Network analysis of neuropsychiatric symptoms in Alzheimer’s disease
Abstract Background Neuropsychiatric symptoms due to Alzheimer’s disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective tre...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-08-01
|
| Series: | Alzheimer’s Research & Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13195-023-01279-6 |
| _version_ | 1797577711510618112 |
|---|---|
| author | Grace J. Goodwin Stacey Moeller Amy Nguyen Jeffrey L. Cummings Samantha E. John |
| author_facet | Grace J. Goodwin Stacey Moeller Amy Nguyen Jeffrey L. Cummings Samantha E. John |
| author_sort | Grace J. Goodwin |
| collection | DOAJ |
| description | Abstract Background Neuropsychiatric symptoms due to Alzheimer’s disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment. Methods The network relationships of behavioral symptoms were estimated from Neuropsychiatric Inventory Questionnaire (NPI-Q) data acquired from 12,494 older adults with MCI and AD during their initial visit. Network analysis provides insight into the relationships among sets of symptoms and allows calculation of the strengths of the relationships. Nodes represented individual NPI-Q symptoms and edges represented the pairwise dependency between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. Results The analysis showed patterns of connectivity among the symptoms of the NPI-Q. The network (M = .28) consisted of mostly positive edges. The strongest edges connected nodes within symptom domain. Disinhibition and agitation/aggression were the most central symptoms in the network. Depression/dysphoria was the most frequently endorsed symptom, but it was not central in the network. Conclusions Neuropsychiatric symptoms in MCI and AD are highly comorbid and mutually reinforcing. The presence of disinhibition and agitation/aggression yielded a higher probability of additional neuropsychiatric symptoms. Interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Future work will compare neuropsychiatric symptom networks across dementia etiologies, informant relationships, and ethnic/racial groups, and will explore the utility of network analysis as a means of interrogating treatment effects. |
| first_indexed | 2024-03-10T22:11:53Z |
| format | Article |
| id | doaj.art-f4787ae87bd64268ac0a7a90c03df4eb |
| institution | Directory Open Access Journal |
| issn | 1758-9193 |
| language | English |
| last_indexed | 2024-03-10T22:11:53Z |
| publishDate | 2023-08-01 |
| publisher | BMC |
| record_format | Article |
| series | Alzheimer’s Research & Therapy |
| spelling | doaj.art-f4787ae87bd64268ac0a7a90c03df4eb2023-11-19T12:35:39ZengBMCAlzheimer’s Research & Therapy1758-91932023-08-0115111210.1186/s13195-023-01279-6Network analysis of neuropsychiatric symptoms in Alzheimer’s diseaseGrace J. Goodwin0Stacey Moeller1Amy Nguyen2Jeffrey L. Cummings3Samantha E. John4Department of Psychology, University of Nevada, Las Vegas (UNLV)Department of Psychology, University of Nevada, Las Vegas (UNLV)Department of Brain Health, University of Nevada, Las Vegas (UNLV)Department of Brain Health, University of Nevada, Las Vegas (UNLV)Department of Brain Health, University of Nevada, Las Vegas (UNLV)Abstract Background Neuropsychiatric symptoms due to Alzheimer’s disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment. Methods The network relationships of behavioral symptoms were estimated from Neuropsychiatric Inventory Questionnaire (NPI-Q) data acquired from 12,494 older adults with MCI and AD during their initial visit. Network analysis provides insight into the relationships among sets of symptoms and allows calculation of the strengths of the relationships. Nodes represented individual NPI-Q symptoms and edges represented the pairwise dependency between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. Results The analysis showed patterns of connectivity among the symptoms of the NPI-Q. The network (M = .28) consisted of mostly positive edges. The strongest edges connected nodes within symptom domain. Disinhibition and agitation/aggression were the most central symptoms in the network. Depression/dysphoria was the most frequently endorsed symptom, but it was not central in the network. Conclusions Neuropsychiatric symptoms in MCI and AD are highly comorbid and mutually reinforcing. The presence of disinhibition and agitation/aggression yielded a higher probability of additional neuropsychiatric symptoms. Interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Future work will compare neuropsychiatric symptom networks across dementia etiologies, informant relationships, and ethnic/racial groups, and will explore the utility of network analysis as a means of interrogating treatment effects.https://doi.org/10.1186/s13195-023-01279-6Alzheimer’s diseaseNeuropsychiatricNetwork analysisMCIDementiaNPI-Q |
| spellingShingle | Grace J. Goodwin Stacey Moeller Amy Nguyen Jeffrey L. Cummings Samantha E. John Network analysis of neuropsychiatric symptoms in Alzheimer’s disease Alzheimer’s Research & Therapy Alzheimer’s disease Neuropsychiatric Network analysis MCI Dementia NPI-Q |
| title | Network analysis of neuropsychiatric symptoms in Alzheimer’s disease |
| title_full | Network analysis of neuropsychiatric symptoms in Alzheimer’s disease |
| title_fullStr | Network analysis of neuropsychiatric symptoms in Alzheimer’s disease |
| title_full_unstemmed | Network analysis of neuropsychiatric symptoms in Alzheimer’s disease |
| title_short | Network analysis of neuropsychiatric symptoms in Alzheimer’s disease |
| title_sort | network analysis of neuropsychiatric symptoms in alzheimer s disease |
| topic | Alzheimer’s disease Neuropsychiatric Network analysis MCI Dementia NPI-Q |
| url | https://doi.org/10.1186/s13195-023-01279-6 |
| work_keys_str_mv | AT gracejgoodwin networkanalysisofneuropsychiatricsymptomsinalzheimersdisease AT staceymoeller networkanalysisofneuropsychiatricsymptomsinalzheimersdisease AT amynguyen networkanalysisofneuropsychiatricsymptomsinalzheimersdisease AT jeffreylcummings networkanalysisofneuropsychiatricsymptomsinalzheimersdisease AT samanthaejohn networkanalysisofneuropsychiatricsymptomsinalzheimersdisease |