Sex Differences in the Risk of Dementia in Older Veterans.

BACKGROUND: Studies have demonstrated women to have a higher prevalence of dementia compared to men. However, sex differences in dementia incidence are controversial with conflicting reports showing women with higher, lower, or similar incidence. Source of difference may be due to clinical setting and lack of consideration of competing risk of death. We examined dementia incidence in a sample of the national Veteran population to determine differences by sex. METHODS: We examined data from the Veterans Health Administration (VHA), the largest integrated health care system in the United States. We studied 947 797 Veterans aged ≥55 years (mean age: 69.9 ± 8.4, 3% female) evaluated in the VHA from October 1, 1999 to September 30, 2019. We estimated age-adjusted incidence rates of dementia (International Classification of Diseases, 9th and 10th Edition codes) by sex, and used Fine-Gray proportional hazards models with age as time scale to examine time to diagnosis, accounting for competing risk of death. RESULTS: During the follow-up (mean 8.4 years), 11.3% (n = 106 977, 11.4% men and 8.0% women) of Veterans developed dementia. Age-adjusted incidence was 12.6/1 000 person-years for men and 12.7/1 000 person-years for women. Compared to male Veterans, risk dementia was slightly higher among females (hazard ratio = 1.15; 95% confidence interval: 1.10-1.20), and on average, female Veterans developed dementia 0.2 years earlier than male Veterans. After additional adjustment for race, education, medical, and psychiatric conditions, results were similar. CONCLUSIONS: Among older Veterans in a national cohort, women had a slightly increased risk for developing dementia compared to men after accounting for competing risk of death.

Remote Assessment of Cardiovascular Risk Factors and Cognition in Middle-Aged and Older Adults: Proof-of-Concept Study.

BACKGROUND: Adults with cardiovascular disease risk factors (CVRFs) are also at increased risk of developing cognitive decline and dementia. However, it is often difficult to study the relationships between CVRFs and cognitive function because cognitive assessment typically requires time-consuming in-person neuropsychological evaluations that may not be feasible for real-world situations. OBJECTIVE: We conducted a proof-of-concept study to determine if the association between CVRFs and cognitive function could be detected using web-based, self-administered cognitive tasks and CVRF assessment. METHODS: We recruited 239 participants aged ≥50 years (mean age 62.7 years, SD 8.8; 42.7% [n=102] female, 88.7% [n=212] White) who were enrolled in the Health eHeart Study, a web-based platform focused on cardiac disease. The participants self-reported CVRFs (hypertension, high cholesterol, diabetes, and atrial fibrillation) using web-based health surveys between August 2016 and July 2018. After an average of 3 years of follow-up, we remotely evaluated episodic memory, working memory, and executive function via the web-based Posit Science platform, BrainHQ. Raw data were normalized and averaged into 3 domain scores. We used linear regression models to examine the association between CVRFs and cognitive function. RESULTS: CVRF prevalence was 62.8% (n=150) for high cholesterol, 45.2% (n=108) for hypertension, 10.9% (n=26) for atrial fibrillation, and 7.5% (n=18) for diabetes. In multivariable models, atrial fibrillation was associated with worse working memory (ß=-.51, 95% CI -0.91 to -0.11) and worse episodic memory (ß=-.31, 95% CI -0.59 to -0.04); hypertension was associated with worse episodic memory (ß=-.27, 95% CI -0.44 to -0.11). Diabetes and high cholesterol were not associated with cognitive performance. CONCLUSIONS: Self-administered web-based tools can be used to detect both CVRFs and cognitive health. We observed that atrial fibrillation and hypertension were associated with worse cognitive function even in those in their 60s and 70s. The potential of mobile assessments to detect risk factors for cognitive aging merits further investigation.

Novel verbal fluency scores and structural brain imaging for prediction of cognitive outcome in mild cognitive impairment.

INTRODUCTION: The objective of this study was to assess the utility of novel verbal fluency scores for predicting conversion from mild cognitive impairment (MCI) to clinical Alzheimer's disease (AD). METHOD: Verbal fluency lists (animals, vegetables, F, A, and S) from 107 MCI patients and 51 cognitively normal controls were transcribed into electronic text files and automatically scored with traditional raw scores and five types of novel scores computed using methods from machine learning and natural language processing. Additional scores were derived from structural MRI scans: region of interest measures of hippocampal and ventricular volumes and gray matter scores derived from performing ICA on measures of cortical thickness. Over 4 years of follow-up, 24 MCI patients converted to AD. Using conversion as the outcome variable, ensemble classifiers were constructed by training classifiers on the individual groups of scores and then entering predictions from the primary classifiers into regularized logistic regression models. Receiver operating characteristic curves were plotted, and the area under the curve (AUC) was measured for classifiers trained with five groups of available variables. RESULTS: Classifiers trained with novel scores outperformed those trained with raw scores (AUC 0.872 vs 0.735; P < .05 by DeLong test). Addition of structural brain measurements did not improve performance based on novel scores alone. CONCLUSION: The brevity and cost profile of verbal fluency tasks recommends their use for clinical decision making. The word lists generated are a rich source of information for predicting outcomes in MCI. Further work is needed to assess the utility of verbal fluency for early AD.

Common variants in ABCA7 and MS4A6A are associated with cortical and hippocampal atrophy.

