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1. Asian Cohort for Alzheimer's Disease (ACAD) pilot study on genetic and non‐genetic risk factors for Alzheimer's disease among Asian Americans and Canadians

Author

Ho, Pei‐Chuan, Yu, Wai Haung, Tee, Boon Lead, Lee, Wan‐Ping, Li, Clara, Gu, Yian, Yokoyama, Jennifer S, Reyes‐Dumeyer, Dolly, Choi, Yun‐Beom, Yang, Hyun‐Sik, Vardarajan, Badri N, Tzuang, Marian, Lieu, Kevin, Lu, Anna, Faber, Kelley M, Potter, Zoë D, Revta, Carolyn, Kirsch, Maureen, McCallum, Jake, Mei, Diana, Booth, Briana, Cantwell, Laura B, Chen, Fangcong, Chou, Sephera, Clark, Dewi, Deng, Michelle, Hong, Ting Hei, Hwang, Ling‐Jen, Jiang, Lilly, Joo, Yoonmee, Kang, Younhee, Kim, Ellen S, Kim, Hoowon, Kim, Kyungmin, Kuzma, Amanda B, Lam, Eleanor, Lanata, Serggio C, Lee, Kunho, Li, Donghe, Li, Mingyao, Li, Xiang, Liu, Chia‐Lun, Liu, Collin, Liu, Linghsi, Lupo, Jody‐Lynn, Nguyen, Khai, Pfleuger, Shannon E, Qian, James, Qian, Winnie, Ramirez, Veronica, Russ, Kristen A, Seo, Eun Hyun, Song, Yeunjoo E, Tartaglia, Maria Carmela, Tian, Lu, Torres, Mina, Vo, Namkhue, Wong, Ellen C, Xie, Yuan, Yau, Eugene B, Yi, Isabelle, Yu, Victoria, Zeng, Xiaoyi, St George‐Hyslop, Peter, Au, Rhoda, Schellenberg, Gerard D, Dage, Jeffrey L, Varma, Rohit, Hsiung, Ging‐Yuek R, Rosen, Howard, Henderson, Victor W, Foroud, Tatiana, Kukull, Walter A, Peavy, Guerry M, Lee, Haeok, Feldman, Howard H, Mayeux, Richard, Chui, Helena, Jun, Gyungah R, Park, Van M Ta, Chow, Tiffany W, and Wang, Li‐San

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Clinical Trials and Supportive Activities, Clinical Research, Acquired Cognitive Impairment, Minority Health, Brain Disorders, Dementia, Alzheimer's Disease, Aging, Neurodegenerative, Prevention, Genetics, Health Disparities, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), 2.4 Surveillance and distribution, Neurological, Humans, Alzheimer Disease, Pilot Projects, Asian, Canada, Risk Factors, North American People, Alzheimer's disease, biosamples, community-based participatory research, dementia, environmental, genetics, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionClinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non-genetic/lifestyle factors impact this multi-ethnic population.MethodsThe ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese.ResultsACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception.DiscussionACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit > 5000 participants to identify genetic and non-genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness.HighlightsThe Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under-investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.

Published
2024

14. A Deep Reinforcement Learning Optimization Method Considering Network Node Failures.

Author

Ding, Xueying, Liao, Xiao, Cui, Wei, Meng, Xiangliang, Liu, Ruosong, Ye, Qingshan, and Li, Donghe

Subjects
REINFORCEMENT learning, DEEP reinforcement learning, ELECTRIC power distribution grids, ELECTRIC power, MICROGRIDS
Abstract

Nowadays, the microgrid system is characterized by a diversification of power factors and a complex network structure. Existing studies on microgrid fault diagnosis and troubleshooting mostly focus on the fault detection and operation optimization of a single power device. However, for increasingly complex microgrid systems, it becomes increasingly challenging to effectively contain faults within a specific spatiotemporal range. This can lead to the spread of power faults, posing great harm to the safety of the microgrid. The topology optimization of the microgrid based on deep reinforcement learning proposed in this paper starts from the overall power grid and aims to minimize the overall failure rate of the microgrid by optimizing the topology of the power grid. This approach can limit internal faults within a small range, greatly improving the safety and reliability of microgrid operation. The method proposed in this paper can optimize the network topology for the single node fault and multi-node fault, reducing the influence range of the node fault by 21% and 58%, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
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22. A missense variant in SHARPIN mediates Alzheimer’s disease-specific brain damages

