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.
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.
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.
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.
•APOE ɛ4 dose correlates with ↓ hippocampal volume across Alzheimer/Lewy body disease.•Hippocampal volume associates with learning performance among APOE ɛ4 carriers.•Hippocampal volume in APOE ɛ4 carriers may be useful as a biomarker of progression.
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.
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.
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.
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.
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.
Background
White matter hyperintensities (WMH) of presumed vascular origin commonly coincide with neurodegeneration. Previous studies have reported heterogeneous relationships between WMH and ...atrophy. Cytochrome P450 (CYP) 2J2 (CYP2J2) is involved in the vascular ischemic response and soluble epoxide hydrolase (EPHX2) metabolizes its products, which have been implicated in vascular pathology and WMH. Here we investigate the potential moderation effect of CYP2J2 and EPHX2 single nucleotide polymorphisms (SNPs), individually and interactively, on the association between WMH and atrophy.
Methods
Patients with vascular cognitive impairment or neurodegenerative diagnoses (n=447) from the Sunnybrook Dementia Study (NCT01800214), Vascular Brain Health (VBH) study, and the Brain‐Eye Amyloid Memory (BEAM) study were genotyped for SNPs in EPHX2 and CYP2J2. SNPs were genotyped by the Illumina Neurochip and were selected a priori based on literature. All participants were confirmed to have European ancestry via multi‐dimensional scaling using the genotype data. Imaging analysis was performed on 3D T1 and T2/PD weighted images for brain segmentation and volumetric acquisition using SABRE, and WMH volumes were acquired on T2/PD/FLAIR images using Lesion Explorer. Linear regression models controlling for age, sex, Mini Mental State Exam, and head size were used to assess moderation effects of the SNPs (WMH×SNP interactions) on associations between WMH and temporal atrophy using SPSS (v.26). Presence of minor alleles were assessed using a dominant genetic model.
Results
The intron variant EPHX2 rs7816586 G/A polymorphism had a trending moderation effect on the association between periventricular WMH and left temporal atrophy where the minor A‐allele (frequency=11.52%) was protective (F=3.958, p=0.047) in extensive WMH. The promoter variant CYP2J2 rs10889162 C/T had a significant moderation effect on the association between deep WMH and right temporal atrophy where the minor T‐allele (frequency=8.61%) was protective in cases of extensive WMH (F=5.771, p=0.017). No interaction between the EPHX2 and CYP2J2 SNPs was detected.
Conclusion
We identified potential moderation effects of genetic variation in EPHX2 and CYP2J2 on the association between WMH and temporal lobe atrophy across neurodegenerative diagnoses. The lack of SNP×SNP interactions suggests that these genes may act independently, consistent with WMH×SNP interaction effects that occurred in association with different anatomical WMH locations.
Abstract
Background
Keratins are genetically polymorphic and are the largest subset of intermediate filaments. Keratins are also implicated in signaling pathways, inflammation, and disease states. ...Keratin 9 (KRT9) protein has been identified to have high diagnostic accuracy for Alzheimer’s disease (AD) (PMID:22045497); it was detected in cerebrospinal fluid (CSF) of AD patients but not healthy controls (PMID:24959311). Plasma keratin 9 concentrations also positively correlated with AD‐associated proteins (e.g., apolipoprotein E and tau) in AD patients (PMID:26973255). Post‐translational modification of keratin 83 (KRT83) protein has been associated with serum asymmetric dimethylarginine levels (PMID:34181092), a vascular risk factor implicated in AD. However, our understanding of the role of genetic variation in AD risk is incomplete. Here, we investigate associations between single nucleotide polymorphisms (SNPs) in KRT9, KRT83, and KRT2 (Keratin 2, couples with keratin 9) and AD biomarker phenotypes.
