Postmortem brain MRI is related to cognitive decline, independent of cerebral vessel disease in older adults

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

Multi-region brain transcriptomes uncover two subtypes of aging individuals with differences in Alzheimer risk and the impact of APOEε4

The heterogeneity of the older population suggests the existence of subsets of individuals which share certain brain molecular features and respond differently to risk factors for Alzheimer's disease, but this population structure remains poorly defined. Here, we performed an unsupervised clustering of individuals with multi-region brain transcriptomes to assess whether a broader approach, simultaneously considering data from multiple regions involved in cognition would uncover such subsets. We implemented a canonical correlation-based analysis in a Discovery cohort of 459 participants from two longitudinal studies of cognitive aging that have RNA sequence profiles in three brain regions. 690 additional participants that have data in only one or two of these regions were used in the Replication effort. These clustering analyses identified two meta-clusters, MC-1 and MC-2. The two sets of participants differ primarily in their trajectories of cognitive decline, with MC-2 having a delay of 3 years to the median age of incident dementia. This is due, in part, to a greater impact of tau pathology on neuronal chromatin architecture and to broader brain changes including greater loss of white matter integrity in MC-1. Further evidence of biological differences includes a significantly larger impact of APOEε4 risk on cognitive decline in MC-1. These findings suggest that our proposed population structure captures an aspect of the more distributed molecular state of the aging brain that either enhances the effect of risk factors in MC-1 or of protective effects in MC-2. These observations may inform the design of therapeutic development efforts and of trials as both become increasingly more targeted molecularly. One Sentence Summary: There are two types of aging brains, with one being more vulnerable to APOEε4 and subsequent neuronal dysfunction and cognitive loss.

Reducing Your Risk of Alzheimer's Dementia: Building a Better Brain as We Age

Alzheimer' dementia is a large and growing public health problem. Of utmost importance for limiting the impact of the disease on society is the prevention of dementia, that is, delay onset either by years whereby death ensues prior to dementia onset. The Religious Orders Study and the Rush Memory and Aging Project are two harmonized cohort studies of aging and dementia that include organ donation at death. Ongoing since 1994 and 1997, respectively, we published on the association of numerous experiential, psychological, and medical risk factors for dementia, many of which are potentially modifiable. Here, selected findings are reviewed based on a presentation at the 2020 National Academy of Neuropsychology given virtually in Chicago in October of 2020.

Physical activity, brain tissue microstructure, and cognition in older adults

Objective

To test whether postmortem MRI captures brain tissue characteristics that mediate the association between physical activity and cognition in older adults.

Methods

Participants (N = 318) were older adults from the Rush Memory and Aging Project who wore a device to quantify physical activity and also underwent detailed cognitive and motor testing. Following death, cerebral hemispheres underwent MRI to quantify the transverse relaxation rate R₂, a metric related to tissue microstructure. For analyses, we reduced the dimensionality of the R₂ maps from approximately 500,000 voxels to 30 components using spatial independent component analysis (ICA). Via path analysis, we examined whether these R₂ components attenuated the association between physical activity and cognition, controlling for motor abilities and indices of common brain pathologies.

Results

Two of the 30 R₂ components were associated with both total daily physical activity and global cognition assessed proximate to death. We visualized these components by highlighting the clusters of voxels whose R₂ values contributed most strongly to each. One of these spatial signatures spanned periventricular white matter and hippocampus, while the other encompassed white matter of the occipital lobe. These two R₂ components partially mediated the association between physical activity and cognition, accounting for 12.7% of the relationship (p = .01). This mediation remained evident after controlling for motor abilities and neurodegenerative and vascular brain pathologies.

Conclusion

The association between physically activity and cognition in older adults is partially accounted for by MRI-based signatures of brain tissue microstructure. Further studies are needed to elucidate the molecular mechanisms underlying this pathway.

Shared proteomic effects of cerebral atherosclerosis and Alzheimer's disease on the human brain

Cerebral atherosclerosis contributes to dementia via unclear processes. We performed proteomic sequencing of dorsolateral prefrontal cortex in 438 older individuals and found associations between cerebral atherosclerosis and reduced synaptic signaling and RNA splicing and increased oligodendrocyte development and myelination. Consistently, single-cell RNA sequencing showed cerebral atherosclerosis associated with higher oligodendrocyte abundance. A subset of proteins and modules associated with cerebral atherosclerosis was also associated with Alzheimer’s disease, suggesting shared mechanisms.

Microstructural changes in the brain mediate the association of AK4, IGFBP5, HSPB2, and ITPK1 with cognitive decline

The associations of 4 proteins-AK4, ITPK1, HSPB2, and IGFBP5-with cognitive function in older adults were largely unexplained by known brain pathologies. We examined the extent to which individual protein associations with cognitive decline were attributable to microstructural changes in the brain. This study included 521 participants (mean age 90.3, 65.9-108.3) with the postmortem reciprocal of transverse relaxation time (R₂) magnetic resonance image. All participants came from one of the 2 ongoing longitudinal cohorts of aging and dementia, the Religious Orders Study and Rush Memory and Aging Project. Higher abundance of AK4, HSPB2, and IGFBP5 was associated with faster cognitive decline and mediated through lower postmortem R₂ in the frontal and temporal white matter regions. In contrast, higher abundance of ITPK1 was associated with slower cognitive decline and mediated through higher postmortem R₂ in the frontal and temporal white matter regions. The associations of 4 proteins-AK4, ITPK1, IGFBP5, and HSPB2-with cognition in late life were explained via microstructural changes in the brain.