INTRODUCTION: The sortilin-related receptor (SORL1) directs APP and Aβ trafficking within the retromer pathway. Cleavage at the cell surface releases soluble SORL1 (sSORL1) into cerebrospinal fluid (CSF). We examined whether CSF-sSORL1 can serve as an in vivo marker of genetically impaired SORL1. METHODS: CSF-sSORL1 was quantified by enzyme-linked immunosorbent assay (ELISA) in 218 participants: 90 carriers of SORL1 variants, 78 SORL1-wildtype (WT) AD patients, and 50 SORL1-WT controls. RESULTS: sSORL1 concentrations were significantly lower in carriers of protein-truncating and damaging missense variants. In SORL1-WT patients, CSF-sSORL1 correlated with pTau181 but not with Aβ42 among AD patients, and did not differ between patients and controls. DISCUSSION: These findings suggest that impaired SORL1 trafficking reduces receptor delivery to the cell surface and thereby decreases sSORL1 shedding, supporting its potential use as a pathway-specific biomarker. Highlights: Enzyme-linked immunosorbent assay (ELISA) enables quantitative measurement of soluble sortilin-related receptor (sSORL1) in cerebrospinal fluid (CSF). sSORL1 levels are reduced in CSF from carriers of a pathogenic SORL1 variant. CSF-sSORL1 levels correlate with tau pathology in Alzheimer's disease. sSORL1 levels represent an in vivo biomarker of SORL1 function.

INTRODUCTION: Cognitive resilience refers to maintaining cognitive function despite Alzheimer's disease (AD) pathophysiology. METHODS: We analyzed amyloid-positive individuals across clinical stages of AD in two cohorts: the Amsterdam Dementia Cohort (ADC, N = 1036) and Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 685). Cognitive resilience was conceptualized from a canonical correlation analysis of magnetic resonance imaging and neuropsychological data in each cohort separately. Model validation involved education as a resilience proxy and key genetic factors (apolipoprotein E [APOE] ε4 and APOE ε2) of AD. We explored associations between 83 AD risk loci and cognitive resilience. RESULTS: Resilience was correlated with education (ADC: β = 0.144, p < 0.001; ADNI: β = 0.149, p < 0.001) and APOE ε4 (β_{meta-analysis}= –0.052, p = 0.014). Exploratory single nucleotide polymorphism meta-analysis identified potential involvement of genetic variants around genes UNC5CL, USP6NL, and TPCN1 in lower, and genes COX7C and MINDY2 in higher resilience. DISCUSSION: Our novel resilience approach showed conceptual validity and potential for future discovery of resilience-related genetic variants. Highlights: ·We define a novel approach to resilience using canonical correlation analysis (CCA). ·Apolipoprotein E ε4 is linked to lower resilience, suggesting increased vulnerability. ·Genetic loci around COX7C and MINDY2 are potentially involved in higher resilience. ·This novel approach may be used for multi-cohort studies such as genome-wide association studies in the future.

We constructed a polygenic protective score specific to Alzheimer’s disease (AD PPS) based on the current literature among the participants enrolled in five studies of healthy aging and extreme longevity in the USA, Europe, and Asia. This AD PPS did not include variants on apolipoprotein E (APOE) gene. Comparisons of AD PPS in different data sets of healthy agers and centenarians showed that centenarians have stronger genetic protection against AD compared to individuals without familial longevity. The current study also shows evidence that this genetic protection increases with increasingly older ages in centenarians (centenarians who died before reaching age 105 years, semi-supercentenarians who reached age 105 to 109 years, and supercentenarians who reached age 110 years and older). However, the genetic protection was of modest size: the average increase in AD PPS was approximately one additional protective allele per 5 years of gained lifetime. Additionally, we show that the higher AD PPS was associated with better cognitive function and decreased mortality. Taken together, this analysis suggests that individuals who achieve the most extreme ages, on average, have the greatest protection against AD. This finding is robust to different genetic backgrounds with important implications for universal applicability of therapeutics that target this AD PPS.

Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.