Method
Individuals with mild cognitive impairment (MCI) or AD, and clinically normal controls were selected among ADNI participants. Participants underwent genome‐wide genotyping. Keratin gene variants were identified from the genome‐wide data using dbSNP variant IDs and genotypes were coded additively. Linkage‐disequilibrium‐based clumping on minor allele frequency (MAF) was applied to prioritize more common SNPs. CSF‐Aβ42, ‐tau, and phosphorylated‐tau (p‐tau) levels were quantified via Roche Elecsys immunoassays. Brain‐Aβ deposition was evaluated via normalized PET‐18F‐AV‐45 cortical summary measures (SUVR). White matter hyperintensities (WMH) were obtained from MRI 3D‐T1 and FLAIR sequences via an automated atlas‐based segmentation pipeline. Linear regression models controlling for age, sex, Mini‐Mental State Exam, APOE‐ε4 status, and head size were used to assess association and interaction effects between SNPs and the AD phenotypes in R.
Result
Among included participants (n = 907, 73±7.2 years, 44% female), SNPs in KRT2 (e.g. 3’UTR‐variant rs117041267‐G/A; MAF = 1.4%) and KRT83 (e.g. upstream‐variant KRT83‐rs17119838‐C/T; MAF = 15.6%) were associated with higher CSF‐Aβ42 concentrations (F
(2,905)
= 4.26,p = 0.014; and F
(2,905)
= 6.61,p = 0.0014, respectively). Upstream‐variant KRT83‐rs182354391‐C/G (MAF = 1%) showed an association with lower CSF‐tau (F
(1,904)
= 5.44,p = 0.020). Multiple KRT9 and KRT2 SNPs also showed association with WMH, while KRT2 and KRT83 intron variants showed associations with PET‐Aβ.
Conclusion
These candidate gene analyses suggest involvement of multiple keratin family genes in AD, as indicated by differences in amyloid and tau biomarkers, and white matter disease.
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 RiskometerTM, 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 RiskometerTM) 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, R2 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 RiskometerTM performed well against the FSRS five‐year AUROC for both males (FSRS = 75·0% (95% CI 72·3%–77·6%), Stroke RiskometerTM = 74·0(95% CI 71·3%–76·7%) and females FSRS = 70·3% (95% CI 67·9%–72·8%, Stroke RiskometerTM = 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 RiskometerTM is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke RiskometerTM 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.
Abstract
Background
Given the rarity of genetic frontotemporal dementia (FTD), researchers across the world have come together to form the FTD Prevention Initiative (FPI) in an effort to improve ...prevention trials design. As this initiative begins to bring together large‐scale data from worldwide cohort series, including ALLFTD in North America and GENFI in Europe and Canada, it is critical for FPI to quantify the level of relatedness between all participants. Here we provide the most recent update to these ongoing analyses.
Methods
Genome‐wide SNP genotyping data from 1,684 ALLFTD and 568 GENFI participants was used to perform lineage analyses using PLINK. Briefly, QC was performed similarly in all datasets to remove individuals with low call rate and filter autosomal SNPs for missingness, frequency, and deviation from Hardy‐Weinberg equilibrium. Genetic ancestry was inferred by projecting genotyped samples into the principal components of the 1000 Genomes reference panel, using R package bigsnpr. Overlapping ALLFTD and GENFI genotyping data was then used, in a two‐stage approach, to calculate pairwise identity‐by‐descent (IBD) estimates and KING coefficients, followed by family‐network identification and pedigree reconstruction using PRIMUS.
Results
First, we calculated IBD estimates among all participants by restricting pairs to those with estimates>0.1875 (up to second‐degree relatives). Overall, we identified a total of 292 second‐degree family networks, including 168 ALLFTD and 120 GENFI families, mostly associated with pathogenic variants in the 3 major FTD‐causing genes. We also identified 4 family networks with participants enrolled in both the ALLFTD and GENFI series, as well as several multi‐site families within the ALLFTD consortium. This first, overall approach allowed us to predict close relationships even between individuals with different ancestral backgrounds, including at least 4 confirmed admixed families. More distant relationships were also detected within ALLFTD and GENFI by performing ancestry‐based analysis among participants with estimated European ancestry, using the KING‐robust algorithm.
Conclusions
These lineage analyses allowed us to identify, otherwise unknown, close (and distant) relatives from different study sites, as well as within the ALLFTD and GENFI series. This dataset will be a crucial resource to increase statistical accuracy and power in upcoming collaborative FPI studies.
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