglucoseandFINDRISK.

Atargetedassaywasalsodevelopedwhichisapplicableinclinicalsetting.Thepanelwasselectedbasedonliterature survey and the available results in DEXLIFE. Furthermore,metabolites associatedwith diabetescomplications,not studies inDEXLIFE,werealsoconsidered for the inclusion in theassay.Specifically, thepanel of metabolic biomarkers (50 compounds) for prediction/diagnosis of (pre)diabetes and its co-morbiditiesandcomplications,andforfollow-upofinterventionsincludesthefollowing:

• Markersofprediabetes• Markersofstatusofglycemiccontrol• Markersoffattyliver• Predictivemarkersforcomplications

The method developed is based on ultra-high performance liquid chromatography combined with triplequadruplemassspectrometry(UHPLC-QqQMS).Duringthemethoddevelopment,theconditionsforsamplepreparation and conditions for theUHPLC-QqQMS have been optimised bothwith standard samples andwithserumandplasmasamples.

Specifically, in thesamplepreparation, theconditions forproteinprecipitationwereoptimised;conditionsfor the derivatisation of amino acids have similarly been optimised. The main goal was to perform theprotein precipitation in aqueous conditions, using acidic conditions, and to modify the derivatisationreagentstobebettercompatiblewiththeMS.ThemethodthatisgenerallyusedforthederivatisationcancauseionsuppressionofMS,leadingtolessrobustquantitation.IntheUHPLCseparation,severaldifferentcolumns have been tested in order to find optimal conditions and good separation for also very polarspecies,aswellastoobtainseparationofspecificisobariccompounds,suchasleucineandisoleucine.

Theongoingandfuturestudieswillestablishifthelipid-basedriskscorecanidentifyspecificrespondersornon-responderstospecificinterventionsaimedatdiabetesprevention.

1.3.8. 10yearfollowupontheRISCcohort

TheDEXLIFEprojecthasprovidedtheresourceandstructuretoconductdetailedclinicalphenotypingofasubsetoftheRISCcohortofhealthysubjects.Theprojecthasresultedinthe10yrfollow-upof235subjectsin the RISC cohort (via UNEW), who have previously undergone baseline (0yr) and 3yr follow-ups. Suchdetailed longitudinal data provide unique and valuable opportunities to investigate the behaviour androbustnessofnovelbiomarkersinanotherwisehealthypopulation.Akeyoutputwillbetheassessmentofmetabolomicbiomarkersaspredictorsofglucosetolerance.


DEXLIFEhasprovidedthe impetusandcatalyst toattractadditional fundingto theRISCcohort toconduct10yr follow-up in a further 400 subjects. Importantly, the groundwork to prepare the protocols/ethicsapprovals and sampling scheduleswill be transferable fromDEXLIFE to the extendedwork. This providesadded value to the DEXLIFE cohort andwill increase the cohort to over 600 subjects with 0, 3 and 10yrfollow-updata.

1.3.9. QuantoseImpairedglucosetolerance(IGT)test

AnIGTtest,QuantoseIGT,whichcanidentifyIGTsubjectsinamixedIGT/NGTpopulationwasdeveloped,inpart,usingdatafromthe23metabolitepanelintheVhicohort.

The23metabolitedatawasusedtodevelopanovelIGTtestbyidentifyingmetaboliteswhoseplasmalevelscorrelatedwiththe2hourplasmaglucose (2hPG) fromtheOGTTandthosewhichhadpredictivevalue inidentifying subjects with IGT. In general the best metabolites were those previously identified as beingbiomarkersof insulin resistanceasmeasuredby the clampand thismaybea reflectionof theperipheralinsulin resistance associated with IGT. The variables with the highest correlation with 2hPG are fastingplasma glucose, AHB, LPGC, and oleic acid. These four metabolites had higher correlations than didanthropometricandmetabolicparameterssuchasinsulin,age,BMI,andHOMA-IR.

A number ofmodelswere generated and one, in particular, including FPG, AHB, LGPC, oleic acid, serine,4MOP,β-hydroxybutyricacid,andpantothenicacidhadAUCsof0.82and0.83inRISCandVhirespectively.This IGT test is calledQuantose IGTand thescore iscalledQIGT. This testestimates theprobability thatasubjectisIGT.Thehigherthescore,themorelikelythesubjectisIGT.Thetesthasasensitivity/specificityof78%/72%andmayserveasaconvenientalternativetotheOGTTtoidentifysubjectsatriskofbeingIGT.Thetest is currently available at Metabolon, Inc. (Durham, NC USA, metabolon.com) and is expected to becommercialised soon inEurope.Metabolon’s clinical diagnostics team isworking to createmetabolomics-driventeststhatgivehealthcareprovidersactionableinformationtoaidinpatientmanagement.

