The Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs) is a longitudinal, global cohort study investigating brain aging and autosomal dominant Alzheimer’s disease (ADAD), a rare monogenic form of Alzheimer’s disease (AD). Established in 2008 with support from the National Institute on Aging (NIA), DIAN Obs is designed to collect comprehensive and uniform data with the aim to characterize brain biology and clinical trajectory of individuals at risk for ADAD. Mutations in the amyloid protein precursor (APP), presenilin 1 (PSEN1), or presenilin 2 (PSEN2) genes cause ADAD with virtually full penetrance and a predictable age at symptomatic onset. Participants, both mutation carriers and non-carriers from affected families, undergo longitudinal clinical and cognitive assessments, neurologic and physical examinations, structural and functional neuro-imaging, and amyloid and tau positron emission tomography (PET). Biospecimens include cerebrospinal fluid, plasma, serum, and whole blood for biochemical, genetic and multi-omic analyses, with brain donation upon death. This dataset enables one of the most detailed longitudinal examinations of the human brain across the continuum from presymptomatic to symptomatic AD. The extensive DIAN Obs data and biospecimen repository provides a globally accessible resource to advance understanding of AD pathophysiology, aging, and the development of preventive and therapeutic interventions.

Predicting not just if, but also when, cognitively unimpaired individuals are likely to develop onset of Alzheimerʼs disease (AD) symptoms would be useful to clinical trials and, eventually, clinical practice. Although clock models based on amyloid and tau positron emission tomography have shown promise in predicting the onset of AD symptoms, a model based on plasma biomarkers would be more accessible. Using longitudinal plasma %p-tau217 (the ratio of phosphorylated to non-phosphorylated tau at position 217) from two independent cohorts ( n = 258 and n = 345), clock models were used to estimate the age at plasma %p-tau217 positivity. The estimated age at plasma %p-tau217 positivity was associated with the age at onset of AD symptoms (adjusted R 2 of 0.337−0.612) with a median absolute error of 3.0−3.7 years. Notably, the time from %p-tau217 positivity to onset of AD symptoms was markedly shorter in older individuals. Similar models were constructed with data from one p-tau217/Aβ42 immunoassay and four plasma p-tau217 immunoassays. These findings suggest that the time until onset of AD symptoms can be estimated using a single blood test within a margin of error that is acceptable for use in clinical trials.

Since 2016, the Alzheimer's Association and the Fondation Alzheimer have hosted Global Alzheimer's Leadership Series (GoALS) global think tanks, with world-leading experts for innovative discussions to advance Alzheimer's disease (AD) research and care. The second GoALS think tank, held in June 2024 in Paris, focused on the relationship between biological changes and clinical manifestations of AD in the context of the evolving therapeutic landscape. Discussions spanned real-world experiences of providers, patients, and their families, theoretical considerations, and health system challenges. The lived experience perspective was central to these discussions. The importance of shared decision-making, clear and transparent communication, and the need for real-world data to holistically support patients during their experiences were highlighted. This manuscript shares key insights from both the think tank meeting in Paris and a featured research session at the 2024 Alzheimer's Association International Conference that expanded the discussion themes for broader dissemination with the community.

Etalanetug (E2814) is designed to delay the clinical progression of Alzheimer’s disease (AD) by binding to the microtubule binding region (MTBR) of tau implicated in seeding and spreading of tau pathology. Dominantly inherited Alzheimer’s disease (DIAD) is a rare form of the disease (< 1

Abstract Cerebrospinal fluid amyloid beta 42, total tau, and phosphorylated tau 181 are well accepted markers of Alzheimer’s disease. These biomarkers better reflect disease pathogenesis compared to clinical diagnosis. Here, we perform a genome wide association study meta-analysis including 18,948 individuals of European ancestry and identify 12 genome-wide significant loci across all three biomarkers, eight of them novel. We replicate the association of biomarkers with APOE , CR1 , GMNC/CCDC50 and C16orf95/MAP1LC3B . Novel loci include BIN1 for amyloid beta and GNA12, MS4A6A, SLCO1A2 with both total tau and phosphorylated tau 181, as well as additional loci on chr. 8, near ANGPT1 and chr. 9 near SMARCA2 . We also demonstrate that these variants have significant association with Alzheimer’s disease risk, disease progression and/or brain amyloidosis. The associated genes are implicated in lipid metabolism independent of APOE , coupled with autophagy and brain volume regulation driven by total tau and phosphorylated tau 181 dysregulation.

