👤 Andrés Villegas

To have maximal benefit, Alzheimer's disease-modifying treatments might need to be started before the onset of clinical symptoms. Mutations of the PSEN1 gene are inherited as fully penetrant, autosomal-dominant traits, which almost always result in the clinical onset of Alzheimer's disease before the age of 65 years. We aimed to evaluate the efficacy, including possible delayed emergence of cognitive impairment, and safety of crenezumab, an anti-amyloid monoclonal antibody, in cognitively unimpaired carriers of the PSEN1 This 5-8-year common-close, double-blind, placebo-controlled, single-centre trial screened kindred members aged 30-60 years from the main health-care site in Medellín, Colombia. Participants who were cognitively unimpaired and carried the PSEN1 619 Colombian API registrants were prescreened, 315 were assessed for eligibility, and 252 were enrolled (crenezumab-carrier, n=85; placebo-carrier, n=84; placebo-non-carrier, n=83; 160 [63%] women and 92 [37%] men) between Dec 20, 2013, and Feb 27, 2017. 237 (94%) completed the trial, with final data collection on March 22, 2022. The annualised rate of change in the API ADAD composite was -1·10 (SE 0·29) in the crenezumab group and -1·43 (0·29) in the placebo group (between-group difference 0·33 [95% CI -0·48 to 1·13]; p=0·43). The annualised rate of change in FCSRT-CI was -0·03 (0·00) in the crenezumab group and -0·04 (0·00) in the placebo group (between-group difference 0·01 [0·00 to 0·02]; p=0·16). All participants had at least one adverse event; serious adverse events occurred in 23 (27%) of 84 in the crenezumab group and 21 (25%) of 84 in the placebo group. No fatalities occurred. Crenezumab therapy administered for 5-8 years did not result in significant benefits on our primary clinical outcomes in cognitively unimpaired participants predisposed to developing ADAD dementia; secondary and exploratory outcomes also showed no significant effect on removal of amyloid plaques or other clinical or biomarker outcomes. Together with the results of other anti-amyloid β trials, robust fibrillar amyloid removal appears necessary for clinical efficacy in people with elevated brain amyloid. This study will further inform the biomarker, cognitive, and clinical trajectory of preclinical ADAD, the risk of clinical progression in amyloid-positive and amyloid-negative mutation carriers, and the size and design of future secondary and primary prevention trials. US National Institute on Aging (NIA), Banner Alzheimer's Institute, Genentech, F Hoffmann-La Roche. Show less

Protein biomarkers in biofluids are highly sensitive indicators of prodromal cognitive impairment yet remain limited for primary prevention. Lipids, essential to brain structure and function, offer untapped prognostic value. Here, we identify a lipidomic signature in serum from asymptomatic PSEN1-E280A mutation carriers aged 6-40 years, that differentiate carriers from non-carriers with an AUC 80-90%. Similarly, to symptomatic carriers (≥41 years; 93%) and sporadic AD cases (85%), using high-resolution mass spectrometry. Latent profile analysis revealed lipid-based signatures of dementia risk and resilience, shaped by genotype, sex, and APOE isoform, and supported by SIMOA protein biomarkers. Age-dependent dysregulation in sphingolipid and glycolipid metabolism was validated by enzymatic activity (TLC), glial phenotyping (flow cytometry), and gene expression (snRNAseq) in postmortem brain. Ganglioside clearance deficits emerged by age 6-12, followed by proinflammatory shifts from age 13 and p-tau217 elevation by age 20, with greater burden in females and APOE4 carriers. APOE3Ch individuals showed differential salvage pathways of ceramides and gangliosides. These findings position early lipid pathway dysregulation as a biological contributor to Alzheimer's pathogenesis and a potential therapeutic target for primary prevention. Show less

Chemical descriptors encode the physicochemical and structural properties of small molecules, and they are at the core of chemoinformatics. The broad release of bioactivity data has prompted enriched representations of compounds, reaching beyond chemical structures and capturing their known biological properties. Unfortunately, bioactivity descriptors are not available for most small molecules, which limits their applicability to a few thousand well characterized compounds. Here we present a collection of deep neural networks able to infer bioactivity signatures for any compound of interest, even when little or no experimental information is available for them. Our signaturizers relate to bioactivities of 25 different types (including target profiles, cellular response and clinical outcomes) and can be used as drop-in replacements for chemical descriptors in day-to-day chemoinformatics tasks. Indeed, we illustrate how inferred bioactivity signatures are useful to navigate the chemical space in a biologically relevant manner, unveiling higher-order organization in natural product collections, and to enrich mostly uncharacterized chemical libraries for activity against the drug-orphan target Snail1. Moreover, we implement a battery of signature-activity relationship (SigAR) models and show a substantial improvement in performance, with respect to chemistry-based classifiers, across a series of biophysics and physiology activity prediction benchmarks. Show less