Apolipoprotein E moderates the association between non-APOE polygenic risk score for Alzheimer's disease and aging on preclinical cognitive function.

INTRODUCTION: Variation in preclinical cognitive decline suggests additional genetic factors related to Alzheimer's disease (eg, a non-APOE polygenic risk score [PRS]) may interact with the APOE ε4 allele to influence cognitive decline. METHODS: We tested the PRS × APOE ε4 × age interaction on preclinical cognition using longitudinal data from the Wisconsin Registry for Alzheimer's Prevention. All analyses were fitted using a linear mixed-effects model and adjusted for within individual/family correlation among 1190 individuals. RESULTS: We found statistically significant PRS × APOE ε4 × age interactions on immediate learning (P = 0.038), delayed recall (P < 0.001), and Preclinical Alzheimer's Cognitive Composite 3 score (P = 0.026). PRS-related differences in overall and memory-related cognitive domains between people with and without APOE ε4 emerge around age 70, with a much stronger adverse PRS effect among APOE ε4 carriers. The findings were replicated in a population-based cohort. DISCUSSIONS: APOE ε4 can modify the association between PRS and cognition decline. HIGHLIGHTS: APOE ε4 can modify the association between polygenic risk scores (PRSs) and longitudinal cognition decline, with the modifying effects more pronounced when the PRS is constructed using a conservative P threshold (eg, P < 5e-8 ). The adverse genetic effect caused by the combined effect of the currently known genetic variants is more detrimental among APOE Îµ4 carriers around age 70. Individuals who are APOE Îµ4 carriers with high PRSs are the most vulnerable to the harmful effects caused by genetic burden.

Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3.

INTRODUCTION: Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear. METHODS: We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269). RESULTS: CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10-5) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10-7). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10-6) and CSF p-tau levels (P = 4.38 × 10-9). DISCUSSION: These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels. HIGHLIGHTS: Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia.

Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts.

Alzheimer's disease biomarkers are becoming increasingly important for characterizing the longitudinal course of disease, predicting the timing of clinical and cognitive symptoms, and for recruitment and treatment monitoring in clinical trials. In this work, we develop and evaluate three methods for modelling the longitudinal course of amyloid accumulation in three cohorts using amyloid PET imaging. We then use these novel approaches to investigate factors that influence the timing of amyloid onset and the timing from amyloid onset to impairment onset in the Alzheimer's disease continuum. Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Baltimore Longitudinal Study of Aging (BLSA) and the Wisconsin Registry for Alzheimer's Prevention (WRAP). Amyloid PET was used to assess global amyloid burden. Three methods were evaluated for modelling amyloid accumulation using 10-fold cross-validation and holdout validation where applicable. Estimated amyloid onset age was compared across all three modelling methods and cohorts. Cox regression and accelerated failure time models were used to investigate whether sex, apolipoprotein E genotype and e4 carriage were associated with amyloid onset age in all cohorts. Cox regression was used to investigate whether apolipoprotein E (e4 carriage and e3e3, e3e4, e4e4 genotypes), sex or age of amyloid onset were associated with the time from amyloid onset to impairment onset (global clinical dementia rating ≥1) in a subset of 595 ADNI participants that were not impaired before amyloid onset. Model prediction and estimated amyloid onset age were similar across all three amyloid modelling methods. Sex and apolipoprotein E e4 carriage were not associated with PET-measured amyloid accumulation rates. Apolipoprotein E genotype and e4 carriage, but not sex, were associated with amyloid onset age such that e4 carriers became amyloid positive at an earlier age compared to non-carriers, and greater e4 dosage was associated with an earlier amyloid onset age. In the ADNI, e4 carriage, being female and a later amyloid onset age were all associated with a shorter time from amyloid onset to impairment onset. The risk of impairment onset due to age of amyloid onset was non-linear and accelerated for amyloid onset age >65. These findings demonstrate the feasibility of modelling longitudinal amyloid accumulation to enable individualized estimates of amyloid onset age from amyloid PET imaging. These estimates provide a more direct way to investigate the role of amyloid and other factors that influence the timing of clinical impairment in Alzheimer's disease.

Sex differences in the genetic architecture of cognitive resilience to Alzheimer's disease.