Antibody therapies can remove amyloid plaques from the brain and slow cognitive decline in people with Alzheimer's disease who are mildly impaired. These drugs are now being evaluated in participants who are cognitively unimpaired but positive for a biomarker of Alzheimer's disease for their safety, tolerability, disease-modifying and cognitive preserving effects, and ability to avert the onset of cognitive impairment. If these studies are successful, and the drugs get regulatory approval, they could accelerate the evaluation and approval of related Alzheimer's disease-modifying treatments in people who are unimpaired with or without a biomarker of the disease. Preclinical Alzheimer's disease therapies that modify the underlying disease in people who are unimpaired with a biomarker of Alzheimer's disease and primary prevention therapies that avert the onset of amyloid plaques in those with a negative test have the potential to substantially prevent ensuing biological and clinical manifestations of Alzheimer's disease. In this Policy View, we assess the challenges and opportunities that trials of these drug treatments will bring, and consider the blood tests, cognitive assessments, and post-marketing strategies needed to enable the approval, affordability, health-care insurance coverage, and equitable use. Our recommendations are intended for consideration in the USA, and relevant refinement in other countries.

Background Alzheimer's disease (AD) clinical trials often involve uneven follow-up durations and long-term open-label extensions (OLE), yet conventional statistical models are typically designed for fixed schedules, limiting their efficiency in such settings. Objective To describe and illustrate alternative statistical modeling approaches developed and implemented in the Dominantly Inherited Alzheimer Network Trials Unit platform trial to optimally leverage data with irregular and extended follow-up. Methods We present three complementary models: (1) a Cox proportional hazards model for recurrent disease progression events that uses all observed worsening events rather than only the first event; (2) a parametric disease progression model based on estimated years from expected symptom onset that estimates proportional slowing or time delay in disease progression; and (3) piecewise linear mixed-effects models tailored to the "gap" period between the double-blind phase and OLE, accommodating variable off-treatment intervals and missing interim data. All methods are illustrated with hypothetical examples, and ready-to-use SAS code is provided in the Supplemental Material. Results The proposed models successfully handle complex longitudinal data structures typical trials with OLE phases, offering greater statistical efficiency and more comprehensive capture of treatment effects over extended periods compared with traditional approaches. Conclusions These flexible, efficient statistical models are well-suited for rare disease and long-duration AD trials. Wider adoption and further validation of these approaches may enhance the power and interpretability of future neurodegenerative disease trials.

Despite advances in understanding the mechanisms, risk factors and treatment strategies for Alzheimer's disease (AD), no approved therapies exist to prevent or delay onset in at-risk individuals or those with elevated biomarkers who do not yet show symptoms. Multiple candidate interventions are now being evaluated in clinical trials in these settings, raising key questions around which populations are most appropriate and what criteria should guide regulatory and clinical decision-making. Data are expected within 1-2 years, underscoring the need for stakeholder alignment on clinically meaningful and acceptable characteristics of preventative therapies or other products. To address this need, the Global CEO Initiative on Alzheimer's Disease convened an international group of experts to develop target product profiles for therapies designed to delay or prevent the onset of clinical symptoms in AD. These target product profiles outline minimum and preferred characteristics, including intended use, target populations, safety expectations and efficacy benchmarks. This effort provides a foundational framework to accelerate therapeutic development and guide researchers, regulators and patients in the evaluation of emerging therapies for preventing symptomatic AD.

INTRODUCTION:Tau species lacking truncation of the N-terminal region, including plasma N-terminal tau fragment 1 (NT1), have been previously associated with cognitive decline, neurodegeneration, and tau pathology in late-onset sporadic Alzheimer's disease (AD). METHODS:Here, we examined cross-sectional and longitudinal plasma NT1 as a possible predictor of cognitive, clinical, and core AD biomarker trajectories in autosomal dominant AD (ADAD). RESULTS:NT1 levels in ADAD mutation carriers (MC; n = 132) increased across the disease continuum, compared to non-carriers (NC; n = 75), becoming elevated about a decade prior to estimated symptom onset. Cross-sectional and longitudinal NT1 levels in MC were associated with clinical, cognitive, and biomarker changes. NT1 increases continued in symptomatic phases of disease, a distinct trajectory from that seen with CSF p-tau217 and other phospho-tau species. DISCUSSION:Together, our results suggest that plasma NT1-alone or combined with other tau measures-may be useful in studying AD-related clinical, cognitive, and biomarker outcomes. HIGHLIGHTS:Leveraging a deeply phenotyped cohort of individuals carrying a pathogenic variant for autosomal dominant Alzheimer's disease (ADAD) and their non-carrier family members, our results suggest that plasma N-terminal tau fragment 1 (NT1) levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with cerebrospinal fluid (CSF) measures of tau pathology but less so with CSF or imaging measures of β-amyloid pathology. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1-alone or combined with other tau measures-may be useful in studying AD-related tau pathology and neurodegeneration across a wide spectrum of disease.

