Interestingly, significantly decreased CSF A42 has been observed in patients with very moderate dementia (MMSE score of 2528 or CDR 0.5) (Fagan et al., 2007;Riemenschneider et al., 2000), and levels have been reported to decrease from moderate to more severe dementia (Jensen et al., 1999;Riemenschneider et al., 2000), suggesting that A42 may be useful in tracking the clinical course of patients. It is important to consider whether a given biomarker makes sense in the context of the disease pathophysiology. estimated to impact 5.1 million individuals in 2007 (Alzheimers Association, 2007). The diagnosis of AD is largely based upon clinical assessment, with definitive diagnosis still requiring pathological evaluation at autopsy. The identification of biomarkers for AD would allow for any less invasive and more accurate diagnosis in the antemortem period. Additionally, biomarkers may facilitate early diagnosis, which is particularly hard given that you will find no signs or symptoms unique to AD. More importantly, they may allow for the identification of individuals with preclinical AD (those with AD neuropathology that do not yet display clinical symptoms) (Gomez-Isla et al., 1996;Hulette et al., 1998;Markesbery et al., 2006;Morris and Price, 2001;Price et al., 2001). Biomarkers SLIT1 may be instrumental not only in the diagnosis of disease cases, but may aid in following disease progression and response to treatment as well. Finally, biomarkers are key in advancing our understanding of the pathophysiology of AD, which in turn has important implications for patient diagnosis and treatment. The identification of reliable biomarkers has been hindered by the fact that individual classification relies on clinical diagnosis which is not always accurate, especially at early stages of the disease. Requiring postmortem confirmation of disease diagnosis has been impractical for biomarker studies. Moreover, control groups are likely to contain individuals with preclinical AD. Limited individual sample size and lack of adjustment for covariates such as age, gender, ethnicity, and APOE genotype have restricted the application of results from some studies to the general populace. In addition, protocols for sample collection, preparation, and analysis often vary widely between labs, thus contributing additional methodological variability. Adopting standardized protocols for clinical assessment, sample analysis, and statistical evaluation would help overcome many of these shortcomings. Given the multifactorial nature of the disease, it is unlikely that a single biomarker will meet the needs for clinical diagnosis, while a panel of biomarkers may offer the appropriate sensitivity, specificity, and positive and negative predictive values. These limitations not withstanding, many potential Albiglutide biomarkers have been identified, the most encouraging of which are discussed below and in the accompanyingTable. Where in the disease course these numerous candidate markers may be useful is usually shown in theFigure. == Table. == Select candidate fluid and imaging biomarkers of AD Decreased in AD Decreased in subjects with brain amyloid deposition Predictive of conversion from MCI to AD (Andreasen et al., 1999a;Andreasen et al., 2001;Clark et al., 2003;Engelborghs et al., 2008;Fagan et al., 2007;Galasko et al., 1998;Hampel et al., 2004;Hulstaert et al., 1999;Ida et al., 1996;Kanai et al., 1998;Kanemaru et al., 2000;Kapaki et al., 2001;Kapaki et al., 2003;Lewczuk et al., 2004;Mehta et al., 2000;Motter et al., 1995;Mulder et al., 2002;Otto et al., 2000;Riemenschneider et al., 2000;Rosler et al., 2001a;Sjogren et al., 2002;Sjogren et al., 2000;Skoog et al., 2003;Sunderland et al., 2003;Tamaoka et al., 1997;Vanderstichele et al., 2000) (Fagan et al., 2006;Fagan et al., 2007) (Andreasen Albiglutide et al., 2003;Hampel et al., 2004;Hansson et al., 2007;Hansson et al., 2006a;Hansson et al., 2008;Herukka et al., 2005;Herukka et al., 2007;Riemenschneider et al., 2002) Mostly no difference in AD Mixed results for prediction of conversion from normal or MCI to AD Increased in FAD (Fagan et al., 2007;Fukumoto et al., 2003;Kosaka et al., 1997;Mehta et al., 2000;Pesaresi et al., 2006;Tamaoka et al., 1996;Vanderstichele et al., 2000) (Ertekin-Taner et al., 2008;Hansson et al., Albiglutide 2008;Lopez et al., 2008;Mayeux et al., 2003;Mayeux et al., 1999) (Kosaka et al., 1997;Scheuner et al., Albiglutide 1996) Mostly no difference in AD Mixed results for prediction of conversion from normal or MCI to AD Decreased in FAD (Fagan et al., 2007;Fukumoto et al., 2003;Kosaka et al., 1997;Mehta et al., 2000;Tamaoka et al., 1996) (Hansson et al., 2008;Lopez et al., 2008;van Oijen et al., 2006) (Kosaka et al., 1997) Discriminates AD from normals Predictive of conversion from MCI to AD (Fagan et al., 2007;Kanai et al., 1998;Lewczuk et al., 2004;Shoji et al., 1998) (Hansson et al., 2007) Increased in AD p-tau231 predicts conversion from MCI to AD (Buerger et al., 2002;Fagan et al., 2007;Hampel et al., 2004b;Itoh et al., 2001;Kohnken et al., 2000) (Buerger et al., 2002) Increased in AD Predictive.
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