Approximately 30% of elderly adults are cognitively unimpaired at time of death despite the presence of Alzheimer's disease neuropathology at autopsy. Studying individuals who are resilient to the cognitive consequences of Alzheimer's disease neuropathology may uncover novel therapeutic targets to treat Alzheimer's disease. It is well established that there are sex differences in response to Alzheimer's disease pathology, and growing evidence suggests that genetic factors may contribute to these differences. Taken together, we sought to elucidate sex-specific genetic drivers of resilience. We extended our recent large scale genomic analysis of resilience in which we harmonized cognitive data across four cohorts of cognitive ageing, in vivo amyloid PET across two cohorts, and autopsy measures of amyloid neuritic plaque burden across two cohorts. These data were leveraged to build robust, continuous resilience phenotypes. With these phenotypes, we performed sex-stratified [n (males) = 2093, n (females) = 2931] and sex-interaction [n (both sexes) = 5024] genome-wide association studies (GWAS), gene and pathway-based tests, and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to resilience in a sex-specific manner. Estimated among cognitively normal individuals of both sexes, resilience was 20-25% heritable, and when estimated in either sex among cognitively normal individuals, resilience was 15-44% heritable. In our GWAS, we identified a female-specific locus on chromosome 10 [rs827389, ß (females) = 0.08, P (females) = 5.76 × 10-09, ß (males) = -0.01, P(males) = 0.70, ß (interaction) = 0.09, P (interaction) = 1.01 × 10-04] in which the minor allele was associated with higher resilience scores among females. This locus is located within chromatin loops that interact with promoters of genes involved in RNA processing, including GATA3. Finally, our genetic correlation analyses revealed shared genetic architecture between resilience phenotypes and other complex traits, including a female-specific association with frontotemporal dementia and male-specific associations with heart rate variability traits. We also observed opposing associations between sexes for multiple sclerosis, such that more resilient females had a lower genetic susceptibility to multiple sclerosis, and more resilient males had a higher genetic susceptibility to multiple sclerosis. Overall, we identified sex differences in the genetic architecture of resilience, identified a female-specific resilience locus and highlighted numerous sex-specific molecular pathways that may underly resilience to Alzheimer's disease pathology. This study illustrates the need to conduct sex-aware genomic analyses to identify novel targets that are unidentified in sex-agnostic models. Our findings support the theory that the most successful treatment for an individual with Alzheimer's disease may be personalized based on their biological sex and genetic context.

Identification of plasma metabolites associated with modifiable risk factors and endophenotypes reflecting Alzheimer's disease pathology.

Modifiable factors can influence the risk for Alzheimer's disease (AD) and serve as targets for intervention; however, the biological mechanisms linking these factors to AD are unknown. This study aims to identify plasma metabolites associated with modifiable factors for AD, including MIND diet, physical activity, smoking, and caffeine intake, and test their association with AD endophenotypes to identify their potential roles in pathophysiological mechanisms. The association between each of the 757 plasma metabolites and four modifiable factors was tested in the wisconsin registry for Alzheimer's prevention cohort of initially cognitively unimpaired, asymptomatic middle-aged adults. After Bonferroni correction, the significant plasma metabolites were tested for association with each of the AD endophenotypes, including twelve cerebrospinal fluid (CSF) biomarkers, reflecting key pathophysiologies for AD, and four cognitive composite scores. Finally, causal mediation analyses were conducted to evaluate possible mediation effects. Analyses were performed using linear mixed-effects regression. A total of 27, 3, 23, and 24 metabolites were associated with MIND diet, physical activity, smoking, and caffeine intake, respectively. Potential mediation effects include beta-cryptoxanthin in the association between MIND diet and preclinical Alzheimer cognitive composite score, hippurate between MIND diet and immediate learning, glutamate between physical activity and CSF neurofilament light, and beta-cryptoxanthin between smoking and immediate learning. Our study identified several plasma metabolites that are associated with modifiable factors. These metabolites can be employed as biomarkers for tracking these factors, and they provide a potential biological pathway of how modifiable factors influence the human body and AD risk.

Cognitive trajectories diverge by genetic risk in a preclinical longitudinal cohort.

