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Browsing by Author "Maillard, Pauline"
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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 Novel rare variant associations with late‐life cognitive performance(Wiley, 2025-01-09) Regelson, Alexandra N.; Archer, Derek B.; Durant, Alaina; Mukherjee, Shubhabrata; Lee, Michael L.; Choi, Seo-Eun; Scollard, Phoebe; Trittschuh, Emily H.; Mez, Jesse; Bush, William S.; Kuzma, Amanda B.; Cuccaro, Michael L.; Cruchaga, Carlos; Farrer, Lindsay A.; Wang, Li-San; Schellenberg, Gerard D.; Mayeux, Richard; Kukull, Walter A.; Keene, C. Dirk; Saykin, Andrew J.; Johnson, Sterling C.; Engelman, Corinne D.; Bennett, David A.; Barnes, Lisa L.; Larson, Eric B.; Nho, Kwangsik; Goate, Alison M.; Renton, Alan E.; Marcora, Edoardo; Fulton-Howard, Brian; Patel, Tulsi; Risacher, Shannon L.; DeStefano, Anita L.; Schneider, Julie A.; Habes, Mohamad; Seshadri, Sudha; Satizabal, Claudia L.; Maillard, Pauline; Toga, Arthur W.; Crawford, Karen; Tosun, Duygu; Vance, Jeffery M.; Mormino, Elizabeth; DeCarli, Charles S.; Montine, Thomas J.; Beecham, Gary; Biber, Sarah A.; De Jager, Philip L.; Vardarajan, Badri N.; Lee, Annie J.; Brickman, Adam M.; Reitz, Christiane; Manly, Jennifer J.; Lu, Qiongshi; Rentería, Miguel Arce; Deming, Yuetiva; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Crane, Paul K.; Hohman, Timothy J.; Dumitrescu, Logan C.; Medical and Molecular Genetics, School of MedicineBackground: Despite evidence that Alzheimer’s disease (AD) is highly heritable, there remains substantial “missing” heritability, likely due in part to the effect of rare variants and to the past reliance on case‐control analysis. Here, we leverage powerful endophenotypes of AD (cognitive performance across multiple cognitive domains) in a rare variant analysis to identify novel genetic drivers of cognition in aging and disease. Method: We leveraged 8 cohorts of cognitive aging with whole genome sequencing data from the AD Sequencing Project to conduct rare variant analyses of multiple domains of cognition (N = 9,317; mean age = 73; 56% female; 52% cognitively unimpaired). Harmonized scores for memory, executive function, and language were derived using confirmatory factor analysis models. Participants genetically similar to the 1000Genomes EUR reference panel were included in analysis. Variants included in the analysis had a minor allele frequency < 0.01, a minor allele count of ≥ 10, and were annotated as a high or moderate impact SNP using VEP. Associations of baseline scores in each cognitive domain were performed using SKAT‐O, including 92,905 rare variants among 16,243 genes. All tests were adjusted for sex, baseline age, sequencing center and platform, and genetic principal components. Correction for multiple comparisons was completed using the Benjamini‐Hochberg false discovery rate (FDR) procedure. Result: APOE was associated with baseline memory, language, and executive function, though only memory survived multiple‐test correction (p.FDR = 0.001). Outside of APOE, ITPKB was associated with baseline executive function (p.FDR = 0.048). AKTIP, SHCBP1L, and CCNF showed nominal associations with multiple domains of cognition that did not survive correction for multiple comparisons (p.FDRs<0.07). Conclusion: These results highlight novel rare variants associated with cognition. IPTKB is an AGORA nominated gene target for potential AD treatment. It is important in the regulation of immune cells and displays higher expression in the cortex of AD patients compared to controls. CCNF and AKTIP are brain eQTLs and have differential RNA expression in AD brains. Previously, variants in AKTIP have been associated with educational attainment, intelligence, and memory, while variants in CCNF have been associated with neuritic plaques and neurofibrillary tangles. Future analyses will incorporate longitudinal cognition and expand into additional populations.Item Plasma neurofilament light as a biomarker for vascular contributions to cognitive impairment and dementia(Wiley, 2025-01-09) Kautz, Tiffany F.; Mathews, Julia J.; Bernal, Rebecca; Wang, Chen-Pin; Liu, Qianqian; Gonzales, Mitzi M.; Tracy, Russell P.; Parent, Danielle; Wilcock, Donna M.; Sudduth, Tiffany L.; Wang, Danny J. J.; Sagare, Abhay P.; Rosenberg, Gary A.; Lu, Hanzhang; Kramer, Joel H.; Decarli, Charles; Jin, Lee-Way; Maillard, Pauline; Singh, Herpreet; Schwab, Kristin; Helmer, Karl; Greenberg, Steven M.; Kivisäkk, Pia; Aparicio, Hugo J.; Beiser, Alexa S.; Ghosh, Saptaparni; Fornage, Myriam; Mosley, Thomas H.; Mbangdadji, Djass; Launer, Lenore J.; Gudnason, Vilmundur; Bis, Josh; Psaty, Bruce M.; Seshadri, Sudha; Satizabal, Claudia L.; Neurology, School of MedicineBackground: The MarkVCID consortium was established to address the paucity of biomarkers for vascular contributions to cognitive impairment and dementia (VCID), a leading cause of dementia. Plasma neurofilament light (NfL), a neuroaxonal injury marker elevated in several neurological and neurodegenerative diseases, was selected as one of the first biomarkers to be examined. We performed comprehensive instrumental and clinical validation of the Quanterix Simoa NfL assay using the first MarkVCID cohort. Method: Plasma NfL was measured using HD‐X and HD‐1 Simoa instruments. Samples from the MarkVCID consortium were used to evaluate intra‐ and inter‐plate reliability, test‐retest repeatability, and inter‐site reproducibility. We used linear regression models to assess the association of NfL in MarkVCID with general cognitive function (GCF) as the primary outcome (n=331). In secondary analyses we assessed NfL associations with white matter hyperintensities (WMH). Models were adjusted for potential confounders, including eGFR as renal function influences NfL clearance. We replicated our findings using cohorts from the CHARGE consortium (CARDIA, ARIC, FHS, AGES; n=4,772), the UKY ADRC (n=350), and the UCD ADRC (n=196). Result: We found the Quanterix Simoa platform to be reliable with low coefficients of variation (average CV<12%), high inter‐site reproducibility (overall ICC = 0.93) and high repeatability in test‐retest samples drawn within 30 days (ICC=0.968). There was strong consistency across Quanterix instruments (HD‐X and HD‐1; R2≥0.98) and kits (N4PA and single molecule NfL; ICC≥0.81). We observed consistent significant associations between higher NfL concentrations and worse GCF in MarkVCID (β=‐0.23; [95% CI ‐0.41; ‐0.01), CHARGE cohorts (meta‐analysis β=‐0.11; [95% CI ‐0.17; ‐0.06]), the UKY ADRC (β=‐0.16; [95% CI ‐0.27; ‐0.05]) and the UCD ADRC (UCD: β=‐0.28; [95% CI ‐0.48; ‐0.08). Secondary analyses revealed significant associations between elevated NfL concentrations and higher WMH burden in MarkVCID (when controlled for eGFR), CHARGE, and the UCD ADRC. Conclusion: We have found that NfL can be reliably measured using the Quanterix platform, making this marker ideal for multi‐site clinical trials. We observed consistent associations for plasma NfL concentrations with cognition and WMH in MarkVCID and across independent samples, providing evidence that it can be a useful biomarker for stratification in VCID trials.