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Browsing by Author "Chen, Christopher"
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Item Designing the next-generation clinical care pathway for Alzheimer’s disease(Springer Nature, 2022) Hampel, Harald; Au, Rhoda; Mattke, Soeren; van der Flier, Wiesje M.; Aisen, Paul; Apostolova, Liana; Chen, Christopher; Cho, Min; De Santi, Susan; Gao, Peng; Iwata, Atsushi; Kurzman, Ricky; Saykin, Andrew J.; Teipel, Stefan; Vellas, Bruno; Vergallo, Andrea; Wang, Huali; Cummings, Jeffrey; Neurology, School of MedicineThe reconceptualization of Alzheimer's disease (AD) as a clinical and biological construct has facilitated the development of biomarker-guided, pathway-based targeted therapies, many of which have reached late-stage development with the near-term potential to enter global clinical practice. These medical advances mark an unprecedented paradigm shift and requires an optimized global framework for clinical care pathways for AD. In this Perspective, we describe the blueprint for transitioning from the current, clinical symptom-focused and inherently late-stage diagnosis and management of AD to the next-generation pathway that incorporates biomarker-guided and digitally facilitated decision-making algorithms for risk stratification, early detection, timely diagnosis, and preventative or therapeutic interventions. We address critical and high-priority challenges, propose evidence-based strategic solutions, and emphasize that the perspectives of affected individuals and care partners need to be considered and integrated.Item Does Renewable Energy Renew the Endeavor in Energy Efficiency?(2022-03-29) Awaysheh, Amrou; Chen, Christopher; Wu, Owen Q.Improvement in energy efficiency (EE) has slowed globally since 2015 and is now falling short of the 2.6% per year target recommended by the United Nations Sustainable Development Goals, despite an abundance of EE opportunities. Barriers to EE have existed long before the rise in renewable energy (RE) investment. However, increased RE adoption may have unintended consequences for improving EE as adoption may raise or lower the barriers to EE. In this paper, we examine whether and how RE adoption can increase or decrease EE improvement. On the one hand, RE represent a competitor to EE for managerial attention and budget. On the other, the adoption of RE may increase the overall awareness of energy usage and drive EE improvement. Using site-level data from an industrial conglomerate, we estimate the impact of changes in RE usage and in the acquisition approach on the EE of 183 manufacturing sites across the globe from 2015 to 2020. On average, we find that using RE to meet 10% more of a site’s energy demand led to an additional 2.0% improvement in EE. However, there is significant heterogeneity in the effects depending on the acquisition approach. We find that while purchasing RE credits or entering into power purchase agreements led to gains in EE, installing on-site RE generators had no effect. To understand these gains, we surveyed site managers regarding their attitudes and intentions. The results suggest that there was a greater focus on EE by both managers and workers after increasing their RE usage. We also find quantitative evidence of managers submitting more budget requests for EE improvements in the twelve months following increases in RE. For corporations looking to use more RE, we offer evidence of additional returns in the form of energy savings, but realizing them requires careful consideration of the acquisition approach of RE.Item Genetic architecture of subcortical brain structures in 38,851 individuals(Nature, 2019-11) Satizabal, Claudia L.; Adams, Hieab H. H.; Hibar, Derrek P.; White, Charles C.; Knol, Maria J.; Stein, Jason L.; Scholz, Markus; Sargurupremraj, Muralidharan; Jahanshad, Neda; Roshchupkin, Gennady V.; Smith, Albert V.; Bis, Joshua