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.

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.

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.

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.

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.

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: Dementia in families can be caused by one genetic variant. Identifying these so-called monogenic causes of dementia is important, because it explains the origin of dementia in families and raises the possibility of predictive testing for relatives. Still, we do not know how frequent these monogenic causes are, due to strict selection criteria for DNA testing based on age at onset and a positive family history. We aimed to identify the mutation frequency of monogenetic dementia by screening a large, unselected cohort of patients from a memory clinic specialized in early onset dementia. METHOD: Between 1-1-2010 and 1-7-2012, 1,138 patients visited the Alzheimer Center Amsterdam and all patients underwent the same diagnostic trajectory (van der Flier et al 2018). Of these, 1,093 (96%) consented to research and donated blood. An additional 73 patients (7%) were excluded because suboptimal DNA quality. Whole exome sequencing and C9orf72-repeat length analysis was performed in the remaining 1,020 patients (90% of all patients). All variants in 54 dementia related genes were analysed and classified. C9orf72 repeat length >30 repeat units was considered pathogenic. Variants classified as likely pathogenic and pathogenic were considered a monogenic cause of dementia. RESULT: The average age at presentation was 62(±6SD) years and 419(41%) were female. We found a monogenic cause of dementia in 34 (3.4%) patients. The most frequently occurring (likely) pathogenic variants were found in the genes C9orf72, PSEN1, NOTCH3 and MAPT. These genes explained 65% of the (likely) pathogenic variants. The clinical characteristics of the patients screened positive; 50% were diagnosed with dementia and 50% had a first degree relative with dementia; and 40% had an age at presentation of <60 years and 44% was between 60 to 70 years, the remainder was older. Surprisingly, only 47% of the patients with a (likely) pathogenic variant fulfilled our current criteria (based on diagnosis, age and familial history) for offering diagnostic genetic testing (21% of patients). CONCLUSION: In our large unselected cohort of patients from a memory clinic specialized in early onset dementia, the majority of the patients with a monogenetic predisposition for dementia did not fulfill our current criteria for genetic testing.

Studying the genome of centenarians may give insights into the molecular mechanisms underlying extreme human longevity and the escape of age-related diseases. Here, we set out to construct polygenic risk scores (PRSs) for longevity and to investigate the functions of longevity-associated variants. Using a cohort of centenarians with maintained cognitive health (N = 343), a population-matched cohort of older adults from 5 cohorts (N = 2905), and summary statistics data from genome-wide association studies on parental longevity, we constructed a PRS including 330 variants that significantly discriminated between centenarians and older adults. This PRS was also associated with longer survival in an independent sample of younger individuals (p =. 02), leading up to a 4-year difference in survival based on common genetic factors only. We show that this PRS was, in part, able to compensate for the deleterious effect of the APOE-ϵ4 allele. Using an integrative framework, we annotated the 330 variants included in this PRS by the genes they associate with. We find that they are enriched with genes associated with cellular differentiation, developmental processes, and cellular response to stress. Together, our results indicate that an extended human life span is, in part, the result of a constellation of variants each exerting small advantageous effects on aging-related biological mechanisms that maintain overall health and decrease the risk of age-related diseases.

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.

Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.