Disentangling the genetic underpinnings of neuropsychiatric symptoms in Alzheimer's disease in the Alzheimer's Disease Sequencing Project: Study design and methodology
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SUBMITTER: Ray N
PROVIDER: S-EPMC11342352 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:IntroductionSequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations, resulting in a lack of understanding of its molecular etiology.MethodsWhole-genome sequencing and harmonization of clinical, neuropathological, and biomarker data of over 5000 EOAD cases of diverse ancestries.ResultsA publicly available genomics resource for EOAD with extensive harmonized phenotypes. Primary analysis will (1) identify novel EOAD risk loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits.DiscussionThis novel resource complements over 50,000 control and late-onset AD samples generated through the Alzheimer's Disease Sequencing Project (ADSP). The harmonized EOAD/ADSP joint call will be available through upcoming ADSP data releases and will allow for additional analyses across the full onset range.HighlightsSequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations. This results in a significant lack of understanding of the molecular etiology of this devastating form of the disease. The Early-Onset Alzheimer's Disease Whole-genome Sequencing Project is a collaborative initiative to generate a large-scale genomics resource for early-onset Alzheimer's disease with extensive harmonized phenotype data. Primary analyses are designed to (1) identify novel EOAD risk and protective loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. The harmonized genomic and phenotypic data from this initiative will be available through NIAGADS.
| S-EPMC10527497 | biostudies-literature
Project description: Not available
| S-EPMC5646177 | biostudies-literature
Project description: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 was 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.
| S-EPMC10168435 | biostudies-literature
Project description:BackgroundNeuropsychiatric 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.MethodsThe 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.ResultsThe 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.ConclusionsNeuropsychiatric 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.
| S-EPMC10416506 | biostudies-literature
Project description:Concomitant neuropsychiatric symptoms (NPS) are associated with accelerated Alzheimer's disease (AD) progression. Identifying multimodal brain imaging patterns associated with NPS may help understand pathophysiology correlates AD. Based on the AD continuum, a supervised learning strategy was used to guide four-way multimodal neuroimaging fusion (Amyloid, Tau, gray matter volume, brain function) by using NPS total score as the reference. Loadings of the identified multimodal patterns were compared across the AD continuum. Then, regression analyses were performed to investigate its predictability of longitudinal cognition performance. Furthermore, the fusion analysis was repeated in the four NPS subsyndromes. Here, an NPS-associated pathological-structural-functional covaried pattern was observed in the frontal-subcortical limbic circuit, occipital, and sensor-motor region. Loading of this multimodal pattern showed a progressive increase with the development of AD. The pattern significantly correlates with multiple cognitive domains and could also predict longitudinal cognitive decline. Notably, repeated fusion analysis using subsyndromes as references identified similar patterns with some unique variations associated with different syndromes. Conclusively, NPS was associated with a multimodal imaging pattern involving complex neuropathologies, which could effectively predict longitudinal cognitive decline. These results highlight the possible neural substrate of NPS in AD, which may provide guidance for clinical management.
| S-EPMC9783460 | biostudies-literature
Project description:The aim of this study was to describe sex differences in neuropsychiatric symptoms (NPSs) in patients with Alzheimer's disease (AD). Baseline scores on the Cohen-Mansfield Agitation Inventory, Neurobehavioral Rating Scale-Agitation subscale, and the Neuropsychiatric Inventory from patients with AD enrolled in a multicenter trial of citalopram for the treatment of agitation were analyzed. We found not only that patients with AD having agitation were likely to exhibit many other NPSs but also that the women in this study were more likely to exhibit a broader range of NPS than were the men. These results suggest greater heterogeneity in the clinical presentation of women compared to men, and thus in the potential targets for treatment in these patients. Further characterization of sex differences in NPS can inform future efforts aimed at establishing subtypes of patients for whom various treatment approaches will be most appropriate.
| S-EPMC6219457 | biostudies-literature
Project description:There is both clinical and neuroanatomical variability at the single-subject level in Alzheimer's disease, complicating our understanding of brain-behaviour relationships and making it challenging to develop neuroimaging biomarkers to track disease severity, progression, and response to treatment. Prior work has shown that both group-level atrophy in clinical dementia syndromes and complex neurological symptoms in patients with focal brain lesions localize to brain networks. Here, we use a new technique termed 'atrophy network mapping' to test the hypothesis that single-subject atrophy maps in patients with a clinical diagnosis of Alzheimer's disease will also localize to syndrome-specific and symptom-specific brain networks. First, we defined single-subject atrophy maps by comparing cortical thickness in each Alzheimer's disease patient versus a group of age-matched, cognitively normal subjects across two independent datasets (total Alzheimer's disease patients = 330). No more than 42% of Alzheimer's disease patients had atrophy at any given location across these datasets. Next, we determined the network of brain regions functionally connected to each Alzheimer's disease patient's location of atrophy using seed-based functional connectivity in a large (n = 1000) normative connectome. Despite the heterogeneity of atrophied regions at the single-subject level, we found that 100% of patients with a clinical diagnosis of Alzheimer's disease had atrophy functionally connected to the same brain regions in the mesial temporal lobe, precuneus cortex, and angular gyrus. Results were specific versus control subjects and replicated across two independent datasets. Finally, we used atrophy network mapping to define symptom-specific networks for impaired memory and delusions, finding that our results matched symptom networks derived from patients with focal brain lesions. Our study supports atrophy network mapping as a method to localize clinical, cognitive, and neuropsychiatric symptoms to brain networks, providing insight into brain-behaviour relationships in patients with dementia.
