Publications by authors named "Thomas Wingo"

Introduction: Early-onset Alzheimer's disease (EOAD) manifests prior to the age of 65, and affects 4%-8% of patients with Alzheimer's disease (AD). The current analyses sought to examine longitudinal cognitive trajectories of participants with early-onset dementia.

Methods: Data from 307 cognitively normal (CN) volunteer participants and those with amyloid-positive EOAD or amyloid-negative cognitive impairment (EOnonAD) were compared.

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Introduction: Early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) share similar amyloid etiology, but evidence from smaller-scale studies suggests that they manifest differently clinically. Current analyses sought to contrast the cognitive profiles of EOAD and LOAD.

Methods: Z-score cognitive-domain composites for 311 amyloid-positive sporadic EOAD and 314 amyloid-positive LOAD participants were calculated from baseline data from age-appropriate control cohorts.

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MicroRNAs (miRNAs) play a crucial role in regulating gene expression and influence many biological processes. Despite their importance, understanding of how genetic variation affects miRNA expression in the brain and how this relates to brain disorders remains limited. Here we investigated these questions by identifying microRNA expression quantitative trait loci (miR-QTLs), or genetic variants associated with brain miRNA levels, using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex samples of 604 older adult donors of European ancestry.

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Introduction: Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non-Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups.

Methods: Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis.

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The gene signatures of Alzheimer's Disease (AD) brains reflect an output of a complex interplay of genetic, epigenetic, epi-transcriptomic, and post-transcriptional regulations. To identify the most significant factor that shapes the AD brain signature, we developed a machine learning model (DEcode-tree) to integrate cellular and molecular factors explaining differential gene expression in AD. Our model indicates that YTHDF proteins, the canonical readers of N6-methyladenosine RNA modification (m6A), are the most influential predictors of the AD brain signature.

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microRNAs (miRNAs) have a broad influence on gene expression; however, we have limited insights into their contribution to rate of cognitive decline over time or Alzheimer's disease (AD). Given this, we tested associations of 528 miRNAs with cognitive trajectory, AD hallmark pathologies, and AD clinical diagnosis using small RNA sequencing from the dorsolateral prefrontal cortex of 641 community-based donors. We found 311 miRNAs differentially expressed in AD or its endophenotypes after adjusting for technical and sociodemographic variables.

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Background: Genetics has the potential to inform biologically relevant drug treatment and repurposing which may ultimately improve patient care. In this study, we combine methods which leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds.

Methods: We used the largest available genome-wide association studies, in European ancestry, of four psychiatric disorders [i.

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MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%.

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Family-based heritability estimates of complex traits are often considerably larger than their single-nucleotide polymorphism (SNP) heritability estimates. This discrepancy may be due to non-additive effects of genetic variation, including variation that interacts with other genes or environmental factors to influence the trait. Variance-based procedures provide a computationally efficient strategy to screen for SNPs with potential interaction effects without requiring the specification of the interacting variable.

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Introduction: Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD.

Methods: To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors.

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Advances have led to a greater understanding of the genetics of Alzheimer's Disease (AD). However, the gap between the predicted and observed genetic heritability estimates when using single nucleotide polymorphisms (SNPs) and small indel data remains. Large genomic rearrangements, known as structural variants (SVs), have the potential to account for this missing genetic heritability.

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Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia.

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Objective: Alzheimer's disease (AD) is believed to be more common in African Americans (AA), but biomarker studies in AA populations are limited. This report represents the largest study to date examining cerebrospinal fluid AD biomarkers in AA individuals.

Methods: We analyzed 3,006 cerebrospinal fluid samples from controls, AD cases, and non-AD cases, including 495 (16.

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Alzheimer's disease (AD) is currently defined by the aggregation of amyloid-β (Aβ) and tau proteins in the brain. Although biofluid biomarkers are available to measure Aβ and tau pathology, few markers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here, we characterized the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals using two different proteomic technologies-tandem mass tag mass spectrometry and SomaScan.

