IU Indianapolis ScholarWorks :: Browsing by Author "Leverenz, James B."

Browsing by Author "Leverenz, James B."

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Artificial intelligence framework identifies candidate targets for drug repurposing in Alzheimer’s disease
(BMC, 2022-01-10) Fang, Jiansong; Zhang, Pengyue; Wang, Quan; Chiang, Chien‑Wei; Zhou, Yadi; Hou, Yuan; Xu, Jielin; Chen, Rui; Zhang, Bin; Lewis, Stephen J.; Leverenz, James B.; Pieper, Andrew A.; Li, Bingshan; Li, Lang; Cummings, Jeffrey; Cheng, Feixiong; Biostatistics and Health Data Science, School of Medicine
Background: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer's disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein-protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, multi-omics data from brain samples of AD patients and AD transgenic animal models, drug-target networks, and the human protein-protein interactome, along with large-scale patient database validation and in vitro mechanistic observations in human microglia cells. Results: Through this approach, we identified 103 ARGs validated by various levels of pathobiological evidence in AD. Via network-based prediction and population-based validation, we then showed that three drugs (pioglitazone, febuxostat, and atenolol) are significantly associated with decreased risk of AD compared with matched control populations. Pioglitazone usage is significantly associated with decreased risk of AD (hazard ratio (HR) = 0.916, 95% confidence interval [CI] 0.861-0.974, P = 0.005) in a retrospective case-control validation. Pioglitazone is a peroxisome proliferator-activated receptor (PPAR) agonist used to treat type 2 diabetes, and propensity score matching cohort studies confirmed its association with reduced risk of AD in comparison to glipizide (HR = 0.921, 95% CI 0.862-0.984, P = 0.0159), an insulin secretagogue that is also used to treat type 2 diabetes. In vitro experiments showed that pioglitazone downregulated glycogen synthase kinase 3 beta (GSK3β) and cyclin-dependent kinase (CDK5) in human microglia cells, supporting a possible mechanism-of-action for its beneficial effect in AD. Conclusions: In summary, we present an integrated, network-based artificial intelligence methodology to rapidly translate GWAS findings and multi-omics data to genotype-informed therapeutic discovery in AD.
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
Florbetaben PET imaging to detect amyloid beta plaques in Alzheimer disease: Phase 3 study
(Elsevier, 2015) Sabri, Osama; Sabbagh, Marwan N.; Seibyl, John; Barthel, Henryk; Akatsu, Hiroyasu; Ouchi, Yasuomi; Senda, Kohei; Murayama, Shigeo; Ishii, Kenji; Takao, Masaki; Beach, Thomas G.; Rowe, Christopher C.; Leverenz, James B.; Ghetti, Bernardino; Ironside, James W.; Catafau, Ana M.; Stephens, Andrew W.; Mueller, Andre; Koglin, Norman; Hoffman, Anja; Roth, Katrin; Reininger, Cornelia; Schulz-Schaeffer, Walter J.; Department of Pathology and Laboratory Medicine, IU School of Medicine
Background Evaluation of brain β-amyloid by positron emission tomography (PET) imaging can assist in the diagnosis of Alzheimer disease (AD) and other dementias. Methods Open-label, nonrandomized, multicenter, phase 3 study to validate the 18F-labeled β-amyloid tracer florbetaben by comparing in vivo PET imaging with post-mortem histopathology. Results Brain images and tissue from 74 deceased subjects (of 216 trial participants) were analyzed. Forty-six of 47 neuritic β-amyloid-positive cases were read as PET positive, and 24 of 27 neuritic β-amyloid plaque-negative cases were read as PET negative (sensitivity 97.9% [95% confidence interval or CI 93.8–100%], specificity 88.9% [95% CI 77.0–100%]). In a subgroup, a regional tissue-scan matched analysis was performed. In areas known to strongly accumulate β-amyloid plaques, sensitivity and specificity were 82% to 90%, and 86% to 95%, respectively. Conclusions Florbetaben PET shows high sensitivity and specificity for the detection of histopathology-confirmed neuritic β-amyloid plaques and may thus be a valuable adjunct to clinical diagnosis, particularly for the exclusion of AD.
Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing
(Springer Nature, 2019-03) Kunkle, Brian W.; Grenier-Boley, Benjamin; Sims, Rebecca; Bis, Joshua C.; Damotte, Vincent; Naj, Adam C.; Boland, Anne; Vronskaya, Maria; van der Lee, Sven J.; Amlie-Wolf, Alexandre; Bellenguez, Céline; Frizatti, Aura; Chouraki, Vincent; Martin, Eden R.; Sleegers, Kristel; Badarinarayan, Nandini; Jakobsdottir, Johanna; Hamilton-Nelson, Kara L.; Moreno-Grau, Sonia; Olaso, Robert; Raybould, Rachel; Chen, Yuning; Kuzma, Amanda B.; Hiltunen, Mikko; Morgan, Taniesha; Ahmad, Shahzad; Vardarajan, Badri N.; Epelbaum, Jacques; Hoffmann, Per; Boada, Merce; Beecham, Gary W.; Garnier, Jean-Guillaume; Harold, Denise; Fitzpatrick, Annette L.; Valladares, Otto; Moutet, Marie-Laure; Gerrish, Amy; Smith, Albert V.; Qu, Liming; Bacq, Delphine; Denning, Nicola; Jian, Xueqiu; Zhao, Yi; Del Zompo, Maria; Fox, Nick C.; Choi, Seung-Hoan; Mateo, Ignacio; Hughes, Joseph T.; Adams, Hieab H.; Malamon, John; Sanchez-Garcia, Florentino; Patel, Yogen; Brody, Jennifer A.; Dombroski, Beth A.; Deniz Naranjo, Maria Candida; Daniilidou, Makrina; Eiriksdottir, Gudny; Mukherjee, Shubhabrata; Wallon, David; Uphill, James; Aspelund, Thor; Cantwell, Laura B.; Garzia, Fabienne; Galimberti, Daniela; Hofer, Edith; Butkiewicz, Mariusz; Fin, Bertrand; Scarpini, Elio; Sarnowski, Chloe; Bush, Will S.; Meslage, Stéphane; Kornhuber, Johannes; White, Charles C.; Song, Yuenjoo; Barber, Robert C.; Engelborghs, Sebastiaan; Sordon, Sabrina; Voijnovic, Dina; Adams, Perrie M.; Vandenberghe, Rik; Mayhaus, Manuel; Cupples, L. Adrienne; Albert, Marilyn S.; De Deyn, Peter P.; Gu, Wei; Himali, Jayanadra J.; Beekly, Duane; Squassina, Alessio; Hartmann, Annette M.; Orellana, Adelina; Blacker, Deborah; Rodriguez-Rodriguez, Eloy; Lovestone, Simon; Garcia, Melissa E.; Doody, Rachelle S.; Munoz-Fernadez, Carmen; Sussams, Rebecca; Lin, Honghuang; Fairchild, Thomas J.; Benit, Yolanda A.; Holmes, Clive; Karamujić-Čomić, Hata; Frosch, Matthew P.; Thonberg, Hakan; Maier, Wolfgang; Roshchupkin, Gennady; Ghetti, Bernardino; Giedraitis, Vilmantas; Kawalia, Amit; Li, Shuo; Huebinger, Ryan M.; Kilander, Lena; Moebus, Susanne; Hernández, Isabel; Kamboh, M. Ilyas; Brundin, RoseMarie; Turton, James; Yang, Qiong; Katz, Mindy J.; Concari, Letizia; Lord, Jenny; Beiser, Alexa S.; Keene, C. Dirk; Helisalmi, Seppo; Kloszewska, Iwona; Kukull, Walter A.; Koivisto, Anne Maria; Lynch, Aoibhinn; Tarraga, Lluís; Larson, Eric B.; Haapasalo, Annakaisa; Lawlor, Brian; Mosley, Thomas H.; Lipton, Richard B.; Solfrizzi, Vincenzo; Gill, Michael; Longstreth, W. T., Jr.; Montine, Thomas J.; Frisardi, Vincenza; Diez-Fairen, Monica; Rivadeneira, Fernando; Petersen, Ronald C.; Deramecourt, Vincent; Alvarez, Ignacio; Salani, Francesca; Ciaramella, Antonio; Boerwinkle, Eric; Reiman, Eric M.; Fievet, Nathalie; Rotter, Jerome I.; Reisch, Joan S.; Hanon, Olivier; Cupidi, Chiara; Uitterlinden, A. G. Andre; Royall, Donald