Quantose IGT is designed to easily identify IGT using a single, fasted blood draw. This simple test is aconvenientsurrogatefortheoralglucosetolerancetest(OGTT),thecurrentlyacceptedclinicalpracticeformeasuringIGT.AlthoughtheOGTTcaneffectivelymeasureIGT,patientsmustfastpriortohavingthetest,and after establishing a fasting glucose level by means of a blood draw, the patient must then drink aglucose-richbeverageandundergomultipleblooddrawsoverthecourseofabouttwohours.Becauseit istimeconsumingandcancausepatients to feelnauseated, sweaty,or lightheaded, theOGTT isunpopularwithprimarycarephysiciansandpatients.DEXLIFEresultswillalso informMetabolon’sQuantosediabetesproduct lineandareexpected toresult innewdiagnosticandmonitoringproducts.Anotherareaof focuscouldbetoidentifythebestbiomarkersformonitoringinterventionresponse;ourresultssofarsuggestthatthe best metabolites for diagnosis may not be the best for monitoring therapy response or diseaseprogression.

1.3.10. NetworkofExcellenceandFutureCollaboration

Beyondthecommercialandfutureresearchopportunitiesdescribedabove,theDEXLIFEprojecthasresultedinthecreationofanewnetworkofexcellenceintheareaofdiabetesandpersonalisedmedicine.Continuedcollaboration within and beyond the current partner consortium will help to meet the rapidly growingscreening and intervention needs Europe and worldwide. The DEXLIFE mailing list will facilitate futurecollaboration. A follow on meeting has also been scheduled after completion of the project to facilitatediscussionofcollaborationonpublications,futureresearch,andexploitationdirections.

Todate,theDEXLIFEworkhasresultedinninepublications(discussedinsomedepthinSection1.4.2below).Furthermore, 11 publications are plannedwithin the next year. Partnerswill continue the analysis of theresults. A meeting is scheduled for 20 September 2016 at Steno, where partners will gather to further


discussourcontinuedpublicationstrategyandstrategiesfornovelresearchprojectsandapplications.Stenowillhostthismeeting.

AftertheendoftheDEXLIFEprojectthereisexcellentpotentialforfurtherresearchandtranslation.DEXLIFEresearcherswillkeepsearchingfornewfundingopportunitiesforresearchintheclinicalimplementationofmeasuringbiomarkersasroutineclinicalcare.

TheDEXLIFE interventionhascollecteda largeamountofphenotypicandbiologicaldataon individualsathigh risk of developing diabetes. A major resource has been created by DEXLIFE and it will be used tocontinuethecollaborationbetweenDEXLIFEpartnersbyfacilitatingnewresearchquestionsandapplicationsforfunding.

1.3.11. Conclusion

DEXLIFEhasharnessedandbuiltuponawiderangeofexpertise(from‘omicsto lifestyle intervention)andtechnologies (bioinformatics and profiling) over a wide range of national contexts. As a result, DEXLIFEresultswillhaveanimpactoninawiderangeofscientificdisciplines:

• Metabolomics: Non-targeted metabolite profiling of fasted EDTA plasma samples provided semi-quantitativemeasurementsofhundredsofsmallmolecules(molecularweightlessthan~1500Daltons).Thisdatawereusedtoidentifycandidatebiomarkers(“discovery”)associatedwithdysglycemiaandtype2 diabetes and quantitative assays were developed for themost promising candidates for validationstudiesinadditionalsamplesnotusedinthediscoveryphase.

• Lipidomics: Global lipidomic profiling of plasma (i.e. molecular lipids such as phosphatodylcholines,sphingomyelins, triacylglycerols) was used in DEXLIFE cohorts in order to identify specific lipidsassociated with progression of type 2 diabetes, both in discovery and validation studies. Targetedquantitativeplatformwasalsoestablished foruse in theclinic,basedon theproject findings.DEXLIFEprojectprovidesevidencethatprofilingofmolecularlipidsisapowerfultoolforidentifyingandutilisingtype2diabetesbiomarkersinclinicalsetting.

• RNA-sequencing:RNAsequencing(RNA-Seq)providedahighlysensitiveandaccuratemeasurementofexpressionacrossthetranscriptomeinmusclesamplesfromhigh-risktype2diabetescohort.RNA-seqwasused toprovidevisibility topreviouslyundetected changesoccurring in type2diabetes.RNA-seqallowedus todetect transcript isoforms,singlenucleotidevariants,allele-specificgeneexpressionandotherfeatureswithoutthelimitationofpriorknowledgebeforeDEXLIFEproject.

• Methylation:Illumina450Kmethylationarraysprovidedaquantitativeinterrogationofthemethylationsites across the genome at single-nucleotide resolution in muscle samples from a high- risk type 2diabetes cohort. Methylation arrays were also used to explore the effect of lifestyle interventionprograms.Statisticaltoolswereusedtoselectalistofcandidategeneswithdifferentialmethylationtobevalidatedinspecificvalidationmodelsbybisulfitesequencing.

• Interventionstudies: It isclearfromtheDEXLIFE interventionthatofferingchoicetoparticipantswhenundertaking lifestyle programmes has a major influence on their adherence, quality of life, andresponsiveness.Itisnotnecessarytodifferentiatebetweentheeffectsofdietandphysicalactivitywhenassessing theoptimal intervention for reducing the riskofdiabetes.DEXLIFEhas identifiedmetabolitesthataresignificantlydifferentevenwithvaryingcontributionfromdietandphysicalactivity.

