Gray-matter macrostructure in cognitively healthy older persons: associations with age and cognition

Preserved brain youthfulness: longitudinal evidence of slower brain aging in superagers

BACKGROUND

Superagers, older adults with exceptional cognitive abilities, show preserved brain structure compared to typical older adults. We investigated whether superagers have biologically younger brains based on their structural integrity.

METHODS

A cohort of 153 older adults (aged 61-93) was recruited, with 63 classified as superagers based on superior episodic memory and 90 as typical older adults, of whom 64 were followed up after two years. A deep learning model for brain age prediction, trained on 899 diverse-aged adults (aged 31-100), was adapted to the older adult cohort via transfer learning. Brain age gap (BAG), a metric based on brain structural patterns, defined as the difference between predicted and chronological age, and its annual rate of change were calculated to assess brain aging status and speed, respectively, and compared among subgroups.

RESULTS

Lower BAGs correlated with more favorable cognitive status in memory and general cognitive function. Superagers exhibited a lower BAG than typical older adults at both baseline and follow-up. Individuals who maintained or attained superager status at follow-up showed a slower annual rate of change in BAG compared to those who remained or became typical older adults.

CONCLUSIONS

Superaging brains manifested maintained neurobiological youthfulness in terms of a more youthful brain aging status and a reduced speed of brain aging. These findings suggest that cognitive resilience, and potentially broader functional resilience, exhibited by superagers during the aging process may be attributable to their younger brains.

Predictive risk model of mild cognitive impairment in patients with malignant haematological diseases after haematopoietic stem cell transplantation

OBJECTIVE

This study is to develop and validate a robust risk prediction model for mild cognitive impairment (MCI) in patients with malignant haematological diseases after haematopoietic stem cell transplantation (HSCT).

METHODS

In this study, we analysed the clinical data of the included patients. Logistic regression analysis was used to identify independent risk factors for cognitive impairment after HSCT in patients with malignant haematological diseases, and a risk prediction model was constructed. Multiple cohorts of patients with haematological malignancies after HSCT (282 cases) from the Affiliated Hospital of Xuzhou Medical University and the First People's Hospital of Yancheng City between April 2019 and February 2022, and patients from the Affiliated Huaian No.1 People's Hospital of Nanjing Medical University between March 2022 and July 2023 were used for external validation. Logistic regression analysis was performed to develop the predictive model. The predictive value and consistency of the model were evaluated using the area under the curve (AUC) and calibration method, respectively. Decision curve analysis (DCA) was performed to access the utility of the model.

RESULTS

Approximately half (52.26%) of the patients in the study developed mild cognitive impairment (MCI). Older age, allogeneic HSCT, anxiety, graft-versus-host disease, and longer hospital stay were associated with a higher risk of developing MCI. ROC curve analysis confirmed the sound performance of the predictive model and external validation, with AUC of 0.897 and 0.789 respectively. The direction of the calibration curves of the training and validation sets is closer to the diagonal (ideal curve), indicating good model consistency; the DCA curves also show that the model has good predictive ability and stability.

CONCLUSIONS

We conclude that it is possible to predict mild cognitive impairment with readily available, mostly pretransplant predictors. The accuracy of the risk prediction models can be improved for use in clinical practice, possibly by adding pretransplant patient-reported functioning and comorbidities.

Integration across biophysical scales identifies molecular and cellular correlates of person-to-person variability in human brain connectivity

Brain connectivity arises from interactions across biophysical scales, ranging from molecular to cellular to anatomical to network level. To date, there has been little progress toward integrated analysis across these scales. To bridge this gap, from a unique cohort of 98 individuals, we collected antemortem neuroimaging and genetic data, as well as postmortem dendritic spine morphometric, proteomic and gene expression data from the superior frontal and inferior temporal gyri. Through the integration of the molecular and dendritic spine morphology data, we identified hundreds of proteins that explain interindividual differences in functional connectivity and structural covariation. These proteins are enriched for synaptic structures and functions, energy metabolism and RNA processing. By integrating data at the genetic, molecular, subcellular and tissue levels, we link specific biochemical changes at synapses to connectivity between brain regions. These results demonstrate the feasibility of integrating data from vastly different biophysical scales to provide a more comprehensive understanding of brain connectivity.

Diabetes accelerates Alzheimer's disease progression in the first year post mild cognitive impairment diagnosis

BACKGROUND

Mild cognitive impairment (MCI) heightens Alzheimer's disease (AD) risk, with diabetes mellitus (DM) potentially exacerbating this vulnerability. This study identifies the optimal intervention period and neurobiological targets in MCI to AD progression using the Alzheimer's Disease Neuroimaging Initiative dataset.

METHODS

Analysis of 980 MCI patients, categorized by DM status, used propensity score matching and inverse probability treatment weighting to assess rate of conversion from MCI to AD, neuroimaging, and cognitive changes.

RESULTS

DM significantly correlates with cognitive decline and an increased risk of progressing to AD, especially within the first year of MCI follow-up. It adversely affects specific brain structures, notably accelerating nucleus accumbens atrophy, decreasing gray matter volume and sulcal depth.

DISCUSSION

Findings suggest the first year after MCI diagnosis as the critical window for intervention. DM accelerates MCI-to-AD progression, targeting specific brain areas, underscoring the need for early therapeutic intervention.

HIGHLIGHTS

Diabetes mellitus (DM) accelerates mild cognitive impairment (MCI)-to-Alzheimer's disease (AD) progression within the first year after MCI diagnosis. DM leads to sharper cognitive decline within 12 months of follow-up. There is notable nucleus accumbens atrophy observed in MCI patients with DM. DM causes significant reductions in gray matter volume and sulcal depth. There are stronger correlations between cognitive decline and brain changes due to DM.

