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1. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

Jo, Taeho, Kim, Junpyo, Bice, Paula, Huynh, Kevin, Wang, Tingting, Arnold, Matthias, Meikle, Peter J, Giles, Corey, Kaddurah-Daouk, Rima, Saykin, Andrew J, Nho, Kwangsik, Kueider-Paisley, Alexandra, Doraiswamy, P Murali, Blach, Colette, Moseley, Arthur, Thompson, Will, St John-Williams, Lisa, Mahmoudiandehkhordi, Siamak, Tenenbaum, Jessica, Welsh-Balmer, Kathleen, Plassman, Brenda, Risacher, Shannon L, Kastenmüller, Gabi, Han, Xianlin, Baillie, Rebecca, Knight, Rob, Dorrestein, Pieter, Brewer, James, Mayer, Emeran, Labus, Jennifer, Baldi, Pierre, Gupta, Arpana, Fiehn, Oliver, Barupal, Dinesh, Meikle, Peter, Mazmanian, Sarkis, Rader, Dan, Kling, Mitchel, Shaw, Leslie, Trojanowski, John, van Duijin, Cornelia, Nevado-Holgado, Alejo, Bennett, David, Krishnan, Ranga, Keshavarzian, Ali, Vogt, Robin, Ikram, Arfan, Hankemeier, Thomas, Thiele, Ines, Price, Nathan, Funk, Cory, Baloni, Priyanka, Jia, Wei, Wishart, David, Brinton, Roberta, Chang, Rui, Farrer, Lindsay, Au, Rhoda, Qiu, Wendy, Würtz, Peter, Koal, Therese, Mangravite, Lara, Krumsiek, Jan, Suhre, Karsten, Newman, John, Moreno, Herman, Foroud, Tatania, Sacks, Frank, Jansson, Janet, Weiner, Michael W, Aisen, Paul, Petersen, Ronald, Jack, Clifford R, Jagust, William, Trojanowki, John Q, Toga, Arthur W, Beckett, Laurel, Green, Robert C, Morris, John C, Perrin, Richard J, Shaw, Leslie M, Khachaturian, Zaven, Carrillo, Maria, Potter, William, Barnes, Lisa, Bernard, Marie, Gonzalez, Hector, Ho, Carole, Hsiao, John K, Jackson, Jonathan, Masliah, Eliezer, Masterman, Donna, Okonkwo, Ozioma, Perrin, Richard, and Ryan, Laurie

Subjects
Medical Biochemistry and Metabolomics, Biomedical and Clinical Sciences, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Acquired Cognitive Impairment, Neurodegenerative, Networking and Information Technology R&D (NITRD), Machine Learning and Artificial Intelligence, Dementia, Alzheimer's Disease, Brain Disorders, Neurological, Humans, Aged, Magnetic Resonance Imaging, Deep Learning, Alzheimer Disease, Neuroimaging, Metabolome, Lipids, Cognitive Dysfunction, Alzheimer's Disease Metabolomics Consortium, Alzheimer's Disease Neuroimaging Initiative, Alzheimer's disease, Deep learning, Lipidomics, Machine learning, Metabolomics, Clinical Sciences, Public Health and Health Services, Clinical sciences, Epidemiology
Abstract

BackgroundDeep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics.MethodsThe c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification.FindingsThe application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6).InterpretationOur results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.FundingThe specific funding of this article is provided in the acknowledgements section.

Published
2023

2. AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT

Author

Lee, Edward H., Kelly, Brendan, Altinmakas, Emre, Dogan, Hakan, Mohammadzadeh, Maryam, Colak, Errol, Fu, Steve, Choudhury, Olivia, Ratan, Ujjwal, Kitamura, Felipe, Chaves, Hernan, Zheng, Jimmy, Said, Mourad, Reis, Eduardo, Lim, Jaekwang, Yokoo, Patricia, Mitchell, Courtney, Houshmand, Golnaz, Ghassemi, Marzyeh, Killeen, Ronan, Qiu, Wendy, Hayden, Joel, Rafiee, Farnaz, Klochko, Chad, Bevins, Nicholas, Sazgara, Faeze, Wong, S. Simon, Moseley, Michael, Halabi, Safwan, and Yeom, Kristen W.

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

While it is well known that population differences from genetics, sex, race, and environmental factors contribute to disease, AI studies in medicine have largely focused on locoregional patient cohorts with less diverse data sources. Such limitation stems from barriers to large-scale data share and ethical concerns over data privacy. Federated learning (FL) is one potential pathway for AI development that enables learning across hospitals without data share. In this study, we show the results of various FL strategies on one of the largest and most diverse COVID-19 chest CT datasets: 21 participating hospitals across five continents that comprise >10,000 patients with >1 million images. We also propose an FL strategy that leverages synthetically generated data to overcome class and size imbalances. We also describe the sources of data heterogeneity in the context of FL, and show how even among the correctly labeled populations, disparities can arise due to these biases.