R.; Dufouil, Carole; Maletta, Raffaele Giovanni; de Rojas, Itziar; Sano, Mary; Brice, Alexis; Cecchetti, Roberta; St. George-Hyslop, Peter; Ritchie, Karen; Tsolaki, Magda; Tsuang, Debby W.; Dubois, Bruno; Craig, David; Wu, Chuang-Kuo; Soininen, Hilkka; Avramidou, Despoina; Albin, Roger L.; Fratiglioni, Laura; Germanou, Antonia; Apostolova, Liana G.; Keller, Lina; Koutroumani, Maria; Arnold, Steven E.; Panza, Francesco; Gkatzima, Olymbia; Asthana, Sanjay; Hannequin, Didier; Whitehead, Patrice; Atwood, Craig S.; Caffarra, Paolo; Hampel, Harald; Quintela, Inés; Carracedo, Ángel; Lannfelt, Lars; Rubinsztein, David C.; Barnes, Lisa L.; Pasquier, Florence; Frölich, Lutz; Barral, Sandra; McGuinness, Bernadette; Beach, Thomas G .; Johnston, Janet A.; Becker, James T.; Passmore, Peter; Bigio, Eileen H.; Schott, Jonathan M.; Bird, Thomas D.; Warren, Jason D.; Boeve, Bradley F.; Lupton, Michelle K.; Bowen, James D.; Proitsi, Petra; Boxer, Adam; Powell, John F.; Burke, James R.; Kauwe, John S.K.; Burns, Jeffrey M.; Mancuso, Michelangelo; Buxbaum, Joseph D.; Bonuccelli, Ubaldo; Cairns, Nigel J.; McQuillin, Andrew; Cao, Chuanhai; Livingston, Gill; Carlson, Chris S.; Bass, Nicholas J.; Carlsson, Cynthia M.; Hardy, John; Carney, Regina M.; Bras, Jose; Carrasquillo, Minerva M.; Guerreiro, Rita; Allen, Mariet; Chui, Helena C.; Fisher, Elizabeth; Masullo, Carlo; Crocco, Elizabeth A.; DeCarli, Charles; Bisceglio, Gina; Dick, Malcolm; Ma, Li; Duara, Ranjan; Graff-Radford, Neill R.; Evans, Denis A.; Hodges, Angela; Faber, Kelley M.; Scherer, Martin; Fallon, Kenneth B.; Riemenschneider, Matthias; Fardo, David W.; Heun, Reinhard; Farlow, Martin R.; Kölsch, Heike; Ferris, Steven; Leber, Markus; Foroud, Tatiana M.; Heuser, Isabella; Galasko, Douglas R.; Giegling, Ina; Gearing, Marla; Hüll, Michael; Geschwind, Daniel H.; Gilbert, John R.; Morris, John; Green, Robert C.; Mayo, Kevin; Growdon, John H.; Feulner, Thomas; Hamilton, Ronald L.; Harrell, Lindy E.; Drichel, Dmitriy; Honig, Lawrence S.; Cushion, Thomas D.; Huentelman, Matthew J.; Hollingworth, Paul; Hulette, Christine M.; Hyman, Bradley T.; Marshall, Rachel; Jarvik, Gail P.; Meggy, Alun; Abner, Erin; Menzies, Georgina E.; Jin, Lee-Way; Leonenko, Ganna; Real, Luis M.; Jun, Gyungah R.; Baldwin, Clinton T.; Grozeva, Detelina; Karydas, Anna; Russo, Giancarlo; Kaye, Jeffrey A.; Kim, Ronald; Jessen, Frank; Kowall, Neil W.; Vellas, Bruno; Kramer, Joel H.; Vardy, Emma; LaFerla, Frank M.; Jöckel, Karl-Heinz; Lah, James J.; Dichgans, Martin; Leverenz, James B.; Mann, David; Levey, Allan I.; Pickering-Brown, Stuart; Lieberman, Andrew P.; Klopp, Norman; Lunetta, Kathryn L.; Wichmann, H-Erich; Lyketsos, Constantine G.; Morgan, Kevin; Marson, Daniel C.; Brown, Kristelle; Martiniuk, Frank; Medway, Christopher; Mash, Deborah C.; Nöthen, Markus M.; Masliah, Eliezer; Hooper, Nigel M.; McCormick, Wayne C.; Daniele, Antonio; McCurry, Susan