| S-EPMC7174048 | biostudies-literature
Project description:The Alzheimer's Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer's Disease and Related Dementias (AD/ADRD) by sequencing whole genomes of affected participants and age-matched cognitive controls from diverse populations. The Genome Center for Alzheimer's Disease (GCAD) processed whole-genome sequencing data from 36,361 ADSP participants, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4). This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 2.2 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls. Researchers can access and analyze the genetic data via NIAGADS Data Sharing Service, the VariXam tool, or NIAGADS GenomicsDB.
| S-EPMC11643159 | biostudies-literature
Project description:IntroductionNeuropsychiatric symptoms are important treatment targets in the management of dementia and can be present at very early clinical stages of neurodegenerative diseases. Increased cortisol has been reported in Alzheimer's disease (AD) and has been associated with faster cognitive decline. Elevated cortisol output has been observed in relation to perceived stress, depression, and anxiety. Dehydroepiandrosterone sulfate (DHEAS) has known anti-glucocorticoid effects and may counter the effects of cortisol.ObjectivesWe aimed to examine whether CSF cortisol and DHEAS levels were associated with (1) neuropsychiatric symptoms at baseline, (2) changes in neuropsychiatric symptoms over 3 years, and (3) whether these associations were related to or independent of AD pathology.MethodsOne hundred and eighteen participants on a prospective study in a memory clinic setting, including patients with cognitive impairment (n = 78), i.e., mild cognitive impairment or mild dementia, and volunteers with normal cognition (n = 40), were included. Neuropsychiatric symptoms were assessed using the Neuropsychiatric Inventory Questionnaire (NPI-Q). CSF cortisol and DHEAS, as well as CSF AD biomarkers, were obtained at baseline. Neuropsychiatric symptoms were re-assessed at follow-up visits 18 and 36 months from baseline. We constructed linear regression models to examine the links between baseline neuropsychiatric symptoms, the presence of AD pathology as indicated by CSF biomarkers, and CSF cortisol and DHEAS. We used repeated-measures mixed ANCOVA models to examine the associations between the neuropsychiatric symptoms' changes over time, baseline CSF cortisol and DHEAS, and AD pathology.ResultsHigher CSF cortisol was associated with higher NPI-Q severity scores at baseline after controlling for covariates including AD pathology status (B = 0.085 [0.027; 0.144], p = 0.027; r = 0.277). In particular, higher CSF cortisol was associated with higher baseline scores of depression/dysphoria, anxiety, and apathy/indifference. Elevated CSF cortisol was also associated with more marked increase in NPI-Q scores over time regardless of AD status (p = 0.036, η2 = 0.207), but this association was no longer significant after controlling for BMI and the use of psychotropic medications. CSF DHEAS was associated neither with NPI-Q scores at baseline nor with their change over time. Cortisol did not mediate the association between baseline NPI-Q and changes in clinical dementia rating sum of boxes over 36 months.ConclusionHigher CSF cortisol may reflect or contribute to more severe neuropsychiatric symptoms at baseline, as well as more pronounced worsening over 3 years, independently of the presence of AD pathology. Our findings also suggest that interventions targeting the HPA axis may be helpful to treat neuropsychiatric symptoms in patients with dementia.
| S-EPMC9762003 | biostudies-literature
Project description:Young-onset and late-onset Alzheimer's disease has different clinical presentations with late-onset presenting most often with memory deficits while young-onset often presents with a non-amnestic syndrome. However, it is unknown whether there are differences in presentation and progression of neuropsychiatric symptoms in young- versus late-onset Alzheimer's disease. We aimed to investigate differences in the prevalence and severity of neuropsychiatric symptoms in patients with young- and late-onset Alzheimer's disease longitudinally with and without accounting for the effect of medication usage. Sex differences were also considered in these patient groups. We included 126 young-onset and 505 late-onset Alzheimer's disease patients from National Alzheimer's Coordinating Center-Uniform Data Set (NACC-UDS) and Alzheimer's Disease Neuroimaging Initiative (ADNI). We investigated the prevalence and severity of neuropsychiatric symptoms using the Neuropsychiatric Inventory-Questionnaire over 4 visits with 1-year intervals, using a linear mixed-effects model. The prevalence of depression was significantly higher in young-onset than late-onset Alzheimer's disease over a 4-year interval when antidepressant usage was included in our analyses. Our findings suggest that neuropsychiatric symptom profiles of young- and late-onset Alzheimer's disease differ cross-sectionally but also display significant differences in progression.
| S-EPMC8050126 | biostudies-literature