Published
2023

3. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

Kaddurah-Daouk, Rima, Kueider-Paisley, Alexandra, Doraiswamy, P. Murali, Blach, Colette, Moseley, Arthur, Thompson, Will, St John-Williams, Lisa, Mahmoudiandehkhordi, Siamak, Tenenbaum, Jessica, Welsh-Balmer, Kathleen, Plassman, Brenda, Saykin, Andrew J., Nho, Kwangsik, Risacher, Shannon L., Kastenmüller, Gabi, Arnold, Matthias, Han, Xianlin, Baillie, Rebecca, Knight, Rob, Dorrestein, Pieter, Brewer, James, Mayer, Emeran, Labus, Jennifer, Baldi, Pierre, Gupta, Arpana, Fiehn, Oliver, Barupal, Dinesh, Meikle, Peter, Mazmanian, Sarkis, Rader, Dan, Kling, Mitchel, Shaw, Leslie, Trojanowski, John, van Duijin, Cornelia, Nevado-Holgado, Alejo, Bennett, David, Krishnan, Ranga, Keshavarzian, Ali, Vogt, Robin, Ikram, Arfan, Hankemeier, Thomas, Thiele, Ines, Price, Nathan, Funk, Cory, Baloni, Priyanka, Jia, Wei, Wishart, David, Brinton, Roberta, Chang, Rui, Farrer, Lindsay, Au, Rhoda, Qiu, Wendy, Würtz, Peter, Koal, Therese, Mangravite, Lara, Krumsiek, Jan, Suhre, Karsten, Newman, John, Moreno, Herman, Foroud, Tatania, Sacks, Frank, Jansson, Janet, Weiner, Michael W., Aisen, Paul, Petersen, Ronald, Jack, Clifford R., Jr., Jagust, William, Trojanowki, John Q., Toga, Arthur W., Beckett, Laurel, Green, Robert C., Morris, John C., Perrin, Richard J., Shaw, Leslie M., Khachaturian, Zaven, Carrillo, Maria, Potter, William, Barnes, Lisa, Bernard, Marie, Gonzalez, Hector, Ho, Carole, Hsiao, John K., Jackson, Jonathan, Masliah, Eliezer, Masterman, Donna, Okonkwo, Ozioma, Perrin, Richard, Ryan, Laurie, Silverberg, Nina, Fleisher, Adam, Sacrey, Diana Truran, Fockler, Juliet, Conti, Cat, Veitch, Dallas, Neuhaus, John, Jin, Chengshi, Nosheny, Rachel, Ashford, Miriam, Flenniken, Derek, Kormos, Adrienne, Montine, Tom, Rafii, Michael, Raman, Rema, Jimenez, Gustavo, Donohue, Michael, Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah, Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Smith, Stephanie, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth, Sloan, Brittany, Harvey, Danielle, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Schwarz, Christopher, Jones, David, Gunter, Jeff, Kantarci, Kejal, Senjem, Matthew, Vemuri, Prashanthi, Reid, Robert, Fox, Nick C., Malone, Ian, Thompson, Paul, Thomopoulos, Sophia I., Nir, Talia M., Jahanshad, Neda, DeCarli, Charles, Knaack, Alexander, Fletcher, Evan, Tosun-Turgut, Duygu, Chen, Stephanie Rossi, Choe, Mark, Crawford, Karen, Yushkevich, Paul A., Das, Sandhitsu, Koeppe, Robert A., Reiman, Eric M., Chen, Kewei, Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Franklin, Erin, Bernhardt, Haley, Taylor-Reinwald, Lisa, Korecka, Magdalena, Figurski, Michal, Neu, Scott, Apostolova, Liana G., Shen, Li, Foroud, Tatiana M., Nudelman, Kelly, Faber, Kelley, Wilmes, Kristi, Thal, Leon, Silbert, Lisa C., Lind, Betty, Crissey, Rachel, Kaye, Jeffrey A., Carter, Raina, Dolen, Sara, Quinn, Joseph, Schneider, Lon S., Pawluczyk, Sonia, Becerra, Mauricio, Teodoro, Liberty, Dagerman, Karen, Spann, Bryan M., Vanderswag, Helen, Ziolkowski, Jaimie, Heidebrink, Judith L., Zbizek-Nulph, Lisa, Lord, Joanne L., Mason, Sara S., Albers, Colleen S., Knopman, David, Johnson, Kris, Villanueva-Meyer, Javier, Pavlik, Valory, Pacini, Nathaniel, Lamb, Ashley, Kass, Joseph S., Doody, Rachelle S., Shibley, Victoria, Chowdhury, Munir, Rountree, Susan, Dang, Mimi, Stern, Yaakov, Honig, Lawrence S., Mintz, Akiva, Ances, Beau, Winkfield, David, Carroll, Maria, Stobbs-Cucchi, Georgia, Oliver, Angela, Creech, Mary L., Mintun, Mark A., Schneider, Stacy, Geldmacher, David, Love, Marissa Natelson, Griffith, Randall, Clark, David, Brockington, John, Marson, Daniel, Grossman, Hillel, Goldstein, Martin A., Greenberg, Jonathan, Mitsis, Effie, Shah, Raj C., Lamar, Melissa, Samuels, Patricia, Duara, Ranjan, Greig-Custo, Maria T., Rodriguez, Rosemarie, Albert, Marilyn, Onyike, Chiadi, Farrington, Leonie, Rudow, Scott, Brichko, Rottislav, Kielb, Stephanie, Smith, Amanda, Raj, Balebail Ashok, Fargher, Kristin, Sadowski, Martin, Wisniewski, Thomas, Shulman, Melanie, Faustin, Arline, Rao, Julia, Castro, Karen M., Ulysse, Anaztasia, Chen, Shannon, Sheikh, Mohammed O., Singleton-Garvin, Jamika, Petrella, JeffreyR., James, Olga, Wong, Terence Z., Borges-Neto, Salvador, Karlawish, Jason H., Wolk, David A., Vaishnavi, Sanjeev, Clark, Christopher M., Arnold, Steven E., Smith, Charles D., Jicha, Gregory A., Raslau, Flavius D., Lopez, Oscar L., Oakley, MaryAnn, Simpson, Donna M., Porsteinsson, Anton P., Martin, Kim, Kowalski, Nancy, Keltz, Melanie, Goldstein, Bonnie S., Makino, Kelly M., Ismail, M. Saleem, Brand, Connie, Thai, Gaby, Pierce, Aimee, Yanez, Beatriz, Sosa, Elizabeth, Witbracht, Megan, Kelley, Brendan, Nguyen, Trung, Womack, Kyle, Mathews, Dana, Quiceno, Mary, Levey, Allan I., Lah, James J., Hajjar, Ihab, Cellar, Janet S., Burns, Jeffrey M., Swerdlow, Russell H., Brooks, William M., Silverman, Daniel H.S., Kremen, Sarah, Apostolova, Liana, Tingus, Kathleen, Lu, Po H., Bartzokis, George, Woo, Ellen, Teng, Edmond, Graff-Radford, Neill R., Parfitt, Francine, Poki-Walker, Kim, Farlow, Martin R., Hake, Ann Marie, Matthews, Brandy R., Brosch, Jared R., Herring, Scott, van, Christopher H., Mecca, Adam P., Good, Susan P., MacAvoy, Martha G., Carson, Richard E., Varma, Pradeep, Chertkow, Howard, Vaitekunis, Susan, Hosein, Chris, Black, Sandra, Stefanovic, Bojana, Heyn, Chris (Chinthaka), Robin Hsiung, Ging-Yuek, Kim, Ellen, Mudge, Benita, Sossi, Vesna, Feldman, Howard, Assaly, Michele, Finger, Elizabeth, Pasternak, Stephen, Rachinsky, Irina, Kertesz, Andrew, Drost, Dick, Rogers, John, Grant, Ian, Muse, Brittanie, Rogalski, Emily, Robson, Jordan, Mesulam, M.-Marsel, Kerwin, Diana, Wu, Chuang-Kuo, Johnson, Nancy, Lipowski, Kristine, Weintraub, Sandra, Bonakdarpour, Borna, Pomara, Nunzio, Hernando, Raymundo, Sarrael, Antero, Rosen, Howard J., Miller, Bruce L., Perry, David, Turner, Raymond Scott, Johnson, Kathleen, Reynolds, Brigid, MCCann, Kelly, Poe, Jessica, Sperling, Reisa A., Johnson, Keith A., Marshall, Gad A., Yesavage, Jerome, Taylor, Joy L., Chao, Steven, Coleman, Jaila, White, Jessica D., Lane, Barton, Rosen, Allyson, Tinklenberg, Jared, Belden, Christine M., Atri, Alireza, Clark, Kelly A., Zamrini, Edward, Sabbagh, Marwan, Killiany, Ronald, Stern, Robert, Mez, Jesse, Kowall, Neil, Budson, Andrew E., Obisesan, Thomas O., Ntekim, Oyonumo E., Wolday, Saba, Khan, Javed I., Nwulia, Evaristus, Nadarajah, Sheeba, Lerner, Alan, Ogrocki, Paula, Tatsuoka, Curtis, Fatica, Parianne, Maillard, Pauline, Olichney, John, Carmichael, Owen, Bates, Vernice, Capote, Horacio, Rainka, Michelle, Borrie, Michael, Lee, T.-Y., Bartha, Dr Rob, Johnson, Sterling, Asthana, Sanjay, Carlsson, Cynthia M., Perrin, Allison, Burke, Anna, Scharre, Douglas W., Kataki, Maria, Tarawneh, Rawan, Hart, David, Zimmerman, Earl A., Celmins, Dzintra, Miller, Delwyn D., BolesPonto, Laura L., Smith, Karen Ekstam, Koleva, Hristina, Shim, Hyungsub, Nam, Ki Won, Schultz, Susan K., Williamson, Jeff D., Craft, Suzanne, Cleveland, Jo, Yang, Mia, Sink, Kaycee M., Ott, Brian R., Drake, Jonathan, Tremont, Geoffrey, Daiello, Lori A., Drake, Jonathan D., Ritter, Aaron, Bernick, Charles, Munic, Donna, O'Connelll, Abigail, Mintzer, Jacobo, Wiliams, Arthur, Masdeu, Joseph, Shi, Jiong, Garcia, Angelica, Newhouse, Paul, Potkin, Steven, Salloway, Stephen, Malloy, Paul, Correia, Stephen, Kittur, Smita, Pearlson, Godfrey D., Blank, Karen, Anderson, Karen, Flashman, Laura A., Seltzer, Marc, Hynes, Mary L., Santulli, Robert B., Relkin, Norman, Chiang, Gloria, Lee, Athena, Lin, Michael, Ravdin, Lisa, Petersen, Ron, Neylan, Thomas, Grafman, Jordan, Danowski, Sarah, Nguyen-Barrera, Catherine, Hayes, Jacqueline, Finley, Shannon, Bernstein, Matthew, Senjem, Matt, Foster, Norm, Kim, Sungeun, Sood, Ajay, Blanchard, Kimberly S., Fleischman, Debra, Arfanakis, Konstantinos, Varon, Daniel, Greig, Maria T., Petrella, Jeffrey R., Goldstein, Bonnie, Martin, Kimberly S., Reist, Christopher, Sadowsky, Carl, Martinez, Walter, Villena, Teresa, Rosen, Howard, Marshall, Gad, Peskind, Elaine R., Petrie, Eric C., Li, Gail, Mackin, Scott, Jimenez-Maggiora, Gustavo, Drake, Erin, Donohue, Mike, Nelson, Craig, Bickford, David, Butters, Meryl, Zmuda, Michelle, Reyes, Denise, Faber, Kelley M., Nudelman, Kelly N., Au, Yiu Ho, Scherer, Kelly, Catalinotto, Daniel, Stark, Samuel, Ong, Elise, Fernandez, Dariella, Jo, Taeho, Kim, Junpyo, Bice, Paula, Huynh, Kevin, Wang, Tingting, Meikle, Peter J., and Giles, Corey

