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TaubCONNECT Research Perspective:
March 2024

Diet, Pace of Biological Aging, and Risk of Dementia in the Framingham Heart Study

Aline Thomas, PhD		Yian Gu, MD, MS, PhD

People who eat healthier diets are less likely to develop dementia, but the biological mechanism of this protection is not well understood. Literature also suggests that a healthy diet slows down the processes of biological aging. However, it is unclear whether the slower pace of biological aging is a mechanism linking healthy diet with reduced dementia risk. In our recent study published in Annals of Neurology, we tested the hypothesis that a healthy diet protects against dementia by slowing down the body’s overall pace of biological aging.

In 1,644 participants (≥60 years-old, free of dementia) from the Framingham Offspring Cohort, we assessed healthy diet as long-term adherence to the Mediterranean-Dash Intervention for Neurodegenerative Delay diet (MIND), over 4 visits spanning 1991-2008. Developed in 2015 for prevention of dementia, the MIND diet emphasizes high intake of neuroprotective foods such as fish, green leafy vegetables, berries, and nuts, while minimizing intake of red meat, butter, and sweets. We measured the pace of aging from blood DNA methylation data collected in 2005-2008 using the DunedinPACE epigenetic clock. Developed by studying changes in 19 indicators of the integrity of several different systems in the body (cardiovascular, hepatic, renal, pulmonary, periodontal, immune, metabolic, endocrine), DunedinPACE functions like a speedometer for the aging process, summarizing the overall the rate of change across these systems. Participants were followed for incident dementia from 2005-2008 visit through 2018.

Figure 3A. Mediation analysis of diet association with dementia by the DunedinPACE epigenetic clock measure of the pace of aging.

Our study confirmed that adherence to a healthier diet slowed the pace of aging and reduced risks for dementia and mortality. Slower DunedinPACE accounted for 27% of the diet-dementia association and 57% of the diet-mortality association.

Our findings show that multi-system processes of aging mediate part of the relationship of healthy diet with reduced dementia risk. Advocating healthy diet for the purpose of dementia prevention can now be supported by partially clarified biological mechanisms. Monitoring the pace of aging may inform dementia prevention.

Aline Thomas, PhD
Postdoctoral Research Scientist in the Taub Institute
at3702@cumc.columbia.edu

Yian Gu, MD, MS, PhD
Associate Professor of Neurological Sciences in Neurology, Epidemiology in the Gertrude H. Sergievsky Center and the Taub Institute
yg2121@cumc.columbia.edu

The Matrix Receptor CD44 Is Present in Astrocytes throughout the Human Central Nervous System and Accumulates in Hypoxia and Seizures

Osama Al Dalahmah, MD, PhD		Carol Troy, MD, PhD		James Goldman, MD, PhD

The Long-Life Family Study (LLFS) is an international collaborative study designed to examine the genetic and non-genetic factors associated with exceptional longevity. Previous studies examining the health of LLFS participants have shown that this cohort appears to be healthier than random cohorts of the same age/sex, including lower rates of dementia and memory decline. This exceptionally healthy cohort provides a unique opportunity to investigate the genetic contributions to Late Onset Alzheimer’s Disease (LOAD).

Our study examined the association between whole genome sequence variants and LOAD in 3,475 LLFS members. We further investigated whether the observed LOAD associated LLFS variants generalize to cohorts characterized by different risk of dementia: high risk populations (familial LOAD and Down Syndrome), Alzheimer’s disease referral-base cohort, and population-based cohorts. As recently reported in Alzheimer’s & Dementia, we identified several genetic variants within the MTUS2 gene significantly associated with LOAD. The association was also observed in the six independent cohorts considered and become significantly stronger within high Aβ42/40 ratio compared to lower amyloid ratio.

Figure 1. Manhattan plot of Seq-GWAS results in LLFS cohort. The X-axis represents the genomic position for each of the SNPs analyzed; Y-axis represents the -log10 transformed p-values. The red line indicates the genome-wide significance threshold (p < 5 × 10−8). GWAS, genome-wide association studies; LLFS, Long-Life Family Study; SNP, single nucleotide polymorphism.

MTUS2 is a plus end tracking protein implicated in the development and function of the nervous system. It is expressed in brain during development and adulthood. RNA-seq analysis of more than 1,100 individuals’ post-mortem brains from the Accelerating Medicines Partnership for Alzheimer’s disease (AMP-AD) consortium demonstrated significant change in MTUS2 gene expression when comparing LOAD cases and cognitively healthy samples. Our results support MTUS2 as a novel LOAD risk locus. Future functional validation analyses will be needed to further investigate the role of MTUS2 in LOAD pathology.

Osama Al Dalahmah, MD, PhD
Assistant Professor in Pathology and Cell Biology
oa2298@cumc.columbia.edu

Microglia Measured by TSPO PET are Associated with Alzheimer's Disease Pathology and Mediate key Steps in a Disease Progression Model

Yaakov Stern, PhD		Adam Brickman, PhD		Patrick Lao, PhD

In vivo neuroimaging biomarkers of tau and amyloid-β pathology have become essential tools in research into normal cognitive aging and preclinical Alzheimer’s disease (AD), as deposition of both proteins begins several years before clinical symptoms emerge. Despite the well-accepted involvement of amyloid-β and tau pathology in AD, questions remain regarding the role of these proteins in age-related cognitive decline. For instance, previous studies found normal aging is associated with the deposition of tau pathology in the medial temporal lobe (MTL) and neocortex even in the absence of or in the context of low amyloid-β pathology. This condition has been termed primary age-related tauopathy and there is still debate as to whether this is part of the AD spectrum or is part of “normal” aging. Previous work reported that tau pathology in transentorhinal regions precedes amyloid-β deposition and tau PET studies indicate a close relationship between patterns of early tau deposition and cognitive impairment.

