| 1. |
- Elman, Jeremy A., et al.
(författare)
-
Issues and recommendations for the residual approach to quantifying cognitive resilience and reserve
- 2022
-
Ingår i: Alzheimer's Research and Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Cognitive reserve and resilience are terms used to explain interindividual variability in maintenance of cognitive health in response to adverse factors, such as brain pathology in the context of aging or neurodegenerative disorders. There is substantial interest in identifying tractable substrates of resilience to potentially leverage this phenomenon into intervention strategies. One way of operationalizing cognitive resilience that has gained popularity is the residual method: regressing cognition on an adverse factor and using the residual as a measure of resilience. This method is attractive because it provides a statistical approach that is an intuitive match to the reserve/resilience conceptual framework. However, due to statistical properties of the regression equation, the residual approach has qualities that complicate its interpretation as an index of resilience and make it statistically inappropriate in certain circumstances. Methods and results: We describe statistical properties of the regression equation to illustrate why the residual is highly correlated with the cognitive score from which it was derived. Using both simulations and real data, we model common applications of the approach by creating a residual score (global cognition residualized for hippocampal volume) in individuals along the AD spectrum. We demonstrate that in most real-life scenarios, the residual measure of cognitive resilience is highly correlated with cognition, and the degree of this correlation depends on the initial relationship between the adverse factor and cognition. Subsequently, any association between this resilience metric and an external variable may actually be driven by cognition, rather than by an operationalized measure of resilience. We then assess several strategies proposed as potential solutions to this problem, such as including both the residual and original cognitive measure in a model. However, we conclude these solutions may be insufficient, and we instead recommend against “pre-regression” strategies altogether in favor of using statistical moderation (e.g., interactions) to quantify resilience. Conclusions: Caution should be taken in the use and interpretation of the residual-based method of cognitive resilience. Rather than identifying resilient individuals, we encourage building more complete models of cognition to better identify the specific adverse and protective factors that influence cognitive decline.
|
|
| 2. |
- Fjell, Anders M., et al.
(författare)
-
The genetic organization of longitudinal subcortical volumetric change is stable throughout the lifespan running title: Genetics of subcortical lifespan change
- 2021
-
Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 10
-
Tidskriftsartikel (refereegranskat)abstract
- Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be traced throughout life by assessing to which degree brain regions that develop together continue to change together through life. Analyzing over 6000 longitudinal MRIs of the brain, we used graph theory to identify five clusters of coordinated development, indexed as patterns of correlated volumetric change in brain structures. The clusters tended to follow placement along the cranial axis in embryonic brain development, suggesting continuity from prenatal stages, and correlated with cognition. Across independent longitudinal datasets, we demonstrated that developmental clusters were conserved through life. Twin-based genetic correlations revealed distinct sets of genes governing change in each cluster. Single nucleotide polymorphisms-based analyses of 38127 cross-sectional MRIs showed a similar pattern of genetic volume-volume correlations. In conclusion, coordination of subcortical change adheres to fundamental principles of lifespan continuity and genetic organization.
|
|
| 3. |
- Beam, Christopher R., et al.
(författare)
-
Estimating Likelihood of Dementia in the Absence of Diagnostic Data : A Latent Dementia Index in 10 Genetically Informed Studies
- 2022
-
Ingår i: Journal of Alzheimer's Disease. - : IOS Press. - 1387-2877 .- 1875-8908. ; 90:3, s. 1187-1201
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Epidemiological research on dementia is hampered by differences across studies in how dementia is classified, especially where clinical diagnoses of dementia may not be available. OBJECTIVE: We apply structural equation modeling to estimate dementia likelihood across heterogeneous samples within a multi-study consortium and use the twin design of the sample to validate the results. METHODS: Using 10 twin studies, we implement a latent variable approach that aligns different tests available in each study to assess cognitive, memory, and functional ability. The model separates general cognitive ability from components indicative of dementia. We examine the validity of this continuous latent dementia index (LDI). We then identify cut-off points along the LDI distributions in each study and align them across studies to distinguish individuals with and without probable dementia. Finally, we validate the LDI by determining its heritability and estimating genetic and environmental correlations between the LDI and clinically diagnosed dementia where available. RESULTS: Results indicate that coordinated estimation of LDI across 10 studies has validity against clinically diagnosed dementia. The LDI can be fit to heterogeneous sets of memory, other cognitive, and functional ability variables to extract a score reflective of likelihood of dementia that can be interpreted similarly across studies despite diverse study designs and sampling characteristics. Finally, the same genetic sources of variance strongly contribute to both the LDI and clinical diagnosis. CONCLUSION: This latent dementia indicator approach may serve as a model for other research consortia confronted with similar data integration challenges.
|
|