Published
2023
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7. Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

Author

Kaddurah-Daouk, Rima, Kueider-Paisley, Alexandra, Louie, Gregory, Doraiswamy, P. Murali, Blach, Colette, Moseley, Arthur, Thompson, J. Will, Mahmoudiandehkhordi, Siamak, Welsh-Balmer, Kathleen, Plassman, Brenda, Saykin, Andrew, Nho, Kwangsik, Kastenmüller, Gabi, Arnold, Matthias, Bhattacharyya, Sudeepa, Han, Xianlin, Baillie, Rebecca, Fiehn, Oliver, Barupal, Dinesh, Meikle, Peter, Mazmanian, Sarkis, Kling, Mitchel, Shaw, Leslie, Trojanowski, John, Toledo, Jon, van Duijin, Cornelia, Hankemier, Thomas, Thiele, Ines, Heinken, Almut, Price, Nathan, Funk, Cory, Baloni, Priyanka, Jia, Wei, Wishart, David, Brinton, Roberta, Chang, Rui, Farrer, Lindsay, Au, Rhoda, Qiu, Wendy, Würtz, Peter, Mangravite, Lara, Krumsiek, Jan, Newman, John, Zhang, Bin, Moreno, Herman, Funk, Cory C., Yan, Jingwen, Yurkovich, James T., Mahmoudiandehkordi, Siamak, Saykin, Andrew J., Griffiths, William J., and Price, Nathan D.

Published
2020
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8. A longitudinal examination of plasma neurofilament light and total tau for the clinical detection and monitoring of Alzheimer's disease

Author

Sugarman, Michael A., Zetterberg, Henrik, Blennow, Kaj, Tripodis, Yorghos, McKee, Ann C., Stein, Thor D., Martin, Brett, Palmisano, Joseph N., Steinberg, Eric G., Simkin, Irene, Budson, Andrew E., Killiany, Ronald, O'Connor, Maureen K., Au, Rhoda, Qiu, Wendy Wei Qiao, Goldstein, Lee E., Kowall, Neil W., Mez, Jesse, Stern, Robert A., and Alosco, Michael L.

Published
2020
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9. A SUMO-ubiquitin relay recruits proteasomes to chromosome axes to regulate meiotic recombination

Author

Rao, HBD Prasada, Qiao, Huanyu, Bhatt, Shubhang K, Bailey, Logan RJ, Tran, Hung D, Bourne, Sarah L, Qiu, Wendy, Deshpande, Anusha, Sharma, Ajay N, Beebout, Connor J, Pezza, Roberto J, and Hunter, Neil

Subjects
Biochemistry and Cell Biology, Biological Sciences, Biotechnology, Genetics, 1.1 Normal biological development and functioning, Generic health relevance, Animals, Cell Cycle Proteins, Chromosome Pairing, Chromosomes, Mammalian, Crossing Over, Genetic, Ligases, Male, Meiosis, Mice, Mice, Mutant Strains, Proteasome Endopeptidase Complex, Proteolysis, Small Ubiquitin-Related Modifier Proteins, Spermatocytes, Ubiquitin, Ubiquitin-Protein Ligases, Ubiquitination, General Science & Technology
Abstract

Meiosis produces haploid gametes through a succession of chromosomal events, including pairing, synapsis, and recombination. Mechanisms that orchestrate these events remain poorly understood. We found that the SUMO (small ubiquitin-like modifier)-modification and ubiquitin-proteasome systems regulate the major events of meiotic prophase in mouse. Interdependent localization of SUMO, ubiquitin, and proteasomes along chromosome axes was mediated largely by RNF212 and HEI10, two E3 ligases that are also essential for crossover recombination. RNF212-dependent SUMO conjugation effected a checkpointlike process that stalls recombination by rendering the turnover of a subset of recombination factors dependent on HEI10-mediated ubiquitylation. We propose that SUMO conjugation establishes a precondition for designating crossover sites via selective protein stabilization. Thus, meiotic chromosome axes are hubs for regulated proteolysis via SUMO-dependent control of the ubiquitin-proteasome system.

Published
2017

10. Cognition Mediates the Association Between Cerebrospinal Fluid Biomarkers of Amyloid and P-Tau and Neuropsychiatric Symptoms.

Author

Frank, Brandon, Walsh, Michael, Hurley, Landon, Groh, Jenna, Blennow, Kaj, Zetterberg, Henrik, Tripodis, Yorghos, Budson, Andrew E., O'Connor, Maureen K., Martin, Brett, Weller, Jason, McKee, Ann, Qiu, Wendy, Stein, Thor D., Stern, Robert A., Mez, Jesse, Henson, Rachel, Long, Justin, Aschenbrenner, Andrew J., and Babulal, Ganesh M.

Subjects
ALZHEIMER'S disease, STRUCTURAL equation modeling, CEREBROSPINAL fluid, NEUROPSYCHOLOGICAL tests, OLDER people
Abstract

Background: Neuropsychiatric symptoms (NPS) can be an early manifestation of Alzheimer's disease (AD). However, the associations among NPS, cognition, and AD biomarkers across the disease spectrum are unclear. Objective: We analyzed cross-sectional mediation pathways between cerebrospinal fluid (CSF) biomarkers of AD (Aβ1-42, p-tau181), cognitive function, and NPS. Methods: Primary models included 781 participants from the National Alzheimer's Coordinating Center (NACC) data set who had CSF analyzed for AD biomarkers using Lumipulse. NPS were assessed with the Neuropsychiatric Inventory Questionnaire (NPI-Q). We assessed cognition with the harmonized MMSE/MoCA, as well as neuropsychological tests sensitive to AD pathology: story recall, naming, animal fluency, and Trails B. The Clinical Dementia Rating (CDR®) scale assessed dementia severity. Mediation models were estimated with Kemeny metric covariance in a structural equation model framework, controlling for age, education, sex, and APOEɛ4. Results: The sample was older adults (M = 73.85, SD = 6.68; 49.9% male, 390; 27.9% dementia, 218) who were predominantly white (n = 688, 88.1%). Higher p-tau181/Aβ1-42 ratio predicted higher NPI-Q, which was partially mediated by the MMSE/MoCA and, in a second model, story recall. No other pathway was statistically significant. Both the MMSE/MoCA and NPI-Q independently mediated the association between p-tau181/Aβ1-42 ratio and CDR global impairment. With dementia excluded, p-tau181/Aβ1-42 ratio was no longer associated with the NPI-Q. Conclusions: NPS may be secondary to cognitive impairment and AD pathology through direct and indirect pathways. NPS independently predict dementia severity in AD. However, AD pathology likely plays less of a role in NPS in samples without dementia. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Investigating Potential Racial Differences in Dementia‐Related Plasma Biomarkers

