BACKGROUND: A number of studies have linked neuropsychiatric symptoms to increase risk of dementia. OBJECTIVE: To determine if risk of conversion to mild cognitive impairment or dementia among healthy controls varied as a function of their pattern of neuropsychiatric symptoms. METHOD: We studied individuals in the National Alzheimer Coordinating Center dataset collected from 34 Alzheimer Disease Centers between 2005 and 2013. The analysis included 4,517 volunteers who were ≥60 years old, cognitively normal, and had complete Neuropsychiatric Inventory data at their baseline visit, and had at least one follow-up. We used latent class analysis to identify four classes based on patterns of NPI symptoms. We used a Cox proportional hazards model to determine if time to MCI or dementia varied by baseline latent class membership. RESULTS: We identified four latent classes of neuropsychiatric symptoms: irritable, depressed, complex (depression, apathy, irritability, and nighttime behaviors) and asymptomatic. 873 participants converted to MCI or dementia. Hazard ratios for conversion by class were 1.76 (95% CI: 1.34, 2.33) for the irritable class, 3.20 (95% CI: 2.24, 4.58) for the complex class, and 1.90 (95% CI: 1.49, 2.43) for the depressed class, with the asymptomatic class as the reference. CONCLUSIONS: Membership in all three symptomatic classes was associated with greater risk of conversion to MCI or dementia; the complex class had the greatest risk. Different patterns of neuropsychiatric symptoms may represent different underlying neuropathological pathways to dementia. Further work imaging and pathology research is necessary to determine if this is the case.
BACKGROUND: A number of studies have linked neuropsychiatric symptoms to increase risk of dementia. OBJECTIVE: To determine if risk of conversion to mild cognitive impairment or dementia among healthy controls varied as a function of their pattern of neuropsychiatric symptoms. METHOD: We studied individuals in the National Alzheimer Coordinating Center dataset collected from 34 Alzheimer Disease Centers between 2005 and 2013. The analysis included 4,517 volunteers who were ≥60 years old, cognitively normal, and had complete Neuropsychiatric Inventory data at their baseline visit, and had at least one follow-up. We used latent class analysis to identify four classes based on patterns of NPI symptoms. We used a Cox proportional hazards model to determine if time to MCI or dementia varied by baseline latent class membership. RESULTS: We identified four latent classes of neuropsychiatric symptoms: irritable, depressed, complex (depression, apathy, irritability, and nighttime behaviors) and asymptomatic. 873 participants converted to MCI or dementia. Hazard ratios for conversion by class were 1.76 (95% CI: 1.34, 2.33) for the irritable class, 3.20 (95% CI: 2.24, 4.58) for the complex class, and 1.90 (95% CI: 1.49, 2.43) for the depressed class, with the asymptomatic class as the reference. CONCLUSIONS: Membership in all three symptomatic classes was associated with greater risk of conversion to MCI or dementia; the complex class had the greatest risk. Different patterns of neuropsychiatric symptoms may represent different underlying neuropathological pathways to dementia. Further work imaging and pathology research is necessary to determine if this is the case.
Entities:
Keywords:
Alzheimer’s disease; dementia; depression; latent class analysis; neuropsychiatric symptoms
Authors: Martin Steinberg; JoAnn T Tschanz; Christopher Corcoran; David C Steffens; Maria C Norton; Constantine G Lyketsos; John C S Breitner Journal: Int J Geriatr Psychiatry Date: 2004-01 Impact factor: 3.485
Authors: Constantine G Lyketsos; Oscar Lopez; Beverly Jones; Annette L Fitzpatrick; John Breitner; Steven DeKosky Journal: JAMA Date: 2002-09-25 Impact factor: 56.272
Authors: B Winblad; K Palmer; M Kivipelto; V Jelic; L Fratiglioni; L-O Wahlund; A Nordberg; L Bäckman; M Albert; O Almkvist; H Arai; H Basun; K Blennow; M de Leon; C DeCarli; T Erkinjuntti; E Giacobini; C Graff; J Hardy; C Jack; A Jorm; K Ritchie; C van Duijn; P Visser; R C Petersen Journal: J Intern Med Date: 2004-09 Impact factor: 8.989
Authors: G C Román; T K Tatemichi; T Erkinjuntti; J L Cummings; J C Masdeu; J H Garcia; L Amaducci; J M Orgogozo; A Brun; A Hofman Journal: Neurology Date: 1993-02 Impact factor: 9.910
Authors: Jasenka Demirovic; Ronald Prineas; David Loewenstein; Judy Bean; Ranjan Duara; Steven Sevush; Jose Szapocznik Journal: Ann Epidemiol Date: 2003-07 Impact factor: 3.797
Authors: Ali Ezzati; Andrea R Zammit; Christian Habeck; Charles B Hall; Richard B Lipton Journal: Brain Imaging Behav Date: 2020-10 Impact factor: 3.978
Authors: Muhammad Haroon Burhanullah; JoAnn T Tschanz; Matthew E Peters; Jeannie-Marie Leoutsakos; Joshua Matyi; Constantine G Lyketsos; Milap A Nowrangi; Paul B Rosenberg Journal: Am J Geriatr Psychiatry Date: 2019-05-23 Impact factor: 4.105
Authors: Michael A Sugarman; Michael L Alosco; Yorghos Tripodis; Eric G Steinberg; Robert A Stern Journal: J Alzheimers Dis Date: 2018 Impact factor: 4.472
Authors: Jeannie-Marie S Leoutsakos; Elizabeth A Wise; Constantine G Lyketsos; Gwenn S Smith Journal: Int J Geriatr Psychiatry Date: 2019-09-02 Impact factor: 3.485
Authors: Zahinoor Ismail; Luis Agüera-Ortiz; Henry Brodaty; Alicja Cieslak; Jeffrey Cummings; Corinne E Fischer; Serge Gauthier; Yonas E Geda; Nathan Herrmann; Jamila Kanji; Krista L Lanctôt; David S Miller; Moyra E Mortby; Chiadi U Onyike; Paul B Rosenberg; Eric E Smith; Gwenn S Smith; David L Sultzer; Constantine Lyketsos Journal: J Alzheimers Dis Date: 2017 Impact factor: 4.472
Authors: Sarah Payne; Jane B Shofer; Andrew Shutes-David; Ge Li; Adrienne Jankowski; Pamela Dean; Debby Tsuang Journal: J Alzheimers Dis Date: 2022 Impact factor: 4.160