INTRODUCTION:It is unknown if neurodegeneration trajectories differ between Down syndrome (DS) and autosomal dominant Alzheimer's disease (ADAD), both of which are genetic forms of Alzheimer's disease (AD). METHODS:We compared brain volumes in DS, ADAD, and unaffected family members serving as controls. Participants underwent magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET), deriving volumetric and amyloid burden, respectively. Nonlinear associations between regional volumes and estimated years to clinical symptom onset (EYO) were evaluated using generalized additive mixed-models. RESULTS:Longitudinal data from 267 controls, 341 participants with DS, and 358 participants with ADAD were included, totaling 1908 scans. DS volumes were lower than ADAD and controls initially and dropped linearly. ADAD had similar volumes to controls until diverging, beginning at EYO -7. Amyloid was negatively associated with volume, with similar slopes in DS and ADAD. DISCUSSION:ADAD and DS demonstrate distinct patterns of brain volume decline prior to symptom onset despite being similarly affected by amyloid.

In precision medicine, subgroup identification is crucial for designing personalized treatments. This research focuses on subgroup identification in longitudinal clinical trials by integrating the Interaction Tree (ITree) with the Mixed Model for Repeated Measures (MMRM). Our ITree-MMRM approach retains the flexibility of tree-based methods in capturing nonlinear treatment interactions for heterogeneous treatment effects, while adhering to Food and Drug Administration guidelines for assessing treatment effects at the conclusion of longitudinal studies using MMRM. Additionally, we explore various options for tuning parameters and employ bootstrap methods to prune trees, reducing the risk of overoptimism. We demonstrate that our method outperforms existing subgroup identification techniques in simulations. The ITree-MMRM model is applied to an Alzheimer's disease clinical trial to identify subgroups with long-term treatment responses.

Alzheimer’s Disease (AD) is the most common neurodegenerative disorder and the leading cause of dementia characterised by the accumulation of beta amyloid (Aβ) plaques and neurofibrillary tangles (NFT). Several monoclonal antibodies against amyloid in early AD have shown the utility of reducing brain amyloid in large phase 3 studies, resulting in modest clinical benefit. To further slow, or even halt disease progression, targeting additional pathobiological pathways is likely to be necessary. In this review, we aim to appraise the scientific rationale for targeting tau in AD. The burden of tau pathology is correlated with disease severity and its role in AD progression is complex, involving synapse dysfunction, neuronal loss, neuroinflammation and autophagy impairment. Evidence suggests that hypersecretion, post-translational modifications and aggregation propensity, dependent and independent of amyloid, are also linked to neurodegeneration. We review the therapeutic agents in development including tau synthesis modifiers, active and passive immunotherapies, post-translational modifiers and aggregation inhibitors. Finally, we consider the available biomarker tools for patient selection and drug effectiveness evaluation, and we identify key knowledge gaps that future novel biomarkers might address to make clinical trials of tau therapies more likely to succeed.

