Browsing by Author "Bekris, Lynn M."

Now showing 1 - 6 of 6
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    Association of cerebrospinal fluid Aβ42 with A2M gene in cognitively normal subjects
    (Elsevier, 2014-02) Millard, Steven P.; Lutz, Franziska; Li, Ge; Galasko, Douglas R.; Farlow, Martin R.; Quinn, Joseph F.; Kaye, Jeffrey A.; Leverenz, James B.; Tsuang, Debby; Yu, Chang-En; Peskind, Elaine R.; Bekris, Lynn M.; Department of Neurology, IU School of Medicine
    Low cerebrospinal fluid (CSF) Aβ42 levels correlate with increased brain Aβ deposition in Alzheimer’s disease (AD), which suggests a disruption in the degradation and clearance of Aβ from the brain. In addition, APOE ε4 carriers have lower CSF Aβ42 levels than non-carriers. The hypothesis of this investigation was that CSF Aβ42 levels correlate with regulatory region variation in genes that are biologically associated with degradation or clearance of Aβ from the brain. CSF Aβ42 levels were tested for associations with Aβ degradation and clearance genes and APOE ε4. Twenty-four SNPs located within the 5′ and 3′ regions of 12 genes were analyzed. The study sample consisted of 99 AD patients and 168 cognitively normal control subjects. CSF Aβ42 levels were associated with APOE ε4 status in controls but not in AD patients
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    Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture
    (Springer Nature, 2021-03) Chia, Ruth; Sabir, Marya S.; Bandres-Ciga, Sara; Saez-Atienzar, Sara; Reynolds, Regina H.; Gustavsson, Emil; Walton, Ronald L.; Ahmed, Sarah; Viollet, Coralie; Ding, Jinhui; Makarious, Mary B.; Diez-Fairen, Monica; Portley, Makayla K.; Shah, Zalak; Abramzon, Yevgeniya; Hernandez, Dena G.; Blauwendraat, Cornelis; Stone, David J.; Eicher, John; Parkkinen, Laura; Ansorge, Olaf; Clark, Lorraine; Honig, Lawrence S.; Marder, Karen; Lemstra, Afina; St. George-Hyslop, Peter; Londos, Elisabet; Morgan, Kevin; Lashley, Tammaryn; Warner, Thomas T.; Jaunmuktane, Zane; Galasko, Douglas; Santana, Isabel; Tienari, Pentti J.; Myllykangas, Liisa; Oinas, Minna; Cairns, Nigel J.; Morris, John C.; Halliday, Glenda M.; Van Deerlin, Vivianna M.; Trojanowski, John Q.; Grassano, Maurizio; Calvo, Andrea; Mora, Gabriele; Canosa, Antonio; Floris, Gianluca; Bohannan, Ryan C.; Brett, Francesca; Gan-Or, Ziv; Geiger, Joshua T.; Moore, Anni; May, Patrick; Krüger, Rejko; Goldstein, David S.; Lopez, Grisel; Tayebi, Nahid; Sidransky, Ellen; Norcliffe-Kaufmann, Lucy; Palma, Jose-Alberto; Kaufmann, Horacio; Shakkottai, Vikram G.; Perkins, Matthew; Newell, Kathy L.; Gasser, Thomas; Schulte, Claudia; Landi, Francesco; Salvi, Erika; Cusi, Daniele; Masliah, Eliezer; Kim, Ronald C.; Caraway, Chad A.; Monuki, Edwin S.; Brunetti, Maura; Dawson, Ted M.; Rosenthal, Liana S.; Albert, Marilyn S.; Pletnikova, Olga; Troncoso, Juan C.; Flanagan, Margaret E.; Mao, Qinwen; Bigio, Eileen H.; Rodríguez-Rodríguez, Eloy; Infante, Jon; Lage, Carmen; González-Aramburu, Isabel; Sanchez-Juan, Pascual; Ghetti, Bernardino; Keith, Julia; Black, Sandra E.; Masellis, Mario; Rogaeva, Ekaterina; Duyckaerts, Charles; Brice, Alexis; Lesage, Suzanne; Xiromerisiou, Georgia; Barrett, Matthew J.; Tilley, Bension S.; Gentleman, Steve; Logroscino, Giancarlo; Serrano, Geidy E.; Beach, Thomas G.; McKeith, Ian G.; Thomas, Alan J.; Attems, Johannes; Morris, Christopher M.; Palmer, Laura; Love, Seth; Troakes, Claire; Al-Sarraj, Safa; Hodges, Angela K.; Aarsland, Dag; Klein, Gregory; Kaiser, Scott M.; Woltjer, Randy; Pastor, Pau; Bekris, Lynn M.; Leverenz, James B.; Besser, Lilah M.; Kuzma, Amanda; Renton, Alan E.; Goate, Alison; Bennett, David A.; Scherzer, Clemens R.; Morris, Huw R.; Ferrari, Raffaele; Albani, Diego; Pickering-Brown, Stuart; Faber, Kelley; Kukull, Walter A.; Morenas-Rodriguez, Estrella; Lleó, Alberto; Fortea, Juan; Alcolea, Daniel; Clarimon, Jordi; Nalls, Mike A.; Ferrucci, Luigi; Resnick, Susan M.; Tanaka, Toshiko; Foroud, Tatiana M.; Graff-Radford, Neill R.; Wszolek, Zbigniew K.; Ferman, Tanis; Boeve, Bradley F.; Hardy, John A.; Topol, Eric J.; Torkamani, Ali; Singleton, Andrew B.; Ryten, Mina; Dickson, Dennis W.; Chiò, Adriano; Ross, Owen A.; Gibbs, J. Raphael; Dalgard, Clifton L.; Traynor, Bryan J.; Scholz, Sonja W.; Pathology and Laboratory Medicine, School of Medicine
    The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.