Author

Park, Jun Young, Lee, Dongsoo, Lee, Jang Jae, Gim, Jungsoo, Gunasekaran, Tamil Iniyan, Choi, Kyu Yeong, Kang, Sarang, Do, Ah Ra, Jo, Jinyeon, Park, Juhong, Park, Kyungtaek, Li, Donghe, Lee, Sanghun, Kim, Hoowon, Dhanasingh, Immanuel, Ghosh, Suparna, Keum, Seula, Choi, Jee Hye, Song, Gyun Jee, Sael, Lee, Rhee, Sangmyung, Lovestone, Simon, Kim, Eunae, Moon, Seung Hwan, Kim, Byeong C., Kim, SangYun, Saykin, Andrew J., Nho, Kwangsik, Lee, Sung Haeng, Farrer, Lindsay A., Jun, Gyungah R., Won, Sungho, and Lee, Kun Ho

Published
2021
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31. Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifiesLRRC4C, LHX5-AS1and nominates ancestry-specific lociPTPRK,GRB14, andKIAA0825as novel risk loci for Alzheimer’s disease: the Alzheimer’s Disease Genetics Consortium

Author

Rajabli, Farid, primary, Benchek, Penelope, additional, Tosto, Giuseppe, additional, Kushch, Nicholas, additional, Sha, Jin, additional, Bazemore, Katrina, additional, Zhu, Congcong, additional, Lee, Wan-Ping, additional, Haut, Jacob, additional, Hamilton-Nelson, Kara L., additional, Wheeler, Nicholas R., additional, Zhao, Yi, additional, Farrell, John J., additional, Grunin, Michelle A., additional, Leung, Yuk Yee, additional, Kuksa, Pavel P., additional, Li, Donghe, additional, Lucio da Fonseca, Eder, additional, Mez, Jesse B., additional, Palmer, Ellen L., additional, Pillai, Jagan, additional, Sherva, Richard M., additional, Song, Yeunjoo E., additional, Zhang, Xiaoling, additional, Iqbal, Taha, additional, Pathak, Omkar, additional, Valladares, Otto, additional, Kuzma, Amanda B., additional, Abner, Erin, additional, Adams, Perrie M., additional, Aguirre, Alyssa, additional, Albert, Marilyn S., additional, Albin, Roger L., additional, Allen, Mariet, additional, Alvarez, Lisa, additional, Apostolova, Liana G., additional, Arnold, Steven E., additional, Asthana, Sanjay, additional, Atwood, Craig S., additional, Ayres, Gayle, additional, Baldwin, Clinton T., additional, Barber, Robert C., additional, Barnes, Lisa L., additional, Barral, Sandra, additional, Beach, Thomas G., additional, Becker, James T., additional, Beecham, Gary W., additional, Beekly, Duane, additional, Benitez, Bruno A., additional, Bennett, David, additional, Bertelson, John, additional, Bird, Thomas D., additional, Blacker, Deborah, additional, Boeve, Bradley F., additional, Bowen, James D., additional, Boxer, Adam, additional, Brewer, James, additional, Burke, James R., additional, Burns, Jeffrey M., additional, Buxbaum, Joseph D., additional, Cairns, Nigel J., additional, Cantwell, Laura B., additional, Cao, Chuanhai, additional, Carlson, Christopher S., additional, Carlsson, Cynthia M., additional, Carney, Regina M., additional, Carrasquillo, Minerva M., additional, Chasse, Scott, additional, Chesselet, Marie-Francoise, additional, Chin, Nathaniel A., additional, Chui, Helena C., additional, Chung, Jaeyoon, additional, Craft, Suzanne, additional, Crane, Paul K., additional, Cribbs, David H., additional, Crocco, Elizabeth A., additional, Cruchaga, Carlos, additional, Cuccaro, Michael L., additional, Cullum, Munro, additional, Darby, Eveleen, additional, Davis, Barbara, additional, De Jager, Philip L., additional, DeCarli, Charles, additional, DeToledo, John, additional, Dick, Malcolm, additional, Dickson, Dennis W., additional, Dombroski, Beth A., additional, Doody, Rachelle S., additional, Duara, Ranjan, additional, Ertekin-Taner, NIlüfer, additional, Evans, Denis A., additional, Faber, Kelley M., additional, Fairchild, Thomas J., additional, Fallon, Kenneth B., additional, Fardo, David W., additional, Farlow, Martin R., additional, Fernandez-Hernandez, Victoria, additional, Ferris, Steven, additional, Foroud, Tatiana M., additional, Frosch, Matthew P., additional, Fulton-Howard, Brian, additional, Galasko, Douglas R., additional, Gamboa, Adriana, additional, Gearing, Marla, additional, Geschwind, Daniel H., additional, Ghetti, Bernardino, additional, Gilbert, John R., additional, Goate, Alison M., additional, Grabowski, Thomas J., additional, Graff-Radford, Neill R., additional, Green, Robert C., additional, Growdon, John H., additional, Hakonarson, Hakon, additional, Hall, James, additional, Hamilton, Ronald L., additional, Harari, Oscar, additional, Hardy, John, additional, Harrell, Lindy E., additional, Head, Elizabeth, additional, Henderson, Victor W., additional, Hernandez, Michelle, additional, Hohman, Timothy, additional, Honig, Lawrence