The precise physiologic function of many of the recently discovered Alzheimer's disease risk variants remains unknown. The downstream effects of genetic variants remain largely unexplored. We studied the relationship between the top 10 non-APOE genes with cortical and hippocampal atrophy as markers of neurodegeneration using 1.5T magnetic resonance imaging, 1-million single nucleotide polymorphism Illumina Human Omni-Quad array and Illumina Human BeadChip peripheral blood expression array data on 50 cognitively normal and 98 mild cognitive impairment subjects. After explicit matching of cortical and hippocampal morphology, we computed in 3D, the cortical thickness and hippocampal radial distance measures for each participant. Associations between the top 10 non-APOE genome-wide hits and neurodegeneration were explored using linear regression. Map-wise statistical significance was determined with permutations using threshold of p < 0.01. MS4A6A rs610932 and ABCA7 rs3764650 demonstrated significant associations with cortical and hippocampal atrophy. Exploratory MS4A6A and ABCA7 peripheral blood expression analyses revealed a similar pattern of associations with cortical neurodegeneration. To our knowledge, this is the first report of the effect of ABCA7 and MS4A6A on neurodegeneration.

Plasma BDNF levels associate with Pittsburgh compound B binding in the brain.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) plays an important role in Alzheimer's disease (AD) and other neurodegenerative disorders. BDNF function is adversely affected by amyloid beta (Aß) in AD. BDNF levels in brain and peripheral tissues are lower in patients with AD and MCI, than in controls. Here we examined the association between plasma levels of BDNF and amyloid deposition in the brain measured with Pittsburgh Compound B (PiB). METHOD: Our dataset consisted of 18 AD, 56 mild cognitive impairment (MCI) and 3 normal control (NC) Alzheimer's Disease Neuroimaging Initiative-1 (ADNI1) subjects with available [11C] PiB and peripheral blood protein data. MRI-coregistered PET data was smoothed with a 15 mm kernel and mapped onto 3D hemispheric models using the warping deformations computed in cortical pattern matching of the associated MRI scans. We applied linear regression to examine in 3D the associations between BDNF and PiB SUVR, while adjusting for age and sex. We used permutation statistics thresholded at p<0.01 for multiple comparisons correction. RESULTS: Plasma BDNF levels showed significant negative associations with left greater than right amyloid burden in the lateral temporal, inferior parietal, inferior frontal, anterior and posterior cingulate, and orbitofrontal regions (left pcorrected=0.03). CONCLUSIONS: As hypothesized, lower plasma levels of BDNF were significantly associated with widespread brain amyloidosis.

Alzheimer risk genes modulate the relationship between plasma apoE and cortical PiB binding.

OBJECTIVE: We investigated the association between apoE protein plasma levels and brain amyloidosis and the effect of the top 10 Alzheimer disease (AD) risk genes on this association. METHODS: Our dataset consisted of 18 AD, 52 mild cognitive impairment, and 3 cognitively normal Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) participants with available [(11)C]-Pittsburgh compound B (PiB) and peripheral blood protein data. We used cortical pattern matching to study associations between plasma apoE and cortical PiB binding and the effect of carrier status for the top 10 AD risk genes. RESULTS: Low plasma apoE was significantly associated with high PiB SUVR, except in the sensorimotor and entorhinal cortex. For BIN1 rs744373, the association was observed only in minor allele carriers. For CD2AP rs9349407 and CR1 rs3818361, the association was preserved only in minor allele noncarriers. We did not find evidence for modulation by CLU, PICALM, ABCA7, BIN1, and MS4A6A. CONCLUSIONS: Our data show that BIN1 rs744373, CD2AP rs9349407, and CR1 rs3818361 genotypes modulate the association between apoE protein plasma levels and brain amyloidosis, implying a potential epigenetic/downstream interaction.

Cortical thickness and semantic fluency in Alzheimer's disease and mild cognitive impairment.

The hallmark of Alzheimer's disease (AD) is declarative memory loss, but deficits in semantic fluency are also observed. We assessed how semantic fluency relates to cortical atrophy to identify specific regions that play a role in the loss of access to semantic information. Whole-brain structural magnetic resonance imaging (MRI) data were analyzed from 9 Normal Control (NC)(M=76.7, SD=5.6), 40 Mild Cognitive Impairment (MCI) (M=74.4, SD=8.6), and 10 probable AD (M=72.4, SD=8.0) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). They all were administered the Category Fluency (CF) animals and vegetables tests. Poorer semantic fluency was associated with bilateral cortical atrophy of the inferior parietal lobule (Brodman areas (BA) 39 and 40) and BA 6, 8, and 9 in the frontal lobe, as well as BA 22 in the temporal lobe. More diffuse frontal associations were seen in the left hemisphere involving BA 9, 10, 32, 44, 45, and 46. Additional cortical atrophy was seen in the temporoparietal (BA 37) and the right parastriate (BA 19, 18) cortices. Associations were more diffuse for performance on vegetable fluency than animal fluency. The permutation-corrected map-wise significance for CF animals was pcorrected=0.01 for the left hemisphere, and pcorrected=0.06 for the right hemisphere. The permutation-corrected map-wise significance for CF vegetables was pcorrected=0.009 for the left hemisphere, and pcorrected=0.03 for the right hemisphere. These results demonstrate the profound effect of cortical atrophy on semantic fluency. Specifically, tapping into semantic knowledge involves the frontal lobe in addition to the language cortices of the temporoparietal region.