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1.  Allelic mRNA expression of sortilin-1 (SORL1) mRNA in Alzheimer’s autopsy brain tissues 
Neuroscience letters  2008;448(1):120-124.
Polymorphisms in the gene encoding SORL1, involved in cellular trafficking of APP, have been implicated in late-onset Alzheimer’s disease, by a mechanism thought to affect mRNA expression. To search for regulatory polymorphisms, we have measured allele-specific mRNA expression of SORL1 in human autopsy tissues from the prefrontal cortex of 26 Alzheimer’s patients, and 51 controls, using two synonymous marker SNPs (rs3824968 in exon 34 (11 heterozygous AD subjects and 16 controls), and rs12364988 in exon 6 (8 heterozygous AD subjects)). Significant allelic expression imbalance (AEI), indicative of the presence of cis-acting regulatory factors, was detected in a single control subject, while allelic ratios were near unity for all other subjects. We genotyped 7 SNPs in two haplotype blocks that had previously been implicated in Alzheimer’s disease. Since each of these SNPs was heterozygous in several subjects lacking AEI, this study fails to support a regulatory role for SORL1 polymorphisms in mRNA expression.
doi:10.1016/j.neulet.2008.10.034
PMCID: PMC2612539  PMID: 18938222
Alzheimer’s disease; SORL1; Allelic expression imbalance
2.  Predicting missing biomarker data in a longitudinal study of Alzheimer disease 
Lo, Raymond Y. | Jagust, William J. | Aisen, Paul | Jack, Clifford R. | Toga, Arthur W. | Beckett, Laurel | Gamst, Anthony | Soares, Holly | C. Green, Robert | Montine, Tom | Thomas, Ronald G. | Donohue, Michael | Walter, Sarah | Dale, Anders | Bernstein, Matthew | Felmlee, Joel | Fox, Nick | Thompson, Paul | Schuff, Norbert | Alexander, Gene | DeCarli, Charles | Bandy, Dan | Chen, Kewei | Morris, John | Lee, Virginia M.-Y. | Korecka, Magdalena | Crawford, Karen | Neu, Scott | Harvey, Danielle | Kornak, John | Saykin, Andrew J. | Foroud, Tatiana M. | Potkin, Steven | Shen, Li | Buckholtz, Neil | Kaye, Jeffrey | Dolen, Sara | Quinn, Joseph | Schneider, Lon | Pawluczyk, Sonia | Spann, Bryan M. | Brewer, James | Vanderswag, Helen | Heidebrink, Judith L. | Lord, Joanne L. | Petersen, Ronald | Johnson, Kris | Doody, Rachelle S. | Villanueva-Meyer, Javier | Chowdhury, Munir | Stern, Yaakov | Honig, Lawrence S. | Bell, Karen L. | Morris, John C. | Mintun, Mark A. | Schneider, Stacy | Marson, Daniel | Griffith, Randall | Clark, David | Grossman, Hillel | Tang, Cheuk | Marzloff, George | Toledo-Morrell, Leylade | Shah, Raj C. | Duara, Ranjan | Varon, Daniel | Roberts, Peggy | Albert, Marilyn S. | Pedroso, Julia | Toroney, Jaimie | Rusinek, Henry | de Leon, Mony J | De Santi, Susan M | Doraiswamy, P. Murali | Petrella, Jeffrey R. | Aiello, Marilyn | Clark, Christopher M. | Pham, Cassie | Nunez, Jessica | Smith, Charles D. | Given, Curtis A. | Hardy, Peter | Lopez, Oscar L. | Oakley, MaryAnn | Simpson, Donna M. | Ismail, M. Saleem | Brand, Connie | Richard, Jennifer | Mulnard, Ruth A. | Thai, Gaby | Mc-Adams-Ortiz, Catherine | Diaz-Arrastia, Ramon | Martin-Cook, Kristen | DeVous, Michael | Levey, Allan I. | Lah, James J. | Cellar, Janet S. | Burns, Jeffrey M. | Anderson, Heather S. | Laubinger, Mary M. | Bartzokis, George | Silverman, Daniel H.S. | Lu, Po H. | Graff-Radford MBBCH, Neill R | Parfitt, Francine | Johnson, Heather | Farlow, Martin | Herring, Scott | Hake, Ann M. | van Dyck, Christopher H. | MacAvoy, Martha G. | Benincasa, Amanda L. | Chertkow, Howard | Bergman, Howard | Hosein, Chris | Black, Sandra | Graham, Simon | Caldwell, Curtis | Hsiung, Ging-Yuek Robin | Feldman, Howard | Assaly, Michele | Kertesz, Andrew | Rogers, John | Trost, Dick | Bernick, Charles | Munic, Donna | Wu, Chuang-Kuo | Johnson, Nancy | Mesulam, Marsel | Sadowsky, Carl | Martinez, Walter | Villena, Teresa | Turner, Scott | Johnson, Kathleen B. | Behan, Kelly E. | Sperling, Reisa A. | Rentz, Dorene M. | Johnson, Keith A. | Rosen, Allyson | Tinklenberg, Jared | Ashford, Wes | Sabbagh, Marwan | Connor, Donald | Jacobson, Sandra | Killiany, Ronald | Norbash, Alexander | Nair, Anil | Obisesan, Thomas O. | Jayam-Trouth, Annapurni | Wang, Paul | Lerner, Alan | Hudson, Leon | Ogrocki, Paula | DeCarli, Charles | Fletcher, Evan | Carmichael, Owen | Kittur, Smita | Mirje, Seema | Borrie, Michael | Lee, T-Y | Bartha, Dr Rob | Johnson, Sterling | Asthana, Sanjay | Carlsson, Cynthia M. | Potkin, Steven G. | Preda, Adrian | Nguyen, Dana | Tariot, Pierre | Fleisher, Adam | Reeder, Stephanie | Bates, Vernice | Capote, Horacio | Rainka, Michelle | Hendin, Barry A. | Scharre, Douglas W. | Kataki, Maria | Zimmerman, Earl A. | Celmins, Dzintra | Brown, Alice D. | Gandy, Sam | Marenberg, Marjorie E. | Rovner, Barry W. | Pearlson, Godfrey | Anderson, Karen | Saykin, Andrew J. | Santulli, Robert B. | Englert, Jessica | Williamson, Jeff D. | Sink, Kaycee M. | Watkins, Franklin | Ott, Brian R. | Wu, Chuang-Kuo | Cohen, Ronald | Salloway, Stephen | Malloy, Paul | Correia, Stephen | Rosen, Howard J. | Miller, Bruce L. | Mintzer, Jacobo
Neurology  2012;78(18):1376-1382.
Objective:
To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD).
Methods:
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005–2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI.
Results:
CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ42. Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD.
Conclusion:
The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD.
doi:10.1212/WNL.0b013e318253d5b3
PMCID: PMC3345787  PMID: 22491869

Results 1-2 (2)