Author

Pettway, Erika C, primary, Labonte, Jacob, additional, II, Robert W Turner, additional, Bragg, Tahlia, additional, Turner, Arlener, additional, Banks, Sarah J, additional, Zetterberg, Henrik, additional, Blennow, Kaj, additional, Ashton, Nicholas J., additional, Karikari, Thomas K, additional, Tripodis, Yorghos, additional, Martin, Brett M, additional, Palmisano, Joseph N, additional, Stern, Robert A, additional, Killiany, Ronald J, additional, Aparicio, Hugo J, additional, Goldstein, Lee E, additional, Qiu, Wendy, additional, Budson, Andrew E, additional, Mez, Jesse B., additional, and Alosco, Michael L, additional

Published
2023
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12. Sex Differences on Tau, Astrocytic and Neurodegeneration Plasma Biomarkers

Author

Labonte, Jacob, primary, Pettway, Erika C, additional, Sugarman, Michael, additional, Zetterberg, Henrik, additional, Blennow, Kaj, additional, Ashton, Nicholas J., additional, Karikari, Thomas K, additional, Tripodis, Yorghos, additional, Martin, Brett M, additional, Palmisano, Joseph N, additional, Stern, Robert A, additional, Killiany, Ronald J, additional, Aparicio, Hugo J, additional, Goldstein, Lee E, additional, Qiu, Wendy, additional, Mez, Jesse B., additional, Banks, Sarah J, additional, and Alosco, Michael L, additional

Published
2023
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13. Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Author