Alzheimer's disease and related dementias (ADRD) are complex neurodegenerative disorders of which the genetic basis remains incompletely understood. Hippocampal volume loss is a core hallmark of AD. Hippocampal volume also has a strong heritable component and its genetic underpinnings may help us to understand the complex biological mechanism underlying ADRD. To identify shared genetic risk loci across late-onset ADRD and bilateral hippocampal volumes, we conducted a cross-trait analysis of existing GWAS data on the two traits using the conjunctional false discovery rate (conjFDR) framework. Functional annotation and phenome-wide association studies (PheWAS) were performed on the identified shared loci to characterize their biological relevance. We identified 11 unique lead genetic loci, of which 7 loci showed discordant directional effects (loci associated with increased risk for ADRD and smaller hippocampal volumes). We found that SHARPIN and TNIP1 genes play a role in ADRD by affecting hippocampal volumes. In addition, we observed 9 novel ADRD-hippocampus loci in genes previously implicated in AD (IGIP and ACE) and novel ADRD-genes (KCTD13, HINT1, SH3TC2, FAM53B, TPM1, IL34 and SSH2). PheWAS results show that most shared loci associated with neuroimaging measurements, white blood cell markers, red blood cell markers, and lipids. This study shows a shared genetic basis between ADRD and bilateral hippocampal volumes. By integrating summary statistics for these two traits, we identified both novel and previously reported ADRD-hippocampus loci. Functional analysis highlights the role of immune cells and lipid markers in the shared loci, suggesting a shared neurobiological basis for ADRD and bilateral hippocampal volumes.

Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.

Background and ObjectivesIdentifying genetic causes of dementia in patients visiting memory clinics is important for patient care and family planning. Traditional clinical selection criteria for genetic testing may miss carriers of pathogenic variants in dementia-related genes. This study aimed identify how many carriers we are missing and to optimize criteria for selecting patients for genetic counseling in memory clinics.MethodsIn this clinical cohort study, we retrospectively genetically tested patients during 2.5 years (2010-2012) visiting the Alzheimer Center Amsterdam, a specialized memory clinic. Genetic tests consisted of a 54-gene dementia panel, focusing on Class IV/V variants per American College of Medical Genetics and Genomics guidelines, including APP duplications and the C9ORF72 repeat expansion. We determined the prevalence of pathogenic variants and propose new eligibility criteria for genetic testing in memory clinics. The eligibility criteria were prospectively applied for 1 year (2021-2022), and results were compared with the retrospective cohort.ResultsGenetic tests were retrospectively performed in in 1,022 of 1,138 patients (90%) who consecutively visited the memory clinic. Among these, 1,022 patients analyzed (mean age 62.1 ± 8.9 years; 40.4% were female), 34 pathogenic variant carriers were identified (3.3%), with 24 being symptomatic. Previous clinical criteria would have identified only 15 carriers (44% of all carriers, 65% of symptomatic carriers). The proposed criteria increased identification to 22 carriers (62.5% of all carriers, 91% of symptomatic carriers). In the prospective cohort, 148 (28.7%) of 515 patients were eligible for testing under the new criteria. Of the 90 eligible patients who consented to testing, 13 pathogenic carriers were identified, representing a 73% increase compared with the previous criteria.DiscussionWe found that patients who visit a memory clinic and carry a pathogenic genetic variant are often not eligible for genetic testing. The proposed new criteria improve the identification of patients with a genetic cause for their cognitive complaints. In systems without practical or financial barriers to genetic testing, the new criteria can enhance personalized care. In other countries where the health care systems differs and in other genetic ancestry groups, the performance of the criteria may be different.

BACKGROUND: Alzheimer's disease (AD) prevalence increases with age, yet a small fraction of the population reaches ages > 100 years without cognitive decline. We studied the genetic factors associated with such resilience against AD. METHODS: Genome-wide association studies identified 86 single nucleotide polymorphisms (SNPs) associated with AD risk. We estimated SNP frequency in 2281 AD cases, 3165 age-matched controls, and 346 cognitively healthy centenarians. We calculated a polygenic risk score (PRS) for each individual and investigated the functional properties of SNPs enriched/depleted in centenarians. RESULTS: Cognitively healthy centenarians were enriched with the protective alleles of the SNPs associated with AD risk. The protective effect concentrated on the alleles in/near ANKH, GRN, TMEM106B, SORT1, PLCG2, RIN3, and APOE genes. This translated to >5-fold lower PRS in centenarians compared to AD cases (P = 7.69 × 10⁻⁷¹), and 2-fold lower compared to age-matched controls (P = 5.83 × 10⁻¹⁷). DISCUSSION: Maintaining cognitive health until extreme ages requires complex genetic protection against AD, which concentrates on the genes associated with the endolysosomal and immune systems. Highlights: Cognitively healthy cent enarians are enriched with the protective alleles of genetic variants associated with Alzheimer's disease (AD). The protective effect is concentrated on variants involved in the immune and endolysosomal systems. Combining variants into a polygenic risk score (PRS) translated to > 5-fold lower PRS in centenarians compared to AD cases, and ≈ 2-fold lower compared to middle-aged healthy controls.

