Biology subjects

Johnson, S. C.

Publications and source records attributed to Johnson, S. C..

34 records · Page 2Linked to original sources

bioRxiv2020

Proper names from story recall are associated with beta-amyloid in cognitively unimpaired adults at risk for Alzheimer's disease

Due to advances in the early detection of Alzheimers disease (AD) biomarkers including beta-amyloid (A{beta}), neuropsychological measures that are sensitive to concurrent, subtle changes in cognition are critically needed. Story recall tasks have shown sensitivity to early memory declines in persons with Mild Cognitive Impairment and early stage dementia, as well as in persons with autosomal dominantly inherited AD up to 10 years prior to a dementia diagnosis. However, the evidence is inconclusive regarding relationships between evidence of A{beta} and story recall measures. Because story recall tasks require the encoding and delayed retrieval of several lexical-semantic categories, such as proper names, verbs, and numerical expressions, and because lexical categories have been shown to be differentially impaired in persons with MCI, we focused on item-level analyses of lexical-semantic retrieval from a quintessential story recall task, Logical Memory from the Wechsler Memory Scale. Our objective was to investigate whether delayed recall of lexical categories (proper names, verbs and/or numerical expressions), as well as the traditional total score measure, was associated with "preclinical AD," or cognitively unimpaired adults with positive A{beta} deposition on positron emission tomography (PET) neuroimaging using Pittsburgh Compound B. We developed an item-level scoring system, in which we parsed items into lexical categories and examined the immediate and delayed recall of these lexical categories from 217 cognitively unimpaired participants from the Wisconsin Registry for Alzheimers Prevention. We performed binary logistic regression models with story recall score as predictor and A{beta} status (positive/negative) as the outcome. Using baseline Logical Memory data, proper names from delayed story recall were significantly associated with A{beta} status, such that participants who recalled more proper names were less likely to be classified as PiB(+) (odds ratio = .58, p=.01). None of the other story recall variables, including total score, were associated with PiB status. Secondary analyses determined that immediate recall of proper names was not significantly associated with A{beta}, suggesting a retrieval deficit rather than that of encoding. The present findings suggest that lexical semantic retrieval measures from existing story recall tasks may be sensitive to A{beta} deposition, and may provide added utility to a widely-used, long-standing neuropsychological test for early detection of cognitive decline on the AD continuum.

neuroscience↗

bioRxiv2020

Inflammatory state of lymphatic vessels and miRNA profiles associated with relapse in ovarian cancer patients

Lymphogenic spread is associated with poor prognosis in epithelial ovarian cancer (EOC), yet little is known regarding roles of non-peri-tumoural lymphatic vessels (LVs) outside the tumour microenvironment that may impact relapse. The aim of this feasibility study was to assess whether inflammatory status of the LVs and/or changes in the miRNA profile of the LVs have potential prognostic and predictive value for overall outcome and risk of relapse. Samples of macroscopically normal human lymph LVs (n=10) were isolated from the external iliac vessels draining the pelvic region of patients undergoing debulking surgery. This was followed by quantification of the inflammatory state (low, medium and high) and presence of cancer-infiltration of each LV using immunohistochemistry. LV miRNA expression profiling was also performed, and analysed in the context of high versus low inflammation, and cancer-infiltrated versus non-cancer-infiltrated. Results were correlated with clinical outcome data including relapse with an average follow-up time of 13.3 months. The presence of a high degree of inflammation correlated significantly with patient relapse (p=0.033). Cancer-infiltrated LVs showed a moderate but non-significant association with relapse (p=0.07). Differential miRNA profiles were identified in cancer-infiltrated LVs and those with high versus low inflammation. In particular, several members of the let-7 family were consistently down-regulated in highly inflamed LVs (>1.8-fold, p<0.05) compared to the less inflamed ones. Down-regulation of the let-7 family appears to be associated with inflammation, but whether inflammation contributes to or is an effect of cancer-infiltration requires further investigation.

