Longitudinal cerebral perfusion in presymptomatic genetic frontotemporal dementia: GENFI results.

INTRODUCTION: Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers. METHODS: We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non-carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment. RESULTS: Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset. DISCUSSION: Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset. HIGHLIGHTS: Gray matter perfusion declines in at-risk genetic frontotemporal dementia (FTD). Regional perfusion decline differs between at-risk genetic FTD subgroups . Hypoperfusion in the left thalamus is common across all presymptomatic groups. Converters exhibit greater right frontal hypoperfusion than non-converters past their expected conversion date. Cerebral hypoperfusion is a potential early biomarker of genetic FTD.

Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning.

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

Association of low-frequency and rare coding variants with information processing speed.

Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10-6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.

Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: a GENFI study.

Genetic forms of frontotemporal dementia are most commonly due to mutations in three genes, C9orf72, GRN or MAPT, with presymptomatic carriers from families representing those at risk. While cerebral blood flow shows differences between frontotemporal dementia and other forms of dementia, there is limited evidence of its utility in presymptomatic stages of frontotemporal dementia. This study aimed to delineate the cerebral blood flow signature of presymptomatic, genetic frontotemporal dementia using a voxel-based approach. In the multicentre GENetic Frontotemporal dementia Initiative (GENFI) study, we investigated cross-sectional differences in arterial spin labelling MRI-based cerebral blood flow between presymptomatic C9orf72, GRN or MAPT mutation carriers (n = 107) and non-carriers (n = 113), using general linear mixed-effects models and voxel-based analyses. Cerebral blood flow within regions of interest derived from this model was then explored to identify differences between individual gene carrier groups and to estimate a timeframe for the expression of these differences. The voxel-based analysis revealed a significant inverse association between cerebral blood flow and the expected age of symptom onset in carriers, but not non-carriers. Regions included the bilateral insulae/orbitofrontal cortices, anterior cingulate/paracingulate gyri, and inferior parietal cortices, as well as the left middle temporal gyrus. For all bilateral regions, associations were greater on the right side. After correction for partial volume effects in a region of interest analysis, the results were found to be largely driven by the C9orf72 genetic subgroup. These cerebral blood flow differences first appeared approximately 12.5 years before the expected symptom onset determined on an individual basis. Cerebral blood flow was lower in presymptomatic mutation carriers closer to and beyond their expected age of symptom onset in key frontotemporal dementia signature regions. These results suggest that arterial spin labelling MRI may be a promising non-invasive imaging biomarker for the presymptomatic stages of genetic frontotemporal dementia.

APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies.

INTRODUCTION: Although the apolipoprotein E ε4-allele (APOE-ε4) is a susceptibility factor for Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), its relationship with imaging and cognitive measures across the AD/DLB spectrum remains unexplored. METHODS: We studied 298 patients (AD = 250, DLB = 48; 38 autopsy-confirmed; NCT01800214) using neuropsychological testing, volumetric magnetic resonance imaging, and APOE genotyping to investigate the association of APOE-ε4 with hippocampal volume and learning/memory phenotypes, irrespective of diagnosis. RESULTS: Across the AD/DLB spectrum: (1) hippocampal volumes were smaller with increasing APOE-ε4 dosage (no genotype × diagnosis interaction observed), (2) learning performance as assessed by total recall scores was associated with hippocampal volumes only among APOE-ε4 carriers, and (3) APOE-ε4 carriers performed worse on long-delay free word recall. DISCUSSION: These findings provide evidence that APOE-ε4 is linked to hippocampal atrophy and learning/memory phenotypes across the AD/DLB spectrum, which could be useful as biomarkers of disease progression in therapeutic trials of mixed disease.

Brain Volumes and Longitudinal Cognitive Change: A Population-based Study.

OBJECTIVE: To investigate the association of brain volumes, white matter lesion (WML) volumes, and lacunes, with cognitive decline in a population-based cohort of nondemented persons. METHODS: Within the Rotterdam Study, 3624 participants underwent brain magnetic resonance imaging. Cognition was evaluated at baseline (2005 to 2009) and at the follow-up visit (2011 to 2013). We used a test battery that tapped into domains of executive function, information processing speed, motor speed, and memory. The volumetric measures assessed were total brain volume, lobar (gray matter and white matter) volumes, and hippocampal volumes. We also studied the association of WML volumes and lacunes with cognitive decline using linear regression models. RESULTS: Total brain volume was associated with decline in global cognition, information processing, and motor speed (P<0.001) in analyses controlled for demographic and vascular factors. Specifically, smaller frontal and parietal lobes were associated with decline in information processing and motor speed, and smaller temporal and parietal lobes were associated with decline in general cognition and motor speed (P<0.001 for all tests). Total WML volume was associated with decline in executive function. Lobar WML volume, hippocampal volume, and lacunes were not associated with cognitive decline. CONCLUSIONS: Lower brain volume is associated with subsequent cognitive decline. Although lower total brain volume was significantly associated with decline in global cognition, specific lobar volumes were associated with decline in certain cognitive domains.

GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN.