INTRODUCTION: We sought to characterize the timing of changes in cognitive trajectories related to genetic risk using the apolipoprotein E (APOE) score, a continuous measure of Alzheimer's disease (AD) risk. We also aimed to determine whether that timing was different when genetic risk was measured using an AD polygenic risk score (PRS) that contains APOE. METHODS: We analyzed trajectories (N ≈1135) for four neuropsychological composite scores using mixed effects regression for longitudinal change across APOE scores and PRS of participants in the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults aged 40 to 70 at baseline, with a median participant follow-up time of 7.8 years. RESULTS: We found a significant non-linear age-by-APOE score interaction in predicting cognitive decline. Cognitive trajectories diverged by APOE score at approximately 65 years of age. A 0.5 standard deviation difference in cognition between extreme percentiles of the PRS was predicted to occur 1 to 2 years before that of the APOE score. DISCUSSION: Cognitive decline differs across time and APOE score. Estimates did not substantially shift with the AD PRS. HIGHLIGHTS: The apolipoprotein E (APOE) score, a continuous measure, accounts for non-linear genetic risk of Alzheimer's disease. Non-linear age interacts with the APOE score to affect cognition. Cognitive decline starts to differ by APOE score levels at approximately age 65. Cognitive decline timing by polygenic risk (including APOE) is similar to APOE alone.

Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk.

INTRODUCTION: Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes. METHODS: We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants. DISCUSSION: The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses.

Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease.

INTRODUCTION: A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest. METHODS: We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n = 137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation. RESULTS: We identified 61 proteins significantly associated with the AT category (P < 5.46 × 10-5 ) and 636 significant protein-biomarker associations (P < 6.07 × 10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n = 717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers. DISCUSSION: These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD. HIGHLIGHTS: Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.

Multi-ethnic analysis shows genetic risk and environmental predictors interact to influence 25(OH)D concentration and optimal vitamin D intake.

25-Hydroxyvitamin D (25(OH)D) concentration is a complex trait with genetic and environmental predictors that may determine how much vitamin D exposure is required to reach optimal concentration. Interactions between continuous measures of a polygenic score (PGS) and vitamin D intake (PGS*intake) or available ultraviolet (UV) radiation (PGS*UV) were evaluated in individuals of African (n = 1,099) or European (n = 8,569) ancestries. Interaction terms and joint effects (main and interaction terms) were tested using one-degree of freedom (1-DF) and 2-DF models, respectively. Models controlled for age, sex, body mass index, cohort, and dietary intake/available UV. In addition, in participants achieving Institute of Medicine (IOM) vitamin D intake recommendations, 25(OH)D was evaluated by level PGS. The 2-DF PGS*intake, 1-DF PGS*UV, and 2-DF PGS*UV results were statistically significant in participants of European ancestry (p = 3.3 × 10-18 , p = 2.1 × 10-2 , and p = 2.4 × 10-19 , respectively), but not in those of African ancestry. In European-ancestry participants reaching IOM vitamin D intake guidelines, the percent of participants achieving adequate 25(OH)D ( >20 ng/ml) increased as genetic risk decreased (72% vs. 89% in highest vs. lowest risk; p = .018). Available UV radiation and vitamin D intake interact with genetics to influence 25(OH)D. Individuals with higher genetic risk may require more vitamin D exposure to maintain optimal 25(OH)D concentrations.

Genetic variants and functional pathways associated with resilience to Alzheimer's disease.

Approximately 30% of older adults exhibit the neuropathological features of Alzheimer's disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer's disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values < 2.5 × 10-20), and we observed novel correlations with neuropsychiatric conditions (P-values < 7.9 × 10-4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer's disease (P-values > 0.42) nor associated with APOE (P-values > 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer's disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.

Integrated analysis of genomics, longitudinal metabolomics, and Alzheimer's risk factors among 1,111 cohort participants.

Although Alzheimer's disease (AD) is highly heritable, genetic variants are known to be associated with AD only explain a small proportion of its heritability. Genetic factors may only convey disease risk in individuals with certain environmental exposures, suggesting that a multiomics approach could reveal underlying mechanisms contributing to complex traits, such as AD. We developed an integrated network to investigate relationships between metabolomics, genomics, and AD risk factors using Wisconsin Registry for Alzheimer's Prevention participants. Analyses included 1,111 non-Hispanic Caucasian participants with whole blood expression for 11,376 genes (imputed from dense genome-wide genotyping), 1,097 fasting plasma metabolites, and 17 AD risk factors. A subset of 155 individuals also had 364 fastings cerebral spinal fluid (CSF) metabolites. After adjusting each of these 12,854 variables for potential confounders, we developed an undirected graphical network, representing all significant pairwise correlations upon adjusting for multiple testing. There were many instances of genes being indirectly linked to AD risk factors through metabolites, suggesting that genes may influence AD risk through particular metabolites. Follow-up analyses suggested that glycine mediates the relationship between carbamoyl-phosphate synthase 1 and measures of cardiovascular and diabetes risk, including body mass index, waist-hip ratio, inflammation, and insulin resistance. Further, 38 CSF metabolites explained more than 60% of the variance of CSF levels of tau, a detrimental protein that accumulates in the brain of AD patients and is necessary for its diagnosis. These results further our understanding of underlying mechanisms contributing to AD risk while demonstrating the utility of generating and integrating multiple omics data types.