cancer biology↗

bioRxiv2020

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

Advances in technology have allowed for the study of metabolomics in the context of disease, enabling the discovery of new potential risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular biomedical importance as it is in direct contact with the brain and spinal cord. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid compared to blood or urine studies. Here, we present a metabolome-wide association study (MWAS), an analysis using individual-level genetic and metabolomic data from two cohorts to impute metabolites into large samples with genome-wide association summary statistics. We conducted a metabolome-wide genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations, 6 of which were novel. Using these results, we then built prediction models for all available CSF metabolites and tested for associations with 27 neurological and psychiatric phenotypes in large cohorts, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the potential of MWAS to overcome the logistic challenges inherent in cerebrospinal fluid research to study the role of metabolomics in brain-related phenotypes and the feasibility of this framework for similar studies of omic data in scarce sample types.

genomics↗

bioRxiv2019

Harmonization of large multi-site imaging datasets: Application to 10,232 MRIs for the analysis of imaging patterns of structural brain change throughout the lifespan

As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,232 structural brain MRI scans from participants without known neuropsychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive normative age trends of brain structure through the lifespan (3 to 96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this normative reference of brain development and aging, and to examine deviations from normative ranges, potentially related to disease.

bioinformatics↗

bioRxiv2019

Amyloid duration is associated with preclinical cognitive decline and tau PET

INTRODUCTIONThis study applies a novel algorithm to longitudinal amyloid positron emission tomography (PET) imaging to identify age-heterogeneous amyloid trajectory groups, estimate the age and duration (chronicity) of amyloid positivity, and investigate chronicity in relation to cognitive decline and tau burden.\n\nMETHODSCognitively unimpaired participants (n=257) underwent 1-4 amyloid PET scans. Group-based trajectory modeling was applied to participants with longitudinal scans (n=171) to identify and model amyloid trajectory groups, which were combined with Bayes theorem to estimate age and chronicity of amyloid positivity. Relationships between chronicity, cognition, clinical progression and tau PET (MK-6240) were investigated using regression models.\n\nRESULTSChronicity explained more heterogeneity in amyloid binding than age and binary amyloid status. Chronicity was associated with faster cognitive decline, increased risk of abnormal cognition, and higher entorhinal tau.\n\nDISCUSSIONAmyloid chronicity provides unique information about cognitive decline and neurofibrillary tangle development and may be useful to investigate preclinical AD.

neuroscience↗

bioRxiv2019

Self-reported health behaviors and longitudinal cognitive performance: Results from the Wisconsin Registry for Alzheimer’s Prevention

BackgroundStudies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimers Prevention (WRAP), an Alzheimers disease risk-enriched cohort who were non-demented and in late midlife at baseline.\n\nMethodWe analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multi-domain cognitive composite, and secondary outcomes were immediate/delayed memory and executive function composites. Predictors of interest were self-reported measures of physical activity, cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) model averaging (MA) approach on a set of models including covariates and combinations of these 2- and 3-way interactions. The IT approach was selected due to the large number of interactions of interest and to avoid pitfalls of traditional model selection approaches.\n\nResultsModel-averaged results identified no significant modifiable behavior*age interactions in relationship to the primary composite outcome. In secondary outcomes, higher MIND diet scores associated with slower decline in executive function. Men showed faster decline than women on delayed memory, independent of health behaviors. There were no other significant interactions among any other health behaviors and cognitive trajectories.\n\nConclusionsWhen multiple covariates and health behaviors were considered simultaneously, there were limited weak associations with cognitive decline in this age range. These results may be explained alone or in combination by three alternative explanations: 1) the range of cognitive decline is in middle age is too small to observe relationships with health behaviors, 2) the putative associations of these health behaviors on cognition may not be robust in this age range, or 3) the self-reported measures of the health behaviors may not be optimal for predicting cognitive decline. More study may be needed that incorporates sensitive measures of health behaviors, AD biomarker profiles, and/or other disease comorbidities.