Comparison between morphometry and radiomics: detecting normal brain aging based on grey matter

Objective

Voxel-based morphometry (VBM), surface-based morphometry (SBM), and radiomics are widely used in the field of neuroimage analysis, while it is still unclear that the performance comparison between traditional morphometry and emerging radiomics methods in diagnosing brain aging. In this study, we aimed to develop a VBM-SBM model and a radiomics model for brain aging based on cognitively normal (CN) individuals and compare their performance to explore both methods' strengths, weaknesses, and relationships.

Methods

967 CN participants were included in this study. Subjects were classified into the middle-aged group (n = 302) and the old-aged group (n = 665) according to the age of 66. The data of 360 subjects from the Alzheimer's Disease Neuroimaging Initiative were used for training and internal test of the VBM-SBM and radiomics models, and the data of 607 subjects from the Australian Imaging, Biomarker and Lifestyle, the National Alzheimer's Coordinating Center, and the Parkinson's Progression Markers Initiative databases were used for the external tests. Logistics regression participated in the construction of both models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate the two model performances. The DeLong test was used to compare the differences in AUCs between models. The Spearman correlation analysis was used to observe the correlations between age, VBM-SBM parameters, and radiomics features.

Results

The AUCs of the VBM-SBM model and radiomics model were 0.697 and 0.778 in the training set (p = 0.018), 0.640 and 0.789 in the internal test set (p = 0.007), 0.736 and 0.737 in the AIBL test set (p = 0.972), 0.746 and 0.838 in the NACC test set (p < 0.001), and 0.701 and 0.830 in the PPMI test set (p = 0.036). Weak correlations were observed between VBM-SBM parameters and radiomics features (p < 0.05).

Conclusion

The radiomics model achieved better performance than the VBM-SBM model. Radiomics provides a good option for researchers who prioritize performance and generalization, whereas VBM-SBM is more suitable for those who emphasize interpretability and clinical practice.

The molecular mechanism of aging and the role in neurodegenerative diseases

Aging is a complex and inevitable biological process affected by a combination of external environmental and genetic factors. Humans are currently living longer than ever before, accompanied with aging-related alterations such as diminished autophagy, decreased immunological function, mitochondrial malfunction, stem cell failure, accumulation of somatic and mitochondrial DNA mutations, loss of telomere, and altered nutrient metabolism. Aging leads to a decline in body functions and age-related diseases, for example, Alzheimer's disease, which adversely affects human health and longevity. The quality of life of the elderly is greatly diminished by the increase in their life expectancy rather than healthy life expectancy. With the rise in the age of the global population, aging and related diseases have become the focus of attention worldwide. In this review, we discuss several major mechanisms of aging, including DNA damage and repair, free radical oxidation, telomeres and telomerase, mitochondrial damage, inflammation, and their role in neurodegenerative diseases to provide a reference for the prevention of aging and its related diseases.

Neurofilaments - Small proteins of physiological significance and predictive power for future neurodegeneration and cognitive decline across the life span

Neurofilaments (NFs) are not only important for axonal integrity and nerve conduction in large myelinated axons but they are also thought to be crucial for receptor and synaptic functioning. Therefore, NFs may play a critical role in cognitive functions, as cognitive processes are known to depend on synaptic integrity and are modulated by dopaminergic signaling. Here, we present a theory-driven interdisciplinary approach that NFs may link inflammation, neurodegeneration, and cognitive functions. We base our hypothesis on a wealth of evidence suggesting a causal link between inflammation and neurodegeneration and between these two and cognitive decline (see Fig. 1), also taking dopaminergic signaling into account. We conclude that NFs may not only serve as biomarkers for inflammatory, neurodegenerative, and cognitive processes but also represent a potential mechanical hinge between them, moreover, they may even have predictive power regarding future cognitive decline. In addition, we advocate the use of both NFs and MRI parameters, as their synthesis offers the opportunity to individualize medical treatment by providing a comprehensive view of underlying disease activity in neurological diseases. Since our society will become significantly older in the upcoming years and decades, maintaining cognitive functions and healthy aging will play an important role. Thanks to technological advances in recent decades, NFs could serve as a rapid, noninvasive, and relatively inexpensive early warning system to identify individuals at increased risk for cognitive decline and could facilitate the management of cognitive dysfunctions across the lifespan.

A Molecular Basis of Human Brain Connectivity

Neuroimaging is commonly used to infer human brain connectivity, but those measurements are far-removed from the molecular underpinnings at synapses. To uncover the molecular basis of human brain connectivity, we analyzed a unique cohort of 98 individuals who provided neuroimaging and genetic data contemporaneous with dendritic spine morphometric, proteomic, and gene expression data from the superior frontal and inferior temporal gyri. Through cellular contextualization of the molecular data with dendritic spine morphology, we identified hundreds of proteins related to synapses, energy metabolism, and RNA processing that explain between-individual differences in functional connectivity and structural covariation. By integrating data at the genetic, molecular, subcellular, and tissue levels, we bridged the divergent fields of molecular biology and neuroimaging to identify a molecular basis of brain connectivity.

One-Sentence Summary

Dendritic spine morphometry and synaptic proteins unite the divergent fields of molecular biology and neuroimaging.

Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study: Rationale, Design, and Background

The Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study (TMM Brain MRI Study) was established to collect multimodal information through neuroimaging and neuropsychological assessments to evaluate the cognitive function and mental health of residents who experienced the Great East Japan Earthquake (GEJE) and associated tsunami. The study also aimed to promote advances in personalized healthcare and medicine related to mental health and cognitive function among the general population. We recruited participants for the first (baseline) survey starting in July 2014, enrolling individuals who were participating in either the TMM Community-Based Cohort Study (TMM CommCohort Study) or the TMM Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). We collected multiple magnetic resonance imaging (MRI) sequences, including 3D T1-weighted sequences, magnetic resonance angiography (MRA), diffusion tensor imaging (DTI), pseudo-continuous arterial spin labeling (pCASL), and three-dimensional fluid-attenuated inversion recovery (FLAIR) sequences. To assess neuropsychological status, we used both questionnaire- and interview-based rating scales. The former assessments included the Tri-axial Coping Scale, Impact of Event Scale in Japanese, Profile of Mood States, and 15-item Depression, Anxiety, and Stress Scale, whereas the latter assessments included the Mini-Mental State Examination, Japanese version. A total of 12,164 individuals were recruited for the first (baseline) survey, including those unable to complete all assessments. In parallel, we returned the MRI results to the participants and subsequently shared the MRI data through the TMM Biobank. At present, the second (first follow-up) survey of the study started in October 2019 is underway. In this study, we established a large and comprehensive database that included robust neuroimaging data as well as psychological and cognitive assessment data. In combination with genomic and omics data already contained in the TMM Biobank database, these data could provide new insights into the relationships of pathological processes with neuropsychological disorders, including age-related cognitive impairment.

Multisystem physiological perspective of human frailty and its modulation by physical activity

"Frailty" is a term used to refer to a state characterized by enhanced vulnerability to, and impaired recovery from, stressors compared with a nonfrail state, which is increasingly viewed as a loss of resilience. With increasing life expectancy and the associated rise in years spent with physical frailty, there is a need to understand the clinical and physiological features of frailty and the factors driving it. We describe the clinical definitions of age-related frailty and their limitations in allowing us to understand the pathogenesis of this prevalent condition. Given that age-related frailty manifests in the form of functional declines such as poor balance, falls, and immobility, as an alternative we view frailty from a physiological viewpoint and describe what is known of the organ-based components of frailty, including adiposity, the brain, and neuromuscular, skeletal muscle, immune, and cardiovascular systems, as individual systems and as components in multisystem dysregulation. By doing so we aim to highlight current understanding of the physiological phenotype of frailty and reveal key knowledge gaps and potential mechanistic drivers of the trajectory to frailty. We also review the studies in humans that have intervened with exercise to reduce frailty. We conclude that more longitudinal and interventional clinical studies are required in older adults. Such observational studies should interrogate the progression from a nonfrail to a frail state, assessing individual elements of frailty to produce a deep physiological phenotype of the syndrome. The findings will identify mechanistic drivers of frailty and allow targeted interventions to diminish frailty progression.

The structural basis of age-related decline in global motion perception at fast and slow speeds

A decrease in global motion perception (GMP) has been reported in older adults, and this age-related decline in GMP varies with the speed of global motion. However, no studies have investigated whether the asynchronous age-related decline in GMP is related to degenerative changes in brain structure. In this study, the random dot kinematogram paradigm and structural magnetic resonance imaging were used to investigate the asynchronous aging of GMP at fast and slow speeds (called fast GMP and slow GMP, respectively) and their relationships with brain structure. Ninety-four older adults (65.74 ± 4.50 yrs) and 90 younger adults (22.83 ± 4.84 yrs) participated in the experiment. The results showed that older adults had higher motion coherence thresholds (MCT) than younger adults at both fast and slow speeds. Brain-behavior correlation analyses of younger adults revealed that none of the correlations between morphological measures and MCTs survived correction for multiple comparisons. For older adults, slow MCT was correlated with cortical thickness in the bilateral V4v, V5/MT+, left V7, V8, LO, and surface area in the right V7. Fast MCT was significantly correlated with gray matter volume in the right V7 and thickness in the left V5/MT+. These results support the view that global motion extraction occurs within two speed-tuned systems that are at least partially independent in terms of their neural substrates, which deteriorate with age at different speeds. Aging of GMP is also associated with morphological changes in the visual cortex. Age-related cerebral atrophy in the dorsal stream may impair both fast and slow GMP, whereas aging of the ventral stream specifically impairs slow GMP.

Associations of deformation-based brain morphometry with cognitive level and decline within older Blacks without dementia

Blacks are at higher risk of developing cognitive impairment with age than non-Hispanic Whites, yet most brain morphometry and cognition research is performed with White samples or with mixed samples that control for race or compare across racial groups. A deeper understanding of the within-group variability in associations between brain structure and cognitive decline in Blacks is critically important for designing appropriate outcomes for clinical trials, predicting adverse outcomes, and developing interventions to preserve cognitive function, but no studies have examined these associations longitudinally within Blacks. We performed deformation-based morphometry in 376 older Black participants without dementia and examined associations of deformation-based morphometry with cognitive level and decline for global cognition and five cognitive domains. After correcting for widespread age-associated effects, there remained regions with less tissue and more cerebrospinal fluid associated with level and rate of decline in global cognition, memory, and perceptual speed. Further study is needed to examine the moderators of these associations, identify adverse outcomes predicted by brain morphometry, and deepen knowledge of underlying biological mechanisms.

Group-guided individual functional parcellation of the hippocampus and application to normal aging

Aging is closely associated with cognitive decline affecting attention, memory and executive functions. The hippocampus is the core brain area for human memory, learning, and cognition processing. To delineate the individual functional patterns of hippocampus is pivotal to reveal the neural basis of aging. In this study, we developed a group‐guided individual parcellation approach based on semisupervised affinity propagation clustering using the resting‐state functional magnetic resonance imaging to identify individual functional subregions of hippocampus and to identify the functional patterns of each subregion during aging. A three‐way group parcellation was yielded and was taken as prior information to guide individual parcellation of hippocampus into head, body, and tail in each subject. The superiority of individual parcellation of hippocampus is validated by higher intraregional functional similarities by compared to group‐level parcellation results. The individual variations of hippocampus were associated with coactivation patterns of three typical functions of hippocampus. Moreover, the individual functional connectivities of hippocampus subregions with predefined target regions could better predict age than group‐level functional connectivities. Our study provides a novel framework for individual brain functional parcellations, which may facilitate the future individual researches for brain cognitions and brain disorders and directing accurate neuromodulation.