Ancestry-specific polygenic scores and SNP heritability of 25(OH)D in African- and European-ancestry populations.

Vitamin D inadequacy, assessed by 25-hydroxyvitamin D [25(OH)D], affects around 50% of adults in the United States and is associated with numerous adverse health outcomes. Blood 25(OH)D concentrations are influenced by genetic factors that may determine how much vitamin D intake is required to reach optimal 25(OH)D. Despite large genome-wide association studies (GWASs), only a small portion of the genetic factors contributing to differences in 25(OH)D has been discovered. Therefore, knowledge of a fuller set of genetic factors could be useful for risk prediction of 25(OH)D inadequacy, personalized vitamin D supplementation, and prevention of downstream morbidity and mortality. Using PRSice and weights from published African- and European-ancestry GWAS summary statistics, ancestry-specific polygenic scores (PGSs) were created to capture a more complete set of genetic factors in those of European (n = 9569) or African ancestry (n = 2761) from three cohort studies. The PGS for African ancestry was derived using all input SNPs (a p value cutoff of 1.0) and had an R2 of 0.3%; for European ancestry, the optimal PGS used a p value cutoff of 3.5 × 10-4 in the target/tuning dataset and had an R2 of 1.0% in the validation cohort. Those with highest genetic risk had 25(OH)D that was 2.8-3.0 ng/mL lower than those with lowest genetic risk (p = 0.0463-3.2 × 10-13), requiring an additional 467-500 IU of vitamin D intake to maintain equivalent 25(OH)D. PGSs are a powerful predictive tool that could be leveraged for personalized vitamin D supplementation to prevent the negative downstream effects of 25(OH)D inadequacy.

Carrier frequency estimation of Zellweger spectrum disorder using ExAC database and bioinformatics tools.

PURPOSE: We aimed to estimate the carrier frequency of Zellweger spectrum disorder (ZSD), a rare autosomal recessive disease, and the associated disease incidence based on data from the Exome Aggregation Consortium (ExAC) of approximately 60,000 individuals. METHODS: We obtained variants from ExAC in 13 PEX genes associated with ZSD. Potentially pathogenic missense variants were identified with computational variant analysis tools according to three stringency levels. Using variants classified as potentially pathogenic, we estimated the carrier frequency and the associated incidence for the entire ExAC population and its subpopulations. We also evaluated variants based on pathogenicity criteria for sequence variant interpretation outlined by the American College of Medical Genetics and Genomics (ACMG) and calculated the carrier frequency and incidence based on those variants. RESULTS: The bioinformatically estimated incidence rate of ZSD in the ExAC population is 1 in 83,841 using our least stringent pathogenicity cutoff. Under clinical guidelines outlined by ACMG, the estimated incidence is 1 in 3,275,751 births. CONCLUSION: We outlined a process for estimating the ZSD disease carrier frequency and incidence in a large consortium using bioinformatics tools. Our results are close to current newborn screening estimates in New York of 1 in 90,000 births, estimated from 1.08 million screenings.

Characterizing the Effects of Sex, APOE ɛ4, and Literacy on Mid-life Cognitive Trajectories: Application of Information-Theoretic Model Averaging and Multi-model Inference Techniques to the Wisconsin Registry for Alzheimer's Prevention Study.

OBJECTIVES: Prior research has identified numerous genetic (including sex), education, health, and lifestyle factors that predict cognitive decline. Traditional model selection approaches (e.g., backward or stepwise selection) attempt to find one model that best fits the observed data, risking interpretations that only the selected predictors are important. In reality, several predictor combinations may fit similarly well but result in different conclusions (e.g., about size and significance of parameter estimates). In this study, we describe an alternative method, Information-Theoretic (IT) model averaging, and apply it to characterize a set of complex interactions in a longitudinal study on cognitive decline. METHODS: Here, we used longitudinal cognitive data from 1256 late-middle aged adults from the Wisconsin Registry for Alzheimer's Prevention study to examine the effects of sex, apolipoprotein E (APOE) ɛ4 allele (non-modifiable factors), and literacy achievement (modifiable) on cognitive decline. For each outcome, we applied IT model averaging to a set of models with different combinations of interactions among sex, APOE, literacy, and age. RESULTS: For a list-learning test, model-averaged results showed better performance for women versus men, with faster decline among men; increased literacy was associated with better performance, particularly among men. APOE had less of an association with cognitive performance in this age range (∼40-70 years). CONCLUSIONS: These results illustrate the utility of the IT approach and point to literacy as a potential modifier of cognitive decline. Whether the protective effect of literacy is due to educational attainment or intrinsic verbal intellectual ability is the topic of ongoing work. (JINS, 2019, 25, 119-133).