• Bioinformatics: Large amounts of data generated in DEXLIFE, particularly in the domains oflipidomics/metabolomics, demanded utilisation of advanced bioinformatics methods to facilitatemetabolite identification, pathway analysis, and ultimately identification of key molecular features(metabolites/lipids, genes) associated with insulin resistance and type 2 diabetes, which weresubsequentlyalsovalidated.Multipleapproacheswereused,togetherdemonstratingthatbioinformaticsisanessentialandpowerfultoolforthediscoveryofclinicalbiomarkersoftype2diabetes.


1.4. Potentialimpact,maindisseminationactivitiesandexploitationofresults

1.4.1. TheDEXLIFEimpactandfutureuse

1.4.1.1. Introduction

The DEXLIFE project has the potential to impact significantly on future health policy and future researchagendas in relation to diabetes screening and interventions. The DEXLIFE screening programme has thepotential for use in a variety of settings and with different populations, to deliver better personalisedinterventionprogrammes,andresultinbetterlongtermhealthandbetterqualityoflifeforpeoplewithinatriskgroups,therebyalsoreducingassociatedhealthcarecosts.Someofthekeylessonswehavelearntandtheirpotentialimplicationsforthefuturearesetoutbelow.

ThereispotentialfortheimpactoftheDEXLIFEinterventiontobefeltonanumberofdifferentlevels:

• General practice and specialist clinical practice: DEXLIFE provides an approach with the potential toimprovescreening,capacityforpersonalisedintervention,patienthealth,andqualityoflife.

• Atthecommunityandpatients’level:Ourresultsshowhealthbenefitsforpeoplewhoparticipateinthepersonalisedintervention.DEXLIFEhasthepotentialtoofferimprovementsinhealthandqualityoflifeforpatientswhoareathigh-risk.

• Researchanddevelopment level:TheDEXLIFE interventionhascollecteda largeamountofphenotypicandbiologicaldataonindividualsathighriskofdevelopingdiabetes.AmajorresourcehasbeencreatedbyDEXLIFE and itwill be used to continue the collaboration betweenDEXLIFE partners by facilitatingnewresearchquestionsandapplicationsforfunding.

1.4.1.2. Lessonslearnt-Diagnostickitstomeasurebiomarkers

A screening panel of 23 metabolite biomarkers linked to present and future dysglycemia and type 2diabetes. Thepanelwasdevelopedusingdiscovery findings from theDEXLIFEproject, internalMetabolondata, and the literature. Thesebiomarkershavebeen run in samples from theRISC,DMVhi, andMETSIMcohorts, and theDCUdietandexercise intervention study cohorts, andhaveconsistently shownvalue indiscriminatingnormalsubjects fromdysglycemicanddiabeticsubjects. Inparticular, selectivemetabolitebiomarkers of isolated impaired glucose tolerance (IIGT) have been identified (alpha-hydroxybutyric acid(AHB), linoleoylglycerophosphocholine (LGPC), oleic acid) as well as selective metabolite biomarkers ofimpairedfastingglucose(3-methyl-2-oxobutyricacid,4-methyl-2-oxopentanoicacid).Wehopetomakethispanelavailabletoresearchersinterestedinprediabetesanddiabetes.

Asimpletestforimpairedglucosetoleranceusingmetabolitesfromthepanelof23metabolitesalongwithplasma glucosewhich requires a single, fasted blood draw. This test, calledQuantose IGT,allows for theidentificationof subjectswith,orat riskof, IGTwithoutperforminganoralglucose tolerance test (OGTT).MetabolonhavebeguncommercialisationofthetestintheUnitedStates,throughTrueHealthDiagnosticsinFrisco,Texas.ThistestistobeusedinsubjectsthoughttobeatriskofhavingIGT.

1.4.1.3. Lessonslearnt-Personalisedinterventionregimensforfront-lineclinicalenvironments

Stenoiscurrentlyworkingonincludinglipidtestingasroutineanalysisfornewlydiagnosedtype2diabetespatients referred to the Steno Clinic. In the short term, the following study is planned: “A ProspectiveObservationalinvestigationofmetabolomic,lipidomic,andproteomicProfilesinbloodfromtype2diabetespatientsatStenoDiabetesCenter”(POPS).

With POPS, Stenowants to test the hypothesis that a patient profile including psychosocial/demographicdataandphysicaltests,complementedbyanarrayofbiologicaltestsfromtheomics-arena(metabolomics,lipidomics, and proteomics) may be used to obtain a more effective treatment recommendation. Theconcept is referred to as profile-omics. Previous studies at Steno suggest that substantial weight lossachievedbynon-surgicalmeanscanbesustainedinthe longterm,andthatthere isasignificanteffectonthe ability to performphysical activity. As proof of concept, they recentlyworked out an index based onprofile-omics which is informative specifically of the health value of losing weight. They identified a


metabolomic riskprofilewhich seemsparticularly responsive toweight loss. It is desirable to complimentthesestudiesbyapplyingtheprofile-omicsapproachtoshortandlongtermdata,particularlystudyingthebloodproteomebyacompletelynewtechnology.Aprofile-omics informedrecommendationonchoiceoftreatmentwillimproveprecisionandwillmoveevidence-basedmedicineclosertopersonalisedmedicine.