neuroscience↗

bioRxiv2018

Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimers disease (AD; N=61,212). Among 1,738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Further, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

genetics↗

bioRxiv2018

Longitudinal plasma metabolomics of aging and sex

Understanding how metabolites are longitudinally influenced by age and sex could facilitate the identification of metabolomic profiles and trajectories that indicate disease risk. We investigated the metabolomics of age and sex using longitudinal plasma samples from the Wisconsin Registry for Alzheimers Prevention (WRAP), a cohort of participants who were dementia free at enrollment. Metabolomic profiles were quantified for 2,316 fasting plasma samples among 1,187 participants, each with up to three study visits. Of 1,097 metabolites tested, 608 (55.4%) were associated with age and 680 (62.0%) with sex after correcting for multiple testing. Approximately twice as many metabolites were associated with age in stratified analyses of women versus men, and 63 metabolite trajectories significantly differed by sex, most notably including sphingolipids, which tended to increase in women and decrease in men with age. Using genome-wide genotyping, we also report the heritabilities of metabolites investigated, which ranged dramatically (0.2-99.2%); however, the median heritability of 36.2% suggests that many metabolites are highly influenced by a complex combination of genomic and environmental influences. These findings offer a more profound description of the aging process and may inform many new hypotheses regarding the role metabolites play in healthy and accelerated aging.

molecular biology↗

bioRxiv2018

Metabolites associated with early cognitive changes implicated in Alzheimer’s disease

We investigated the metabolomics of early cognitive changes related to Alzheimers disease (AD) in order to better understand mechanisms that could contribute to early stages and progression of this disease. This investigation used longitudinal plasma samples from the Wisconsin Registry for Alzheimers Prevention (WRAP), a cohort of participants who were dementia free at enrollment and enriched with a parental history of AD. Metabolomic profiles were quantified for 2,338 fasting plasma samples among 1,206 participants, each with up to three study visits. Of 1,097 metabolites tested, levels of seven were associated with executive function trajectories, including an amino acid and three fatty acids, but none were associated with delayed recall trajectories. Our time-varying metabolomic results suggest potential mechanisms that could contribute to the earliest signs of cognitive decline. In particular, fatty acids may be associated with cognition in a manner that is more complex than previously suspected.

neuroscience↗

bioRxiv2018

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

Although Alzheimers disease (AD) is highly heritable, genetic variants 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 multi-omics 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 Alzheimers 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 fasting 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 CPS1 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.

genomics↗

bioRxiv2018

In vivo characterization and quantification of neurofibrillary tau PET radioligand [18F]MK-6240 in humans from Alzheimer’s disease dementia to young controls

Tau positron emission tomography (PET) imaging has potential for elucidating changes in the deposition of neuropathological tau aggregates that are occurring during the progression of Alzheimers disease (AD). This work investigates in vivo kinetics, quantification strategies and imaging characteristics of a novel tau PET radioligand [18F]MK-6240 in humans.\n\nMethodsFifty-one individuals ranging from cognitively normal young controls to persons with dementia underwent T1-weighted magnetic resonance imaging (MRI), and [11C]PiB and [18F]MK-6240 PET imaging. PET data were coregistered to the MRI and time-activity curves were extracted from regions of interest to assess [18F]MK-6240 kinetics. The pons and inferior cerebellum were investigated as potential reference regions. Reference tissue methods (Logan graphical analysis (LGA) and multilinear reference tissue method (MRTM2)) were investigated for quantification of [18F]MK-6240 distribution volume ratios (DVRs) in a subset of nineteen participants. Stability of DVR methods was evaluated using truncated scan durations. Standard uptake value ratio (SUVR) estimates were compared to DVR estimates to determine the optimal timing window for SUVR analysis. Parametric SUVR images were used to identify regions of potential off-target binding and to compare binding patterns with neurofibrillary tau staging established in neuropathology literature.\n\nResultsStandard uptake values in the pons and the inferior cerebellum indicated consistent clearance across all 51 subjects. LGA and MRTM2 DVR estimates were similar, with LGA slightly underestimating DVR compared to MRTM2. DVR estimates remained stable when truncating the scan duration to 60 minutes. SUVR determined 70-90 minutes post-injection of [18F]MK-6240 indicated linearity near unity when compared to DVR estimates and minimized potential spill-in from uptake outside of the brain. [18F]MK-6240 binding patterns in target regions were consistent with neuropathological neurofibrillary tau staging. Off-target binding regions included the ethmoid sinus, clivus, meninges, substantia nigra, but not the basal ganglia or choroid plexus.\n\nConclusions[18F]MK-6240 is a promising PET radioligand for in vivo imaging of neurofibrillary tau aggregates in AD with minimal off-target binding in the human brain.

