Many studies have

Many studies have Cisplatin DNA Synthesis inhibitor formulated panels of biomarkers to distinguish between healthy and AD participants and evaluated broad ranges of proteins in different combinations to yield high sensitivity and specificity [37,38]. There has been considerable development in the discovery of cost-effective plasma protein biomarkers for AD [39]. In a panel of 120 signalling proteins, 18 proteins had 82% specificity in differentiating AD from healthy subjects and predicting the conversion from MCI to AD [40]. Tuenissen and colleagues [36] evaluated 29 serum biomarkers that can differentiate AD from healthy participants. These included inflammatory biomarkers such asIL-6 and metabolic biomarkers such as cholesterol metabolites, cysteine and homocysteine.

Doecke and colleagues [41] reported on AIBL baseline plasma screening of 151 analytes combined with targeted biomarker and clinical pathology data in a total of 961 participants. An initial plasma biomarker panel consisting of 18 biomarkers was identified that distinguishes individuals with AD from cognitively healthy controls with high sensitivity and specificity. A final signature panel of eight proteins (beta2 microglobulin, carcinoembryonic antigen, cortisol, epidermal growth factor receptor, IGFBP-2, IL-17, PPY and VCAM-1) was identified that showed increased prediction accuracy when validated in an Alzheimer’sDisease Neuroimaging Initiative (ADNI) dataset. A similar study [42] reported on the measured levels of 190 plasma proteins in a total of 600 participants. An initial panel of 17 analytes associated with the diagnosis of very mild dementia/MCI or AD was identified.

Their analysis yielded a set of four plasma analytes (ApoE, B-typenatriuretic peptide, C-reactive protein, pancreatic polypeptide) that were consistently associated with the diagnosis of very mild dementia/MCI/AD when validated across the ADNI cohort. A comparison among panels of analytes derived from such similar studies reveals very few common blood biomarkers for AD. Despite having Entinostat similar analytical platforms and common validation cohorts, there are discrepancies in the numbers of plasma biomarkers identified by these studies. The likely reasons for this could be variation in pre-analytical variable selection, which could lead to differential interaction between analytes of interest, differences in innate characteristics of a cohort based on region and different statistical approaches employed by the different groups.

There are different methods for identifying biomarkers in blood (Table ?(Table1);1); hence, it is important to standardize the methods of generation of proteomic data and the entire workflow. In order to standardize a panel of biomarkers for AD neverless diagnosis, consensus on protocols and ultrasensitive analytical methods are required through multi centre studies.

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