• TheprimarypurposeofPOPSistomeasurethemetabolomic,lipidomic,andproteomicbloodprofilesoftype2diabetespatientsbeforeandafterthe12monthscourseprograminthetype2diabetesclinicatStenoDiabetesCenter.

• ThesecondarypurposeofPOPSistoaddtheomics-datageneratedtootherclinicallyavailablepre-andpost-treatment data in order to work out a predictive tool for which patients benefit from whattreatmentsbasedonthecompletepre-treatmentprofiles.

After evaluation of the POPS study, the goal is to implement routine testing of DEXLIFE identifiedmetabolitesplusPOPSidentifiedpeptidesonallpatientsatStenoDiabetesCenter.

1.4.1.4. Lessonslearnt-Automationandsimplificationofthebiomarkeranalysisprocess

DEXLIFE identifiedandvalidatedapanelofbiomarkerspredictiveofprogressionof type2diabetes,whicharealsosensitivetopatients’responsestopreventivetherapy.Basedonthesefindings,clinicalassaysweredeveloped which can be implemented in a typical clinical chemistry laboratory and thus can be D6.2Exploitation&Up-ScalingPlanappliedbyGPsintheclinic.Theassayoutputsallowsimpleread-outssuchasadded/decreased risk of progression to type 2 diabetes, and can thus be used to assess the efficacy ofparticulartherapy.

1.4.1.5. Education-Diabetesmodulesforpersonalisedmedicine

DuringthecourseofDEXLIFEStenohasestablishedaformalaffiliationwithCopenhagenUniversityandJohnNolan has been appointed professor at Copenhagen University. In the future, Stenowill take part in theeducationofmedicalstudents,especiallyinthefieldofpersonalisedmedicine.

1.4.1.6. Preventingdiabetes-usingDEXLIFEpersonalisedmedicinetomanagepatientsdiagnosedwithdiabetes

Preventiveactionatanearlystageisoneofthemostimportantstepsthatcanbetakentoreducediabetesprevalence. Pre-diabetes, in particular, is an important clinical state in which type 2 diabetes can beprevented.Thisisanimportantandgrowingissueastheglobalobesityanddiabetespandemiccontinuetoaccelerate.ThecurrentresultsandtheemergingnewbiomarkersdiscoveredbytheDEXLIFEprojectprovideacompletelynewtooltodeterminevulnerabilitytoprogressiontotype2diabetes.Followingsimpleriskbasedscreeningwitharisk-score,theuseofanovel,simplebloodtestforatargetedsetofmetabolomicandlipidomic markers will deliver a better method to define in simple terms ‘high risk’ or ‘low risk’ forprogression todiabetes.ThenewknowledgebeinggainedbyDEXLIFE in relation tobiomarkers that trackwith lifestyle interventionresponsewillprovidetheclinicianwithanadditional tool toassessandmonitorresponse to a chosen approach with exercise and diet. Vulnerability to diabetes is complex and multi-factorial. The new DEXLIFE biomarkers will provide the clinician with a relatively simple tool to moreaccuratelydefinebiologicalvulnerabilityintheearlystagesofdiabetesprogression.

1.4.1.7. Managingdiabetes-usingDEXLIFEpersonalisedmedicinetomanagepatientsdiagnosedwithdiabetes

Theapplicationofmetabolicandlipidbiomarkersindiabetestreatmentwillneedfurtherstudy.Takingtheapproach from DEXLIFE, the next step is to test the responses of the leading biomarkers in patients,followingtheintroductionofvarioustargetedtherapies.Thecurrentapproachtothemedicaltreatmentoftype2diabetesconsistsofawidemenuofoptionsaftermetformin, increasingfromdualtotripletherapyanduptocombinedoralandinjectedtherapy.

WhatDEXLIFEmakesavailablenowisthecapabilitytoinformthesetherapeuticchoices,ateachstep,withnewphenotypic information(regardingmetabolitesandlipids),andtotestpatientresponsestotreatmentearly in the course of care. This will help to define individual response or non-response to treatment(includingearlyresponsetodietandexercise).


Thesenewcapabilitieswillsupportaneweraofmorepersonalisedtreatmentoftype2diabetes,basedonthe individual metabolic phenotype. Such a scenario is possible and follows a natural extension of theDEXLIFEproject.Itwillhoweverrequirefurtherstudyinsettingswherethenewbiomarkersareavailableintheclinic forallpatientsatbaselineandduringcarefullyselectedtimepointsduring treatment.ThePOPSstudywillbeinitiatedatStenoin2016,andwillprovidethebasisforpersonalisedtreatmentofdiabetesatSteno.

1.4.1.8. Conclusion

In DEXLIFE we have generated new knowledge about metabolomics, lipidomics, RNA-sequencing,methylation,interventionstudies,andbioinformatics.Webelievethatthisnewknowledgeprovideshealthcare providers and policy makers with a sound basis on which to shape future health policy, diabetessupportsandinterventions.Wehavealsoopenedupavenuesforfurtherresearchandstudy,particularlyintranslationalresearchandfurtherdevelopmentofdiagnosticinstrumentationallowinganalysisofbloodandothersamplesatanacceptablecostforclinicalpractice.

