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Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN).

Nicole S McKayBrian A GordonRuss C HornbeckAylin DincerShaney FloresSarah J KeefeNelly Joseph-MathurinClifford R JackRobert KoeppePeter R MillarBeau M AncesCharles D ChenAlisha DanielsDiana A HobbsKelley JacksonDeborah KoudelisParinaz MassoumzadehAustin McCulloughMichael L NickelsFarzaneh RahmaniLaura SwisherQing WangRicardo Francisco AllegriSarah B BermanAdam M BrickmanWilliam S BrooksDavid M CashJasmeer P ChhatwalGregory S DayMartin R FarlowChristian Peter la FougèreNick C FoxMichael J FulhamBernardino F GhettiNeill Graff-RadfordTakeshi IkeuchiWilliam KlunkJae-Hong LeeJohannes LevinRalph MartinsColin L MastersJonathan McConathyHiroshi MoriJames M NobleGerald ReischlChristopher RoweStephen P SallowayRaquel Sanchez-VallePeter R SchofieldHiroyuki ShimadaMikio ShojiYi SuKazushi SuzukiJonathan VögleinIgor YakushevCruchaga CarlosJason HassenstabCeleste M KarchEric McDadeRichard J PerrinChengjie XiongJohn C MorrisRandell J BatemanTammie L S Benzingernull null
Published in: Nature neuroscience (2023)
The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers.
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