Using recursive feature elimination in random forest to account for correlated variables in high dimensional data.

BACKGROUND: Random forest (RF) is a machine-learning method that generally works well with high-dimensional problems and allows for nonlinear relationships between predictors; however, the presence of correlated predictors has been shown to impact its ability to identify strong predictors. The Random Forest-Recursive Feature Elimination algorithm (RF-RFE) mitigates this problem in smaller data sets, but this approach has not been tested in high-dimensional omics data sets. RESULTS: We integrated 202,919 genotypes and 153,422 methylation sites in 680 individuals, and compared the abilities of RF and RF-RFE to detect simulated causal associations, which included simulated genotype-methylation interactions, between these variables and triglyceride levels. Results show that RF was able to identify strong causal variables with a few highly correlated variables, but it did not detect other causal variables. CONCLUSIONS: Although RF-RFE decreased the importance of correlated variables, in the presence of many correlated variables, it also decreased the importance of causal variables, making both hard to detect. These findings suggest that RF-RFE may not scale to high-dimensional data.

Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20.

BACKGROUND: Multiple layers of genetic and epigenetic variability are being simultaneously explored in an increasing number of health studies. We summarize here different approaches applied in the Data Mining and Machine Learning group at the GAW20 to integrate genome-wide genotype and methylation array data. RESULTS: We provide a non-intimidating introduction to some frequently used methods to investigate high-dimensional molecular data and compare the different approaches tried by group members: random forest, deep learning, cluster analysis, mixed models, and gene-set enrichment analysis. Group contributions were quite heterogeneous regarding investigated data sets (real vs simulated), conducted data quality control and assessed phenotypes (eg, metabolic syndrome vs relative differences of log-transformed triglyceride concentrations before and after fenofibrate treatment). However, some common technical issues were detected, leading to practical recommendations. CONCLUSIONS: Different sources of correlation were identified by group members, including population stratification, family structure, batch effects, linkage disequilibrium and correlation of methylation values at neighboring cytosine-phosphate-guanine (CpG) sites, and the majority of applied approaches were able to take into account identified correlation structures. The ability to efficiently deal with high-dimensional omics data, and the model free nature of the approaches that did not require detailed model specifications were clearly recognized as the main strengths of applied methods. A limitation of random forest is its sensitivity to highly correlated variables. The parameter setup and the interpretation of results from deep learning methods, in particular deep neural networks, can be extremely challenging. Cluster analysis and mixed models may need some predimension reduction based on existing literature, data filtering, and supplementary statistical methods, and gene-set enrichment analysis requires biological insight.

Beta-amyloid and cognitive decline in late middle age: Findings from the Wisconsin Registry for Alzheimer's Prevention study.

INTRODUCTION: The present study investigated the relationship between beta-amyloid (Aß) and cognition in a late middle-aged cohort at risk for Alzheimer's disease (AD). METHODS: One eighty-four participants (mean age = 60; 72% parental history of AD) completed a [C-11]Pittsburgh compound B positron emission tomography scan and serial cognitive evaluations. A global measure of Aß burden was calculated, and composite scores assessing learning, delayed memory, and executive functioning were computed. RESULTS: Higher Aß was associated with classification of psychometric mild cognitive impairment (MCI) at follow-up (P < .01). Linear mixed effects regression results indicated higher Aß was associated with greater rates of decline in delayed memory (P < .01) and executive functioning (P < .05). Apolipoprotein E (APOE) ε4 status moderated the relationship between Aß and cognitive trajectories (P values <.01). DISCUSSION: In individuals at risk for AD, greater Aß in late middle age is associated with increased likelihood of MCI at follow-up and steeper rates of cognitive decline.

Methods for collapsing multiple rare variants in whole-genome sequence data.