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    Inflammatory pathway analytes predicting rapid cognitive decline in MCI stage of Alzheimer’s disease
    (Wiley, 2020-07-07) Pillai, Jagan A.; Bena, James; Bebek, Gurkan; Bekris, Lynn M.; Bonner‐Jackson, Aaron; Kou, Lei; Pai, Akshay; Sørensen, Lauge; Neilsen, Mads; Rao, Stephen M.; Chance, Mark; Lamb, Bruce T.; Leverenz, James B.; Psychiatry, School of Medicine
    Objective To determine the inflammatory analytes that predict clinical progression and evaluate their performance against biomarkers of neurodegeneration. Methods A longitudinal study of MCI‐AD patients in a Discovery cohort over 15 months, with replication in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) MCI cohort over 36 months. Fifty‐three inflammatory analytes were measured in the CSF and plasma with a RBM multiplex analyte platform. Inflammatory analytes that predict clinical progression on Clinical Dementia Rating Scale‐Sum of Boxes (CDR‐SB) and Mini Mental State Exam scores were assessed in multivariate regression models. To provide context, key analyte results in ADNI were compared against biomarkers of neurodegeneration, hippocampal volume, and CSF neurofilament light (NfL), in receiver operating characteristic (ROC) analyses evaluating highest quartile of CDR‐SB change over two years (≥3 points). Results Cerebrospinal fluid inflammatory analytes in relation to cognitive decline were best described by gene ontology terms, natural killer cell chemotaxis, and endothelial cell apoptotic process and in plasma, extracellular matrix organization, blood coagulation, and fibrin clot formation described the analytes. CSF CCL2 was most robust in predicting rate of cognitive change and analytes that correlated to CCL2 suggest IL‐10 pathway dysregulation. The ROC curves for ≥3 points change in CDR‐SB over 2 years when comparing baseline hippocampal volume, CSF NfL, and CCL2 were not significantly different. Interpretation Baseline levels of immune cell chemotactic cytokine CCL2 in the CSF and IL‐10 pathway dysregulation impact longitudinal cognitive and functional decline in MCI‐AD. CCL2’s utility appears comparable to biomarkers of neurodegeneration in predicting rapid decline.
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    Key inflammatory pathway activations in the MCI stage of Alzheimer's disease
    (Wiley, 2019-07) Pillai, Jagan A.; Maxwell, Sean; Bena, James; Bekris, Lynn M.; Rao, Stephen M.; Chance, Mark; Lamb, Bruce T.; Leverenz, James B.; Neurology, School of Medicine
    OBJECTIVE: To determine the key inflammatory pathways that are activated in the peripheral and CNS compartments at the mild cognitive impairment (MCI) stage of Alzheimer's disease (AD). METHODS: A cross-sectional study of patients with clinical and biomarker characteristics consistent with MCI-AD in a discovery cohort, with replication in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Inflammatory analytes were measured in the CSF and plasma with the same validated multiplex analyte platform in both cohorts and correlated with AD biomarkers (CSF Aβ42, total tau (t-tau), phosphorylated tau (p-tau) to identify key inflammatory pathway activations. The pathways were additionally validated by evaluating genes related to all analytes in coexpression networks of brain tissue transcriptome from an autopsy confirmed AD cohort to interrogate if the same pathway activations were conserved in the brain tissue gene modules. RESULTS: Analytes of the tumor necrosis factor (TNF) signaling pathway (KEGG ID:4668) in the CSF and plasma best correlated with CSF t-tau and p-tau levels, and analytes of the complement and coagulation pathway (KEGG ID:4610) best correlated with CSF Aβ42 levels. The top inflammatory signaling pathways of significance were conserved in the peripheral and the CNS compartments. They were also confirmed to be enriched in AD brain transcriptome gene clusters. INTERPRETATION: A cell-protective rather than a proinflammatory analyte profile predominates in the CSF in relation to neurodegeneration markers among MCI-AD patients. Analytes from the TNF signaling and the complement and coagulation pathways are relevant in evaluating disease severity at the MCI stage of AD.