M.; Bayer, Anthony; McDavid, Andrew N.; Gallacher, John; McKee, Ann C.; van den Bussche, Hendrik; Mesulam, Marsel; Brayne, Carol; Miller, Bruce L.; Riedel-Heller, Steffi; Miller, Carol A.; Miller, Joshua W.; Al-Chalabi, Ammar; Morris, John C.; Shaw, Christopher E.; Myers, Amanda J.; Wiltfang, Jens; O'Bryant, Sid; Olichney, John M.; Alvarez, Victoria; Parisi, Joseph E.; Singleton, Andrew B.; Paulson, Henry L.; Collinge, John; Perry, William R.; Mead, Simon; Peskind, Elaine; Cribbs, David H.; Rossor, Martin; Pierce, Aimee; Ryan, Natalie S.; Poon, Wayne W.; Nacmias, Benedetta; Potter, Huntington; Sorbi, Sandro; Quinn, Joseph F.; Sacchinelli, Eleonora; Raj, Ashok; Spalletta, Gianfranco; Raskind, Murray; Caltagirone, Carlo; Bossù, Paola; Orfei, Maria Donata; Reisberg, Barry; Clarke, Robert; Reitz, Christiane; Smith, A. David; Ringman, John M.; Warden, Donald; Roberson, Erik D.; Wilcock, Gordon; Rogaeva, Ekaterina; Bruni, Amalia Cecilia; Rosen, Howard J.; Gallo, Maura; Rosenberg, R.N.; Ben-Shlomo, Yoav; Sager, Mark A.; Mecocci, Patrizia; Saykin, Andrew J.; Pastor, Pau; Cuccaro, Michael L.; Vance, Jeffery M.; Schneider, Julie A.; Schneider, Lori S.; Slifer, Susan; Seeley, William W.; Smith, Amanda G.; Sonnen, Joshua A.; Spina, Salvatore; Stern, Robert A.; Swerdlow, Russell H.; Tang, Mitchell; Tanzi, Rudolph E.; Trojanowski, John Q.; Troncoso, Juan C.; Van Deerlin, Vivianna M.; Van Eldik, Linda J.; Vinters, Harry V.; Vonsattel, Jean Paul; Weintraub, Sandra; Welsh-Bohmer, Kathleen A.; Wilhelmsen, Kirk C.; Williamson, Jennifer; Wingo, Thomas S.; Woltjer, Randall L.; Wright, Clinton B.; Yu, Chang-En; Yu, Lei; Saba, Yasaman; Pilotto, Alberto; Bullido, Maria J.; Peters, Oliver; Crane, Paul K.; Bennett, David; Bosco, Paola; Coto, Eliecer; Boccardi, Virginia; De Jager, Phil L.; Lleo, Alberto; Warner, Nick; Lopez, Oscar L.; Ingelsson, Martin; Deloukas, Panagiotis; Cruchaga, Carlos; Graff, Caroline; Gwilliam, Rhian; Fornage, Myriam; Goate, Alison M.; Sanchez-Juan, Pascual; Kehoe, Patrick G.; Amin, Najaf; Ertekin-Taner, Nilifur; Berr, Claudine; Debette, Stéphanie; Love, Seth; Launer, Lenore J.; Younkin, Steven G.; Dartigues, Jean-Francois; Corcoran, Chris; Ikram, M. Arfan; Dickson, Dennis W.; Nicolas, Gael; Campion, Dominique; Tschanz, JoAnn; Schmidt, Helena; Hakonarson, Hakon; Clarimon, Jordi; Munger, Ron; Schmidt, Reinhold; Farrer, Lindsay A.; Van Broeckhoven, Christine; O'Donovan, Michael C.; DeStefano, Anita L.; Jones, Lesley; Haines, Jonathan L.; Deleuze, Jean-Francois; Owen, Michael J.; Gudnason, Vilmundur; Mayeux, Richard; Escott-Price, Valentina; Psaty, Bruce M.; Ramirez, Alfredo; Wang, Li-San; Ruiz, Agustin; van Duijn, Cornelia M.; Holmans, Peter A.; Seshadri, Sudha; Williams, Julie; Amouyel, Phillippe; Schellenberg, Gerard D.; Lambert, Jean-Charles; Pericak-Vance, Margaret A.; Pathology and Laboratory Medicine, School of Medicine
Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.