The ultimate legacy of DEXLIFE will be diagnostic kits to measure biomarkers, personalised interventionregimesforfront-lineclinicalenvironments,automationandsimplificationofthebiomarkeranalysisprocess,aswellas feeding into futurepersonalisedmedicineeducation;eachofwhichwillalsohelp toreducetheburdenonthehealthsectoranddeliverrelatedsocialandsocioeconomicbenefits.


1.4.2. DEXLIFEdissemination

Our target audience included academics and researchers, health professionals, voluntary organisations,policymakers, patients and the general public. Our aim has been to raise awareness about diabetesscreening and intervention, and the findings from our research and the DEXLIFE intervention. Below wedescribe the dissemination activities undertaken including online, peer reviewed publications, conferencepresentationsandposters,projectmaterials,eventsandexhibitions,DEXLIFEonEuronews,andtheDEXLIFEfinalconference.

1.4.2.1. Websiteandonline

The project website is at http://dexlife.eu/ and was established in July 2012. The website includes thefollowingsections:

• Homepage (including a brief summary of the project and contact details, this includes news andupdatesregardingrecentdevelopmentsandevents).

• Results(settingoutmoredetailabouttheproject’saimsandobjectives).• PartnersList(detailsofeachbeneficiary,includingtheleadsfromeachorganisation).• Management(providesinformationonthecoordinatorandtheexternaladvisorycommittee)• Press/Media(providesprojectinformationandaprojectpressrelease)• Publications(liststheprojectpublications)• DiabetesRiskScore(givesaccesstothe‘DiabetesRiskScore’quiz)The website has represented an important communication tool for DEXLIFE and has been regularlyupdatedthroughouttheproject.

Figure 4 DEXLIFE website and facebook pages


The@dexlifeand@dexlifeDCUtwitterpagesandtheprojectfacebookpage(illustratedinFigure4above)haveprovidedanonlineforumwithwhichtoengagewithpeopledirectlyaswellastoshareusefulresultsfrom related studies and articles. Participants engaged in the DEXLIFE programme have been able tocommunicate with the team through facebook. Some participants tagged their DEXLIFE exercise relatedactivities–oninstagram.comandflickr.com(socialphotographsharingcommunities),the#dexlifehashtagwasusedtotagphotostakenaspartoftheinterventionregimewhereasontwitter#dexlifehasbeenlinkedto#nikeplusrunningresults.

1.4.2.2. ProjectMaterials

Theprojectmaterialsissuedoverthecourseoftheprojectincludedthefollowing:

• DEXLIFE flyer and leaflets (distributed at the “Research in Action” exhibition, 9th July - 20th July2012,Ireland;EuropeanDiabetesLeadershipForum25th–26thJuly2012,Copenhagen;OpenDoorsBrussels,17thMay2014.)

• DEXLIFEHandbook (draftpresentedat theDEXLIFEconference20thMay2015;updateplanned forearly2016)

Theproject leaflets (Figure5)setouttheproject’saimsandobjectives.Theyalsosummarisedtherisksofdiabetesandprovidetipsonpreventingpeoplefromdevelopingtype2diabetes.

TheDEXLIFEhandbook(Figure6)providesclinicalguidelinesand“recipes”whichcanbeusedbyaclinicianorgeneralpractitionertoidentifytheoptimalinterventionregimenforanindividual.Itpresentsbiomarkersand personalised medicine for predicting diabetes and preparing individualised treatment regimes. ThepurposeofthehandbookistoaidtranslationoftheDEXLIFEprojectresultstotheclinicalenvironment.

An important output of our integrational analysis (across the different ‘omic analyses that took place inDEXLIFE)istheidentificationofourbiomarkers,whichindicatehigherdiabetesriskorpre-diabetes.Also,ithasbeenpossible to identifybiomarkers that trackwitha lifestyle interventionstudy.As thesebiomarkersetsaresimple(consistingoffewand/oreasilymeasuredbiomarkers)thiswillrepresentanimportanttoolforlarge-populationscreeningprogrammes.

ThedraftversionofthishandbookwaspresentedattheDEXLIFEconference20thMay2015.Theconferenceaudiencewas 100 cliniciansworkingwith diabetes. The clinicians represented the entireworld and all inattendance received a copy of the draft version of the handbook. An updated (with new graphic design)versionwassharedonlineon2ndJune2015.


Figure 5 DEXLIFE flyers

Figure 6 DEXLIFE handbook screen shots. The full version can be found online: http://dexlife.eu/eu-project-

description.html


1.4.2.3. Eventsandexhibitions

TheDEXLIFEteamorganisedaseriesofregionalandinternationaleventsinordertodiscussprojectresults,implementationofinterventionsandpotentialimpact.

