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Observational Study
. 2019 Jul 31;11(1):66.
doi: 10.1186/s13195-019-0515-y.

Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study

Lisa Miebach  1   2 , Steffen Wolfsgruber  3   4 , Alexandra Polcher  3   4 , Oliver Peters  5   6 , Felix Menne  5   6 , Katja Luther  5 , Enise Incesoy  5 , Josef Priller  6   7 , Eike Spruth  6   7 , Slawek Altenstein  6   7 , Katharina Buerger  8   9 , Cihan Catak  8 , Daniel Janowitz  8 , Robert Perneczky  9   10   11   12 , Julia Utecht  9   10 , Christoph Laske  13   14 , Martina Buchmann  13   14 , Anja Schneider  3   4 , Klaus Fliessbach  3   4 , Pascal Kalbhen  4 , Michael T Heneka  3   4 , Frederic Brosseron  3   4 , Annika Spottke  3   15 , Nina Roy  3 , Stefan J Teipel  16   17 , Ingo Kilimann  16   17 , Jens Wiltfang  18   19 , Claudia Bartels  18   19 , Emrah Düzel  20   21 , Laura Dobisch  21 , Coraline Metzger  20   21   22 , Dix Meiberth  3   23 , Alfredo Ramirez  23 , Frank Jessen  3   23 , Michael Wagner  3   4
Affiliations
Observational Study

Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study

Lisa Miebach et al. Alzheimers Res Ther. .

Abstract

Background: Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer's disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers.

Methods: We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers.

Results: Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181.

Conclusions: Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology.

Keywords: Aß42; CSF biomarkers; Cerebrospinal fluid (CSF); Preclinical AD; Preclinical Alzheimer’s disease (AD); Subjective cognitive decline (SCD).

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Frequency of domains reported with an experienced decline and associated worries, respectively
Fig. 2
Fig. 2
Relationship between CSF biomarkers and the number of fulfilled SCD-plus features in cognitively normal individuals (n = 205)
Fig. 3
Fig. 3
Relationship between CSF-biomarkers and the number of fulfilled SCD domains in cognitively normal individuals (n = 205)
See this image and copyright information in PMC

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