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Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences.

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Article Synopsis
  • Neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD) are different behaviors related to emotions, thinking, and social interactions that can happen just as often as memory problems.
  • Most research on AD has focused more on memory loss rather than these behaviors, which makes studying them tricky.
  • The article suggests that understanding these symptoms better could help improve ways to diagnose and treat Alzheimer's disease, making it more personalized for each person.
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Background: Polygenic risk scores (PRS) are linear combinations of genetic markers weighted by effect size that are commonly used to predict disease risk. For complex heritable diseases such as late-onset Alzheimer's disease (LOAD), PRS models fail to capture much of the heritability. Additionally, PRS models are highly dependent on the population structure of the data on which effect sizes are assessed and have poor generalizability to new data.

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Article Synopsis
  • Alzheimer's disease (AD) primarily affects diverse populations, but most research has focused on the non-Hispanic White demographic, necessitating a broader understanding across different racial and ethnic groups.
  • This study involved analyzing brain tissues from donors of various racial backgrounds, utilizing mass spectrometry to examine protein levels in key brain regions related to AD, resulting in a large dataset of proteins associated with the disease.
  • The findings highlighted significant protein elevations linked to AD across all groups, emphasizing the importance of ethnoracial-specific differences in protein expression for future research and potential treatments.
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The "missing" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods.

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  • Previous research links living in disadvantaged neighborhoods to poor health, potentially affecting inflammation and immune responses through epigenetic changes like DNA methylation (DNAm).
  • The study utilized robust linear regression models to analyze the association between neighborhood deprivation and DNAm in brain tissue from 159 donors, identifying one significant CpG site (cg26514961) linked to neighborhood deprivation.
  • Notably, the study found that the association was more pronounced in individuals with at least one ε4 allele, with some CpG sites showing agreement between brain tissue and easily accessible tissues, suggesting their potential as biomarkers for studying health effects in living individuals.
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Introduction: Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD.

Methods: To bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors.

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Article Synopsis
  • The study examines the links between air pollution, specifically fine particulate matter, and Alzheimer's disease risk indicators in cognitively healthy adults aged 45-75.
  • Researchers analyzed CSF biomarkers related to Alzheimer’s using data from 1,113 participants, alongside estimated exposure to ambient and traffic-related air pollution over 1, 3, and 5 years.
  • Results indicate that increased exposure to ambient air pollution correlates with lower CSF biomarker levels that may predict Alzheimer’s risk, while traffic-related pollution showed similar patterns but lacked statistical significance.
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Air pollution and neighborhood socioeconomic status (N-SES) are associated with adverse cardiovascular health and neuropsychiatric functioning in older adults. This study examines the degree to which the joint effects of air pollution and N-SES on the cognitive decline are mediated by high cholesterol levels, high blood pressure (HBP), and depression. In the Emory Healthy Aging Study, 14,390 participants aged 50+ years from Metro Atlanta, GA, were assessed for subjective cognitive decline using the cognitive function instrument (CFI).

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Background And Objectives: Fine particulate matter (PM) exposure has been found to be associated with Alzheimer disease (AD) and is hypothesized to cause inflammation and oxidative stress in the brain, contributing to neuropathology. The gene, a major genetic risk factor of AD, has been hypothesized to modify the association between PM and AD. However, little prior research exists to support these hypotheses.

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Article Synopsis
  • The study investigates how fine particulate matter (PM) may contribute to Alzheimer's disease (AD) through changes in DNA methylation (DNAm) in the brain, focusing on prefrontal cortex tissue from 159 donors.
  • Researchers identified specific CpG sites (cg25433380 and cg10495669) where DNAm differed significantly due to PM exposure, and they found 24 additional sites mediating the relationship between PM and AD-related neuropathological markers.
  • The findings highlight the role of neuroinflammation-related DNAm changes in linking traffic-related PM to Alzheimer's disease, marking this as a pioneering study in understanding how air pollution impacts brain health.
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