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Whereas lenalidomide is an effective therapy for del(5q) MDS patients, a minority of non-del(5q) MDS patients achieve hematologic improvement with lenalidomide. We used computational biology modeling and digital drug simulation to examine genomic data from 56 non-del(5q) MDS patients treated with lenalidomide, and then matched treatment response with molecular pathways. The computer inferred genomic abnormalities associating with lenalidomide treatment response in non-del(5q) MDS to include trisomy 8, del(20q), or RUNX1 loss of function mutations. Genomic abnormalities associating with lenalidomide resistance in non-del(5q) MDS patients included mutations in SF3B1, TET2, WNT3A amplification, MCL1 amplification, and/or PSEN2 amplification. These results may inform protocols for determining appropriateness of lenalidomide in non-del(5q) MDS.

Alzheimer’s disease (AD) is the most common neurodegenerative disease in the world. It is classified as familial and sporadic. The dominant familial or autosomal presentation represents 1–5% of the total number of cases. It is categorized as early onset (EOAD; <65 years of age) and presents genetic mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or the Amyloid precursor protein (APP). Sporadic AD represents 95% of the cases and is categorized as late-onset (LOAD), occurring in patients older than 65 years of age. Several risk factors have been identified in sporadic AD; aging is the main one. Nonetheless, multiple genes have been associated with the different neuropathological events involved in LOAD, such as the pathological processing of Amyloid beta (Aβ) peptide and Tau protein, as well as synaptic and mitochondrial dysfunctions, neurovascular alterations, oxidative stress, and neuroinflammation, among others. Interestingly, using genome-wide association study (GWAS) technology, many polymorphisms associated with LOAD have been identified. This review aims to analyze the new genetic findings that are closely related to the pathophysiology of AD. Likewise, it analyzes the multiple mutations identified to date through GWAS that are associated with a high or low risk of developing this neurodegeneration. Understanding genetic variability will allow for the identification of early biomarkers and opportune therapeutic targets for AD.

Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal. Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11C-Pittsburgh Compound B (11C-PiB) PET, 18F-Fluorodeoxyglucose (18F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) 11C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning). Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials. US National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK.

The search for the genetic factors contributing to Alzheimer disease (AD) has evolved tremendously throughout the years. It started from the discovery of fully penetrant mutations in Amyloid precursor protein, Presenilin 1, and Presenilin 2 as a cause of autosomal dominant AD, the identification of the ɛ4 allele of Apolipoprotein E as a strong genetic risk factor for both early-onset and late-onset AD, and evolved to the more recent detection of at least 21 additional genetic risk loci for the genetically complex form of AD emerging from genome-wide association studies and massive parallel resequencing efforts. These advances in AD genetics are positioned in light of the current endeavor directing toward translational research and personalized treatment of AD. We discuss the current state of the art of AD genetics and address the implications and relevance of AD genetics in clinical diagnosis and risk prediction, distinguishing between monogenic and multifactorial AD. Furthermore, the potential and current limitations of molecular reclassification of AD to streamline clinical trials in drug development and biomarker studies are addressed.

Amyloid protein precursor (APP), presenilin-1 (PSEN1), and presenilin-2 (PSEN2) mutations cause autosomal dominant forms of early-onset Alzheimer disease (AD-EOAD). Although these genes were identified in the 1990s, variant classification remains a challenge, highlighting the need to colligate mutations from large series. We report here a novel update (2012-2016) of the genetic screening of the large AD-EOAD series ascertained across 28 French hospitals from 1993 onwards, bringing the total number of families with identified mutations to n = 170. Families were included when at least two first-degree relatives suffered from early-onset Alzheimer disease (EOAD) with an age of onset (AOO) ≤65 y in two generations. Furthermore, we also screened 129 sporadic cases of Alzheimer disease with an AOO below age 51 (44% males, mean AOO = 45 ± 2 y). APP, PSEN1, or PSEN2 mutations were identified in 53 novel AD-EOAD families. Of the 129 sporadic cases screened, 17 carried a PSEN1 mutation and 1 carried an APP duplication (13%). Parental DNA was available for 10 sporadic mutation carriers, allowing us to show that the mutation had occurred de novo in each case. Thirteen mutations (12 in PSEN1 and 1 in PSEN2) identified either in familial or in sporadic cases were previously unreported. Of the 53 mutation carriers with available cerebrospinal fluid (CSF) biomarkers, 46 (87%) had all three CSF biomarkers-total tau protein (Tau), phospho-tau protein (P-Tau), and amyloid β (Aβ)42-in abnormal ranges. No mutation carrier had the three biomarkers in normal ranges. One limitation of this study is the absence of functional assessment of the possibly and probably pathogenic variants, which should help their classification. Our findings suggest that a nonnegligible fraction of PSEN1 mutations occurs de novo, which is of high importance for genetic counseling, as PSEN1 mutational screening is currently performed in familial cases only. Among the 90 distinct mutations found in the whole sample of families and isolated cases, definite pathogenicity is currently established for only 77%, emphasizing the need to pursue the effort to classify variants.