Jo, Taeho, primary, Kim, Junpyo, additional, Bice, Paula, additional, Huynh, Kevin, additional, Wang, Tingting, additional, Arnold, Matthias, additional, Meikle, Peter J., additional, Giles, Corey, additional, Kaddurah-Daouk, Rima, additional, Saykin, Andrew J., additional, Nho, Kwangsik, additional, Kueider-Paisley, Alexandra, additional, Doraiswamy, P. Murali, additional, Blach, Colette, additional, Moseley, Arthur, additional, Thompson, Will, additional, St John-Williams, Lisa, additional, Mahmoudiandehkhordi, Siamak, additional, Tenenbaum, Jessica, additional, Welsh-Balmer, Kathleen, additional, Plassman, Brenda, additional, Risacher, Shannon L., additional, Kastenmüller, Gabi, additional, Han, Xianlin, additional, Baillie, Rebecca, additional, Knight, Rob, additional, Dorrestein, Pieter, additional, Brewer, James, additional, Mayer, Emeran, additional, Labus, Jennifer, additional, Baldi, Pierre, additional, Gupta, Arpana, additional, Fiehn, Oliver, additional, Barupal, Dinesh, additional, Meikle, Peter, additional, Mazmanian, Sarkis, additional, Rader, Dan, additional, Kling, Mitchel, additional, Shaw, Leslie, additional, Trojanowski, John, additional, van Duijin, Cornelia, additional, Nevado-Holgado, Alejo, additional, Bennett, David, additional, Krishnan, Ranga, additional, Keshavarzian, Ali, additional, Vogt, Robin, additional, Ikram, Arfan, additional, Hankemeier, Thomas, additional, Thiele, Ines, additional, Price, Nathan, additional, Funk, Cory, additional, Baloni, Priyanka, additional, Jia, Wei, additional, Wishart, David, additional, Brinton, Roberta, additional, Chang, Rui, additional, Farrer, Lindsay, additional, Au, Rhoda, additional, Qiu, Wendy, additional, Würtz, Peter, additional, Koal, Therese, additional, Mangravite, Lara, additional, Krumsiek, Jan, additional, Suhre, Karsten, additional, Newman, John, additional, Moreno, Herman, additional, Foroud, Tatania, additional, Sacks, Frank, additional, Jansson, Janet, additional, Weiner, Michael W., additional, Aisen, Paul, additional, Petersen, Ronald, additional, Jack, Clifford R., additional, Jagust, William, additional, Trojanowki, John Q., additional, Toga, Arthur W., additional, Beckett, Laurel, additional, Green, Robert C., additional, Morris, John C., additional, Perrin, Richard J., additional, Shaw, Leslie M., additional, Khachaturian, Zaven, additional, Carrillo, Maria, additional, Potter, William, additional, Barnes, Lisa, additional, Bernard, Marie, additional, Gonzalez, Hector, additional, Ho, Carole, additional, Hsiao, John K., additional, Jackson, Jonathan, additional, Masliah, Eliezer, additional, Masterman, Donna, additional, Okonkwo, Ozioma, additional, Perrin, Richard, additional, Ryan, Laurie, additional, Silverberg, Nina, additional, Fleisher, Adam, additional, Sacrey, Diana Truran, additional, Fockler, Juliet, additional, Conti, Cat, additional, Veitch, Dallas, additional, Neuhaus, John, additional, Jin, Chengshi, additional, Nosheny, Rachel, additional, Ashford, Miriam, additional, Flenniken, Derek, additional, Kormos, Adrienne, additional, Montine, Tom, additional, Rafii, Michael, additional, Raman, Rema, additional, Jimenez, Gustavo, additional, Donohue, Michael, additional, Gessert, Devon, additional, Salazar, Jennifer, additional, Zimmerman, Caileigh, additional, Cabrera, Yuliana, additional, Walter, Sarah, additional, Miller, Garrett, additional, Coker, Godfrey, additional, Clanton, Taylor, additional, Hergesheimer, Lindsey, additional, Smith, Stephanie, additional, Adegoke, Olusegun, additional, Mahboubi, Payam, additional, Moore, Shelley, additional, Pizzola, Jeremy, additional, Shaffer, Elizabeth, additional, Sloan, Brittany, additional, Harvey, Danielle, additional, Forghanian-Arani, Arvin, additional, Borowski, Bret, additional, Ward, Chad, additional, Schwarz, Christopher, additional, Jones, David, additional, Gunter, Jeff, additional, Kantarci, Kejal, additional, Senjem, Matthew, additional, Vemuri, Prashanthi, additional, Reid, Robert, additional, Fox, Nick C., additional, Malone, Ian, additional, Thompson, Paul, additional, Thomopoulos, Sophia I., additional, Nir, Talia M., additional, Jahanshad, Neda, additional, DeCarli, Charles, additional, Knaack, Alexander, additional, Fletcher, Evan, additional, Tosun-Turgut, Duygu, additional, Chen, Stephanie Rossi, additional, Choe, Mark, additional, Crawford, Karen, additional, Yushkevich, Paul A., additional, Das, Sandhitsu, additional, Koeppe, Robert A., additional, Reiman, Eric M., additional, Chen, Kewei, additional, Mathis, Chet, additional, Landau, Susan, additional, Cairns, Nigel J., additional, Householder, Erin, additional, Franklin, Erin, additional, Bernhardt, Haley, additional, Taylor-Reinwald, Lisa, additional, Korecka, Magdalena, additional, Figurski, Michal, additional, Neu, Scott, additional, Apostolova, Liana G., additional, Shen, Li, additional, Foroud, Tatiana M., additional, Nudelman, Kelly, additional, Faber, Kelley, additional, Wilmes, Kristi, additional, Thal, Leon, additional, Silbert, Lisa C., additional, Lind, Betty, additional, Crissey, Rachel, additional, Kaye, Jeffrey A., additional, Carter, Raina, additional, Dolen, Sara, additional, Quinn, Joseph, additional, Schneider, Lon S., additional, Pawluczyk, Sonia, additional, Becerra, Mauricio, additional, Teodoro, Liberty, additional, Dagerman, Karen, additional, Spann, Bryan M., additional, Vanderswag, Helen, additional, Ziolkowski, Jaimie, additional, Heidebrink, Judith L., additional, Zbizek-Nulph, Lisa, additional, Lord, Joanne L., additional, Mason, Sara S., additional, Albers, Colleen S., additional, Knopman, David, additional, Johnson, Kris, additional, Villanueva-Meyer, Javier, additional, Pavlik, Valory, additional, Pacini, Nathaniel, additional, Lamb, Ashley, additional, Kass, Joseph S., additional, Doody, Rachelle S., additional, Shibley, Victoria, additional, Chowdhury, Munir, additional, Rountree, Susan, additional, Dang, Mimi, additional, Stern, Yaakov, additional, Honig, Lawrence S., additional, Mintz, Akiva, additional, Ances, Beau, additional, Winkfield, David, additional, Carroll, Maria, additional, Stobbs-Cucchi, Georgia, additional, Oliver, Angela, additional, Creech, Mary L., additional, Mintun, Mark A., additional, Schneider, Stacy, additional, Geldmacher, David, additional, Love, Marissa Natelson, additional, Griffith, Randall, additional, Clark, David, additional, Brockington, John, additional, Marson, Daniel, additional, Grossman, Hillel, additional, Goldstein, Martin A., additional, Greenberg, Jonathan, additional, Mitsis, Effie, additional, Shah, Raj C., additional, Lamar, Melissa, additional, Samuels, Patricia, additional, Duara, Ranjan, additional, Greig-Custo, Maria T., additional, Rodriguez, Rosemarie, additional, Albert, Marilyn, additional, Onyike, Chiadi, additional, Farrington, Leonie, additional, Rudow, Scott, additional, Brichko, Rottislav, additional, Kielb, Stephanie, additional, Smith, Amanda, additional, Raj, Balebail Ashok, additional, Fargher, Kristin, additional, Sadowski, Martin, additional, Wisniewski, Thomas, additional, Shulman, Melanie, additional, Faustin, Arline, additional, Rao, Julia, additional, Castro, Karen M., additional, Ulysse, Anaztasia, additional, Chen, Shannon, additional, Sheikh, Mohammed O., additional, Singleton-Garvin, Jamika, additional, Petrella, JeffreyR., additional, James, Olga, additional, Wong, Terence Z., additional, Borges-Neto, Salvador, additional, Karlawish, Jason H., additional, Wolk, David A., additional, Vaishnavi, Sanjeev, additional, Clark, Christopher M., additional, Arnold, Steven E., additional, Smith, Charles D., additional, Jicha, Gregory A., additional, Raslau, Flavius D., additional, Lopez, Oscar L., additional, Oakley, MaryAnn, additional, Simpson, Donna M., additional, Porsteinsson, Anton P., additional, Martin, Kim, additional, Kowalski, Nancy, additional, Keltz, Melanie, additional, Goldstein, Bonnie S., additional, Makino, Kelly M., additional, Ismail, M. Saleem, additional, Brand, Connie, additional, Thai, Gaby, additional, Pierce, Aimee, additional, Yanez, Beatriz, additional, Sosa, Elizabeth, additional, Witbracht, Megan, additional, Kelley, Brendan, additional, Nguyen, Trung, additional, Womack, Kyle, additional, Mathews, Dana, additional, Quiceno, Mary, additional, Levey, Allan I., additional, Lah, James J., additional, Hajjar, Ihab, additional, Cellar, Janet S., additional, Burns, Jeffrey M., additional, Swerdlow, Russell H., additional, Brooks, William M., additional, Silverman, Daniel H.S., additional, Kremen, Sarah, additional, Apostolova, Liana, additional, Tingus, Kathleen, additional, Lu, Po H., additional, Bartzokis, George, additional, Woo, Ellen, additional, Teng, Edmond, additional, Graff-Radford, Neill R., additional, Parfitt, Francine, additional, Poki-Walker, Kim, additional, Farlow, Martin R., additional, Hake, Ann Marie, additional, Matthews, Brandy R., additional, Brosch, Jared R., additional, Herring, Scott, additional, van, Christopher H., additional, Mecca, Adam P., additional, Good, Susan P., additional, MacAvoy, Martha G., additional, Carson, Richard E., additional, Varma, Pradeep, additional, Chertkow, Howard, additional, Vaitekunis, Susan, additional, Hosein, Chris, additional, Black, Sandra, additional, Stefanovic, Bojana, additional, Heyn, Chris (Chinthaka), additional, Robin Hsiung, Ging-Yuek, additional, Kim, Ellen, additional, Mudge, Benita, additional, Sossi, Vesna, additional, Feldman, Howard, additional, Assaly, Michele, additional, Finger, Elizabeth, additional, Pasternak, Stephen, additional, Rachinsky, Irina, additional, Kertesz, Andrew, additional, Drost, Dick, additional, Rogers, John, additional, Grant, Ian, additional, Muse, Brittanie, additional, Rogalski, Emily, additional, Robson, Jordan, additional, Mesulam, M.-Marsel, additional, Kerwin, Diana, additional, Wu, Chuang-Kuo, additional, Johnson, Nancy, additional, Lipowski, Kristine, additional, Weintraub, Sandra, additional, Bonakdarpour, Borna, additional, Pomara, Nunzio, additional, Hernando, Raymundo, additional, Sarrael, Antero, additional, Rosen, Howard J., additional, Miller, Bruce L., additional, Perry, David, additional, Turner, Raymond Scott, additional, Johnson, Kathleen, additional, Reynolds, Brigid, additional, MCCann, Kelly, additional, Poe, Jessica, additional, Sperling, Reisa A., additional, Johnson, Keith A., additional, Marshall, Gad A., additional, Yesavage, Jerome, additional, Taylor, Joy L., additional, Chao, Steven, additional, Coleman, Jaila, additional, White, Jessica D., additional, Lane, Barton, additional, Rosen, Allyson, additional, Tinklenberg, Jared, additional, Belden, Christine M., additional, Atri, Alireza, additional, Clark, Kelly A., additional, Zamrini, Edward, additional, Sabbagh, Marwan, additional, Killiany, Ronald, additional, Stern, Robert, additional, Mez, Jesse, additional, Kowall, Neil, additional, Budson, Andrew E., additional, Obisesan, Thomas O., additional, Ntekim, Oyonumo E., additional, Wolday, Saba, additional, Khan, Javed I., additional, Nwulia, Evaristus, additional, Nadarajah, Sheeba, additional, Lerner, Alan, additional, Ogrocki, Paula, additional, Tatsuoka, Curtis, additional, Fatica, Parianne, additional, Maillard, Pauline, additional, Olichney, John, additional, Carmichael, Owen, additional, Bates, Vernice, additional, Capote, Horacio, additional, Rainka, Michelle, additional, Borrie, Michael, additional, Lee, T.-Y., additional, Bartha, Dr Rob, additional, Johnson, Sterling, additional, Asthana, Sanjay, additional, Carlsson, Cynthia M., additional, Perrin, Allison, additional, Burke, Anna, additional, Scharre, Douglas W., additional, Kataki, Maria, additional, Tarawneh, Rawan, additional, Hart, David, additional, Zimmerman, Earl A., additional, Celmins, Dzintra, additional, Miller, Delwyn D., additional, BolesPonto, Laura L., additional, Smith, Karen Ekstam, additional, Koleva, Hristina, additional, Shim, Hyungsub, additional, Nam, Ki Won, additional, Schultz, Susan K., additional, Williamson, Jeff D., additional, Craft, Suzanne, additional, Cleveland, Jo, additional, Yang, Mia, additional, Sink, Kaycee M., additional, Ott, Brian R., additional, Drake, Jonathan, additional, Tremont, Geoffrey, additional, Daiello, Lori A., additional, Drake, Jonathan D., additional, Ritter, Aaron, additional, Bernick, Charles, additional, Munic, Donna, additional, O'Connelll, Abigail, additional, Mintzer, Jacobo, additional, Wiliams, Arthur, additional, Masdeu, Joseph, additional, Shi, Jiong, additional, Garcia, Angelica, additional, Newhouse, Paul, additional, Potkin, Steven, additional, Salloway, Stephen, additional, Malloy, Paul, additional, Correia, Stephen, additional, Kittur, Smita, additional, Pearlson, Godfrey D., additional, Blank, Karen, additional, Anderson, Karen, additional, Flashman, Laura A., additional, Seltzer, Marc, additional, Hynes, Mary L., additional, Santulli, Robert B., additional, Relkin, Norman, additional, Chiang, Gloria, additional, Lee, Athena, additional, Lin, Michael, additional, Ravdin, Lisa, additional, Petersen, Ron, additional, Neylan, Thomas, additional, Grafman, Jordan, additional, Danowski, Sarah, additional, Nguyen-Barrera, Catherine, additional, Hayes, Jacqueline, additional, Finley, Shannon, additional, Bernstein, Matthew, additional, Senjem, Matt, additional, Foster, Norm, additional, Kim, Sungeun, additional, Sood, Ajay, additional, Blanchard, Kimberly S., additional, Fleischman, Debra, additional, Arfanakis, Konstantinos, additional, Varon, Daniel, additional, Greig, Maria T., additional, Petrella, Jeffrey R., additional, Goldstein, Bonnie, additional, Martin, Kimberly S., additional, Reist, Christopher, additional, Sadowsky, Carl, additional, Martinez, Walter, additional, Villena, Teresa, additional, Rosen, Howard, additional, Marshall, Gad, additional, Peskind, Elaine R., additional, Petrie, Eric C., additional, Li, Gail, additional, Mackin, Scott, additional, Jimenez-Maggiora, Gustavo, additional, Drake, Erin, additional, Donohue, Mike, additional, Nelson, Craig, additional, Bickford, David, additional, Butters, Meryl, additional, Zmuda, Michelle, additional, Reyes, Denise, additional, Faber, Kelley M., additional, Nudelman, Kelly N., additional, Au, Yiu Ho, additional, Scherer, Kelly, additional, Catalinotto, Daniel, additional, Stark, Samuel, additional, Ong, Elise, additional, and Fernandez, Dariella, additional

