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Item A pathway linking pulse pressure to dementia in adults with Down syndrome(Oxford University Press, 2024-05-09) Rizvi, Batool; Lao, Patrick J.; Sathishkumar, Mithra; Taylor, Lisa; Queder, Nazek; McMillan, Liv; Edwards, Natalie C.; Keator, David B.; Doran, Eric; Hom, Christy; Nguyen, Dana; Rosas, H. Diana; Lai, Florence; Schupf, Nicole; Gutierrez, Jose; Silverman, Wayne; Lott, Ira T.; Mapstone, Mark; Wilcock, Donna M.; Head, Elizabeth; Yassa, Michael A.; Brickman, Adam M.; Neurology, School of MedicineAdults with Down syndrome are less likely to have hypertension than neurotypical adults. However, whether blood pressure measures are associated with brain health and clinical outcomes in this population has not been studied in detail. Here, we assessed whether pulse pressure is associated with markers of cerebrovascular disease and is linked to a diagnosis of dementia in adults with Down syndrome via structural imaging markers of cerebrovascular disease and atrophy. The study included participants with Down syndrome from the Alzheimer’s Disease - Down Syndrome study (n = 195, age = 50.6 ± 7.2 years, 44% women, 18% diagnosed with dementia). Higher pulse pressure was associated with greater global, parietal and occipital white matter hyperintensity volume but not with enlarged perivascular spaces, microbleeds or infarcts. Using a structural equation model, we found that pulse pressure was associated with greater white matter hyperintensity volume, which in turn was related to increased neurodegeneration, and subsequent dementia diagnosis. Pulse pressure is an important determinant of brain health and clinical outcomes in individuals with Down syndrome despite the low likelihood of frank hypertension.Item Comparison of amyloid accumulation between Down syndrome and autosomal-dominant Alzheimer disease(Wiley, 2022) Boerwinkle, Anna H.; Gordon, Brian A.; Wisch, Julie K.; Flores, Shaney; Henson, Rachel L.; Butt, Omar Hameed; Chen, Charles D.; Benzinger, Tammie L. S.; Fagan, Anne M.; Handen, Benjamin L.; Christian, Bradley T.; Head, Elizabeth; Mapstone, Mark; Klunk, William E.; Rafii, Michael S.; O’Bryant, Sid E.; Price, Julie C.; Schupf, Nicole; Laymon, Charles M.; Krinsky-McHale, Sharon J.; Lai, Florence; Rosas, H. Diana; Hartley, Sigan L.; Zaman, Shahid; Lott, Ira T.; Silverman, Wayne; Brickman, Adam M.; Lee, Joseph H.; Allegri, Ricardo Francisco; Berman, Sarah; Chhatwal, Jasmeer P.; Chui, Helena C.; Cruchaga, Carlos; Farlow, Martin R.; Fox, Nick C.; Goate, Alison; Day, Gregory S.; Graff-Radford, Neill R.; Jucker, Mathias; Lee, Jae-Hong; Levin, Johannes; Martins, Ralph N.; Mori, Hiroshi; Perrin, Richard J.; Salloway, Stephen P.; Sanchez-Valle, Raquel; Schofield, Peter R.; Xiong, Chengjie; Karch, Celeste M.; Hassenstab, Jason J.; McDade, Eric; Bateman, Randall J.; Ances, Beau M.; Neurology, School of MedicineBackground: Given the triplication of chromosome 21 and the location of the amyloid precursor protein gene on chromosome 21, almost all adults with Down syndrome (DS) develop Alzheimer disease (AD)-like pathology and dementia during their lifetime. Comparing amyloid accumulation in DS to autosomal dominant AD (ADAD), another genetic form of AD, may improve our understanding of early AD pathology development. Method: We assessed amyloid positron emission tomography (PET) imaging in 192 participants with DS and 33 sibling controls from the Alzheimer’s Biomarker Consortium-Down Syndrome (ABC-DS) and 265 mutation-carriers (MC) and 169 familial controls from the Dominantly Inherited Alzheimer Network (DIAN) (Table 1). We calculated regional standard uptake value ratios (SUVR) using a cerebellar cortex reference region and converted global amyloid burden SUVR to centiloids. We compared amyloid PET by cognitive status and estimated-years-to-symptom-onset (EYO). EYO was calculated for DIAN participants by subtracting their age from parental age of symptom onset and for ABC-DS participants by subtracting their age from 50.2 years, a published average age of symptom onset in a large sample of individuals with DS (Fortea et al., 2020). In a subset of participants, we assessed the relationship between amyloid PET and CSF Aβ42/40. Result: The relationship between CSF Aβ42/40 and amyloid PET was similar in DS and MC participants (Figure 1). We did not observe significant differences between MC and DS grouped by cognitive status (Figure 2). However, when assessed over EYO, global amyloid burden was significantly elevated in MC at EYO ≥ -23 but was not elevated in DS until EYO ≥ -15 (Figure 3). We observed early cortical and subcortical amyloid PET increases in both groups, but we also measured some regional differences in amyloid PET changes between MC and DS, specifically in the medial occipital region (Figure 4 and 5). Conclusion: These results demonstrate similarities in the relationship between amyloid biomarkers and the levels of amyloid accumulation in ADAD and DS. However, we also observed a 5-10 year delay and some regional differences in amyloid accumulation in DS. This is important for future clinical trials to consider when recruiting participants and determining treatment efficacy.Item Genome-wide analysis identifies 12 loci influencing human reproductive behavior(Nature, 2016-10) Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; van der Laan, Sander W.; Perry, John R. B.; Kong, Augustine; Ahluwalia, Tarunveer; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; van der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Panagiota, Kalafati Ioanna; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathy; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tonjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellman, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverly; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Daniela, Toniolo; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M.; de Geus, Eco J. C.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Felicita, Sala Cinzia; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J. F.; de Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G.; Hopper, John; Hypponen, Elina; Jacobsson, Bo; Jaddoe, Vincent W.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L. R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William; Lai, Sandra; Lehtimäki, Terho; Liewald, David C.; Lindgren, Cecilia; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K. E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Michela, Traglia; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A.; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda W. J. H.; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tönjes, Anke; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefannson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.; Department of Epidemiology, Richard M. Fairbanks School of Public HealthThe genetic architecture of human reproductive behavior—age at first birth (AFB) and number of children ever born (NEB)—has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.Item Guidelines for the standardization of preanalytic variables for blood-based biomarker studies in Alzheimer's disease research(Elsevier, 2015-05) O’Bryant, Sid E.; Gupta, Veer; Henriksen, Kim; Edwards, Melissa; Jeromin, Andreas; Lista, Simone; Bazenet, Chantal; Soares, Holly; Lovestone, Simon; Hampel, Harald; Montine, Thomas; Blennow, Kaj; Foroud, Tatiana; Carrillo, Maria; Graff-Radford, Neill; Laske, Christoph; Breteler, Monique; Shaw, Leslie; Trojanowski, John Q.; Schupf, Nicole; Rissman, Robert A.; Fagan, Anne M.; Oberoi, Pankaj; Umek, Robert; Weiner, Michael W.; Grammas, Paul; Posner, Holly; Martins, Ralph; Department of Medical & Molecular Genetics, IU School of MedicineThe lack of readily available biomarkers is a significant hindrance towards progressing to effective therapeutic and preventative strategies for Alzheimer’s disease (AD). Blood-based biomarkers have potential to overcome access and cost barriers and greatly facilitate advanced neuroimaging and cerebrospinal fluid biomarker approaches. Despite the fact that preanalytical processing is the largest source of variability in laboratory testing, there are no currently available standardized preanalytical guidelines. The current international working group provides the initial starting point for such guidelines for standardized operating procedures (SOPs). It is anticipated that these guidelines will be updated as additional research findings become available. The statement provides (1) a synopsis of selected preanalytical methods utilized in many international AD cohort studies, (2) initial draft guidelines/SOPs for preanalytical methods, and (3) a list of required methodological information and protocols to be made available for publications in the field in order to foster cross-validation across cohorts and laboratories.Item Joint-label fusion brain atlases for dementia research in Down syndrome(Wiley, 2022-05-25) Queder, Nazek; Phelan, Michael J.; Taylor, Lisa; Tustison, Nicholas; Doran, Eric; Hom, Christy; Nguyen, Dana; Lai, Florence; Pulsifer, Margaret; Price, Julie; Kreisl, William