Browsing by Author "Allen, Mariet"

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    Blood-based gene and co-expression network levels are associated with AD/MCI diagnosis and cognitive phenotypes
    (Wiley, 2025-01-09) Chen, Xuan; Reddy, Joseph S.; Wang, Xue; Quicksall, Zachary; Nguyen, Thuy; Reyes, Denise A.; Graff-Radford, Jonathan; Jack, Clifford R., Jr.; Lowe, Val J.; Knopman, David S.; Petersen, Ronald C.; Kantarci, Kejal; Nho, Kwangsik; Allen, Mariet; Carrasquillo, Minerva M.; Saykin, Andrew J.; Ertekin-Taner, Nilüfer; Radiology and Imaging Sciences, School of Medicine
    Background: Alzheimer’s disease (AD) patients have decline in cognitive domains including memory, language, visuospatial, and/or executive function and brain pathology including amyloid‐β and tau deposition, neurodegeneration, and frequent vascular co‐pathologies detectable by neuroimaging and/or cerebrospinal fluid biomarkers. However, molecular disease mechanisms are complex and heterogeneous. It is necessary to develop cost‐effective blood‐based biomarkers reflecting brain molecular perturbations in AD. We identified blood‐based gene and co‐expression network level changes associated with AD/mild cognitive impairment (MCI) diagnosis and AD‐related phenotypes. Method: We performed differential gene expression and weighted gene co‐expression network analysis, followed by meta‐analysis, using blood transcriptome data of 391 participants from the Mayo Clinic Study of Aging and 654 participants from the Alzheimer's Disease Neuroimaging Initiative. The neuroimaging phenotypes include microhemorrhages, infarcts, amyloid burden, hippocampal volume, and white matter hyperintensities. The cognitive phenotypes include standardized cognitive subtest scores and composite scores for memory, language, visuospatial, and executive function. Result: Five out of 18 modules(M) are significantly associated with diagnosis or cognition (FDR‐adjusted p<0.05). M1 and M15 both positively associates with memory, M1 positively associated with language and M15 with visuospatial function. M1 and M15 are enriched in differentially expressed genes (DEGs) associated with language and executive function, respectively. M2 negatively associates with logical memory delayed recall scores(LMDR), memory, executive, and language functions and is enriched in DEGs for these phenotypes. M8 negatively associates with memory, language and executive functions and is enriched in DEGs for memory and language. M12 positively associates with LMDR. M1 and M15 are down‐regulated while M2 and M8 are up‐regulated in AD/MCI patients. Cell‐type enrichment analysis showed M2 is enriched in monocytes and neutrophils; M8 in monocytes; M15 in B cells (FDR <0.05). Gene ontology terms enriched in these modules indicated broad consistency with their cell types. Conclusion: We identified five modules significantly associated with AD/MCI or cognitive phenotypes using blood transcriptome data. These findings nominate blood transcriptome changes and their enriched biological processes as potential pathomechanisms in cognitive decline and AD/MCI development. We aim to investigate these blood transcripts as potential biomarkers for AD or AD‐related phenotypes and therapeutic targets through additional replication and experimental validation studies.
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    Discovery of Genes Underlying Cognitive Resilience in Individuals Predisposed to Alzheimer's Disease Risk
    (Wiley, 2025-01-09) Tsai, Wei; McNiff, Caitlin E.; Reddy, Joseph S.; Wang, Xue; Quicksall, Zachary; Nho, Kwangsik; Dunn, Amy R.; Allen, Mariet; Heckman, Michael G.; Ren, Yingxue; Zhao, Na; Kantarci, Kejal; Mielke, Michelle M.; Petersen, Ronald C.; Kaczorowski, Catherine C.; Carrasquillo, Minerva M.; Saykin, Andrew J.; Ertekin-Taner, Nilüfer; Radiology and Imaging Sciences, School of Medicine
    Background: Two main risk factors of Alzheimer’s disease (AD) are aging and APOE‐ε4. However, some individuals remain cognitively normal despite having these risk factors. They are considered “cognitively resilient”. This study aimed to identify molecular factors that confer cognitive resilience in APOE‐ε4 carriers ≥ 80 years of age and may serve as biomarkers. Method: We applied weighted gene co‐expression network analysis (WGCNA) to generate consensus co‐expression networks from blood of participants in two antemortem cohorts, the Mayo Clinic Study of Aging (MCSA, n=105), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=91), using RNA‐sequencing and microarray data, respectively. We associated these networks with resilience (resilient vs non‐resilient), cognitive endophenotypes and hippocampal volume. Preservation between consensus networks from blood and those derived from postmortem brain tissues of AD and control donors from AMP‐AD (n=1174) was evaluated. We validated the human findings in four AD mouse models. Finally, machine learning models were utilized to discriminate cases (AD+mild cognitive impairment (MCI)) from controls in MCSA, ADNI and ANMerge antemortem cohorts. Result: Four consensus networks were significantly correlated with a memory phenotype (logical memory delayed recall=LMDR) and hippocampal volume in both MCSA and ADNI. Among these, blood expression module M3 was most preserved with the brain transcriptome. M3 was enriched with NDUF hub genes that are involved in the mitochondrial respiratory chain. Expression levels of M3 and many blood NDUFs had significant associations with better LMDR and hippocampal volume. In brain, NDUFs were upregulated in controls compared to AD, and their expression levels were associated with better global cognition and decreased AD neuropathology. Many NDUFs were significantly downregulated in the hippocampus or cortex of AD mice compared to wild‐types. Lastly, models that included blood NDUFs improved diagnostic accuracy of AD+MCI compared to models that only included demographic and risk variables (age, sex, APOE‐ε4) in MCSA, ADNI and ANMerge. In MCSA and ADNI, adding NDUFs’ expression to models that included established blood biomarkers (Aβ42/40, ptau181, NFL) further improved diagnostic accuracy. Conclusion: Our results suggest that mitochondrial NDUFs are centrally‐linked peripheral molecular signatures that may be resilience factors against AD and serve as both therapeutic targets and novel diagnostic biomarkers.