Published
2023
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16. Identification of an APOE ε4–specific blood‐based molecular pathway for Alzheimer's disease risk.

Author

Tao, Qiushan, Zhang, Chao, Mercier, Gustavo, Lunetta, Kathryn, Ang, Ting Fang Alvin, Akhter‐Khan, Samia, Zhang, Zhengrong, Taylor, Andrew, Killiany, Ronald J., Alosco, Michael, Mez, Jesse, Au, Rhoda, Zhang, Xiaoling, Farrer, Lindsay A., and Qiu, Wendy Wei Qiao

Subjects
DISEASE risk factors, APOLIPOPROTEIN E4, COMPLEMENT factor H, BLOOD proteins, DEFAULT mode network, APOLIPOPROTEIN E, TAU proteins
Abstract

INTRODUCTION: The precise apolipoprotein E (APOE) ε4‐specific molecular pathway(s) for Alzheimer's disease (AD) risk are unclear. METHODS: Plasma protein modules/cascades were analyzed using weighted gene co‐expression network analysis (WGCNA) in the Alzheimer's Disease Neuroimaging Initiative study. Multivariable regression analyses were used to examine the associations among protein modules, AD diagnoses, cerebrospinal fluid (CSF) phosphorylated tau (p‐tau), and brain glucose metabolism, stratified by APOE genotype. RESULTS: The Green Module was associated with AD diagnosis in APOE ε4 homozygotes. Three proteins from this module, C‐reactive protein (CRP), complement C3, and complement factor H (CFH), had dose‐dependent associations with CSF p‐tau and cognitive impairment only in APOE ε4 homozygotes. The link among these three proteins and glucose hypometabolism was observed in brain regions of the default mode network (DMN) in APOE ε4 homozygotes. A Framingham Heart Study validation study supported the findings for AD. DISCUSSION: The study identifies the APOE ε4–specific CRP–C3–CFH inflammation pathway for AD, suggesting potential drug targets for the disease. Highlights: Identification of an APOE ε4 specific molecular pathway involving blood CRP, C3, and CFH for the risk of AD.CRP, C3, and CFH had dose‐dependent associations with CSF p‐Tau and brain glucose hypometabolism as well as with cognitive impairment only in APOE ε4 homozygotes.Targeting CRP, C3, and CFH may be protective and therapeutic for AD onset in APOE ε4 carriers. [ABSTRACT FROM AUTHOR]

Published
2023
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19. Midlife measures of lipid fractions and fasting glucose are associated with late‐onset Alzheimer disease

Author

Zhang, Xiaoling, primary, Tong, Tong, additional, Chang, Andrew, additional, Ang, Ting Fang Alvin, additional, Tao, Qiushan, additional, Auerbach, Sandford H., additional, Devine, Sherral, additional, Qiu, Wendy, additional, Mez, Jesse, additional, Massaro, Joseph, additional, Lunetta, Kathryn L., additional, Au, Rhoda, additional, and Farrer, Lindsay A., additional

Published
2021
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21. Plasma P‐tau181 and NfL are central nodes in a network of diagnostic, biomarker, and demographic data

Author

Frank, Brandon E., primary, Ally, Madeline, additional, Brekke, Bailee, additional, Zetterberg, Henrik, additional, Blennow, Kaj, additional, Sugarman, Michael, additional, Ashton, Nicholas J., additional, Karikari, Thomas K., additional, Tripodis, Yorghos, additional, McKee, Ann C., additional, Stein, Thor D., additional, Martin, Brett M., additional, Palmisano, Joseph, additional, Steinberg, Eric, additional, Simkin, Irene, additional, Turk, Katherine W., additional, Budson, Andrew, additional, O'Connor, Maureen K., additional, Au, Rhoda, additional, Qiu, Wendy, additional, Goldstein, Lee E., additional, Killiany, Ronald J., additional, Kowall, Neil W., additional, Mez, Jesse, additional, Stern, Robert A., additional, and Alosco, Michael L., additional

Published
2021
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22. Long‐term effects of repetitive head impacts on gray matter cortical thickness

Author

Brekke, Bailee, primary, DeVivo, Renee, additional, McKee, Ann C., additional, Stein, Thor D., additional, Tripodis, Yorghos, additional, Phelps, Alyssa, additional, Weller, Jason, additional, Martin, Brett M, additional, Palmisano, Joseph, additional, Steinberg, Eric, additional, Turk, Katherine W, additional, Budson, Andrew, additional, O'Connor, Maureen K, additional, Au, Rhoda, additional, Qiu, Wendy, additional, Goldstein, Lee E, additional, Kowall, Neil W, additional, Stern, Robert A, additional, Killiany, Ronald J, additional, Mez, Jesse, additional, and Alosco, Michael L, additional

Published
2021
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25. Early‐mid adulthood measures of HDL, triglycerides and fasting glucose are associated with late‐onset Alzheimer disease