Figure 4. Scatterplot diagrams illustrating the relationship between tau PET uptake [ 18F-MK-6240] and memory change across brain regions. (A–D) The associations considering regional tau uptake (meta-ROIs). (E) A forest plot representing the unstandardized betas and 95% interval confidence for each linear regression considering 36 brain areas. The results highlighted (*) are not corrected for multiple comparisons. All regressions accounted for age at follow-up, sex/gender, education, and baseline memory performance. Abbreviations: C/P, cingulate/parietal lobe; LTL, lateral temporal lobe; MTL, medial temporal lobe; ROI, region of interest; SUVR, standardized uptake value ratio.

Tau accumulation has been associated with longitudinal cognitive decline, typically in episodic memory. Due to the initial tau accumulation in the MTL, memory has been the domain typically investigated; however, few studies suggest tau accumulation to be associated with a decline in global cognition, executive functions, and speed processing. Therefore, the impact of early tau accumulation on cognitive trajectories beyond memory in cognitively unimpaired older adults still needs to be further characterized and understood, particularly with second-generation tau tracers. For instance, the tracer 18F-MK-6240 is a PET ligand for imaging neurofibrillary tangles in vivo that has shown favorable imaging characteristics and spatial distributions consistent with the neuropathological staging of neurofibrillary tangles in AD in preliminary studies. Studies evaluating 18F-MK-6240 in humans have indicated high affinity to neurofibrillary tangles in AD, minimal off-target binding in the brain, and the presence of extra-axial signals in some cases. In addition, the tracer 18F-MK-6240 was shown to predict cognitive decline in cognitively unimpaired older adults.

Figure 5. Scatterplot diagrams illustrating the relationship between tau PET [ 18F-MK-6240] and processing speed change across brain regions. (A–D) The associations considering regional tau uptakes (meta-ROIs). (E) A forest plot representing the unstandardized betas and 95% interval confidence for each linear regression considering different 36 brain areas. The results highlighted (*) are not corrected for multiple comparisons. All regressions accounted for age at follow-up, sex/ gender, education, and baseline memory performance. Abbreviations: C/P, cingulate/parietal lobe; LTL, lateral temporal lobe; MTL, medial temporal lobe; ROI, region of interest; SUVR, standardized uptake value ratio.

Using data from the ongoing, longitudinal Reference Ability Neural Network Study, we evaluated the association of late-life tau deposition with retrospective cognitive change considering cognitive domains well established to decline with aging: episodic memory, speed processing, and reasoning. For tau quantification, a set of regions of interest (ROIs) was selected a priori: (1) total-ROI comprising selected areas, (2) medial temporal lobe-ROI, (3) lateral temporal lobe-ROI and (4) cingulate/parietal lobe-ROI. Using a sample of 41 cognitively healthy older adults, we found that higher levels of 18F-MK-6240 in brain regions linked to Alzheimer's disease—namely, the medial temporal lobe, cingulate, and parietal regions—were associated with faster declines in episodic memory and processing speed, but not in reasoning ability. This association persisted even when adjusting for demographic variables (like age, sex, and education), baseline cognitive function, and amyloid-β levels. As recently reported in Neurobiology of Aging, our findings highlight the role of pathological tau in areas susceptible to early buildup in driving cognitive changes seen in Alzheimer's disease, even in older adults without cognitive impairments and who have low amyloid-β levels. Despite the small sample size of the present study, our findings suggest that memory and processing speed declines typically seen in normal aging may be partly due to tau accumulation, emphasizing the importance of exploring long-term relationships between tau buildup and cognitive abilities beyond memory.

Sharon Sanz Simon, PhD
Associate Research Scientist (in the Taub Institute and the Gertrude H. Sergievsky Center)
sss2278@cumc.columbia.edu

Yaakov Stern, PhD
Florence Irving Professor of Neuropsychology (in Neurology, Psychiatry, the Gertrude H. Sergievsky Center, and the Taub Institute)
ys11@cumc.columbia.edu

A Comparative Study of Structural Variant Calling in WGS from Alzheimer's Disease Families

Badri Vardarajan, PhD, MS

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Figure 2. Differences in performance on the List Sorting Working Memory test from the NIH Toolbox across the four study visits. The improved score from the baseline of the first condition (B1) to the baseline of the second condition (B2) indicates a practice effect. Following the adequate sleep condition, participants showed greater improvement than what would be expected with practice. However, following the insufficient sleep condition, participants did not improve as much as would be expected with practice; there were no statistical differences between B1 and performance following the insufficient sleep condition. Values plotted are means (SE) derived from the repeated measures analysis of variance models.

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Badri N. Vardarajan, PhD, MS
Assistant Professor of Neurological Science (in Neurology, the Sergievsky Center, and the Taub Institute) at CUMC
bnv2103@cumc.columbia.edu