Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics.

The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aß), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.

Diagnosing dementia and cognitive dysfunction in the elderly in primary health care: A systematic review.

Dementia is a public health issue making the screening and diagnosing of dementia and its prodromal phases in all health settings imperative. OBJECTIVE: using PRISMA, this systematic review aimed to identify how low-, middle-, and high-income countries establish dementia and cognitive dysfunction diagnoses in primary health care. METHODS: studies from the past five years in English, Spanish, and Portuguese were retrieved from Scopus, PubMed, Embase, Lilacs, Scielo, and Web of Science. Of 1987 articles, 33 were selected for analysis. RESULTS: only three articles were from middle-income countries and there were no studies from low-income countries. The most used instrument was the Mini-Mental State Examination (MMSE). Mild Cognitive Impairment (MCI) and dementia criteria were based on experts' recommendation as well as on the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD-10), respectively. CONCLUSION: differences between these criteria among high- and middle-income countries were observed.

Demência é uma questão de saúde pública logo, rastrear e diagnosticar demência e suas fases prodrômicas em todos os níveis de atenção à saúde é imperativo. OBJETIVO: uilizando o PRISMA, esta revisão sistemática verificou como os países de baixa, média e alta renda realizam o diagnóstico de demência e disfunção cognitiva na atenção primária. MÉTODOS: estudos dos últimos cinco anos, em inglês, português e espanhol foram obtidos no Scopus, PubMed, Embase, Lilacs, Scielo, e Web of Science. De 1987 artigos, 33 foram selecionados para a análise. RESULTADOS: três artigos eram de países de média renda e nenhum de baixa renda. O Mini-Exame do Estado Mental (MEEM) foi o instrumento mais utilizado. Os diagnósticos de Comprometimento Cognitivo Leve (CCL) e demência foram baseados em recomendações de especialistas e no Manual Diagnóstico e Estatístico de Transtornos Mentais (DSM)/Classificação Internacional de Doenças (CID-10), respectivamente. CONCLUSÃO: houve diferenças para estes critérios entre países de alta e média renda.