C.; Rosas, Herminia D.; Krinsky-McHale, Sharon; Brickman, Adam M.; Yassa, Michael A.; Schupf, Nicole; Silverman, Wayne; Lott, Ira T.; Head, Elizabeth; Mapstone, Mark; Keator, David B.; Alzheimer’s Biomarkers Consortium; Neurology, School of MedicineResearch suggests a link between Alzheimer's Disease in Down Syndrome (DS) and the overproduction of amyloid plaques. Using Positron Emission Tomography (PET) we can assess the in-vivo regional amyloid load using several available ligands. To measure amyloid distributions in specific brain regions, a brain atlas is used. A popular method of creating a brain atlas is to segment a participant's structural Magnetic Resonance Imaging (MRI) scan. Acquiring an MRI is often challenging in intellectually-imparied populations because of contraindications or data exclusion due to significant motion artifacts or incomplete sequences related to general discomfort. When an MRI cannot be acquired, it is typically replaced with a standardized brain atlas derived from neurotypical populations (i.e. healthy individuals without DS) which may be inappropriate for use in DS. In this project, we create a series of disease and diagnosis-specific (cognitively stable (CS-DS), mild cognitive impairment (MCI-DS), and dementia (DEM-DS)) probabilistic group atlases of participants with DS and evaluate their accuracy of quantifying regional amyloid load compared to the individually-based MRI segmentations. Further, we compare the diagnostic-specific atlases with a probabilistic atlas constructed from similar-aged cognitively-stable neurotypical participants. We hypothesized that regional PET signals will best match the individually-based MRI segmentations by using DS group atlases that aligns with a participant's disorder and disease status (e.g. DS and MCI-DS). Our results vary by brain region but generally show that using a disorder-specific atlas in DS better matches the individually-based MRI segmentations than using an atlas constructed from cognitively-stable neurotypical participants. We found no additional benefit of using diagnose-specific atlases matching disease status. All atlases are made publicly available for the research community.Item Plasma Total-Tau and Neurofilament Light Chain as Diagnostic Biomarkers of Alzheimer's Disease Dementia and Mild Cognitive Impairment in Adults with Down Syndrome(IOS Press, 2021) Petersen, Melissa E.; Rafii, Michael S.; Zhang, Fan; Hall, James; Julovich, David; Ances, Beau M.; Schupf, Nicole; Krinsky-McHale, Sharon J.; Mapstone, Mark; Silverman, Wayne; Lott, Ira; Klunk, William; Head, Elizabeth; Christian, Brad; Foroud, Tatiana; Lai, Florence; Rosas, H. Diana; Zaman, Shahid; Wang, Mei-Cheng; Tycko, Benjamin; Lee, Joseph H.; Handen, Benjamin; Hartley, Sigan; Fortea, Juan; O’Bryant, Sid; Alzheimer’s Biomarker Consortium – Down Syndrome (ABC-DS); Medical and Molecular Genetics, School of MedicineBackground: The need for diagnostic biomarkers of cognitive decline is particularly important among aging adults with Down syndrome (DS). Growing empirical support has identified the utility of plasma derived biomarkers among neurotypical adults with mild cognitive impairment (MCI) and Alzheimer's disease (AD); however, the application of such biomarkers has been limited among the DS population. Objective: This study aimed to investigate the cross-sectional diagnostic performance of plasma neurofilament light chain (Nf-L) and total-tau, individually and in combination among a cohort of DS adults. Methods: Plasma samples were analyzed from n = 305 (n = 225 cognitively stable (CS); n = 44 MCI-DS; n = 36 DS-AD) participants enrolled in the Alzheimer's Biomarker Consortium -Down Syndrome. Results: In distinguishing DS-AD participants from CS, Nf-L alone produced an AUC of 90%, total-tau alone reached 74%, and combined reached an AUC of 86%. When age and gender were included, AUC increased to 93%. Higher values of Nf-L, total-tau, and age were all shown to be associated with increased risk for DS-AD. When distinguishing MCI-DS participants from CS, Nf-L alone produced an AUC of 65%, while total-tau alone reached 56%. A combined model with Nf-L, total-tau, age, and gender produced an AUC of 87%. Both higher values in age and total-tau were found to increase risk for MCI-DS; Nf-L levels were not associated with increased risk for MCI-DS. Conclusion: Advanced assay techniques make total-tau and particularly Nf-L useful biomarkers of both AD pathology and clinical status in DS and have the potential to serve as outcome measures in clinical trials for future disease-modifying drugs.