The role of docosahexaenoic acid (DHA) in the prevention of cognitive impairment in the elderly

Aging is an inevitable and progressive biological process that leads to irreversible physiological and functional changes, also in the nervous system. Cognitive decline occurring with age can significantly affect the quality of life of older people. Docosahexaenoic acid (DHA) is necessary for the proper functioning of the nervous system; it can affect its action directly through its impact on neurogenesis and neuroplasticity, but also indirectly by affecting the functioning of the cardiovascular system or anti-inflammatory effect. Literature analysis shows that good nutritional status of n-3 fatty acids, determined on the basis of their level in blood plasma or erythrocytes, is associated with a lower risk of cognitive decline in selected cognitive domains, as well as a lower risk of dementia or Alzheimer’s disease, although studies are also available where the above relationship has not been confirmed. Apart from this, studies on DHA and EPA diet intake, as well as in the form of dietary supplements, show their beneficial effects in the context of cognitive functioning and the risk of dementia. Also, the results of intervention studies, although not explicit, suggest that high doses of DHA and EPA in the form of dietary supplements may slow down the process of deteriorating the cognitive functioning of the elderly within selected domains. Based on the review of the literature, it can be concluded that DHA and EPA play an essential role in the prevention of cognitive impairment.

Longitudinal change in executive function is associated with impaired top-down frontolimbic regulation during reappraisal in older adults

Networks in the prefrontal cortex (PFC) that are important for executive function are also engaged in adaptive responding to negative events. These networks are particularly vulnerable to age-related structural atrophy and an associated loss of executive function, yet existing evidence suggests preserved emotion processing ability in ageing. Using longitudinally acquired data from a battery of cognitive tasks, we defined a metric for the rate of decline of executive function. With this metric, we investigated relationships between changes in executive function and emotion reappraisal ability and brain structure, in 34 older adults, using functional and structural MRI. During task-based fMRI, participants were asked to cognitively reappraise negatively valenced images. We hypothesised one of two associations with decreasing executive function over time: 1) a decreased ability to reappraise reflected in decreased PFC and increased amygdala activation, or 2) a neural compensation mechanism characterised by increased PFC activation but no differential amygdala activation. Structurally, for a decreased reappraisal ability, we predicted a decrease in grey matter in PFC and/or a decrease of white matter integrity in amygdala-PFC pathways. Neither of the two hypotheses relating to brain function were completely supported, with the findings indicating a steeper decline in executive function associated with both increased PFC and increased left amygdala activity when reappraising negative stimuli. In addition, white matter integrity of the uncinate fasciculus, a primary white matter tract connecting the amygdala and ventromedial areas of PFC, was lower in those individuals who demonstrated a greater decrease in executive function. These findings highlight the association of diminishing cognitive ability with brain structure and function linked to emotion regulation.

Cognitive and neural architecture of decision making competence

Although cognitive neuroscience has made remarkable progress in understanding the neural foundations of goal-directed behavior and decision making, neuroscience research on decision making competence, the capacity to resist biases in human judgment and decision making, remain to be established. Here, we investigated the cognitive and neural mechanisms of decision making competence in 283 healthy young adults. We administered the Adult Decision Making Competence battery to assess the respondent's capacity to resist standard biases in decision making, including: (1) resistance to framing, (2) recognizing social norms, (3) over/under confidence, (4) applying decision rules, (5) consistency in risk perception, and (6) resistance to sunk costs. Decision making competence was assessed in relation to core facets of intelligence, including measures of crystallized intelligence (Shipley Vocabulary), fluid intelligence (Figure Series), and logical reasoning (LSAT). Structural equation modeling was applied to examine the relationship(s) between each cognitive domain, followed by an investigation of their association with individual differences in cortical thickness, cortical surface area, and cortical gray matter volume as measured by high-resolution structural MRI. The results suggest that: (i) decision making competence is associated with cognitive operations for logical reasoning, and (ii) these convergent processes are associated with individual differences within cortical regions that are widely implicated in cognitive control (left dACC) and social decision making (right superior temporal sulcus; STS). Our findings motivate an integrative framework for understanding the neural mechanisms of decision making competence, suggesting that individual differences in the cortical surface area of left dACC and right STS are associated with the capacity to overcome decision biases and exhibit competence in decision making.

Association of Lifespan Cognitive Reserve Indicator With Dementia Risk in the Presence of Brain Pathologies

IMPORTANCE

Evidence on the association of lifespan cognitive reserve (CR) with dementia is limited, and the strength of this association in the presence of brain pathologies is unknown.

OBJECTIVE

To examine the association of lifespan CR with dementia risk, taking brain pathologies into account.

DESIGN, SETTING, AND PARTICIPANTS

This study used data from 2022 participants in the Rush Memory and Aging Project, an ongoing community-based cohort study with annual follow-up from 1997 to 2018 (mean follow-up, 6 years; maximum follow-up, 20 years). After excluding 420 individuals who had prevalent dementia, missing data on CR, or dropped out, 1602 dementia-free adults were identified at baseline and evaluated to detect incident dementia. During follow-up, 611 died and underwent autopsies. Data were analyzed from May to September 2018.

EXPOSURES

Information on CR factors (education; early-life, midlife, and late-life cognitive activities; and social activities in late life) was obtained at baseline. Based on these factors, lifespan CR scores were captured using a latent variable from a structural equation model and was divided into tertiles (lowest, middle, and highest).

MAIN OUTCOMES AND MEASURES

Dementia was diagnosed following international criteria. Neuropathologic evaluations for Alzheimer disease and other brain pathologies were performed in autopsied participants. The association of lifespan CR with dementia or brain pathologies was estimated using Cox regression models or logistic regression.