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    Key inflammatory pathway activations in the MCI stage of Alzheimer’s disease
    (Wiley, 2019-07-04) Pillai, Jagan A.; Maxwell, Sean; Bena, James; Bekris, Lynn M.; Rao, Stephen M.; Chance, Mark; Lamb, Bruce T.; Leverenz, James B.; Neurology, School of Medicine
    Objective To determine the key inflammatory pathways that are activated in the peripheral and CNS compartments at the mild cognitive impairment (MCI) stage of Alzheimer’s disease (AD). Methods A cross-sectional study of patients with clinical and biomarker characteristics consistent with MCI-AD in a discovery cohort, with replication in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Inflammatory analytes were measured in the CSF and plasma with the same validated multiplex analyte platform in both cohorts and correlated with AD biomarkers (CSF Aβ42, total tau (t-tau), phosphorylated tau (p-tau) to identify key inflammatory pathway activations. The pathways were additionally validated by evaluating genes related to all analytes in coexpression networks of brain tissue transcriptome from an autopsy confirmed AD cohort to interrogate if the same pathway activations were conserved in the brain tissue gene modules. Results Analytes of the tumor necrosis factor (TNF) signaling pathway (KEGG ID:4668) in the CSF and plasma best correlated with CSF t-tau and p-tau levels, and analytes of the complement and coagulation pathway (KEGG ID:4610) best correlated with CSF Aβ42 levels. The top inflammatory signaling pathways of significance were conserved in the peripheral and the CNS compartments. They were also confirmed to be enriched in AD brain transcriptome gene clusters. Interpretation A cell-protective rather than a proinflammatory analyte profile predominates in the CSF in relation to neurodegeneration markers among MCI-AD patients. Analytes from the TNF signaling and the complement and coagulation pathways are relevant in evaluating disease severity at the MCI stage of AD.
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    Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease
    (Cold Spring Harbor Laboratory, 2021) Xu, Jielin; Zhang, Pengyue; Huang, Yin; Zhou, Yadi; Hou, Yuan; Bekris, Lynn M.; Lathia, Justin; Chiang, Chien-Wei; Li, Lang; Pieper, Andrew A.; Leverenz, James B.; Cummings, Jeffrey; Cheng, Feixiong; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network-based methodology that leverages single-cell/nucleus RNA sequencing data from both transgenic mouse models and AD patient brains, as well as drug-target network, metabolite-enzyme associations, the human protein-protein interactome, and large-scale longitudinal patient data. Through this approach, we find both common and unique gene network regulators between DAM (i.e., PAK1, MAPK14, and CSF1R) and DAA (i.e., NFKB1, FOS, and JUN) that are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., BIN1). We identify shared immune pathways between DAM and DAA, including Th17 cell differentiation and chemokine signaling. Last, integrative metabolite-enzyme network analyses suggest that fatty acids and amino acids may trigger molecular alterations in DAM and DAA. Combining network-based prediction and retrospective case-control observations with 7.2 million individuals, we identify that usage of fluticasone (an approved glucocorticoid receptor agonist) is significantly associated with a reduced incidence of AD (hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.83-0.89, P < 1.0 × 10-8). Propensity score-stratified cohort studies reveal that usage of mometasone (a stronger glucocorticoid receptor agonist) is significantly associated with a decreased risk of AD (HR = 0.74, 95% CI 0.68-0.81, P < 1.0 × 10-8) compared to fluticasone after adjusting age, gender, and disease comorbidities. In summary, we present a network-based, multimodal methodology for single-cell/nucleus genomics-informed drug discovery and have identified fluticasone and mometasone as potential treatments in AD.