neuroscience↗

bioRxiv2017

Characterizing the effects of sex, APOE 4, 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

In this paper we apply Information-Theoretic (IT) model averaging to characterize a set of complex interactions in a longitudinal study on cognitive decline. Prior research has identified numerous genetic (including sex), education, health and lifestyle factors that predict abnormal cognitive decline.Traditional model selection approaches (e.g., backward or stepwise selection), attempt to find models that best fit the observed data; these techniques risk interpretations that only the selected predictors are important. In reality, several models may fit similarly well but result in different conclusions (e.g., about size and significance of parameter estimates), and inference from a single model chosen after a selection procedure can lead to overly simplistic conclusions. Here we utilize longitudinal cognitive data from the Wisconsin Registry for Alzheimers Prevention to examine the effects of sex and the Apolipoprotein E (APOE) 4 allele (non-modifiable factors), and reading literacy achievement (modifiable) on cognitive decline. For each outcome, we applied IT model averaging to a model set with combinations of interactions among sex, APOE, literacy, and age. For a list-learning test, model-averaged results showed better performance for women vs men, with faster decline among men; increased literacy was associated with better performance, particularly among men. APOE had less effect in this age range (~40-70). These results illustrate the utility of the IT approach and point to verbal ability as a potential modifier of decline. Whether the protective effect of literacy is due to educational attainment or intrinsic verbal intellectual ability is the topic of ongoing work.

neuroscience↗

bioRxiv2017

Modifiable risk factors moderate the relationship between amyloid and cognition in midlife

Although evidence suggests a relationship between elevated beta-amyloid and cognitive decline, approximately 30% of older adults with positive markers of amyloid remain cognitively healthy. Our objective was to test if the presence of modifiable risk factors (i.e., central obesity, hypertension, and depressive symptoms) moderated the relationship between amyloid and longitudinal cognitive performance. Data were from 207 adults (140 females; age range=40-70) enriched for Alzheimers disease risk (73% parental history of Alzheimers disease) enrolled in the Wisconsin Registry for Alzheimers Prevention study. Participants completed at least two neuropsychological evaluations and one biomarker visit ([C11] Pittsburgh Compound B PET scan or lumbar puncture). Participants were characterized as high or low on amyloid using cutoffs developed for [C11] Pittsburgh Compound B-PET distribution volume ratio or CSF amyloid beta 1-42 values. Participants were also coded as high or low risk on obesity, hypertension, and depressive symptoms. Linear mixed effects regression models examined three-way interactions between modifiable risk factor status x amyloid group x age at each study visit on longitudinal Verbal Learning & Memory and Speed & Flexibility factor scores. Results indicated that the relationship between beta-amyloid and Verbal Learning & Memory decline was associated with hypertension status (Likelihood ratio test for significance of hypertension status age x amyloid status x visit age interaction term;{chi} 2 (1) = 5.28, p = .02). The relationship between beta-amyloid and Speed & Flexibility decline was associated with depression status (Likelihood ratio test for significance of amyloid status x depression status x visit age interaction term;{chi} 2 (1) = 7.10, p = .03). The presence of obesity did not significantly moderate the relationship between beta-amyloid status and cognitive performance, although the direction of relationship was similar to above relationships (Likelihood ratio test for significance of obesity status x amyloid status x visit age interaction term;{chi} 2 (1) = 1.52, p = .21). In this at-risk for Alzheimers disease cohort, the modifiable risk factors of hypertension and depression significantly moderated the relationship between beta-amyloid and cognitive decline. Identification and modification of these risk factors in late middle age may slow the effect of amyloid on the progression of cognitive symptoms.

neuroscience↗

bioRxiv2017

Longitudinal standards for mid-life cognitive performance: Identifying abnormal within-person changes in the Wisconsin Registry for Alzheimer’s Prevention