RESULTS

Of the 1602 included participants, 1216 (75.9%) were women, and the mean (SD) age was 79.6 (7.5) years. During follow-up, 386 participants developed dementia (24.1%), including 357 participants with Alzheimer disease-related dementia (22.3%). The multiadjusted hazards ratios (HRs) of dementia were 0.77 (95% CI, 0.59-0.99) for participants in the middle CR score tertile and 0.61 (95% CI, 0.47-0.81) for those in the highest CR score tertile compared with those in the lowest CR score tertile. In autopsied participants, CR was not associated with most brain pathologies, and the association of CR with dementia remained significant after additional adjustment for brain pathologies (HR, 0.60; 95% CI, 0.42-0.86). The highest CR score tertile was associated with a reduction in dementia risk, even among participants with high Alzheimer disease pathology (HR, 0.57; 95% CI, 0.37-0.87) and any gross infarcts (HR, 0.34; 95% CI, 0.18-0.62).

CONCLUSIONS AND RELEVANCE

High lifespan CR is associated with a reduction in dementia risk, even in the presence of high brain pathologies. Our findings highlight the importance of lifespan CR accumulation in dementia prevention.

High-Dimensional Mapping of Cognition to the Brain Using Voxel-Based Morphometry and Subcortical Shape Analysis

BACKGROUND

It is increasingly recognized that the complex functions of human cognition are not accurately represented by arbitrarily-defined anatomical brain regions. Given the considerable functional specialization within such regions, more fine-grained studies of brain structure could capture such localized associations. However, such analyses/studies in a large community-dwelling population are lacking.

OBJECTIVE

To perform a fine-mapping of cognitive ability to cortical and subcortical grey matter on magnetic resonance imaging (MRI).

METHODS

In 3,813 stroke-free and non-demented persons from the Rotterdam Study (mean age 69.1 (±8.8) years; 55.8% women) with cognitive assessments and brain MRI, we performed voxel-based morphometry and subcortical shape analysis on global cognition and separate tests that tapped into memory, information processing speed, fine motor speed, and executive function domains.

RESULTS

We found that the different cognitive tests significantly associated with grey matter density in differential but also overlapping brain regions, primarily in the left hemisphere. Clusters of significantly associated voxels with global cognition were located within multiple anatomic regions: left amygdala, hippocampus, parietal lobule, superior temporal gyrus, insula and posterior temporal lobe. Subcortical shape analysis revealed associations primarily within the head and tail of the caudate nucleus, putamen, ventral part of the thalamus, and nucleus accumbens, more equally distributed among the left and right hemisphere. Within the caudate nucleus both positive (head) as well as negative (tail) associations were observed with global cognition.

CONCLUSIONS

In a large population-based sample, we mapped cognitive performance to cortical and subcortical grey matter density using a hypothesis-free approach with high-dimensional neuroimaging. Leveraging the power of our large sample size, we confirmed well-known associations as well as identified novel brain regions related to cognition.

Impaired olfaction is associated with cognitive decline and neurodegeneration in the brain

Objective

We aimed to examine whether impaired olfaction is associated with cognitive decline and indicators of neurodegeneration in the brain of dementia-free older adults.

Methods

Within the Rush Memory and Aging Project, 380 dementia-free participants (mean age = 78 years) were followed for up to 15 years, and underwent MRI scans. Olfactory function was assessed using the Brief Smell Identification Test (B-SIT) at baseline, and categorized as anosmia (B-SIT <6), hyposmia (B-SIT 6–10 in men and 6–10.25 in women), and normal (B-SIT 10.25–12 in men and 10.5–12 in women). Cognitive function was annually assessed with a battery of 21 tests, from which composite scores were derived. Structural total and regional brain volumes were estimated. Data were analyzed using linear regression and mixed-effects models.

Results

At study entry, 138 (36.3%) had normal olfactory function, 213 (56.1%) had hyposmia, and 29 (7.6%) had anosmia. In multiadjusted mixed-effects models, hyposmia (β = −0.03, 95% confidence interval [CI] −0.05 to −0.02) and anosmia (β = −0.13, 95% CI −0.16 to −0.09) were associated with faster rate of cognitive decline compared to normal olfaction. On MRI, impaired olfaction (hyposmia or anosmia) was related to smaller volumes of the hippocampus (β = −0.19, 95% CI −0.33 to −0.05), and in the entorhinal (β = −0.16, 95% CI −0.24 to −0.08), fusiform (β = −0.45, 95% CI −0.78 to −0.14), and middle temporal (β = −0.38, 95% CI −0.72 to −0.01) cortices.

Conclusion

Impaired olfaction predicts faster cognitive decline and might indicate neurodegeneration in the brain among dementia-free older adults.

Examining the relationship between nutrition and cerebral structural integrity in older adults without dementia

The proportion of adults aged 60 years and over is expected to increase over the coming decades. This ageing of the population represents an important health issue, given that marked reductions to cerebral macro- and microstructural integrity are apparent with increasing age. Reduced cerebral structural integrity in older adults appears to predict poorer cognitive performance, even in the absence of clinical disorders such as dementia. As such, it is becoming increasingly important to identify those factors predicting cerebral structural integrity, especially factors that are modifiable. One such factor is nutritional intake. While the literature is limited, data from available cross-sectional studies indicate that increased intake of nutrients such as B vitamins (for example, B6, B12 and folate), choline, n-3 fatty acids and vitamin D, or increased adherence to prudent whole diets (for example, the Mediterranean diet) predicts greater cerebral structural integrity in older adults. There is even greater scarcity of randomised clinical trials investigating the effects of nutritional supplementation on cerebral structure, though it appears that supplementation with B vitamins (B6, B12 and folic acid) or n-3 fatty acids (DHA or EPA) may be beneficial. The current review presents an overview of available research examining the relationship between key nutrients or adherence to select diets and cerebral structural integrity in dementia-free older adults.

