The Value of Biomarker Comparisons Between Autosomal Dominant and Late-Onset Alzheimer Disease
Authors: Adam S. Fleisher
Journal: JAMA Neurology (2014)

AutosomaldominantAlzheimerdisease (ADAD)accounts for less than 1%of those affected byAlzheimer disease (AD) in the world’s population.However, because temporal progression is fairlypredictableandtheunderlyingneuropathologyandclinical presentation parallel that of late-onset sporadic AD (sAD), it provides an important human model for researchonmoreprevalentsAD.Morethan500familieswithmore than200knownmutations intheamyloidprecursorproteinand presenilingenesassociatedwithamyloid-β(Aβ)productionhave beenidentified.Muchofwhatweknowaboutthemolecularand neuropathologic origins of AD stems fromdiscoveries in these geneticvariantsandassociatedanimalmodels.GeneticAβoverproductiondisordersoffer researchers theopportunity toevaluate thenaturalprogressionofAD inahighlypredictablemodel. Application of fluid biomarkers and neuroimaging tools in the study of ADAD can aid in the understanding of early neuropathological changes and assist in identifying predictive presymptomaticmarkers of clinically significantAD.On theother hand, althoughADADhasmanysimilarities in clinical progressionandpathology tosAD, thesearearguablydiseaseswithdistinct inciting mechanisms that lead to similar downstream effects. In ADAD, mutations in encoding sequences and splicing enzymes responsible for the production of Aβ lead to increases in Aβ oligomers that may be the principal etiological factors leading todementia.Toxic solubleAβoligomersarealso critical to the amyloid hypothesis in sAD. However, sporadic AD is a more complex multifactorial disease of abnormal aging likely to involve inadequate clearance of Aβ, tau protein misfolding and tangle formation, mitochondrial dysfunction, inflammation, oxidative stress, and other influences whose ultimate consequence is neurodegeneration. Despite thesedifferences, abetterunderstandingofADAD has the potential to inform and expedite the development of predictive biomarkers of AD dementia and the development of treatments to prevent progression to clinical stages of both early-onset and late-onset AD. For this purpose, a close and careful comparison of knownbiomarkers betweenADADand sAD will facilitate an understanding of phenotypic similarities and incongruences and bidirectionally inform the use of biomarkers inclinical trials inboth formsofAD.Althoughthere is increasing literatureevaluatingbiomarkers inADADandsAD, apaucityof studiesdirectly compares theminADADwith sAD. In this issue of JAMANeurology, Thomas and colleagues1 havepresenteda sophisticated evaluationof resting statenetworks (RSNs) in the brain that directly compares resting-state functionalconnectivitymagnetic resonance imaging (rs-fcMRI) data fromtheDominantly InheritedAlzheimerNetwork (DIAN) studywithpatientswith sADandhealthy control participants enrolled inobservational studies at theWashingtonUniversity Knight Alzheimer Disease Research Center. They compared rs-fcMRI as a biomarker of earlyAD in a cross-sectional cohort of ADAD (n = 87) from the DIAN study with sAD participants (n = 507) from theAlzheimerDiseaseResearchCenter cohort. In this direct comparison, the authors reportmany similarities between RSNs in ADAD and sAD,with findings in one form of ADpredictingclinical stages in theother.Forexample, rs-fcMRI changes associatedwith theClinicalDementiaRating inADAD wereable todistinguishClinicalDementiaRating stages in sAD andviceversa.This is akeyexampleofhowbiomarker changes in ADADmay be similar to thosemanifested in sAD. Resting-state functional connectivitymagnetic resonance imagingmeasuresregionsofcoordinatedorcorrelatedbloodoxygenlevel–dependentsignalduringtherestingstatewithoutcognitive task performance. In sAD, several RSNs differ from agematchedhealthy individuals.ThemostextensivelystudiedRSN insAD is thedefaultmodenetwork,which involvesmanybrain regions thathaveprominentAβand taupathology indementia duetoAD.Othernotablenetworksassessed in theThomasetal1 studyincludethedorsalattentionnetwork,executivecontrolnetwork,saliencenetworkforemotionalregulation,andsensorimotornetwork.Resting-statebrainnetworkswereoften impacted, withagreatereffectofdiseaseseverity inADADthaninsAD,suggestingamoreaggressivepathophysiologiccourse.Severalnetworks (executivecontrol, salience,andsensorimotor) indicated a greater rate of rs-fcMRI decline with disease progression in ADADcomparedwithsAD,withexecutivedysfunction inADAD moreaggressivelyaffectedrelativetoothernetworks.Whencomparing internetworkassociations, therewerereductionswithrespecttotheClincialDementiaRatinginbothsADandADAD.This was seen in the relationship between the defaultmode–dorsal attention networks and the default mode–sensorimotor networks,withcross-networkimpairmentsmoreaggressiveinADAD progressionthaninsAD.However, thisstudywasunabletodemonstratesignificantrs-fcMRIchangespriortotheageofestimated symptomonset inADAD, implyingthat theseRSNseitherdonot change until later in the pathological stage of disease or this methodforassessmentofrs-fcMRIisnotsensitivetoearlyphysiological changes in presymptomatic AD. This studybyThomas andcolleagues1 highlights theneed fordirect comparisonsbetweenbiomarkers inADADandsAD.1 It is a step in the right direction toward the elusive goal of deRelated article page 1111 Opinion