Presenilin-1 (PSEN1) has been verified as an important causative factor for early onset Alzheimer’s disease (EOAD). PSEN1 is a part of γ-secretase, and in addition to amyloid precursor protein (APP) cleavage, it can also affect other processes, such as Notch signaling, β-cadherin processing, and calcium metabolism. Several motifs and residues have been identified in PSEN1, which may play a significant role in γ-secretase mechanisms, such as the WNF, GxGD, and PALP motifs. More than 300 mutations have been described in PSEN1; however, the clinical phenotypes related to these mutations may be diverse. In addition to classical EOAD, patients with PSEN1 mutations regularly present with atypical phenotypic symptoms, such as spasticity, seizures, and visual impairment. In vivo and in vitro studies were performed to verify the effect of PSEN1 mutations on EOAD. The pathogenic nature of PSEN1 mutations can be categorized according to the ACMG-AMP guidelines; however, some mutations could not be categorized because they were detected only in a single case, and their presence could not be confirmed in family members. Genetic modifiers, therefore, may play a critical role in the age of disease onset and clinical phenotypes of PSEN1 mutations. This review introduces the role of PSEN1 in γ-secretase, the clinical phenotypes related to its mutations, and possible significant residues of the protein.

Pathogenic variants in presenilin 1 (PSEN1) or presenilin 2 (PSEN2) cause familial Alzheimer's disease (AD). Recent long-read RNA sequencing of PSEN2 revealed cryptic exon inclusion and differential regulation of the 3' untranslated region (3'UTR) in sporadic AD. Notably, two-thirds of PSEN2 reads harbored the canonical short 3'UTR, while the other third contained an extended ∼4kb long 3'UTR. Given that 3'UTRs contain critical regulatory elements, we sought to determine the functional significance of PSEN2 3'UTR isoforms in AD. To develop in vitro models to assess PSEN2 3'UTR isoforms, we designed constructs containing the PSEN2 3'UTR short and long isoforms to overexpress in either HMC3 human microglial or SH-SY5Y human neuroblastoma cell lines. Since miRNAs are known to target 3'UTRs, we also completed homogenate and synaptosome small RNA sequencing on AD and control samples to profile miRNA expression. Finally, we tested whether PSEN2 3'UTR length or inclusion of cryptic exon 9B altered cellular localization in human frontal cortex samples using BaseScope in-situ hybridization. We primarily detected short PSEN2 in the cytoplasm with significantly reduced levels in AD versus control frontal cortex. Conversely, long PSEN2 was retained in the nucleus and expressed at similar levels between cases and controls. These findings are relevant for PSEN2 expression studies as in vitro findings indicated increased long PSEN2 3'UTR isoform abundance relative to the short PSEN2 3'UTR. Small RNA sequencing analysis identified 53 homogenate and 76 synaptosome miRNAs with significant differential regulation in AD, including one miRNA, miR-34c, that was significantly downregulated in both fractions. The long PSEN2 3'UTR contains 10 binding sites for 5 miRNAs with significant differential regulation in AD brains relative to controls, including 3 miRNAs with significant synaptosome downregulation (miR-346, miR-326, and miR-548p), and 2 miRNAs with significant homogenate downregulation (miR-217) and upregulation (miR-890). Collectively, our data establish 1) an in vitro model to test PSEN2 3'UTR isoforms, 2) miRNA expression differences in human AD synaptosome and homogenate fractions, and 3) decreased PSEN2 transcript signal in human AD frontal cortex tissue. Elucidating the functional significance of PSEN2 3'UTR isoform regulation will further our understanding of AD.

