Alzheimer's disease (AD) is the leading cause of dementia, with an increasing incidence due to population aging. Approximately two-thirds of the people affected are women, possibly due to biological a Show more
Alzheimer's disease (AD) is the leading cause of dementia, with an increasing incidence due to population aging. Approximately two-thirds of the people affected are women, possibly due to biological and hormonal factors. Also, lipids could play an important role in AD and show associations with cognitive impairment. Apolipoprotein E allele 4 (ApoE ε4) genotype and cardiovascular (CV) risk lipid ratios could be relevant in lipidomic studies. This work aims to identify specific alterations in plasma lipid profiles associated with AD in women and to explore these alterations related to ApoE and 2 CV risk lipid ratios. A lipidomic mass spectrometry-based method was applied to plasma samples from a clinical cohort of women. The patients were accurately classified into AD (n = 76) and non-AD (n = 74) groups by cerebrospinal fluid amyloid beta (Aβ)42/Aβ40 levels. The identified lipid species were evaluated and grouped into families and subfamilies. The lipids with significant differences between groups were examined in relation to ApoE genotype and 2 CV risk ratios (total cholesterol/high-density lipoprotein [HDL], triglycerides/HDL). Fatty acyls and monoacylglycerols showed higher levels in AD compared with non-AD, while diacylglycerols showed lower levels in AD. Also, specific subfamilies correlated with aging, CV risk, AD biomarkers, and cognitive status. Of the 627 lipid species detected, 45 showed statistically significant differences between groups, and some of them [lysophosphatidylcholine (24:1), diacylglycerol (18:0/18:1), and triacylglycerol (50:3)] showed significant associations with ApoE genotype and CV risk. This study identified associations between lipid profiles in women and AD pathology, ApoE ε4 genotype, and high CV risk ratios. Show less
Nowadays, there is an unmet need for reliable and minimally-invasive diagnosis tools capable of detecting Alzheimer's disease at early stages. Such tools could significantly reduce the reliance on con Show more
Nowadays, there is an unmet need for reliable and minimally-invasive diagnosis tools capable of detecting Alzheimer's disease at early stages. Such tools could significantly reduce the reliance on confirmatory tests that are invasive and costly, such as cerebrospinal fluid (CSF) biomarkers and neuroimaging. The aim of this study is to validate previously developed diagnosis tools (multivariate models and plasma p-Tau217 levels) in three independents cohorts. For this, a cohort was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) including some variables (age, Apolipoprotein E (ApoE) genotype, plasma p-Tau217, CSF biomarkers) (n = 113); and two cohorts from cognitive disorders units (Hospital Universitari i Politècnic La Fe (HUiPLaFe, n = 163), Hospital Doctor Peset (n = 31)), whose plasma samples were analysed to determine plasma p-Tau217, and to evaluate the previous diagnosis tools performance. For the cohort from HUiPLaFe, the multivariate model (plasma p-Tau217, age, ApoE genotype) showed a sensitivity of 94.9% and a specificity of 88.2%; for the cohort from Hospital Doctor Peset, the sensitivity was 100% and specificity 80%; for the ADNI cohort, sensitivity was 89.5% and specificity 39.5%. Regarding the plasma p-Tau217 levels, the results were satisfactory for the cognitive disorders units; while ADNI cohort showed very low specificity. In conclusion, the multivariate model was clinically validated in independent cohorts from clinical units, representing its first step for implementation. Show less