BACKGROUND: Genome-wide association studies (GWAS) have made little progress in identifying variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (GxE) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide by environment interaction study (GWEIS) of depressive symptoms. METHODS: Using data from the SHARe cohort of the Women's Health Initiative, comprising African Americans (n = 7,179) and Hispanics/Latinas (n = 3,138), we examined genetic main effects and GxE with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. RESULTS: No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20 kb from GPR139, P = 5.75 × 10(-8) ) and rs75407252 (intronic to CACNA2D3, P = 6.99 × 10(-7) ). In Hispanics/Latinas, the top signals were rs2532087 (located 27 kb from CD38, P = 2.44 × 10(-7) ) and rs4542757 (intronic to DCC, P = 7.31 × 10(-7) ). In the GEWIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; P = 4.10 × 10(-10) ; located 14 kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG = 0.95), suggesting that common variation underlying self-reported depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. CONCLUSIONS: Our results underscore the need for larger samples, more GEWIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities.

The Stroke Riskometer(TM) App: validation of a data collection tool and stroke risk predictor.

BACKGROUND: The greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the 'mass' approach), the 'high risk' approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer(TM) , has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods. METHODS: 752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke Riskometer(TM) ) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R(2) statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm. RESULTS: The Stroke Riskometer(TM) performed well against the FSRS five-year AUROC for both males (FSRS = 75.0% (95% CI 72.3%-77.6%), Stroke Riskometer(TM) = 74.0(95% CI 71.3%-76.7%) and females [FSRS = 70.3% (95% CI 67.9%-72.8%, Stroke Riskometer(TM) = 71.5% (95% CI 69.0%-73.9%)], and better than QStroke [males - 59.7% (95% CI 57.3%-62.0%) and comparable to females = 71.1% (95% CI 69.0%-73.1%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 0.51-0.56, D-statistic ranging from 0.01-0.12). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data (P < 0.006). CONCLUSIONS: The Stroke Riskometer(TM) is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer(TM) will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors.

Location of residence or social class, which is the stronger determinant associated with cardiovascular risk factors among Pakistani population? A cross sectional study.

INTRODUCTION: The prevalence of cardiovascular disease and associated risk factors are increasing globally, particularly in the developing world. Those in the South Asian region are especially at risk of cardiovascular disease due to an increasing prevalence of its risk factors. This study was undertaken to investigate the association of social class with location of residence in the distribution of cardiovascular risk factors (mainly hypertension and diabetes mellitus) in Pakistan. METHODS: A cross-sectional study of 2495 subjects aged between 30-75 years was conducted in Punjab Province, which includes urban and rural areas. Subjects completed a detailed questionnaire, and anthropometric measurements and blood samples were taken after a written informed consent. Participants were categorized as urban or rural and assigned a social class according to their occupation. A logistic regression model was used to explore the association between social class and location of residence. RESULTS: The overall prevalence of hypertension and diabetes was 24.2% and 16.6%, respectively. Of the total number of participants, 56.8% (n=1417) were rural residents and 43.2% (n=1078) were urban. Urban individuals were significantly more likely (p<0.001) to be hypertensive (OR=3.03, 95% CI 2.14-4.30) and more likely (p<0.001) to be diabetic (OR=1.77, 95% CI 1.29-2.42) than rural dwellers, after multivariate adjustments for age, sex, BMI and social class. Social class was not significantly associated with the prevalence of either hypertension or diabetes. CONCLUSIONS: In the Pakistani population, rural or urban location of residence is a more powerful determinant of cardiovascular risk factors than social class.

Areca nut chewing and dependency syndrome: is the dependence comparable to smoking? a cross sectional study.

BACKGROUND: Areca nut is the seed of fruit oriental palm known as Areca catechu. Many adverse effects of nut chewing have been well documented in the medical literature. As these nuts are mixed with some other substances like tobacco and flavouring agents, it has been hypothesized that it might also cause some dependency symptoms among its users. Therefore, the objective of this study was to investigate dependency syndrome among areca nut users with and without tobacco additives and compare it with dependency associated with cigarette smoking among the male Pakistani population. METHODS: This was an observational cross sectional study carried out on healthy individuals, who were users of any one of the three products (areca nut only, areca nut with tobacco additives, cigarette smokers). Participants were selected by convenience sampling of people coming to hospital to seek a free oral check up. Information was collected about the socio-demographic profile, pattern of use and symptoms of dependency using the DSM-IV criteria for substance dependence. We carried out multiple logistic regressions to investigate association between socio-demographic profile, pattern of substance use and dependency syndrome. RESULTS: We carried out final analysis on 851 individuals, of which 36.8% (n = 314) were areca nut users, 28.4% (n = 242) were the chewers of areca with tobacco additives and 34.7% (n = 295) were regular cigarette smokers. Multivariate analyses showed that individuals using areca nut with tobacco additives were significantly more likely to have dependency syndrome (OR = 2.17, 95% CI 1.39-3.40) while cigarette smokers were eight times more likely to have dependency syndrome as compared to areca nut only users. CONCLUSIONS: Areca nut use with and without tobacco additives was significantly associated with dependency syndrome. In comparison to exclusive areca nut users, the smokers were eight times more likely to develop dependence while areca nut users with tobacco additives were also significantly more likely to suffer from the dependence.