Author

Zhang, Xiaoling, primary, Tong, Tong, additional, Chang, Andrew, additional, Ang, Ting Fang Alvin, additional, Tao, Qiushan, additional, Auerbach, Sandford H, additional, Devine, Sherral, additional, Qiu, Wendy, additional, Mez, Jesse, additional, Massaro, Joseph, additional, Lunetta, Kathryn L, additional, Au, Rhoda, additional, and Farrer, Lindsay A, additional

Published
2020
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26. Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

Author

Baloni, Priyanka, primary, Funk, Cory C., additional, Yan, Jingwen, additional, Yurkovich, James T., additional, Kueider-Paisley, Alexandra, additional, Nho, Kwangsik, additional, Heinken, Almut, additional, Jia, Wei, additional, Mahmoudiandehkordi, Siamak, additional, Louie, Gregory, additional, Saykin, Andrew J., additional, Arnold, Matthias, additional, Kastenmüller, Gabi, additional, Griffiths, William J., additional, Thiele, Ines, additional, Kaddurah-Daouk, Rima, additional, Price, Nathan D., additional, Doraiswamy, P. Murali, additional, Blach, Colette, additional, Moseley, Arthur, additional, Thompson, J. Will, additional, Mahmoudiandehkhordi, Siamak, additional, Welsh-Balmer, Kathleen, additional, Plassman, Brenda, additional, Saykin, Andrew, additional, Bhattacharyya, Sudeepa, additional, Han, Xianlin, additional, Baillie, Rebecca, additional, Fiehn, Oliver, additional, Barupal, Dinesh, additional, Meikle, Peter, additional, Mazmanian, Sarkis, additional, Kling, Mitchel, additional, Shaw, Leslie, additional, Trojanowski, John, additional, Toledo, Jon, additional, van Duijin, Cornelia, additional, Hankemier, Thomas, additional, Price, Nathan, additional, Funk, Cory, additional, Baloni, Priyanka, additional, Wishart, David, additional, Brinton, Roberta, additional, Chang, Rui, additional, Farrer, Lindsay, additional, Au, Rhoda, additional, Qiu, Wendy, additional, Würtz, Peter, additional, Mangravite, Lara, additional, Krumsiek, Jan, additional, Newman, John, additional, Zhang, Bin, additional, and Moreno, Herman, additional

Published
2020
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27. Association of inflammatory proteins with cognitive aging, brain MRI markers, and incident dementia.

Author

Fang, Yuan, Doyle, Margaret F, Mez, Jesse B., Alosco, Michael L, Satizabal, Claudia L., Qiu, Wendy, Chen, Jiachen, Lunetta, Kathryn L., and Murabito, Joanne M

Abstract

Background: Inflammatory cytokines and chemokines related to the innate and adaptive immune system have been linked to neuroinflammation in Alzheimer's Disease (AD) dementia. We hypothesized that individual blood‐based inflammatory biomarkers would associate with cognitive function, brain magnetic resonance imaging (MRI) volumes, and risk for dementia in Framingham Heart Study (FHS) participants. Method: Protein biomarkers related to immune cells or associated with inflammatory responses including CD14, CD163, CD5L, CD56, CD40L, CXCL16, SDF1, DPP4, SGP130, sRAGE, and MPO were measured at FHS Offspring exam 7. We identified FHS Offspring participants who underwent neuropsychological (NP) testing (n = 2394) or brain MRI (n = 2135) within five years of the examination; and who were followed up 10 years after age 60 for incident all‐cause dementia (n = 1650). We used linear mixed effect models accounting for family relationships to investigate the associations between the protein biomarkers and NP test performance and brain MRI volumes and Cox proportional hazards models to examine the association with incident dementia. A false discovery rate (FDR) within each outcome set was computed to adjust for multiple testing and FDR ≤ 0.1 indicated significance. Result: Participants from the NP and MRI samples were on average 61 years old and 54% female. Participants from the incident dementia sample (mean age 68 years) included 126 incident dementia cases within 10 years. In addition to CD14 which has an established association, we observed significant associations between higher CD40L and MPO with poorer NP performance from the executive function domain. Higher CD5L levels were significantly associated with smaller total brain volumes (TCBV), whereas higher sRAGE was associated with larger TCBV. Associations persisted after further adjusting for APOE ϵ4 carrier status and cardiovascular risk factors. None of the protein biomarkers included were significantly associated with risk of incident dementia, with trend towards an association for CD5L. Conclusion: Since the proinflammatory factors CD5L, CD40L, sRAGE and MPO are associated with immune cells and are involved in vascular pathology, our study suggests the immune‐vascular axis is associated with cognitive and brain aging. If confirmed in other samples, our findings may provide informative biomarkers of abnormal brain aging. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Association Between Elevated Depressive Symptoms and Cognitive Function Moderated by APOE4 Status: Framingham Offspring Study.

Author

Piers, Ryan J., Liu, Yulin, Ang, Ting F.A., Tao, Qiushan, Au, Rhoda, Qiu, Wei Qiao, and Qiu, Wendy Q

Subjects
COGNITIVE ability, MENTAL depression, APOLIPOPROTEIN E4, VISUAL memory, MAGNETIC resonance imaging, NEUROPSYCHOLOGICAL tests, STROKE, REMINISCENCE therapy, RESEARCH, RESEARCH methodology, COGNITION, MEDICAL cooperation, EVALUATION research, COMPARATIVE studies, APOLIPOPROTEINS, DISEASE susceptibility, RESEARCH funding, LONGITUDINAL method
Abstract

Background: Depression and Apolipoprotein E4 (APOE4) are associated with decreased cognitive function and differences in brain structure.Objective: This study investigated whether APOE4 status moderates the association between elevated depressive symptoms, cognitive function, and brain structure.Methods: Stroke- and dementia-free participants (n = 1,968) underwent neuropsychological evaluation, brain MRI, and depression screening. Linear and logistic regression was used to examine all associations. Secondary analyses were performed using interaction terms to assess effect modification by APOE4 status.Results: Elevated depressive symptoms were associated with lower cognitive performance in several domains. In stratified analyses, elevated depressive symptoms were associated with poorer visual short- and long-term memory performance for APOE4 + participants. Elevated depressive symptoms were not associated with any brain structure in this study sample.Conclusion: Elevated depressive symptoms impact cognitive function in non-demented individuals. Having the APOE4 allele may exacerbate the deleterious effects of elevated depressive symptoms on visual memory performance. Screening for elevated depressive symptoms in both research studies and clinical practice may be warranted to avoid false positive identification of neurodegeneration, particularly among those who are APOE4 + . [ABSTRACT FROM AUTHOR]

Published
2021
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33. A SUMO-ubiquitin relay recruits proteasomes to chromosome axes to regulate meiotic recombination.

Author

Rao, H, Rao, H, Qiao, Huanyu, Bhatt, Shubhang, Bailey, Logan, Tran, Hung, Bourne, Sarah, Qiu, Wendy, Deshpande, Anusha, Sharma, Ajay, Beebout, Connor, Pezza, Roberto, Hunter, Neil, Rao, H, Rao, H, Qiao, Huanyu, Bhatt, Shubhang, Bailey, Logan, Tran, Hung, Bourne, Sarah, Qiu, Wendy, Deshpande, Anusha, Sharma, Ajay, Beebout, Connor, Pezza, Roberto, and Hunter, Neil

Abstract

Meiosis produces haploid gametes through a succession of chromosomal events, including pairing, synapsis, and recombination. Mechanisms that orchestrate these events remain poorly understood. We found that the SUMO (small ubiquitin-like modifier)-modification and ubiquitin-proteasome systems regulate the major events of meiotic prophase in mouse. Interdependent localization of SUMO, ubiquitin, and proteasomes along chromosome axes was mediated largely by RNF212 and HEI10, two E3 ligases that are also essential for crossover recombination. RNF212-dependent SUMO conjugation effected a checkpointlike process that stalls recombination by rendering the turnover of a subset of recombination factors dependent on HEI10-mediated ubiquitylation. We propose that SUMO conjugation establishes a precondition for designating crossover sites via selective protein stabilization. Thus, meiotic chromosome axes are hubs for regulated proteolysis via SUMO-dependent control of the ubiquitin-proteasome system.