S., additional, Huebinger, Ryan M., additional, Huentelman, Matthew J., additional, Hulette, Christine M., additional, Hyman, Bradley T., additional, Hynan, Linda S., additional, Ibanez, Laura, additional, Jarvik, Gail P., additional, Jayadev, Suman, additional, Jin, Lee-Way, additional, Johnson, Kim, additional, Johnson, Leigh, additional, Kamboh, M. Ilyas, additional, Karydas, Anna M., additional, Katz, Mindy J., additional, Kauwe, John S., additional, Kaye, Jeffrey A., additional, Keene, C. Dirk, additional, Khaleeq, Aisha, additional, Kim, Ronald, additional, Knebl, Janice, additional, Kowall, Neil W., additional, Kramer, Joel H., additional, Kukull, Walter A., additional, LaFerla, Frank M., additional, Lah, James J., additional, Larson, Eric B., additional, Lerner, Alan, additional, Leverenz, James B., additional, Levey, Allan I., additional, Lieberman, Andrew P., additional, Lipton, Richard B., additional, Logue, Mark, additional, Lopez, Oscar L., additional, Lunetta, Kathryn L., additional, Lyketsos, Constantine G., additional, Mains, Douglas, additional, Margaret, Flanagan E., additional, Marson, Daniel C., additional, Martin, Eden R R., additional, Martiniuk, Frank, additional, Mash, Deborah C., additional, Masliah, Eliezer, additional, Massman, Paul, additional, Masurkar, Arjun, additional, McCormick, Wayne C., additional, McCurry, Susan M., additional, McDavid, Andrew N., additional, McDonough, Stefan, additional, McKee, Ann C., additional, Mesulam, Marsel, additional, Miller, Bruce L., additional, Miller, Carol A., additional, Miller, Joshua W., additional, Montine, Thomas J., additional, Monuki, Edwin S., additional, Morris, John C., additional, Mukherjee, Shubhabrata, additional, Myers, Amanda J., additional, Nguyen, Trung, additional, O’Bryant, Sid, additional, Olichney, John M., additional, Ory, Marcia, additional, Palmer, Raymond, additional, Parisi, Joseph E., additional, Paulson, Henry L., additional, Pavlik, Valory, additional, Paydarfar, David, additional, Perez, Victoria, additional, Peskind, Elaine, additional, Petersen, Ronald C., additional, Pierce, Aimee, additional, Polk, Marsha, additional, Poon, Wayne W., additional, Potter, Huntington, additional, Qu, Liming, additional, Quiceno, Mary, additional, Quinn, Joseph F., additional, Raj, Ashok, additional, Raskind, Murray, additional, Reiman, Eric M., additional, Reisberg, Barry, additional, Reisch, Joan S., additional, Ringman, John M., additional, Roberson, Erik D., additional, Rodriguear, Monica, additional, Rogaeva, Ekaterina, additional, Rosen, Howard J., additional, Rosenberg, Roger N., additional, Royall, Donald R., additional, Sager, Mark A., additional, Sano, Mary, additional, Saykin, Andrew J., additional, Schneider, Julie A., additional, Schneider, Lon S., additional, Seeley, William W., additional, Slifer, Susan H., additional, Small, Scott, additional, Smith, Amanda G., additional, Smith, Janet P., additional, Sonnen, Joshua A., additional, Spina, Salvatore, additional, St George-Hyslop, Peter, additional, Stern, Robert A., additional, Stevens, Alan B., additional, Strittmatter, Stephen M., additional, Sultzer, David, additional, Swerdlow, Russell H., additional, Tanzi, Rudolph E., additional, Tilson, Jeffrey L., additional, Trojanowski, John Q., additional, Troncoso, Juan C., additional, Tsuang, Debby W., additional, Van Deerlin, Vivianna M., additional, van Eldik, Linda J., additional, Vance, Jeffery M., additional, Vardarajan, Badri N., additional, Vassar, Robert, additional, Vinters, Harry V., additional, Vonsattel, Jean-Paul, additional, Weintraub, Sandra, additional, Welsh-Bohmer, Kathleen A., additional, Whitehead, Patrice L., additional, Wijsman, Ellen M., additional, Wilhelmsen, Kirk C., additional, Williams, Benjamin, additional, Williamson, Jennifer, additional, Wilms, Henrik, additional, Wingo, Thomas S., additional, Wisniewski, Thomas, additional, Woltjer, Randall L., additional, Woon, Martin, additional, Wright, Clinton B., additional, Wu, Chuang-Kuo, additional, Younkin, Steven G., additional, Yu, Chang-En, additional, Yu, Lei, additional, Zhu, Xiongwei, additional, Kunkle, Brian W., additional, Bush, William S., additional, Wang, Li-San, additional, Farrer, Lindsay A., additional, Haines, Jonathan L., additional, Mayeux, Richard, additional, Pericak-Vance, Margaret A., additional, Schellenberg, Gerard D., additional, Jun, Gyungah R., additional, Reitz, Christiane, additional, and Naj, Adam C., additional