Genetic Analysis Workshop 18 provided whole-genome sequence data in a pedigree-based sample and longitudinal phenotype data for hypertension and related traits, presenting an excellent opportunity for evaluating analysis choices. We summarize the nine contributions to the working group on collapsing methods, which evaluated various approaches for the analysis of multiple rare variants. One contributor defined a variant prioritization scheme, whereas the remaining eight contributors evaluated statistical methods for association analysis. Six contributors chose the gene as the genomic region for collapsing variants, whereas three contributors chose nonoverlapping sliding windows across the entire genome. Statistical methods spanned most of the published methods, including well-established burden tests, variance-components-type tests, and recently developed hybrid approaches. Lesser known methods, such as functional principal components analysis, higher criticism, and homozygosity association, and some newly introduced methods were also used. We found that performance of these methods depended on the characteristics of the genomic region, such as effect size and direction of variants under consideration. Except for MAP4 and FLT3, the performance of all statistical methods to identify rare casual variants was disappointingly poor, providing overall power almost identical to the type I error. This poor performance may have arisen from a combination of (1) small sample size, (2) small effects of most of the causal variants, explaining a small fraction of variance, (3) use of incomplete annotation information, and (4) linkage disequilibrium between causal variants in a gene and noncausal variants in nearby genes. Our findings demonstrate challenges in analyzing rare variants identified from sequence data.

Association between informal caregiving and cellular aging in the survey of the health of wisconsin: the role of caregiving characteristics, stress, and strain.

The pathophysiological consequences of caregiving have not been fully elucidated. We evaluated how caregiving, stress, and caregiver strain were associated with shorter relative telomere length (RTL), a marker of cellular aging. Caregivers (n = 240) and some noncaregivers (n = 98) in the 2008-2010 Survey of the Health of Wisconsin, comprising a representative sample of Wisconsin adults aged 21-74 years, reported their sociodemographic, health, and psychological characteristics. RTL was assayed from blood or saliva samples. Median T and S values were used to determine the telomere-to-single copy gene ratio (T/S) for each sample, and log(T/S) was used as the dependent variable in analyses. Multivariable generalized additive models showed that RTL did not differ between caregivers and noncaregivers (difference in log(T/S) = -0.03; P > 0.05), but moderate-to-high levels of stress versus low stress were associated with longer RTL (difference = 0.15; P = 0.04). Among caregivers, more hours per week of care, caring for a young person, and greater strain were associated with shorter RTL (P < 0.05). Caregivers with discordant levels of stress and strain (i.e., low perceived stress/high strain) compared with low stress/low strain had the shortest RTL (difference = -0.24; P = 0.02, Pinteraction = 0.13), corresponding to approximately 10-15 additional years of aging. Caregivers with these characteristics may be at increased risk for accelerated aging. Future work is necessary to better elucidate these relationships and develop interventions to improve the long-term health and well-being of caregivers.

The Wisconsin Assessment of the Social and Built Environment (WASABE): a multi-dimensional objective audit instrument for examining neighborhood effects on health.

BACKGROUND: Growing evidence suggests that mixed methods approaches to measuring neighborhood effects on health are needed. The Wisconsin Assessment of the Social and Built Environment (WASABE) is an objective audit tool designed as an addition to a statewide household-based health examination survey, the Survey of the Health of Wisconsin (SHOW), to objectively measure participant's neighborhoods. METHODS: This paper describes the development and implementation of the WASABE and examines the instrument's ability to capture a range of social and built environment features in urban and rural communities. A systematic literature review and formative research were used to create the tool. Inter-rater reliability parameters across items were calculated. Prevalence and density of features were estimated for strata formed according to several sociodemographic and urbanicity factors. RESULTS: The tool is highly reliable with over 81% of 115 derived items having percent agreement above 95%. It captured variance in neighborhood features in for a diverse sample of SHOW participants. Sidewalk density in neighborhoods surrounding households of participants living at less than 100% of the poverty level was 67% (95% confidence interval, 55-80%) compared to 34% (25-44%) for those living at greater than 400% of the poverty level. Walking and biking trails were present in 29% (19-39%) of participant buffer in urban areas compared to only 7% (2-12%) in rural communities. Significant environmental differences were also observed for white versus non-white, high versus low income, and college graduates versus individuals with lower level of education. CONCLUSIONS: The WASABE has strong inter-rater reliability and validity properties. It builds on previous work to provide a rigorous and standardized method for systematically gathering objective built and social environmental data in a number of geographic settings. Findings illustrate the complex milieu of built environment features found in participants neighborhoods and have relevance for future research, policy, and community engagement purposes.