Published
2017

34. A SUMO-Ubiquitin Relay Recruits Proteasomes to Chromosome Axes to Regulate Meiotic Recombination

Author

Rao, H.B.D. Prasada, primary, Qiao, Huanyu, additional, Bhatt, Shubhang K., additional, Bailey, Logan R.J., additional, Tran, Hung D., additional, Bourne, Sarah L., additional, Qiu, Wendy, additional, Deshpande, Anusha, additional, Sharma, Ajay N., additional, Beebout, Connor J., additional, Pezza, Roberto J., additional, and Hunter, Neil, additional

Published
2016
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45. Plasma P‐tau181 and NfL are central nodes in a network of diagnostic, biomarker, and demographic data.

Author

Frank, Brandon E., Ally, Madeline, Brekke, Bailee, Zetterberg, Henrik, Blennow, Kaj, Sugarman, Michael, Ashton, Nicholas J., Karikari, Thomas K., Tripodis, Yorghos, McKee, Ann C., Stein, Thor D., Martin, Brett M., Palmisano, Joseph, Steinberg, Eric, Simkin, Irene, Turk, Katherine W., Budson, Andrew, O'Connor, Maureen K., Au, Rhoda, and Qiu, Wendy

Abstract

Background: In Alzheimer's disease (AD), plasma biomarkers of neurodegeneration and phosphorylated tau have initial support for their relationship to clinical diagnosis and cognitive outcomes over time (total tau [t‐tau], neurofilament light [NfL], and p‐tau). To date, only one study has assessed a network model with these data. Here, we assessed the network relations (i.e., conditional dependencies) between diagnostic variables, plasma biomarkers, neuropsychological test performance, and demographic variables using a Gaussian graphical model (GGM) with participants from the Boston University (BU) Alzheimer's Disease Research Center (ADRC) Longitudinal Clinical Core Registry. Method: The sample included individuals with normal cognition (n=235), MCI due to AD (n=181), and AD dementia (n=153). Participants completed a comprehensive battery of neuropsychological tests to assess global cognition, attention, executive function, episodic memory, and language abilities. Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa technique. Regularized GGMs were estimated with Pearson, polychoric, and polyserial correlations depending on whether the variables were continuous, ordinal, or mixed. Network stability was assessed with a non‐parametric bootstrap of standardized edge weights and a person‐dropping bootstrap of centrality measures with 10,000 samples. Latent dimensions were estimated with Markov chain Monte Carlo (MCMC) simulation. Result: Assessment of the model suggested adequate fit, χ2(184, N = 569) = 620.46, EBIC = 27,444.53, RMSEA = 0.06, TLI = 0.95. Metrics of strength, closeness centrality, and expected influence met established thresholds of stability. Among biomarkers, diagnosis was connected to p‐tau181, βz = 0.07, 95% CI [0.01, 0.12]. Assessment of network centrality suggested that p‐tau181 ranked relatively highly for betweenness centrality and expected influence and NfL ranked highly for betweenness centrality. In contrast, t‐tau was not connected to any functional or diagnostic variable and did not rank highly for centrality. The biomarker variables loaded similarly on the two latent dimensions and were clustered near consensus conference diagnosis. Conclusion: Unlike t‐tau, plasma biomarkers p‐tau181 and NfL were influential as "central junctions" for other connections in a network of diagnostic, biomarker, and demographic data. The findings support recent research that posits p‐tau181 and NfL reflect distinct aspects of AD progression (respectively, AD pathology and neurodegeneration). [ABSTRACT FROM AUTHOR]

Published
2021
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48. Association of mid-age Life's Essential 8 score with digital cognitive performance and incident Alzheimer's disease: The Framingham Heart Study.

Author

Yang J, Ding H, Li Y, Ang TFA, Devine S, Liu Y, Qiu W, Au R, Ma J, and Liu C

Abstract

Background: Cardiovascular health (CVH) is a modifiable risk factor for Alzheimer's disease (AD). However, studies examining the association between mid-age CVH, as indicated by Life's Essential 8 (LE8) health metrics, and digital cognitive performance or AD risk are limited., Objective: To examine the associations between mid-age CVH, assessed by LE8 scores during ages 45 to 65, and digital Clock Drawing Test (dCDT) performance as well as the incidence of AD., Methods: We included 1198 participants (51.6% women) from the Framingham Heart Study (FHS) Offspring cohort. Linear regression and Cox proportional hazards models were applied to examine the associations between mid-age CVH and dCDT performance, as well as the incidence of AD., Results: Over a median follow-up of 17.5 years, 45 participants developed AD. Each standard deviation (SD) higher mid-age LE8 total score was associated with a 0.16 SD higher level of the dCDT total score (p < 0.001) and a 0.35-fold lower risk of incident AD (HR = 0.65, 95% CI: 0.49-0.87, p = 0.003). The dCDT measures showed stronger associations with mid-age LE8 and AD risk compared to the conventional CDT (cCDT). For example, the drawing score on copy tasks was more strongly associated with LE8 (beta = 0.10, p = 0.007 versus beta = 0.08, p = 0.27) and had higher discrimination for incident AD (C-statistic = 0.89 versus 0.83) compared to the cCDT., Conclusions: Our results highlight the potential of digital cognitive assessments for evaluating AD risk and emphasize the importance of mid-age CVH in shaping cognitive outcomes and the development of AD., Competing Interests: Declaration of conflicting interestsThe authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr Au is a scientific advisor to Signant Health and Novo Nordisk. The remaining authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Published
2025
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49. Identification of an APOE ε4-specific blood-based molecular pathway for Alzheimer's disease risk.

Author

Tao Q, Zhang C, Mercier G, Lunetta K, Ang TFA, Akhter-Khan S, Zhang Z, Taylor A, Killiany RJ, Alosco M, Mez J, Au R, Zhang X, Farrer LA, and Qiu WWQ

Abstract

Introduction: The precise apolipoprotein E ( APOE ) ε4-specific molecular pathway(s) for Alzheimer's disease (AD) risk are unclear., Methods: Plasma protein modules/cascades were analyzed using weighted gene co-expression network analysis (WGCNA) in the Alzheimer's Disease Neuroimaging Initiative study. Multivariable regression analyses were used to examine the associations among protein modules, AD diagnoses, cerebrospinal fluid (CSF) phosphorylated tau (p-tau), and brain glucose metabolism, stratified by APOE genotype., Results: The Green Module was associated with AD diagnosis in APOE ε4 homozygotes. Three proteins from this module, C-reactive protein (CRP), complement C3, and complement factor H (CFH), had dose-dependent associations with CSF p-tau and cognitive impairment only in APOE ε4 homozygotes. The link among these three proteins and glucose hypometabolism was observed in brain regions of the default mode network (DMN) in APOE ε4 homozygotes. A Framingham Heart Study validation study supported the findings for AD., Discussion: The study identifies the APOE ε4-specific CRP-C3-CFH inflammation pathway for AD, suggesting potential drug targets for the disease. Highlights: Identification of an APOE ε4 specific molecular pathway involving blood CRP, C3, and CFH for the risk of AD.CRP, C3, and CFH had dose-dependent associations with CSF p-Tau and brain glucose hypometabolism as well as with cognitive impairment only in APOE ε4 homozygotes.Targeting CRP, C3, and CFH may be protective and therapeutic for AD onset in APOE ε4 carriers., Competing Interests: The authors declare no competing interests. The sponsor institutes did not play any role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Author disclosures are available in the supporting information., (© 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2023
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