Performance Level and Cortical Atrophy Modulate the Neural Response to Increasing Working Memory Load in Younger and Older Adults

There is evidence that the neural response to increasing working memory (WM) load is modulated by age and performance level. For a valid interpretation of these effects, however, it is important to understand, whether and how they are related to gray matter atrophy. In the current work, we therefore used functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) to examine the association between age, performance level, spatial WM load-related brain activation and gray matter volume in 18 younger high-performers (YHP), 17 younger low-performers (YLP), 17 older high-performers (OHP), and 18 older low-performers (OLP). In multiple sub regions of the prefrontal cortex (PFC), load-related activation followed a linear trend with increasing activation at increasing load in all experimental groups. Results did not reveal differences between the sub groups. Older adults additionally showed a pattern of increasing activation from low to medium load but stable or even decreasing activation from medium to high load in other sub regions of the PFC (quadratic trend). Quadratic trend related brain activation was higher in older than in younger adults and in OLP compared to OHP. In OLP, quadratic trend related brain activation was negatively correlated with both performance accuracy and prefrontal gray matter volume. The results suggest an efficient upregulation of multiple PFC areas as response to increasing WM load in younger and older adults. Older adults and particularly OLP additionally show dysfunctional response patterns (i.e., enhanced quadratic trend related brain activation compared to younger adults and OHP, respectively) in other PFC clusters being associated with gray matter atrophy.

Structural and functional cerebral bases of diminished inhibitory control during healthy aging

Inhibitory control or the ability to refrain from incorrect responses is a critical executive function known to diminish during aging. Imaging studies have elucidated cerebral changes that may underlie the age-related deficits. However, it remains unclear whether the structural and functional changes occur in the same brain regions and whether reduced gray matter volumes (GMV) mediate decreased activation during inhibition. Here, in a sample of 149 participants, we addressed the issues using structural and functional magnetic resonance imaging. Individual's response inhibition was evaluated by the stop signal reaction time (SSRT) in a stop signal task. The results showed that age was associated with prolonged SSRT across participants. Many cortical and subcortical regions demonstrated age-related reduction in GMV and activation to response inhibition. Additionally, age-related diminution in inhibitory control, as indexed by the SSRT, was associated with both shared and distinct morphometric and functional changes. Voxel-based morphometry demonstrated age-related reduction in GMV in the right dorsolateral prefrontal cortex and caudate head as well as bilateral insula, in association with prolonged SSRT. In a contrast of stop success versus go success trials, age was associated with lower activation in the medial and inferior frontal cortex and inferior parietal cortex. Further, reduction in GMV mediated age-related differences in activations only of the medial prefrontal cortex, providing limited evidence for structure function association. Thus, the decline in inhibitory control, as evidenced in the stop signal task, manifest with both shared and distinct structural and functional processes during aging.

Age-related changes in cortical and subcortical structures of healthy adult brains: A surface-based morphometry study

BACKGROUND

Cerebral structures in both cortical and subcortical regions change with aging. More specific and comprehensive studies are needed to better elucidate these changes.

PURPOSE

To investigate the relationships between age and cerebral structures regarding cortical and subcortical changes.

STUDY TYPE

Cross-cohort research.

POPULATION

54 healthy adults (28 females) aged 21-71 years.

FIELD STRENGTH/SEQUENCE

T₁ -weighted imaging was performed at 1.5T.

ASSESSMENT

The cortical thickness, local gyrification index (LGI), and the volumes of total gray matter (GM), white matter (WM), white matter hyperintensity (WMH), deep gray matter nuclei (putamen, pallidum, thalamus, caudate, amygdala, accumbens area, and hippocampus), ventricles, and hippocampal subfields were obtained using FreeSurfer software.

STATISTICAL TESTS

Regression analysis was performed to determine the relationships between age and cortical thickness, LGI, and volumes of subcortical structures. Uncorrected P values ≤ 0.001 and R²  > 0.16 were considered significant.

RESULTS

The cortical thickness and LGI decreased with age throughout almost all brain regions (R²  > 0.16; P ≤ 0.001). Except for the volumes of the WM and 4th ventricle (R²  < 0.16; P > 0.001), the volumes of the GM, WMH, lateral ventricle, inferior lateral ventricle, and 3rd ventricle showed a nonlinear correlation with aging (R²  > 0.16; P ≤ 0.001). For deep gray matter nuclei, the thalamus volume was significantly decreased with aging (R²  = 0.256; P = 0.001). Additionally, the hippocampus volume was initially increased and then decreased at age of 50, mainly in the granule cell layer of the dentate gyrus (GC-DG), cornus ammonis 2/3 (CA2/3), CA4, and fissure (R²  > 0.16; P ≤ 0.001). The volumes of the putamen, pallidum, accumbens area, amygdala and caudate showed no significance with aging (R²  < 0.16; P > 0.001).

DATA CONCLUSION

The results comprehensively show the relationships between age and cerebral structures in multiple brain regions, and these findings may help identify normal aging and other age-related neuroradiological disorders.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:152-163.