Published
2023
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32. Novel loci for Alzheimer's disease identified by a genome‐wide association study in Ashkenazi Jews

Author

Li, Donghe, primary, Farrell, John J., additional, Mez, Jesse, additional, Martin, Eden R., additional, Bush, William S., additional, Ruiz, Agustin, additional, Boada, Mercè, additional, de Rojas, Itziar, additional, Mayeux, Richard, additional, Haines, Jonathan L., additional, Vance, Margaret A. Pericak, additional, Wang, Li‐San, additional, Schellenberg, Gerard D., additional, Lunetta, Kathryn L., additional, and Farrer, Lindsay A., additional

Published
2023
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36. Research on Privacy Issues in Smart Metering System: An Improved TCN-Based NILM Attack Method and Practical DRL-Based Rechargeable Battery Assisted Privacy Preserving Method

Author

Li, Donghe, Yang, Qingyu, Zhang, Feiye, Wang, Yiqun, Qian, Yingchen, and An, Dou

Abstract

Smart meters, as a key component of Advanced Metering Infrastructure (AMI), collect fine-grained electricity consumption data for demand response in smart grids. While this data improves the grid’s accuracy, it also poses significant threats to users’ privacy. In this paper, we study the privacy issue in smart metering systems from both attacker and defender perspectives. First, we propose an improved Temporal Convolutional Network (TCN) based Non-Intrusive Load Monitoring (NILM) attack method, which infers electrical appliance usage from public load curves, addressing the gradient vanishing, gradient exploding, and other problems while improving attack accuracy. Second, we develop a rechargeable battery-assisted energy management system to hide load characteristics of electrical appliances by adding physical noise, thus resisting NILM attacks. To address the privacy-cost trade-off optimization problem, we propose a Practical Deep Reinforcement Learning-based Rechargeable Battery assist Privacy Preserving Method (PRoP) that learns optimal battery charging/discharging policies. We design a novel privacy measurement method and constraints to ensure the feasibility of system deployment and prove PRoP’s effectiveness in resisting NILM attacks. Comprehensive evaluations demonstrate that our improved TCN-based NILM method achieves an attack success rate of over 80% on various electrical appliances, improving attack performance (MAE, RMSE) by 20% compared to existing methods while reducing model training time. Moreover, our proposed PRoP achieves a better trade-off between privacy protection and electricity cost than existing battery-assisted methods, reducing costs by 5% and the attack success ratio to 36%, while increasing the MAE and RMAE obtained by NILM by 3 times. Note to Practitioners—Smart grid, which can support bidirectional information transmission, has a series of advantages, such as high efficiency and high stability. However, it also brings a significant threat to users’ electricity privacy. Although encryption-based privacy protection methods have been deployed on terminal devices of smart grids to prevent privacy leaks, this method can often only defend against intrusive attacks and has little effect on non-intrusive attacks. To this end, this paper studies the privacy issues caused by non-intrusive attacks. Specifically, to better study the protection method, we first investigate the attack mechanism and design an improved TCN-based Non-Intrusive Load Monitoring method. Then, we propose a Practical Reinforcement learning-based rechargeable battery-assisted Privacy preserving method (PRoP) to defend against this attack physically. The most practical contribution of this paper is that, compared with existing battery-assisted privacy protection methods, we do not blindly pursue algorithm performance but fully consider the practical factors of deployment, such as limiting battery capacity and constraining battery charging and discharging behavior. This can guide practitioners to better apply this technology in practice.

