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- Lennol, M. P., et al.
(författare)
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Apolipoprotein E imbalance in the cerebrospinal fluid of Alzheimer's disease patients
- 2022
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Ingår i: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The purpose of this study was to examine the levels of cerebrospinal fluid (CSF) apolipoprotein E (apoE) species in Alzheimer's disease (AD) patients. Methods: We analyzed two CSF cohorts of AD and control individuals expressing different APOE genotypes. Moreover, CSF samples from the TgF344-AD rat model were included. Samples were run in native- and SDS-PAGE under reducing or non-reducing conditions (with or without beta-mercaptoethanol). Immunoprecipitation combined with mass spectrometry or western blotting analyses served to assess the identity of apoE complexes. Results: In TgF344-AD rats expressing a unique apoE variant resembling human apoE4, a similar to 35-kDa apoE monomer was identified, increasing at 16.5 months compared with wild-types. In humans, apoE isoforms form disulfide-linked dimers in CSF, except apoE4, which lacks a cysteine residue. Thus, controls showed a decrease in the apoE dimer/monomer quotient in the APOE epsilon 3/epsilon 4 group compared with epsilon 3/epsilon 3 by native electrophoresis. A major contribution of dimers was found in APOE epsilon 3/epsilon 4 AD cases, and, unexpectedly, dimers were also found in epsilon 4/epsilon 4 AD cases. Under reducing conditions, two apoE monomeric glycoforms at 36 kDa and at 34 kDa were found in all human samples. In AD patients, the amount of the 34-kDa species increased, while the 36-kDa/34-kDa quotient was lower compared with controls. Interestingly, under reducing conditions, a similar to 100-kDa apoE complex, the identity of which was confirmed by mass spectrometry, also appeared in human AD individuals across all APOE genotypes, suggesting the occurrence of aberrantly resistant apoE aggregates. A second independent cohort of CSF samples validated these results. Conclusion: These results indicate that despite the increase in total apoE content the apoE protein is altered in AD CSF, suggesting that function may be compromised.
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| 2. |
- Smart, Sophie E., et al.
(författare)
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Clinical predictors of antipsychotic treatment resistance: Development and internal validation of a prognostic prediction model by the STRATA-G consortium
- 2022
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Ingår i: Schizophrenia Research. - : Elsevier. - 0920-9964 .- 1573-2509. ; 250
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionOur aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR.MethodsWe combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction.ResultsOur sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %).ImplicationsOur findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR.
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