Background: Many families with clinical early-onset Alzheimer’s disease (EOAD) remain genetically unexplained. A combination of genetic factors is not standardly investigated. In addition to monogenic causes, we evaluated the possible polygenic architecture in a large series of families, to assess if genetic testing of familial EOAD could be expanded. Methods: Thirty-six pedigrees (77 patients) were ascertained from a larger cohort of patients, with relationships determined by genetic data (exome sequencing data and/or SNP arrays). All families included at least one AD patient with symptom onset <70 years. We evaluated segregating rare variants in known dementia-related genes, and other genes or variants if shared by multiple families. APOE was genotyped and duplications in APP were assessed by targeted test or using SNP array data. We computed polygenic risk scores (PRS) compared with a reference population-based dataset, by imputing SNP arrays or exome sequencing data. Results: In eight families, we identified a pathogenic variant, including the genes APP, PSEN1, SORL1, and an unexpected GRN frameshift variant. APOE-ε4 homozygosity was present in eighteen families, showing full segregation with disease in seven families. Eight families harbored a variant of uncertain significance (VUS), of which six included APOE-ε4 homozygous carriers. PRS was not higher in the families combined compared with the population mean (beta 0.05, P = 0.21), with a maximum increase of 0.61 (OR = 1.84) in the GRN family. Subgroup analyses indicated lower PRS in six APP/PSEN1 families compared with the rest (beta −0.22 vs. 0.10; P = 0.009) and lower APOE burden in all eight families with monogenic cause (beta 0.29 vs. 1.15, P = 0.010). Nine families remained without a genetic cause or risk factor identified. Conclusion: Besides monogenic causes, we suspect a polygenic disease architecture in multiple families based on APOE and rare VUS. The risk conveyed by PRS is modest across the studied families. Families without any identified risk factor render suitable candidates for further in-depth genetic evaluation.

Background: Dementia with Lewy bodies (DLB) is a complex, progressive neurodegenerative disease with considerable phenotypic, pathological, and genetic heterogeneity. Objective: We tested if genetic variants in part explain the heterogeneity in DLB. Methods: We tested the effects of variants previously associated with DLB (near APOE, GBA, and SNCA) and polygenic risk scores for Alzheimer's disease (AD-PRS) and Parkinson's disease (PD-PRS). We studied 190 probable DLB patients from the Alzheimer's dementia cohort and compared them to 2,552 control subjects. The p-tau/Aβ1-42 ratio in cerebrospinal fluid was used as in vivo proxy to separate DLB cases into DLB with concomitant AD pathology (DLB-AD) or DLB without AD (DLB-pure). We studied the clinical measures age, Mini-Mental State Examination (MMSE), and the presence of core symptoms at diagnosis and disease duration. Results: We found that all studied genetic factors significantly associated with DLB risk (all-DLB). Second, we stratified the DLB patients by the presence of concomitant AD pathology and found that APOE ϵ4 and the AD-PRS associated specifically with DLB-AD, but less with DLB-pure. In addition, the GBA p.E365K variant showed strong associated with DLB-pure and less with DLB-AD. Last, we studied the clinical measures and found that APOE ϵ4 associated with reduced MMSE, higher odds to have fluctuations and a shorter disease duration. In addition, the GBA p.E365K variant reduced the age at onset by 5.7 years, but the other variants and the PRS did not associate with clinical features. Conclusion: These finding increase our understanding of the pathological and clinical heterogeneity in DLB.

Genetic association studies are frequently used to study the genetic basis of numerous human phenotypes. However, the rapid interrogation of how well a certain genomic region associates across traits as well as the interpretation of genetic associations is often complex and requires the integration of multiple sources of annotation, which involves advanced bioinformatic skills. We developed snpXplorer, an easy-to-use web-server application for exploring Single Nucleotide Polymorphisms (SNP) association statistics and to functionally annotate sets of SNPs. snpXplorer can superimpose association statistics from multiple studies, and displays regional information including SNP associations, structural variations, recombination rates, eQTL, linkage disequilibrium patterns, genes and gene-expressions per tissue. By overlaying multiple GWAS studies, snpXplorer can be used to compare levels of association across different traits, which may help the interpretation of variant consequences. Given a list of SNPs, snpXplorer can also be used to perform variant-to-gene mapping and gene-set enrichment analysis to identify molecular pathways that are overrepresented in the list of input SNPs. snpXplorer is freely available at https://snpxplorer.net. Source code, documentation, example files and tutorial videos are available within the Help section of snpXplorer and at https://github.com/TesiNicco/snpXplorer.

