How plausible is an Alzheimer’s disease vaccine?

Abstract

Introduction: Alzheimer's disease (AD) vaccination is one of the last therapeutic options after two decades of stagnation in terms of drug development. About 140 (85%) immunization procedures against Aβ deposition and 25 (15%) against Tau have been reported, but no Food and Drug Administration approval of any AD vaccine has been achieved. This might be attributed to deficient pathogenic targets, inappropriate models, defective immunotherapeutic procedures, and inadequate clinical trial design. Areas covered: The issues covered include the following: AD pathogenic mechanisms, rationale for active and passive immunization, vaccine targets, anti-Aβ/Tau vaccines, vaccine technologies, animal models, and clinical trials. Expert opinion: A vaccine against AD is technically feasible; however, important methodological aspects should be changed for a tentative clinical success, including (i) the development of multitarget AD immunotherapies; (ii) the optimization of antibody titers and epitopes; (iii) the pharmacogenetic/pharmacoepigenetic validation of the immunization procedure; (iv) the prophylactic treatment of genetically stratified patients at a pre-symptomatic stage; and (v) the definition of primary endpoints in prevention, based on objective/multifactorial biomarkers. Even with exquisite protocols, a successful vaccine would be potentially useful in at most 20-30% of defined cases, according to the genetic, epigenetic, and pharmacogenetic background of AD patients. ARTICLE HISTORY

Peptide-Based Vaccines for Neurodegenerative Diseases: Recent Endeavors and Future Perspectives

“…The development of peptide-based active immunotherapies/vaccines for the treatment of neurodegenerative diseases has been the objective of many research endeavors for the last two decades [4,25]. Since the pioneering work of Schenk et al [58], who vaccinated PDAPP transgenic mice overexpressing mutant human APP with pre-aggregated Aβ(1-42) as a putative active immunotherapeutic strategy against AD, several other vaccines have been described; these vaccines have been mainly based on the most popular scenarios concerning the pathogenesis of neurodegeneration, i.e., amyloidosis and tauopathies [126] as well as synucleinopathies [46]. Though a monoclonal antibody, i.e., a passive immunotherapeutic agent, has been the first immunotherapy to be approved by the FDA for patients with AD [20], vaccines can eventually prove to be an advantageous treatment that can be widely used against neurodegeneration [3].…”

“…Careful selection/design of peptide (neo)epitope(s), which may ideally be recognized by the host's B-but not T-cells [127], is a parameter of utmost importance for achieving the safety and efficacy necessary for a peptide-based vaccine against AD and other neurodegenerative diseases. In addition to the selection of suitable B-cell peptide epitopes, the safety and efficacy of a peptide-based vaccine depend on various other parameters, including the carriers/delivery systems that usually provide the external T-cell epitopes and/or facilitate final access to the in vivo biological target as well as the adjuvants ensuring enhanced immune response of the desired type, i.e., Th2-biased [5,126]. Formulation systems, in general, consist of factors that may greatly affect the final outcome of peptide-based vaccination; to support this, it is noteworthy mentioning that a new phase II clinical trial was announced for an optimized formulation of the α-syn peptide-based vaccine, PD01, a few months ago [108].…”

“…Formulation systems, in general, consist of factors that may greatly affect the final outcome of peptide-based vaccination; to support this, it is noteworthy mentioning that a new phase II clinical trial was announced for an optimized formulation of the α-syn peptide-based vaccine, PD01, a few months ago [108]. Concerning the pre-clinical in vivo animal studies, it should be noticed that specific parameters, such as the animal model, the specific vaccine excipients, and the vaccination schemes used [34,81,84,126] might have highly contributed to the overall outcome [70,72]. This issue may be responsible for the non-optimal results obtained in the subsequent trials with human subjects and should be carefully considered in future endeavors.…”

“…The N-terminal α-syn(1-10) and C-terminal α-syn (90-140) fragments were found to be exposed with ELISA experiments [101]. On the other hand, the C-terminal epitopes α-syn(111-140)/α-syn (121)(122)(123)(124)(125)(126)(127)(128)(129)(130)(131)(132)(133)(134)(135)(136)(137)(138)(139)(140) were recognized by human anti-α-syn antibodies isolated from PD patients [102]. Moreover, the secondary structural features of α-syn in an aqueous environment have been studied with computer simulation [103].…”

Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19

“…Deep learning techniques and feature engineering were compared in order to efficiently diagnose COVID-19 from CT images [ 14 ]. Various neural network architectures and generative models such as RNN, autoencoders with adversarial learning, and reinforcement learning are suggested for ligand-based drug discovery [ 15 ]. Classification performance of DNN on imbalance compound datasets is explored by applying data balancing techniques in [ 16 ].…”