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    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.
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    Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's disease related proteins
    (BMC, 2023-01-07) Oatman, Stephanie R.; Reddy, Joseph S.; Quicksall, Zachary; Carrasquillo, Minerva M.; Wang, Xue; Liu, Chia‑Chen; Yamazaki, Yu; Nguyen, Thuy T.; Malphrus, Kimberly; Heckman, Michael; Biswas, Kristi; Nho, Kwangsik; Baker, Matthew; Martens, Yuka A.; Zhao, Na; Kim, Jun Pyo; Risacher, Shannon L.; Rademakers, Rosa; Saykin, Andrew J.; DeTure, Michael; Murray, Melissa E.; Kanekiyo, Takahisa; Alzheimer’s Disease Neuroimaging Initiative; Dickson, Dennis W.; Bu, Guojun; Allen, Mariet; Ertekin‑Taner, Nilüfer; Radiology and Imaging Sciences, School of Medicine
    Background: Alzheimer's disease (AD) is neuropathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The main protein components of these hallmarks include Aβ40, Aβ42, tau, phosphor-tau, and APOE. We hypothesize that genetic variants influence the levels and solubility of these AD-related proteins in the brain; identifying these may provide key insights into disease pathogenesis. Methods: Genome-wide genotypes were collected from 441 AD cases, imputed to the haplotype reference consortium (HRC) panel, and filtered for quality and frequency. Temporal cortex levels of five AD-related proteins from three fractions, buffer-soluble (TBS), detergent-soluble (Triton-X = TX), and insoluble (Formic acid = FA), were available for these same individuals. Variants were tested for association with each quantitative biochemical measure using linear regression, and GSA-SNP2 was used to identify enriched Gene Ontology (GO) terms. Implicated variants and genes were further assessed for association with other relevant variables. Results: We identified genome-wide significant associations at seven novel loci and the APOE locus. Genes and variants at these loci also associate with multiple AD-related measures, regulate gene expression, have cell-type specific enrichment, and roles in brain health and other neuropsychiatric diseases. Pathway analysis identified significant enrichment of shared and distinct biological pathways. Conclusions: Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest that each have unique genetic architecture and biological pathways that influence their specific biochemical states in the brain. Our novel approach of deep brain biochemical endophenotype GWAS has implications for pathophysiology of proteostasis in AD that can guide therapeutic discovery efforts focused on these proteins.
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    Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology
    (Wiley, 2020-08-05) Nho, Kwangsik; Nudelman, Kelly; Allen, Mariet; Hodges, Angela; Kim, Sungeun; Risacher, Shannon L.; Apostolova, Liana G.; Lin, Kuang; Lunnon, Katie; Wang, Xue; Burgess, Jeremy D.; Ertekin-Taner, Nilüfer; Petersen, Ronald C.; Wang, Lisu; Qi, Zhenhao; He, Aiqing; Neuhaus, Isaac; Patel, Vishal; Foroud, Tatiana; Faber, Kelley M.; Lovestone, Simon; Simmons, Andrew; Weiner, Michael W.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of Medicine
    INTRODUCTION: Abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer’s disease (LOAD). METHODS: We performed transcriptome-wide meta-analysis (N=1,440) of blood-based microarray gene expression profiles as well as neuroimaging and CSF endophenotype analysis. RESULTS: We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid-β accumulation, especially in the entorhinal cortex region. cis-eQTL mapping analysis of CREB5 detected five significant associations (p<5x10−8), where rs56388170 (most significant) was also significantly associated with global cortical amyloid-β (Aβ) deposition measured by [18F]Florbetapir PET and CSF Aβ1-42. DISCUSSION: RNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to AD. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity and learning and memory.