C.; Jian, Xueqiu; Luciano, Michelle; Hofer, Edith; Teumer, Alexander; van der Lee, Sven J.; Yang, Jingyun; Yanek, Lisa R.; Lee, Tom V.; Li, Shuo; Hu, Yanhui; Koh, Jia Yu; Eicher, John D.; Desrivières, Sylvane; Arias-Vasquez, Alejandro; Chauhan, Ganesh; Athanasiu, Lavinia; Rentería, Miguel E.; Kim, Sungeun; Hoehn, David; Armstrong, Nicola J.; Chen, Qiang; Holmes, Avram J.; den Braber, Anouk; Kloszewska, Iwona; Andersson, Micael; Espeseth, Thomas; Grimm, Oliver; Abramovic, Lucija; Alhusaini, Saud; Milaneschi, Yuri; Papmeyer, Martina; Axelsson, Tomas; Ehrlich, Stefan; Roiz-Santiañez, Roberto; Kraemer, Bernd; Håberg, Asta K.; Jones, Hannah J.; Pike, G. Bruce; Stein, Dan J.; Stevens, Allison; Bralten, Janita; Vernooij, Meike W.; Harris, Tamara B.; Filippi, Irina; Witte, A. Veronica; Guadalupe, Tulio; Wittfeld, Katharina; Mosley, Thomas H.; Becker, James T.; Doan, Nhat Trung; Hagenaars, Saskia P.; Saba, Yasaman; Cuellar-Partida, Gabriel; Amin, Najaf; Hilal, Saima; Nho, Kwangsik; Mirza-Schreiber, Nazanin; Arfanakis, Konstantinos; Becker, Diane M.; Ames, David; Goldman, Aaron L.; Lee, Phil H.; Boomsma, Dorret I.; Lovestone, Simon; Giddaluru, Sudheer; Le Hellard, Stephanie; Mattheisen, Manuel; Bohlken, Marc M.; Kasperaviciute, Dalia; Schmaal, Lianne; Lawrie, Stephen M.; Agartz, Ingrid; Walton, Esther; Tordesillas-Gutierrez, Diana; Davies, Gareth E.; Shin, Jean; Ipser, Jonathan C.; Vinke, Louis N.; Hoogman, Martine; Jia, Tianye; Burkhardt, Ralph; Klein, Marieke; Crivello, Fabrice; Janowitz, Deborah; Carmichael, Owen; Haukvik, Unn K.; Aribisala, Benjamin S.; Schmidt, Helena; Strike, Lachlan T.; Cheng, Ching-Yu; Risacher, Shannon L.; Pütz, Benno; Fleischman, Debra A.; Assareh, Amelia A.; Mattay, Venkata S.; Buckner, Randy L.; Mecocci, Patrizia; Dale, Anders M.; Cichon, Sven; Boks, Marco P.; Matarin, Mar; Penninx, Brenda W. J. H.; Calhoun, Vince D.; Chakravarty, M. Mallar; Marquand, Andre F.; Macare, Christine; Kharabian Masouleh, Shahrzad; Oosterlaan, Jaap; Amouyel, Philippe; Hegenscheid, Katrin; Rotter, Jerome I.; Schork, Andrew J.; Liewald, David C. M.; de Zubicaray, Greig I.; Wong, Tien Yin; Shen, Li; Sämann, Philipp G.; Brodaty, Henry; Roffman, Joshua L.; de Geus, Eco J. C.; Tsolaki, Magda; Erk, Susanne; van Eijk, Kristel R.; Cavalleri, Gianpiero L.; van der Wee, Nic J. A.; McIntosh, Andrew M.; Gollub, Randy L.; Bulayeva, Kazima B.; Bernard, Manon; Richards, Jennifer S.; Himali, Jayandra J.; Loeffler, Markus; Rommelse, Nanda; Hoffmann, Wolfgang; Westlye, Lars T.; Valdés Hernández, Maria C.; Hansell, Narelle K.; van Erp, Theo G. M.; Wolf, Christiane; Kwok, John B. J.; Vellas, Bruno; Heinz, Andreas; Olde Loohuis, Loes M.; Delanty, Norman; Ho, Beng-Choon; Ching, Christopher R. K.; Shumskaya, Elena; Singh, Baljeet; Hofman, Albert; van der Meer, Dennis; Homuth, Georg; Psaty, Bruce M.; Bastin, Mark E.; Montgomery, Grant W.; Foroud, Tatiana M.; Reppermund, Simone; Hottenga, Jouke-Jan; Simmons, Andrew; Meyer-Lindenberg, Andreas; Cahn, Wiepke; Whelan, Christopher D.; van Donkelaar, Marjolein M. J.; Yang, Qiong; Hosten, Norbert; Green, Robert C; Thalamuthu, Anbupalam; Mohnke, Sebastian; Hulshoff Pol, Hilleke E.; Lin, Honghuang; Jack, Clifford R.; Schofield, Peter R.; Mühleisen, Thomas W.; Maillard, Pauline; Potkin, Steven G.; Wen, Wei; Fletcher, Evan; Toga, Arthur W.; Gruber, Oliver; Huentelman, Matthew; Davey Smith, George; Launer, Lenore J.; Nyberg, Lars; Jönsson, Erik G.; Crespo-Facorro, Benedicto; Koen, Nastassja; Greve, Douglas N.; Uitterlinden, André G.; Weinberger, Daniel R.; Steen, Vidar M.; Fedko, Iryna O.; Groenewold, Nynke A.; Niessen, Wiro J.; Toro, Roberto; Tzourio, Christophe; Longstreth, William T.; Ikram, M. Kamran; Smoller, Jordan W.; van Tol, Marie-Jose; Sussmann, Jessika E.; Paus, Tomas; Lemaître, Hervé; Schroeter, Matthias L.; Mazoyer, Bernard; Andreassen, Ole A.; Holsboer, Florian; Depondt, Chantal; Veltman, Dick J.; Turner, Jessica A.; Pausova, Zdenka; Schumann, Gunter; van