Brain structural covariance network centrality in maltreated youth with PTSD and in maltreated youth resilient to PTSD

Child maltreatment is a major cause of pediatric posttraumatic stress disorder (PTSD). Previous studies have not investigated potential differences in network architecture in maltreated youth with PTSD and those resilient to PTSD. High-resolution magnetic resonance imaging brain scans at 3 T were completed in maltreated youth with PTSD (n = 31), without PTSD (n = 32), and nonmaltreated controls (n = 57). Structural covariance network architecture was derived from between-subject intraregional correlations in measures of cortical thickness in 148 cortical regions (nodes). Interregional positive partial correlations controlling for demographic variables were assessed, and those correlations that exceeded specified thresholds constituted connections in cortical brain networks. Four measures of network centrality characterized topology, and the importance of cortical regions (nodes) within the network architecture were calculated for each group. Permutation testing and principle component analysis method were employed to calculate between-group differences. Principle component analysis is a methodological improvement to methods used in previous brain structural covariance network studies. Differences in centrality were observed between groups. Larger centrality was found in maltreated youth with PTSD in the right posterior cingulate cortex; smaller centrality was detected in the right inferior frontal cortex compared to youth resilient to PTSD and controls, demonstrating network characteristics unique to pediatric maltreatment-related PTSD. Larger centrality was detected in right frontal pole in maltreated youth resilient to PTSD compared to youth with PTSD and controls, demonstrating structural covariance network differences in youth resilience to PTSD following maltreatment. Smaller centrality was found in the left posterior cingulate cortex and in the right inferior frontal cortex in maltreated youth compared to controls, demonstrating attributes of structural covariance network topology that is unique to experiencing maltreatment. This work is the first to identify cortical thickness-based structural covariance network differences between maltreated youth with and without PTSD. We demonstrated network differences in both networks unique to maltreated youth with PTSD and those resilient to PTSD. The networks identified are important for the successful attainment of age-appropriate social cognition, attention, emotional processing, and inhibitory control. Our findings in maltreated youth with PTSD versus those without PTSD suggest vulnerability mechanisms for developing PTSD.

Religious Orders Study and Rush Memory and Aging Project

BACKGROUND

The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD).

OBJECTIVES

To summarize progress over the past five years and its implications for understanding neurodegenerative diseases.

METHODS

Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future.

RESULTS

We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform.

CONCLUSION

Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.

Brain cortical characteristics of lifetime cognitive ageing

Regional cortical brain volume is the product of surface area and thickness. These measures exhibit partially distinct trajectories of change across the brain’s cortex in older age, but it is unclear which cortical characteristics at which loci are sensitive to cognitive ageing differences. We examine associations between change in intelligence from age 11 to 73 years and regional cortical volume, surface area, and thickness measured at age 73 years in 568 community-dwelling older adults, all born in 1936. A relative positive change in intelligence from 11 to 73 was associated with larger volume and surface area in selective frontal, temporal, parietal, and occipital regions (r < 0.180, FDR-corrected q < 0.05). There were no significant associations between cognitive ageing and a thinner cortex for any region. Interestingly, thickness and surface area were phenotypically independent across bilateral lateral temporal loci, whose surface area was significantly related to change in intelligence. These findings suggest that associations between regional cortical volume and cognitive ageing differences are predominantly driven by surface area rather than thickness among healthy older adults. Regional brain surface area has been relatively underexplored, and is a potentially informative biomarker for identifying determinants of cognitive ageing differences.

Dissociating Normal Aging from Alzheimer's Disease: A View from Cognitive Neuroscience

Both normal aging and Alzheimer's disease (AD) are associated with changes in cognition, grey and white matter volume, white matter integrity, neural activation, functional connectivity, and neurotransmission. Obviously, all of these changes are more pronounced in AD and proceed faster providing the basis for an AD diagnosis. Since these differences are quantitative, however, it was hypothesized that AD might simply reflect an accelerated aging process. The present article highlights the different neurocognitive changes associated with normal aging and AD and shows that, next to quantitative differences, there are multiple qualitative differences as well. These differences comprise different neurocognitive dissociations as different cognitive deficit profiles, different weights of grey and white matter atrophy, and different gradients of structural decline. These qualitative differences clearly indicate that AD cannot be simply described as accelerated aging process but on the contrary represents a solid entity.

Cerebrovascular and microglial states are not altered by functional neuroinflammatory gene variant

The translocator protein, a microglial-expressed marker of neuroinflammation, has been implicated in Alzheimer's disease, which is characterized by alterations in vascular and inflammatory states. ATSPOvariant, rs6971, determines binding affinity of exogenous radioligandsin vivo; however, the effect of these altered binding characteristics on inflammatory and cerebrovascular biomarkers has not been assessed. In 2345 living subjects (Alzheimer's Disease Neuroimaging Initiative, n = 1330) and postmortem brain samples (Religious Orders Study and Memory and Aging Project, n = 1015), we analyzed effects of rs6971 on white matter hyperintensisites, cerebral infarcts, circulating inflammatory biomarkers, amyloid angiopathy, and microglial activation. We found that rs6971 does not alter translocator protein in a way that impacts cerebrovascular and inflammatory states known to be affected in dementia.

Regional Neocortical Gray Matter Structure and Sleep Fragmentation in Older Adults

STUDY OBJECTIVES

To test the hypothesis that greater sleep fragmentation is associated with regionally decreased cortical gray matter volume in older community-dwelling adults without cognitive impairment.

METHODS

We studied 141 community-dwelling older adults (median age 82.9; 73% female) without cognitive impairment or stroke, and not using sedative/ hypnotic medications, participating in the Rush Memory and Aging Project. We quantified sleep fragmentation from 7 d of actigraphy using the metric kRA and related this to total cortical gray matter volume, and regional gray matter volume in 34 cortical regions quantified by automated segmentation of magnetic resonance imaging data. We determined statistical significance and accounted for multiple comparisons by empirically estimating the false discovery rate by permutation.