Published
2024
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37. Distributed Online Incentive Scheme for Energy Trading in Multi-Microgrid Systems

Author

An, Dou, Yang, Qingyu, Li, Donghe, and Wu, Zongze

Abstract

Microgrids (MGs) are essential components of a smart grid, and they play an important role in assisting smart grid operation. Furthermore, multi-MG systems, which can further improve smart grid operation, raise significant challenges in terms of management and interoperation because of their increased complexity. To address this, we propose a multi-bid online incentive scheme for energy trading in multi-MG systems, in which MGs act as buyers and sellers to trade surplus energy. In the proposed system, buyer MGs can submit multiple bids to different sellers, and the distributed MG system operator matches buyer and seller MGs in a way that maximizes the utility of buyers. Theoretical analysis demonstrates that the proposed method meets the properties of incentive compatibility and individual rationality. Moreover, through detailed performance evaluation, the proposed scheme was capable of achieving better performance in comparison with existing schemes regarding utility, energy purchasing cost, and buyer MG’s satisfaction ratio. Our experimental results also demonstrated that the proposed scheme could shift the system peak-load, improving the robustness of the multi-MG system. Note to Practitioners—In this article, we addressed the energy trading issues in multi-microgrid (MG) system, and proposed a distributed incentive mechanism to achieve more flexible and efficient energy allocation. Most existing works on energy trading use centralized methods, which means all electrical users will submit only one bid to the platform, and finally the platform decides to match the trading parties. This will lead to users unable to actively choose trading partners, thus reducing the volume of the whole market. To this end, in this paper, we proposed a distributed incentive mechanism for the multiple microgrid system, in which the buyer microgrids are able to submit multiple bids to different sellers. Moreover, each seller microgrids act as a distributed energy market, and the distributed MG system operator matches the buyers and sellers which aims to maximize the utility of buyers. The proposed scheme is helpful in managing the energy trading among the multi-MG system and can be readily implemented in the real-world large-scale electricity trading market.

Published
2024
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47. Novel Loci for Alzheimer Disease Identified by Genome Wide Association Study in Ashkenazi Jews

Author

Li, Donghe, primary, Farrell, John, additional, Mez, Jesse B., additional, Martin, Eden R., additional, Bush, William S., additional, Mayeux, Richard, additional, Haines, Jonathan L., additional, Pericak‐Vance, Margaret A., additional, Wang, Li‐San, additional, Schellenberg, Gerard D., additional, Lunetta, Kathryn L., additional, and Farrer, Lindsay A., additional

Published
2022
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49. Heritability Analyses Uncover Shared Genetic Effects of Lung Function and Change over Time

Author

Li, Donghe, primary, Kim, Woojin, additional, An, Jahoon, additional, Kim, Soriul, additional, Lee, Seungku, additional, Do, Ahra, additional, Kim, Wonji, additional, Lee, Sanghun, additional, Yoon, Dankyu, additional, Lee, Kwangbae, additional, Ha, Seounguk, additional, Silverman, Edwin K., additional, Cho, Michael, additional, Shin, Chol, additional, and Won, Sungho, additional

Published
2022
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