Human longevity is influenced by the genetic risk of age-related diseases. As Alzheimer’s disease (AD) represents a common condition at old age, an interplay between genetic factors affecting AD and longevity is expected. We explored this interplay by studying the prevalence of AD-associated single-nucleotide-polymorphisms (SNPs) in cognitively healthy centenarians, and replicated findings in a parental-longevity GWAS. We found that 28/38 SNPs that increased AD-risk also associated with lower odds of longevity. For each SNP, we express the imbalance between AD- and longevity-risk as an effect-size distribution. Based on these distributions, we grouped the SNPs in three groups: 17 SNPs increased AD-risk more than they decreased longevity-risk, and were enriched for β-amyloid metabolism and immune signaling; 11 variants reported a larger longevity-effect compared to their AD-effect, were enriched for endocytosis/immune-signaling, and were previously associated with other age-related diseases. Unexpectedly, 10 variants associated with an increased risk of AD and higher odds of longevity. Altogether, we show that different AD-associated SNPs have different effects on longevity, including SNPs that may confer general neuro-protective functions against AD and other age-related diseases.

BACKGROUND: Several collaborative genome-wide-association studies (GWAS) have characterized the genetic landscape of Alzheimer's disease (AD), which now counts >70 single-nucleotide polymorphisms (SNPs) associated with AD-risk. METHOD: We linked these SNPs to their affected biological pathways, and combined the effect of multiple SNPs into pathway-specific polygenic-risk-scores (PRS). Using a genetically homogeneous dataset of 2,458 AD-patients (age=70.2±10.4), 3,848 healthy controls (age=61.1±14.8), 343 cognitively healthy centenarians (age=101.1±1.8) and 705 individuals with mild-cognitive-impairment (MCI, age=69.1±8.9), we studied the association between pathway-PRS and AD-risk, MCI-to-AD conversion, and resilience against AD. RESULT: With an integrative strategy, we linked 72 AD-associated SNPs to 5 clusters of biological pathways: beta-amyloid cluster, immune cluster, vascular cluster, endocytosis cluster and a trafficking cluster (Figure 1). A PRS comprising all 72 SNPs (excluding APOE-SNPs) was significantly associated with AD-risk (OR=1.53, p<2e-16), progression of MCI to AD dementia (OR=1.45, p=5.5e-4), and, albeit in the opposite direction, resilience against AD in healthy centenarians (OR=0.82, p=6.4e-4) (Figure 2, Figure 3). At the pathway level, all pathway-PRS significantly associated with increased AD-risk while specifically the vascular-, endocytosis- and trafficking-PRS associated with resilience against AD (p<0.05) (Figure 4). Interestingly, the beta-amyloid-, endocytosis and trafficking-PRSs were significantly associated with MCI-to-AD progression (p<0.05), with a higher-PRS leading up to 1.5-year shorter conversion time. CONCLUSION: Our results add on the efficacy of pathway-specific PRSs to identify individuals at highest or the lowest risk for the development of AD. Further, our results suggest that specific biological pathways are more important at different stages of the disease or in fact, associate with the escape of disease. AD diagnostic procedures may benefit from the identification of individual, pathway-specific vulnerabilities. In the future, pathway-specific PRSs may contribute to the selection of patients who may benefit most from pathway-specific treatment strategies.

Dysfunction of the endolysosomal-autophagy network is emerging as an important pathogenic process in Alzheimer's disease. Mutations in the sorting receptor-encoding gene SORL1 cause autosomal-dominant Alzheimer's disease, and SORL1 variants increase risk for late-onset AD. To understand the contribution of SORL1 mutations to AD pathogenesis, we analyze the effects of a SORL1 truncating mutation on SORL1 protein levels and endolysosome function in human neurons. We find that truncating mutation results in SORL1 haploinsufficiency and enlarged endosomes in human neurons. Analysis of isogenic SORL1 wild-type, heterozygous, and homozygous null neurons demonstrates that, whereas SORL1 haploinsufficiency results in endosome dysfunction, complete loss of SORL1 leads to additional defects in lysosome function and autophagy. Neuronal endolysosomal dysfunction caused by loss of SORL1 is relieved by extracellular antisense oligonucleotide-mediated reduction of APP protein, demonstrating that PSEN1, APP, and SORL1 act in a common pathway regulating the endolysosome system, which becomes dysfunctional in AD.