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    Gliovascular transcriptional perturbations in Alzheimer's disease reveal molecular mechanisms of blood brain barrier dysfunction
    (Springer Nature, 2024-06-20) İş, Özkan; Wang, Xue; Reddy, Joseph S.; Min, Yuhao; Yilmaz, Elanur; Bhattarai, Prabesh; Patel, Tulsi; Bergman, Jeremiah; Quicksall, Zachary; Heckman, Michael G.; Tutor-New, Frederick Q.; Demirdogen, Birsen Can; White, Launia; Koga, Shunsuke; Krause, Vincent; Inoue, Yasuteru; Kanekiyo, Takahisa; Cosacak, Mehmet Ilyas; Nelson, Nastasia; Lee, Annie J.; Vardarajan, Badri; Mayeux, Richard; Kouri, Naomi; Deniz, Kaancan; Carnwath, Troy; Oatman, Stephanie R.; Lewis-Tuffin, Laura J.; Nguyen, Thuy; Alzheimer’s Disease Neuroimaging Initiative; Carrasquillo, Minerva M.; Graff-Radford, Jonathan; Petersen, Ronald C.; Jack, Clifford R., Jr.; Kantarci, Kejal; Murray, Melissa E.; Nho, Kwangsik; Saykin, Andrew J.; Dickson, Dennis W.; Kizil, Caghan; Allen, Mariet; Ertekin-Taner, Nilüfer; Radiology and Imaging Sciences, School of Medicine
    To uncover molecular changes underlying blood-brain-barrier dysfunction in Alzheimer’s disease, we performed single nucleus RNA sequencing in 24 Alzheimer’s disease and control brains and focused on vascular and astrocyte clusters as main cell types of blood-brain-barrier gliovascular-unit. The majority of the vascular transcriptional changes were in pericytes. Of the vascular molecular targets predicted to interact with astrocytic ligands, SMAD3, upregulated in Alzheimer’s disease pericytes, has the highest number of ligands including VEGFA, downregulated in Alzheimer’s disease astrocytes. We validated these findings with external datasets comprising 4,730 pericyte and 150,664 astrocyte nuclei. Blood SMAD3 levels are associated with Alzheimer’s disease-related neuroimaging outcomes. We determined inverse relationships between pericytic SMAD3 and astrocytic VEGFA in human iPSC and zebrafish models. Here, we detect vast transcriptome changes in Alzheimer’s disease at the gliovascular-unit, prioritize perturbed pericytic SMAD3-astrocytic VEGFA interactions, and validate these in cross-species models to provide a molecular mechanism of blood-brain-barrier disintegrity in Alzheimer’s disease.
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    Preserved transcriptional networks in immune signaling pathways associated with chronic disease identified in Alzheimer’s disease and Parkinson’s disease, cross‐tissue analysis
    (Wiley, 2025-01-03) Strickland, Samantha L.; Tsai, Wei; Chen, Xuan; Cherukuri, Yesesri; Allen, Mariet; Quicksall, Zachary; Wang, Xue; Kantarci, Kejal; Carrasquillo, Minerva M.; Nho, Kwangsik; Saykin, Andrew J.; Petersen, Ronald C.; Reddy, Joseph S.; Ertekin-Taner, Nilüfer; Radiology and Imaging Sciences, School of Medicine
    Background: Systemic inflammation plays a pivotal role in many chronic diseases including Alzheimer’s disease (AD). Assessing the composition of immune pathways in neurodegenerative diseases can contribute to precision medicine. Using publicly available transcriptomic data, we sought to elucidate transcriptional networks pertinent to inflammatory pathways across brain regions and peripheral blood in AD/mild cognitive impairment (MCI) and peripheral blood in Parkinson’s disease (PD). Method: For the AD/MCI vs. control dataset, we analyzed bulk‐RNAseq collected from 6 brain regions of donors from ROSMAP, Mayo Clinic, and Mount Sinai School of Medicine (MSSM) brain banks available from the AMP‐AD consortium. Ante‐mortem, blood RNAseq expression data was retrieved from the AMP‐AD Emory Vascular cohort and Mayo Clinic Study of Aging (MCSA). We also collected blood‐derived microarray expression data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For the PD vs Control dataset, blood‐derived bulk‐RNAseq from the PDBP and PPMI cohorts were available through the AMP‐PD consortium. Following quality control, normalization, and residual generation to account for biological and technical variables, co‐expression network modules and their enriched pathways were identified using WGCNA within each dataset. Module/trait correlation tests for aging and diagnosis (cases [AD/MCI or PD] vs control) phenotypes were evaluated. Gene Ontology enrichment analyses were executed to identify enriched pathways and brain or blood cell types within the modules. Modules were tested for preservation across cohorts. Result: We identified conserved immune signatures across brain regions and cohorts. Modules involved in immune response were preserved across all cohorts. Blood consensus modules involved in immune response were preserved in the brain and vice versa. Some immune modules were associated with AD/MCI, PD, and/or aging. Brain immune modules are significantly associated with aging and/or AD. Significant correlations (q<0.05) with PD diagnosis were present. In the MCSA and Emory vascular cohorts, there were no significant (q<0.05) associations between modules and diagnosis, while in ADNI there were nominal (p<0.05) associations. Conclusion: Preserved transcriptional immune networks were identified across blood and brain and across two neurodegenerative diseases. Expanding gene co‐expression network analyses to other diseases and integrating additional omics measures and phenotypes can further strengthen these findings to unravel the immune signatures across complex diseases.