Purpose of ReviewEarly-onset Alzheimer’s disease (EOAD), defined as Alzheimer’s disease (AD) occurring before age 65, is significantly less well studied than the late-onset form (LOAD) despite EOAD often presenting with a more aggressive disease progression. The aim of this review is to summarize the current understanding of the etiology of EOAD, their translation into clinical practice, and to suggest steps to be taken to move our understanding forward.Recent FindingsEOAD cases make up 5–10% of AD cases but only 10–15% of these cases show known mutations in the APP, PSEN1, and PSEN2, which are linked to EOAD. New data suggests that these unexplained cases following a non-Mendelian pattern of inheritance is potentially caused by a mix of common and newly discovered rare variants. However, only a fraction of this genetic variation has been identified to date leaving the molecular mechanisms underlying this type of AD and their association with clinical, biomarker, and neuropathological changes unclear.SummaryWhile great advancements have been made in characterizing EOAD, much work is needed to disentangle the molecular mechanisms underlying this type of AD and to identify putative targets for more precise disease screening, diagnosis, prevention, and treatment.

The subcellular localization of γ-secretase is to a large extent defined by the presenilin homologue: a unique sorting motif restricts PSEN2/γ-secretase to late endosomes/lysosomes (LE/Lys) whereas PSEN1 complexes reside at the cell surface and in endosomal compartments. While these distinct locations promote substrate specificity and different amyloid β pools, they also suggest additional roles in maintaining organellar homeostasis. Using new APP knockin models with altered PSEN2 expression, we recently correlated impairments in working memory and LTP to PSEN2's role in neuronal endolysosomal homeostasis (Perdok et al., 2024). Currently we are exploring in detail how altered PSEN2 expression molecularly affects LE/Lys functions and dynamics. We used nonneuronal, primary hippocampal and iPSC-derived human neurons that are either deficient in PSEN2 or gene-edited to express the FAD-linked PSEN2 N141I mutation. PSEN-deficient cells stably expressing APEX2-tagged PSEN2 were used for proximity-dependent biotinylation to identify the local PSEN2 interactome in LE/Lys. Hits were prioritized based on their relevance to organellar homeostasis and validated using biochemical assays and functional studies in neuronal models. Proximity labeling identified novel interactors connecting PSEN2 function to LE/Lys transport regulation and nutrient sensing. Furthermore, super-resolution microscopy was used to more precisely identify the nano-domain organization of PSEN2 at the limiting membrane of LE/Lys. In neurons, axonal LE/Lys motility is differently affected in PSEN2KO versus FAD-mutant PSEN2, suggesting a more complex toxic mechanism in disease context. We are currently exploiting microfluidic chambers combined with omics for a more comprehensive view on the impact of altered PSEN2 expression on the axonal compartment. Our data revealed new insights in how PSEN2/γ-secretase may regulate LE/Lys homeostasis, providing novel starting points to better understand the etiology of endolysosomal dysfunctions as observed at early, preclinical stages of AD. Notably, specific FAD-mutations also re-locate PSEN1/γ-secretase to LE/Lys, underscoring that knowledge gained here could aid to understand the more heterogeneous PSEN1 mutations.

γ-secretase is an intramembrane protease complex consisting of nicastrin, presenilin-1/2, APH-1a/b, and Pen-2. Hydrolysis of the 99-residue transmembrane fragment of amyloid precursor protein (APP-C99) by γ-secretase produces β-amyloid (Aβ) peptides. Pathogenic mutations in PSEN1 and PSEN2, which encode the catalytic subunit presenilin-1/2 of γ-secretase, lead to familial Alzheimer’s disease in an autosomal dominant manner. However, the underlying mechanism of how the mutant PSEN gene may affect the function of the WT allele remains to be elucidated. Here we report that each of the loss-of-function γ-secretase variants that carries a PSEN1 mutation suppresses the protease activity of the WT γ-secretase on Aβ production. Each of these γ-secretase variants forms a stable oligomer with the WT γ-secretase in vitro in the presence of the detergent CHAPSO {3-[(3-cholamidopropyl)dimethylammonio]-2-hydroxy-1-propanesulfonate}, but not digitonin. Importantly, robust protease activity of γ-secretase is detectable in the presence of CHAPSO, but not digitonin. These experimental observations suggest a dominant negative effect of the γ-secretase, in which the protease activity of WT γ-secretase is suppressed by the loss-of-function γ-secretase variants through hetero-oligomerization. The relevance of this finding to the genesis of Alzheimer’s disease is critically evaluated.