Rooij, Daan; Djurovic, Srdjan; Deary, Ian J.; McMahon, Katie L.; Müller-Myhsok, Bertram; Brouwer, Rachel M.; Soininen, Hilkka; Pandolfo, Massimo; Wassink, Thomas H.; Cheung, Joshua W.; Wolfers, Thomas; Martinot, Jean-Luc; Zwiers, Marcel P.; Nauck, Matthias; Melle, Ingrid; Martin, Nicholas G.; Kanai, Ryota; Westman, Eric; Kahn, René S.; Sisodiya, Sanjay M.; White, Tonya; Saremi, Arvin; van Bokhoven, Hans; Brunner, Han G.; Völzke, Henry; Wright, Margaret J.; van ‘t Ent, Dennis; Nöthen, Markus M.; Ophoff, Roel A.; Buitelaar, Jan K.; Fernández, Guillén; Sachdev, Perminder S.; Rietschel, Marcella; van Haren, Neeltje E. M.; Fisher, Simon E.; Beiser, Alexa S.; Francks, Clyde; Saykin, Andrew J.; Mather, Karen A.; Romanczuk-Seiferth, Nina; Hartman, Catharina A.; DeStefano, Anita L.; Heslenfeld, Dirk J.; Weiner, Michael W.; Walter, Henrik; Hoekstra, Pieter J.; Nyquist, Paul A.; Franke, Barbara; Bennett, David A.; Grabe, Hans J.; Johnson, Andrew D.; Chen, Christopher; van Duijn, Cornelia M.; Lopez, Oscar L.; Fornage, Myriam; Wardlaw, Joanna M.; Schmidt, Reinhold; DeCarli, Charles; De Jager, Philip L.; Villringer, Arno; Debette, Stéphanie; Gudnason, Vilmundur; Medland, Sarah E.; Shulman, Joshua M.; Thompson, Paul M.; Seshadri, Sudha; Ikram, M. Arfan; Medical and Molecular Genetics, School of MedicineSubcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.Item Independent and joint associations of cardiometabolic multimorbidity and depression on cognitive function: findings from multi-regional cohorts and generalisation from community to clinic(Elsevier, 2024-09-12) Zhao, Xuhao; Xu, Xiaolin; Yan, Yifan; Lipnicki, Darren M.; Pang, Ting; Crawford, John D.; Chen, Christopher; Cheng, Ching-Yu; Venketasubramanian, Narayanaswamy; Chong, Eddie; Blay, Sergio Luis; Lima-Costa, Maria Fernanda; Castro-Costa, Erico; Lipton, Richard B.; Katz, Mindy J.; Ritchie, Karen; Scarmeas, Nikolaos; Yannakoulia, Mary; Kosmidis, Mary H.; Gureje, Oye; Ojagbemi, Akin; Bello, Toyin; Hendrie, Hugh C.; Gao, Sujuan; Guerra, Ricardo Oliveira; Auais, Mohammad; Gomez, José Fernando; Rolandi, Elena; Davin, Annalisa; Rossi, Michele; Riedel-Heller, Steffi G.; Löbner, Margit; Roehr, Susanne; Ganguli, Mary; Jacobsen, Erin P.; Chang, Chung-Chou H.; Aiello, Allison E.; Ho, Roger; Sanchez-Juan, Pascual; Valentí-Soler, Meritxell; Del Ser, Teodoro; Lobo, Antonio; De-la-Cámara, Concepción; Lobo, Elena; Sachdev, Perminder S.; Xu, Xin; Cohort Studies of Memory in an International Consortium (COSMIC); Psychiatry, School of MedicineBackground: Cardiometabolic multimorbidity (CMM) and depression are often co-occurring in older adults and associated with neurodegenerative outcomes. The present study aimed to estimate the independent and joint associations of CMM and depression on cognitive function in multi-regional cohorts, and to validate the generalizability of the findings in additional settings, including clinical. Methods: Data harmonization was performed across 14 longitudinal cohort studies within the Cohort Studies of Memory in an International Consortium (COSMIC) group, spanning North America, South America, Europe, Africa, Asia, and Australia. Three external validation studies with distinct settings were employed for generalization. Participants were eligible for inclusion if they had data for CMM and were free of dementia at baseline. Baseline CMM was defined as: 1) CMM 5, ≥2 among hypertension, hyperlipidemia, diabetes, stroke, and heart disease and 2) CMM 3 (aligned with previous studies), ≥2 among diabetes, stroke, and heart disease. Baseline depression was primarily characterized by binary classification of depressive symptom measurements, employing the Geriatric Depression Scale and the Center for Epidemiological Studies-Depression scale. Global cognition was standardized as z-scores through harmonizing multiple cognitive measures. Longitudinal cognition was calculated as changes in global cognitive z-scores. A pooled individual participant