• DEXLIFEparticipatedintheEuropeanCommission's“ResearchinAction”exhibition,9thJuly-20thJuly2012, in ‘The European Commission Representation’ in Ireland, European Union House, 18 DawsonStreet, Dublin 2. DEXLIFE had an interactive exhibition stand for the duration of the event providinginformation about the DEXLIFE project to the general public, in addition to information regardingdiabetes prevention.Members of the public in attendance, over the twoweeks, were able to assesstheirownriskofdevelopingtype2diabetes,usingtheFINDRISCquestionnairebasedassessment.DCUprovided theequipmentnecessary to complete thequestionnaire, so thatpeoplewere able toweighthemselves,measuretheirheight,calculateBMI,andmeasuretheirwaistcircumference.

• TheDEXLIFE team in the School of Health andHuman Performance at DCU ran several public type 2Diabetes Risk Screening Events.These occurred on the 25-26th July 2012 atDCU13th August 2012 inPhibsboro,Dublin,20thand23rdAugust2012inBallymun,Dublin,andthe31stAugust2012inClontarf,Dublin. Twitter and Facebook were used to publicise these events. At these events, the public wereinvited to complete the FINDISC assessment, were provide with information about their risk fordeveloping diabetes and had the opportunity to volunteer for the 12-week diet and exerciseintervention.

• DEXLIFE participated in the EU Commission Stand at theAnnual BT Young Scientist and TechnologyExhibition in Dublin in January 2013, showcasing the work done by researchers in the DCU DEXLIFEproject. This exhibition showcases the work of primary and secondary school children in Ireland andallowsthemtheopportunityofengagingwithscientists.

• DEXLIFEparticipatedintheEuropeanDiabetesLeadershipForum,hostedbyOrganisationforEconomicCo-operationandDevelopment(OECD)andtheDanishDiabetesAssociationinCopenhagenon25th-26thApril2012.

• StenohostedanexhibitionofresearchatStenoDiabetesCenteron22ndFebruary2013.Atthisevent,apresentationwasmade to the Danish HealthMinister Astrid Kragh. This included an overview of theDEXLIFEproject.

• DEXLIFE participated inOpenDoorsBrussels 17thMay 2014. EoinDurkan fromDCUand Tanja ThybofromStenoparticipated in this eventwith an exhibition standwhere themessagewas delivered thatthatearlydiscoveryofdiabetesmakesitpossibletoavoidorreversethedisease.Therewasamovieontype2diabetesandflyerswerehandedout.Furthermore+500peopleassessedtheirFINDRISCscoreonpaper.EoinandTanjaassistedinweighingandmeasuringwaistcircumference.AftercompletionoftheFINDRISCscore,advicewasgivenaccordingtoresultsandapedometerhandedout.

• AnexhibitionwasheldatStenotoopenthenewmetabolomicslabon5thNovember2014.MatejOrešičandTuuliaHyötyläinen,formerlyatVTT,movedtoStenoDiabetesCenterinApril2014,wheretheysinceestablishedanewsystemsmedicineresearchgroupandametabolomiclaboratory.

1.4.2.4. DEXLIFEonEuronews

Euronews produced a 10 min TV documentary on latest European research on type 2 diabetes earlydetection and diagnosis, including the DEXLIFE project(http://www.euronews.com/2015/11/09/confronting-the-epidemy-that-is-diabetes/). It was aired from 9thNovember2015forawholeweek(22times)ontheprogrammeFuturis.FuturisisprogrammethatfeaturesEuropean science, researchand innovation. Thedocumentarywasbroadcast to430millionhouseholds in130 countries in EuroNews´ thirteen broadcasting languages (English, German, Spanish, French, Greek,Italian,Russian,Portuguese,Arabic,Turkish,Persian,Ukrainian,andHungarian).


Figure7ThemoviewasannouncedonLinkedInandTwitterandisalsoavailableatdexlife.eu.

Figure8JohnNolanwasinterviewedfortheEuronewsdocumentary.


1.4.2.5. DEXLIFEConference

TheDEXLIFEconference,hostedbySteno,washeldon20May2015inconjunctionwiththeStenoFrontiersonpersonalmedicineindiabetescare.Duringthatconference,thefirstdaywasdedicatedtoDEXLIFE.ThefollowingDEXLIFEpartnersgavetalksonDEXLIFEresults:

• TheDEXLIFEstudy:Overviewandmainresults.JohnNolan,Steno. • Lifestyleinterventioninpre-diabetes.DonalO’Gorman,DCU. • Metabolitemarkersofglucosetoleranceandinsulinresistance.JeffCobb,Metabolon.• Useofmetabolomicsinpreventionoftype2diabetes.MatejOresic,Steno.

120internationalseniordiabetologistsattendedtheconferenceinordertobeupdatedonfrontlinediabetesresearchandclinicaldiabetology.

1.4.2.6. Publications

Publishing in peer-reviewed journals has been a key aim of our dissemination strategy in order to reachacademics, researchers, and medical professionals. In total there are now nine project publicationsregistered on the EU portal. These publications are listed in part 2 Template A1 of this final report andincludethefollowing:

• G.S.Andersen,T.Thybo,H.Cederberg,M.Orešič,M.Esteller,A.Zorzano,B.Carr,M.Walker,J.Cobb,C.Clissmann,D.J.O'Gorman,J.J.Nolan;onbehalfoftheDEXLIFEConsortium.TheDEXLIFEstudymethods:Identifying novel candidate biomarkers that predict progression to type 2 diabetes in high riskindividuals.DiabetesRes.Clin.Pract.106,383-389(2014).