A major challenge in the field of cognitive aging is differentiating disease-related cognitive change that has not yet become overt impairment from the more gradual decline in performance expected with normal aging. Published normative reference values are nearly always for single time point performances rather than longitudinal change in performance. To gain insight into how we might tackle the problem of identifying worrisome trajectories, we borrow a method from anthropometry: the development of standards that are conditional on an individuals past measurements. We use quantile regression to create growth-curve-like models of performance on several common neuropsychological tests of memory and executive function while accounting for age, sex, education, estimated verbal ability, and past performance on the test, and then use these to estimate individuals percentile ranks. Choosing the 7th percentile as a threshold (corresponding to approximately 1.5 standard deviations below the expected mean), we then explore relationships between subthreshold performance, clinical outcomes, and subjective impairment. Participants whose performance fell below the 7th percentile were more likely to be given an abnormal research diagnosis at the current visit, but not at later visits. Performance below this threshold was also linked to subjective and informant reports of worsening memory function. We discuss potential uses of this method in theoretical and applied research and clinical settings.

neuroscience↗

bioRxiv2017

The Wisconsin Registry for Alzheimer’s Prevention: A Review of findings and current directions

The Wisconsin Registry for Alzheimers Prevention (WRAP) is a longitudinal observational cohort study enriched with persons with a parental history (PH) of probable Alzheimers Disease (AD) dementia. Since late 2001, WRAP has enrolled 1,561 people at a mean baseline age of 54. Participants return for a second visit four years after baseline and subsequent visits occur every two years. Eighty-one percent (1270) of participants remain active in the study at a current mean age of 64 and 9 years of follow-up. Serially assessed cognition, self-reported medical and lifestyle histories (e.g. diet, physical and cognitive activity, sleep, and mood), laboratory tests, genetics, and linked studies comprising molecular imaging, structural imaging and cerebrospinal fluid data, have yielded many important findings. In this cohort, PH of probable AD is associated with 46% APOE {varepsilon}4 positivity, more than twice the rate of 22% among persons without PH. Subclinical or worse cognitive decline relative to internal normative data has been observed in 17.6% of the cohort. Twenty-eight percent exhibit amyloid and/or tau positivity. Biomarker elevations, but not APOE or PH status, are associated with cognitive decline. Salutary health and lifestyle factors are associated with better cognition and brain structure, and lower AD pathophysiologic burden. Of paramount importance is establishing the amyloid and tau AD endophenotypes to which cognitive outcomes can be linked. Such data will provide new knowledge on the early temporal course of AD pathophysiology and inform the design of secondary prevention clinical trials.

neuroscience↗

bioRxiv2016

Temporal order of Alzheimer’s disease-related cognitive marker changes in BLSA and WRAP longitudinal studies

Investigation of the temporal trajectories of currently used neuropsychological tests is critical to identifying earliest changing measures on the path to dementia due to Alzheimers disease (AD). We used the Progression Score (PS) method to characterize the temporal trajectories of measures of verbal memory, executive function, attention, processing speed, language, and mental state using data spanning normal cognition, mild cognitive impairment (MCI), and AD from 1661 participants with a total of 7839 visits (age at last visit 77.6 SD 9.2) in the Baltimore Longitudinal Study of Aging and 1542 participants with a total of 4467 visits (age at last visit 59.9 SD 7.3) in the Wisconsin Registry for Alzheimers Prevention. This method aligns individuals in time based on the similarity of their longitudinal measurements to reveal temporal trajectories. As a validation of our methodology, we explored the associations between the individualized cognitive progression scores (Cog-PS) computed by our method and clinical diagnosis. Digit span tests were the first to show declines in both data sets, and were detected mainly among cognitively normal individuals. These were followed by tests of verbal memory, which were in turn followed by Trail Making Tests, Boston Naming Test, and Mini-Mental State Examination. Differences in Cog-PS across the clinical diagnosis groups were statistically significant, highlighting the potential use of Cog-PS as individualized indicators of disease progression. Identifying cognitive measures that are changing in preclinical AD can lead to the development of novel cognitive tests that are finely tuned to detecting earliest changes.\n\nABBREVIATIONS

neuroscience↗