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.
Impact of Training Method on the Robustness of the Visual Assessment of 18F-Florbetaben PET Scans: Results from a Phase-3 Study
(SNM, 2016-06) Seibyl, John; Catafau, Ana M.; Barthel, Henryk; Ishii, Kenji; Rowe, Christopher C.; Leverenz, James B.; Ghetti, Bernardino; Ironside, James W.; Takao, Masaki; Akatsu, Hiroyasu; Murayama, Shigeo; Bullich, Santiago; Mueller, Andre; Koglin, Norman; Schulz-Schaeffer, Walter J.; Hoffmann, Anja; Sabbagh, Marwan N.; Stephens, Andrew W.; Sabri, Osama; Department of Pathology & Laboratory Medicine, IU School of Medicine
Training for accurate image interpretation is essential for the clinical use of β-amyloid PET imaging, but the role of interpreter training and the accuracy of the algorithm for routine visual assessment of florbetaben PET scans are unclear. The aim of this study was to test the robustness of the visual assessment method for florbetaben scans, comparing efficacy readouts across different interpreters and training methods and against a histopathology standard of truth (SoT). Methods: Analysis was based on data from an international open-label, nonrandomized, multicenter phase-3 study in patients with or without dementia (ClinicalTrials.gov: NCT01020838). Florbetaben scans were assessed visually and quantitatively, and results were compared with amyloid plaque scores. For visual assessment, either in-person training (n = 3 expert interpreters) or an electronic training method (n = 5 naïve interpreters) was used. Brain samples from participants who died during the study were used to determine the histopathologic SoT using Bielschowsky silver staining (BSS) and immunohistochemistry for β-amyloid plaques. Results: Data were available from 82 patients who died and underwent postmortem histopathology. When visual assessment results were compared with BSS + immunohistochemistry as SoT, median sensitivity was 98.2% for the in-person–trained interpreters and 96.4% for the e-trained interpreters, and median specificity was 92.3% and 88.5%, respectively. Median accuracy was 95.1% and 91.5%, respectively. On the basis of BSS only as the SoT, median sensitivity was 98.1% and 96.2%, respectively; median specificity was 80.0% and 76.7%, respectively; and median accuracy was 91.5% and 86.6%, respectively. Interinterpreter agreement (Fleiss κ) was excellent (0.89) for in-person–trained interpreters and very good (0.71) for e-trained interpreters. Median intrainterpreter agreement was 0.9 for both in-person–trained and e-trained interpreters. Visual and quantitative assessments were concordant in 88.9% of scans for in-person–trained interpreters and in 87.7% of scans for e-trained interpreters. Conclusion: Visual assessment of florbetaben images was robust in challenging scans from elderly end-of-life individuals. Sensitivity, specificity, and interinterpreter agreement were high, independent of expertise and training method. Visual assessment was accurate and reliable for detection of plaques using BSS and immunohistochemistry and well correlated with quantitative assessments.
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.
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.
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.
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, School of Medicine
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.

Browsing by Author "Leverenz, James B."

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