• O'DonoghueG,CunninghamC,MurphyF,WoodsC,Aagaard-HansenJ.;Assessmentandmanagementofriskfactorsforthepreventionoflifestyle-relateddisease:across-sectionalsurveyofcurrentactivities,barriers and perceived training needs of primary care physiotherapists in the Republic of Ireland.Physiotherapy.2014Jun;100(2):116-22.

• J.Cobbetal.ANovelTestforIGTUtilizingMetaboliteMarkersofGlucoseTolerance.JournalofDiabetesScienceandTechnology2015;9(1):69-76.

• T.HyötyläinenandM.Orešič.Systemsbiologystrategiestostudylipidomesinhealthanddisease.Prog.LipidRes.55,43-60(2014).

• HyötyläinenT,OrešičM.Optimizingthelipidomicsworkflowforclinicalstudies-practicalconsiderations.AnalBioanalChem.2015Apr9.PubMedPMID:25855150.

• MargaretSinnott,BrendanT.Kinsley,AbaigealD.Jackson,CathalWalsh,TonyO’Grady,JohnJ.Nolan,Peter Gaffney , Gerard Boran , Cecily Kelleher, Bernadette Carr: Fasting Plasma Glucose as InitialScreening for Diabetes and Prediabetes in Irish Adults: The Diabetes Mellitus and Vascular HealthInitiative(DMVhi).PLoSOneVol.10/Issue4

• Jørgenrud B, Jäntti S, Mattila I, Pöhö P, Rønningen KS, Yki-Järvinen H, Orešič M, Hyötyläinen T. Theinfluenceof samplecollectionmethodologyandsamplepreprocessingon thebloodmetabolicprofile.Bioanalysis.2015May;7(8):991-1006.doi:10.4155/bio.15.16.

• Hyötyläinen T, Orešič M: Analytical Lipidomics in Metabolic and Clinical Research: Trends inEndocrinologyandMetabolismS1043-2760(15)00158-7.

• GrainneM.O’Donoghue,AileenKennedy,GregersStigAndersen,EoinDurkan,TanjaThybo,MargaretSinnott , John J. Nolan , Donal J. O’Gorman: An evaluation of the DEXLIFE ‘self-selected’ lifestyleinterventionaimedatimprovinginsulinsensitivityinpeopleatriskofdevelopingtype2diabetes:studyprotocolforarandomisedcontrolledtrial.Trials.Vol.16,529-534.

Aswell as the articles that have already been published, the team isworking on a number of additionalpapers,manyofwhicharealreadyatanadvancedstage.


1.4.2.7. Presentations

Sincethebeginningoftheproject,theDEXLIFEteamhaverecorded55disseminationactivities(aspertheEUportalandincludedinpart2templateA2ofthisfinalreport), includingpresentationsatnumerouskeyconferencesandevents.Somenotablepresentationsandpostersaresetoutbelow:

• Prof María Berdasco (IDIBELL) attended the EASD Berlin, on 4th October 2012 and presented on‘Epigeneticmodificationsincomplexdiseases’.

• StenopresentedaposterattheWorldCongressofthePreventionofDiabetesanditscomplications,on13thNovember2012inMadridon‘Mechanismsofpreventionoftype2diabetesbylifestyleinterventioninsubjectswithpre-diabetes’.

• VTT gave a presentation at EASD Barcelona on 13th September 2013 on ‘Serum lipidomic profilingidentifies biomarkers associatedwith progression to type 2 diabetes in theMETSIM study’. Jeff Cobb(Metabolon)presentedaposterat thesameevent, titled ‘MetabolomicProfiling IdentifiesBiomarkersAssociatedwithDysglycemiaandIncidentType2DiabetesintheMETSIMStudy’.

• Jeff Cobb (Metabolon) presented two poster at the American Diabetes Association'smeeting on 13thJune 2013 in San Francisco; ‘Metabolomic Characterization of Impaired Fasting Glucose (IFG) andImpaired Glucose Tolerance (IGT)’ and ‘Novel Metabolite Models that Distinguish Impaired GlucoseTolerance(IGT)fromNormalGlucoseTolerance(NGT)’.

• Project coordinators Steno presented theDEXLIFE project at ameeting in The Shanghai Institutes forBiologicalScienceson10thJanuary2014.

• AileenKennedyrepresentedDEXLIFEattheEASDViennaon15thSeptember2014,whereshepresenteda poster on ‘The Identification of Novel Metabolites that Track with Improvements in GlycaemiaFollowinga12-WeekLifestyleInterventioninHighRiskIndividuals’.JeffCobb(Metabolon)alsogaveanoral presentation at this meeting on, ‘Novel Metabolite Models that Distinguish Impaired GlucoseTolerance(IGT)FromNormalGlucoseTolerance(NGT)’.