RESULTS

Lower total cortical gray matter volume was associated with higher sleep fragmentation (coefficient +0.23, standard error [SE] 0.11, P = 0.037). Lower gray matter volumes in four cortical regions were accompanied by higher sleep fragmentation with a false discovery rate < 0.05: the left (coefficient +0.36, SE 0.10, P = 2.7 × 10(-4)) and right (coefficient +0.31, SE 0.10, P = 4.0 × 10(-3)) lateral orbitofrontal cortices, and the adjacent left (coefficient +0.31, SE 0.10, 5.4 × 10(-4)) and right (coefficient +0.39, SE 0.10, P = 1.2 × 10(-4)) inferior frontal gyri pars orbitalis. These associations were unchanged after accounting for age, sex, education, depression, cognitive function, and a number of medical comorbidities.

CONCLUSIONS

Lower cortical gray matter volume in the lateral orbitofrontal cortex and inferior frontal gyrus pars orbitalis is associated with greater sleep fragmentation in older community-dwelling adults. Further work is needed to clarify whether this is a consequence of or contributor to sleep fragmentation.

COMMENTARY

A commentary on this article appears in this issue on page 15.

Brain volumetric changes and cognitive ageing during the eighth decade of life

Later‐life changes in brain tissue volumes—decreases in the volume of healthy grey and white matter and increases in the volume of white matter hyperintensities (WMH)—are strong candidates to explain some of the variation in ageing‐related cognitive decline. We assessed fluid intelligence, memory, processing speed, and brain volumes (from structural MRI) at mean age 73 years, and at mean age 76 in a narrow‐age sample of older individuals (n = 657 with brain volumetric data at the initial wave, n = 465 at follow‐up). We used latent variable modeling to extract error‐free cognitive levels and slopes. Initial levels of cognitive ability were predictive of subsequent brain tissue volume changes. Initial brain volumes were not predictive of subsequent cognitive changes. Brain volume changes, especially increases in WMH, were associated with declines in each of the cognitive abilities. All statistically significant results were modest in size (absolute r‐values ranged from 0.114 to 0.334). These results build a comprehensive picture of macrostructural brain volume changes and declines in important cognitive faculties during the eighth decade of life. Hum Brain Mapp 36:4910–4925, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc

Association of white matter hyperintensities and gray matter volume with cognition in older individuals without cognitive impairment

Both presence of white matter hyperintensities (WMH) and smaller total gray matter volume on brain magnetic resonance imaging (MRI) are common findings in old age, and contribute to impaired cognition. We tested whether total WMH volume and gray matter volume had independent associations with cognition in community-dwelling individuals without dementia or mild cognitive impairment (MCI). We used data from participants of the Rush Memory and Aging Project. Brain MRI was available in 209 subjects without dementia or MCI (mean age 80; education = 15 years; 74 % women). WMH and gray matter were automatically segmented, and the total WMH and gray matter volumes were measured. Both MRI-derived measures were normalized by the intracranial volume. Cognitive data included composite measures of five different cognitive domains, based on 19 individual tests. Linear regression analyses, adjusted for age, sex, and education, were used to examine the relationship of logarithmically-transformed total WMH volume and of total gray matter volume to cognition. Larger total WMH volumes were associated with lower levels of perceptual speed (p < 0.001), but not with episodic memory, semantic memory, working memory, or visuospatial abilities (all p > 0.10). Smaller total gray matter volumes were associated with lower levels of perceptual speed (p = 0.013) and episodic memory (p = 0.001), but not with the other three cognitive domains (all p > 0.14). Larger total WMH volume was correlated with smaller total gray matter volume (p < 0.001). In a model with both MRI-derived measures included, the relation of WMH to perceptual speed remained significant (p < 0.001), while gray matter volumes were no longer related (p = 0.14). This study of older community-dwelling individuals without overt cognitive impairment suggests that the association of larger total WMH volume with lower perceptual speed is independent of total gray matter volume. These results help elucidate the pathological processes leading to lower cognitive function in aging.

Variation in longevity gene KLOTHO is associated with greater cortical volumes

OBJECTIVE

Identifying genetic variation associated with brain structures in aging may elucidate new biologic mechanisms underlying resilience to cognitive decline. We investigated whether carrying one copy of the protective haplotype "KL-VS" in longevity gene KLOTHO (KL) is associated with greater gray matter volume in healthy human aging compared to carrying no copies.

METHODS

We performed unbiased whole-brain analysis in cognitively normal older adults from two independent cohorts to assess the relationship between KL-VS and gray matter volume using voxel-based morphometry.

RESULTS

We found that KL-VS heterozygosity was associated with greater volume in right dorsolateral prefrontal cortex (rDLPFC). Because rDLPFC is important for executive function, we analyzed working memory and processing speed in individuals. KL-VS heterozygosity was associated with enhanced executive function. Larger rDLPFC volume correlated with better executive function across the lifespan examined. Statistical analysis suggested that volume partially mediates the effect of genotype on cognition.

INTERPRETATION

These results suggest that variation in KL is associated with bigger brain volume and better function.

The Genetic Association Between Neocortical Volume and General Cognitive Ability Is Driven by Global Surface Area Rather Than Thickness

Total gray matter volume is associated with general cognitive ability (GCA), an association mediated by genetic factors. It is expectable that total neocortical volume should be similarly associated with GCA. Neocortical volume is the product of thickness and surface area, but global thickness and surface area are unrelated phenotypically and genetically in humans. The nature of the genetic association between GCA and either of these 2 cortical dimensions has not been examined. Humans possess greater cognitive capacity than other species, and surface area increases appear to be the primary driver of the increased size of the human cortex. Thus, we expected neocortical surface area to be more strongly associated with cognition than thickness. Using multivariate genetic analysis in 515 middle-aged twins, we demonstrated that both the phenotypic and genetic associations between neocortical volume and GCA are driven primarily by surface area rather than thickness. Results were generally similar for each of 4 specific cognitive abilities that comprised the GCA measure. Our results suggest that emphasis on neocortical surface area, rather than thickness, could be more fruitful for elucidating neocortical-GCA associations and identifying specific genes underlying those associations.