data (IPD) analysis was utilized to estimate the independent and joint associations of CMM and depression on cognitive outcomes in COSMIC studies, both cross-sectionally and longitudinally. Repeated analyses were performed in three external validation studies. Findings: Of the 32,931 older adults in the 14 COSMIC cohorts, we included 30,382 participants with complete data on baseline CMM, depression, and cognitive assessments for cross-sectional analyses. Among them, 22,599 who had at least 1 follow-up cognitive assessment were included in the longitudinal analyses. The three external studies for validation had 1964 participants from 3 multi-ethnic Asian older adult cohorts in different settings (community-based, memory clinic, and post-stroke study). In COSMIC studies, each of CMM and depression was independently associated with cross-sectional and longitudinal cognitive function, without significant interactions between them (Ps > 0.05). Participants with both CMM and depression had lower cross-sectional cognitive performance (e.g. β = -0.207, 95% CI = (-0.255, -0.159) for CMM5 (+)/depression (+)) and a faster rate of cognitive decline (e.g. β = -0.040, 95% CI = (-0.047, -0.034) for CMM5 (+)/depression (+)), compared with those without either condition. These associations remained consistent after additional adjustment for APOE genotype and were robust in two-step random-effects IPD analyses. The findings regarding the joint association of CMM and depression on cognitive function were reproduced in the three external validation studies. Interpretation: Our findings highlighted the importance of investigating age-related co-morbidities in a multi-dimensional perspective. Targeting both cardiometabolic and psychological conditions to prevent cognitive decline could enhance effectiveness.Item Operations (management) warp speed: Rapid deployment of hospital‐focused predictive/prescriptive analytics for the COVID‐19 pandemic(Wiley, 2022) Shi, Pengyi; Helm, Jonathan E.; Chen, Christopher; Lim, Jeff; Parker, Rodney P.; Tinsley, Troy; Cecil, Jacob; Indiana University HealthAt the onset of the COVID-19 pandemic, hospitals were in dire need of data-driven analytics to provide support for critical, expensive, and complex decisions. Yet, the majority of analytics being developed were targeted at state- and national-level policy decisions, with little availability of actionable information to support tactical and operational decision making and execution at the hospital level. To fill this gap, we developed a multi-method framework leveraging a parsimonious design philosophy that allows for rapid deployment of high-impact predictive and prescriptive analytics in a time-sensitive, dynamic, data-limited environment, such as a novel pandemic. The product of this research is a workload prediction and decision support tool to provide mission-critical, actionable information for individual hospitals. Our framework forecasts time-varying patient workload and demand for critical resources by integrating disease progression models, tailored to data availability during different stages of the pandemic, with a stochastic network model of patient movements among units within individual hospitals. Both components employ adaptive tuning to account for hospital-dependent, time-varying parameters that provide consistently accurate predictions by dynamically learning the impact of latent changes in system dynamics. Our decision support system is designed to be portable and easily implementable across hospital data systems for expeditious expansion and deployment. This work was contextually grounded in close collaboration with IU Health, the largest health system in Indiana, which has 18 hospitals serving over one million residents. Our initial prototype was implemented in April 2020 and has supported managerial decisions, from the operational to the strategic, across multiple functionalities at IU Health.