• Jeff Cobb (Metabolon) gave an oral to the American Association of Clinical Endocrinologists annualmeeting inNashville,USon13thMay2015,on ‘SelectiveBiomarkersof Isolated IFG(iIFG)andIsolatedIGT(iIGT)’.

• Jeff Cobb (Metabolon) presented a poster at the American Diabetes Association annual meeting inBoston,USon5thJune2015,2015entitled,‘AHBandLGPCareSelectiveBiomarkersofImpairedGlucoseTolerance(IGT)’.

• DEXLIFEwererepresentedattheEASD2015meetinginStockholm.Oralpresentationsincluded(Steno)‘Serumlipidomeasanindependentpredictorofprogressiontotype2diabetes:theMETSIMstudy’and(Metabolon)‘SelectivemetabolitebiomarkersofisolatedIFG(iIFG)andisolatedIGT(iIGT)’.

• Steno presented a poster at the First Annual Danish Bioinformatics Conference, 27th August 2015, inOdense,Denmark.Theposterwastitled,‘Lipidome-BasedEarlyPredictorsofType2Diabetes’.

• Steno gave two oral presentations at the 8th World Congress on Prevention of Diabetes and ItsComplications, Cartagena, Colombia (15th – 17th October 2015) including: ‘The DEXLIFE project’ and‘Predictionoftype2diabetesusingmolecularprofiling(openingplenarylecture)’.

• UNEW represented DEXLIFE at the DICP Symposium (XXXIX) on functional metabolomicson the 9thNovember2015 inDalian,China.Theygavea talkon ‘Serum lipidomeasan independentpredictorofprogressiontotype2diabetes’.

• DCUpresented aposter at theDanishDiabetesAcademy&CambridgeMetabolicNetworkWorkshop10th December 2015 titled ‘The identification of novel metabolites that track with improvements inglycaemiafollowinga12-weeklifestyleinterventioninhighriskindividuals’.


• KristineFærch(Steno)willanoralpresentationatACSM's63rdAnnualMeeting,7thWorldCongressonExercise isMedicine inBoston,Massachusettson1st June2016.Her talk is entitled, ‘Heterogeneity infitnessresponsetoalifestyleintervention:TheDEXLIFEinterventionstudy’.

1.4.2.8. Other

TheDEXLIFEteamhasalsoengagedwithotherstakeholdersandinitiativesoverthecourseoftheproject.

Steno (Tanja Thybo) explored the possible collaboration with “SIBS-Novo Nordisk Translational ResearchCentre forPre-Diabetes".TheShanghai Institutes forBiological Sciences (SIBS),ChineseAcademySciences(CAS)andNovoNordiskhavedecidedtocollaborateincertainrespectsintheareaofpre-diabetesresearchand development, and established in 2008 a joint research centre for pre-diabetes named "SIBS-NovoNordiskTranslationalResearchCentreforPre-Diabetes".

Theirannualreviewwasheldatthekeylabofsystembiology,SIBS,ShanghaionJanuary10,2014,andTanjaThybowas invited to presentDEXLIFE. Several of the PDC results areparticularly exciting, as theDEXLIFEconsortium has obtained similar results in Caucasian cohorts. Different scenarios for collaboration wereexploredincludingaH2020application.

Each project partner has their own relationship with regional and national stakeholders, in particulardiabetesassociations,andcontinuestoengagewiththemlocally(e.g. localmeetings,diabetesguidebooksetc.).

1.4.2.9. Conclusion

DEXLIFE partners have achieved several significant publications, with several more in preparation.ResearchersalsopresentedonDEXLIFEandthedevelopmentofnoveldiagnosticsandpredictivebiomarkersconferences.

Throughout the DEXLIFE project, we have grown our presence online through the project website andTwitter account. We have issued project resources and our project handbook (uploading them to ourwebsite and distributing them in hard copy). The DEXLIFE conference took place on 20th May 2015 inCopenhagen and provided a valuable opportunity for the team to engage with external experts, gathervaluablefeedbackabouttheproject,andconsidernextstepsfortheDEXLIFEoutputs.

Webelievethatourworkondissemination(withinWP6)haslaidasolidfoundationforscreeningtestsandinterventions to help prevent progression to diabetes in high-risk European citizens. Our disseminationstrategy has spread theDEXLIFEmessage about the future of personalised lifestyle interventions and theimportance of focusing on the individualwhen characterising baseline risk and subsequent interventions.Theworkundertakenwillcontinuetobearfruitbeyondthelifeoftheproject.

Webelievethatourresultsandfindingshaverealpotentialtoimpactonhealthpolicyinthefutureandthatour personalised lifestyle intervention has the potential to make a significant contribution to self-managementsupporttohelppreventprogressiontodiabetesinhigh-riskEuropeancitizen.


1.5. Projectwebsiteandcontactdetails

ContactDetails

ProjectCoordinator:ProfessorJohnNolan,[email protected]:TanjaThybo,[email protected],pleaseseeourprojectwebsite:http://dexlife.eu/(Figure9).

ProjectpartnersarelistedinFigure10.


Figure 9 DEXLIFE website


Figure 10 DEXLIFE partner list

dexlife final report - cordis · diabetes prevention project, which ran between 2012 and 2015 and...

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