BACKGROUND: The association of subjective memory impairment (SMI) with cognitive performance in healthy elderly subjects is poor because of confounds such as depression. However, SMI is also a predictor for future dementia. Thus, there is a need to identify subtypes of SMI that are particularly related to inferior memory performance and may represent at-risk stages for cognitive decline. METHOD: A total of 2389 unimpaired subjects were recruited from the German Study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe), as part of the German Competence Network on Dementia. Clusters of SMI according to patterns of response to SMI questions were identified. Gender, age, depressive symptoms, apolipoprotein E (apoE) genotype, delayed recall and verbal fluency were included in a Classification and Regression Tree (CART) analysis to identify discriminators between the clusters. RESULTS: We identified three clusters. Cluster 1 contained subjects without memory complaints. Cluster 2 contained subjects with general memory complaints, but mainly without memory complaints on individual tasks of daily living. Cluster 3 contained subjects with general memory complaints and complaints on individual tasks of daily living. Depressive symptoms, as the first-level discriminator, distinguished between clusters 1 and 2 versus cluster 3. In subjects with only a few depressive symptoms, delayed recall discriminated between cluster 1 versus clusters 2 and 3. CONCLUSIONS: In SMI subjects with only a minor number of depressive symptoms, memory complaints are associated with delayed recall. As delayed recall is a sensitive predictor for future cognitive decline, SMI may be the first manifestation of future dementia in elderly subjects without depression.
BACKGROUND: The association of subjective memory impairment (SMI) with cognitive performance in healthy elderly subjects is poor because of confounds such as depression. However, SMI is also a predictor for future dementia. Thus, there is a need to identify subtypes of SMI that are particularly related to inferior memory performance and may represent at-risk stages for cognitive decline. METHOD: A total of 2389 unimpaired subjects were recruited from the German Study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe), as part of the German Competence Network on Dementia. Clusters of SMI according to patterns of response to SMI questions were identified. Gender, age, depressive symptoms, apolipoprotein E (apoE) genotype, delayed recall and verbal fluency were included in a Classification and Regression Tree (CART) analysis to identify discriminators between the clusters. RESULTS: We identified three clusters. Cluster 1 contained subjects without memory complaints. Cluster 2 contained subjects with general memory complaints, but mainly without memory complaints on individual tasks of daily living. Cluster 3 contained subjects with general memory complaints and complaints on individual tasks of daily living. Depressive symptoms, as the first-level discriminator, distinguished between clusters 1 and 2 versus cluster 3. In subjects with only a few depressive symptoms, delayed recall discriminated between cluster 1 versus clusters 2 and 3. CONCLUSIONS: In SMI subjects with only a minor number of depressive symptoms, memory complaints are associated with delayed recall. As delayed recall is a sensitive predictor for future cognitive decline, SMI may be the first manifestation of future dementia in elderly subjects without depression.
Authors: A Peters; A Döring; K-H Ladwig; C Meisinger; B Linkohr; C Autenrieth; S E Baumeister; J Behr; A Bergner; H Bickel; M Bidlingmaier; A Dias; R T Emeny; B Fischer; E Grill; L Gorzelniak; H Hänsch; S Heidbreder; M Heier; A Horsch; D Huber; R M Huber; R A Jörres; S Kääb; S Karrasch; I Kirchberger; G Klug; B Kranz; B Kuch; M E Lacruz; O Lang; A Mielck; D Nowak; S Perz; A Schneider; H Schulz; M Müller; H Seidl; R Strobl; B Thorand; R Wende; W Weidenhammer; A-K Zimmermann; H-E Wichmann; R Holle Journal: Z Gerontol Geriatr Date: 2011-12 Impact factor: 1.281
Authors: Laura A Rabin; Colette M Smart; Paul K Crane; Rebecca E Amariglio; Lorin M Berman; Mercé Boada; Rachel F Buckley; Gaël Chételat; Bruno Dubois; Kathryn A Ellis; Katherine A Gifford; Angela L Jefferson; Frank Jessen; Mindy J Katz; Richard B Lipton; Tobias Luck; Paul Maruff; Michelle M Mielke; José Luis Molinuevo; Farnia Naeem; Audrey Perrotin; Ronald C Petersen; Lorena Rami; Barry Reisberg; Dorene M Rentz; Steffi G Riedel-Heller; Shannon L Risacher; Octavio Rodriguez; Perminder S Sachdev; Andrew J Saykin; Melissa J Slavin; Beth E Snitz; Reisa A Sperling; Caroline Tandetnik; Wiesje M van der Flier; Michael Wagner; Steffen Wolfsgruber; Sietske A M Sikkes Journal: J Alzheimers Dis Date: 2015-09-24 Impact factor: 4.472
Authors: Katja Hagen; Ann-Christine Ehlis; Florian B Haeussinger; Stefan Beeretz; Gina V Kromer; Sebastian Heinzel; Walter Maetzler; Gerhard W Eschweiler; Daniela Berg; Andreas J Fallgatter; Florian G Metzger Journal: J Neural Transm (Vienna) Date: 2014-12-18 Impact factor: 3.575
Authors: Richard J Kryscio; Erin L Abner; Gregory E Cooper; David W Fardo; Gregory A Jicha; Peter T Nelson; Charles D Smith; Linda J Van Eldik; Lijie Wan; Frederick A Schmitt Journal: Neurology Date: 2014-09-24 Impact factor: 9.910
Authors: Katherine A Gifford; Dandan Liu; Hugo Carmona; Zengqi Lu; Raymond Romano; Yorghos Tripodis; Brett Martin; Neil Kowall; Angela L Jefferson Journal: J Alzheimers Dis Date: 2015 Impact factor: 4.472
Authors: Heather D Lucas; Jim M Monti; Edward McAuley; Patrick D Watson; Arthur F Kramer; Neal J Cohen Journal: Neuropsychology Date: 2016-04-07 Impact factor: 3.295
Authors: Nikki L Hill; Jacqueline Mogle; Rachel Wion; Elizabeth Munoz; Nicole DePasquale; Andrea M Yevchak; Jeanine M Parisi Journal: Gerontologist Date: 2016-06-23