BACKGROUND: Individuals with autosomal dominant Alzheimer's disease (ADAD) arising from mutations in PSEN1, PSEN2, or APP exhibit variability in clinical presentation. Genetic studies of ADAD have shaped our understanding of the disease, and the discovery of genetic modifiers can inform therapeutic interventions and improve patient outcomes. We aimed to discover new genetic modifiers in individuals with mutations in the three ADAD genes. METHODS: In this genome-wide association study, we analysed data from participants in three study cohorts (the Knight Alzheimer Disease Research Center [Knight-ADRC], the Dominantly Inherited Alzheimer Network [DIAN] observational study, and the Alzheimer Disease Sequencing Project [ADSP] R4). We did whole-genome sequencing on 101 unrelated, non-Hispanic, White, symptomatic participants with ADAD mutations and 5050 asymptomatic, unrelated control participants. Sensitivity analyses included related participants (148 cases and 5813 controls). We assessed the molecular mechanisms associated with each risk variant, including cis-regulatory effects, plasma protein levels (Knight-ADRC, 2338 participants), CSF concentrations of Alzheimer's disease biomarkers (DIAN, 64 participants), and neuroimaging data (MRI and PET; DIAN, 64 participants). We evaluated the association of risk variants with age at onset in ADAD and in 6177 participants with sporadic Alzheimer's disease (ADSP R5). FINDINGS: Three genome-wide loci with significant risk were associated with ADAD risk, irrespective of the specific ADAD gene mutation. The CNIH4 locus association was driven by a missense variant (is caused by Gly54Ser, p<0·0001, odds ratio [OR] 11·99 [5·39-26·64]). The CCNG1 locus risk allele increased the risk of Alzheimer's disease (p<0·0001, OR 9·56 [4·29-21·24]) and reduced the age at dementia onset (p=0·0068, β=-10·15 [95% CI -17·31 to -2·77]). This allele was also positively associated with Tar DNA binding protein 43 (TDP-43) plasma protein levels and a larger gap between chronological age and structural MRI predicted brain age. The RHOJ risk allele (p<0·0001, OR 5·96 [3·42-10·36]) was associated with increased the risk of Alzheimer's disease, higher CSF total tau (p=0·0056, β=358·37) and phosphorated tau 181 (pTau181; p=0·0006, β=81·28), and lower Aβ42/Aβ40 ratio (p=0·016, β=-0·11) in DIAN ADAD participants, comparing those carrying the risk allele with those not carrying it. INTERPRETATION: Our findings provide potential insights into disease biology, emphasising the role of Aβ, tau, TDP-43, astrocytes, and angiogenesis in Alzheimer's disease aetiology. This study offers invaluable insight for family genetic counselling and future clinical trial designs. FUNDING: National Institute of Health, National Institute on Aging, Alzheimer's Association, Hope Center Pilot 2025 Award, NGI Pilot Grant 2025 Award, BrightFocus Foundation, UK Dementia Research Institute at University College London, UK National Institutes for Health and Care Research University College London Hospitals Biomedical Research Centre, Dominantly Inherited Alzheimer Network, Freedom Together Foundation.

Objective:Disease progression modeling (DPM) or "amyloid time" is increasingly used to stage Alzheimer disease (AD). DPM performance depends on within-individual heterogeneity in rates of pathological accumulation as well as test-retest reliability of the biomarker. The relative contributions of these variabilities have not been systematically assessed. This would be particularly relevant if extrapolations from DPM were to be used to make individual-level predictions for research, clinical trials, or potentially future clinical practice. Methods:We conducted simulation studies incorporating empirically-derived noise properties from amyloid biomarkers to assess the contributions of inter- and intra-individual variability. Findings generalized in an autosomal dominant AD cohort with amyloid positron emission tomography (PET), cerebrospinal fluid (CSF), and plasma biomarkers and in a sporadic AD cohort with both amyloid PET and plasma biomarkers. We assessed group level DPM performance via mean average error (MAE) and root mean squared error (RMSE). At the individual level, we evaluated distinctness of distributions of biomarker levels associated with specific disease timings. Results:Inter-individual variability was the dominant source of error in temporal estimates. Intra-individual variability reduced estimate stability. Optimal performance occurred in biomarkers with positive average accumulation rates where a subset of individuals had exceptionally high levels of accumulation. In research study data, amyloid PET outperformed CSF and plasma biomarkers. Interpretation:DPM is fundamentally constrained by dynamic range, variability, and test-retest reliability of the biomarker of interest. Current DPM approaches are more robust at the group level, particularly when applied to biomarkers with more than 10-15% variability like fluid biomarkers. Funding:National Institute on Aging, Alzheimer's Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Korean Ministry of Health & Welfare and Ministry of Science and ICT, Spanish Institute of Health.

BACKGROUND:This study evaluates a tailored genetic counseling and testing (GTC) protocol for families at risk of Autosomal Dominant Alzheimer ´s Disease (ADAD) in Latin America, focusing on the essential cultural and regional adaptations. Several factors may influence the decision of whether family members decide to learn genetic status. Although the main drivers influencing the decisions to seek genetic testing have been widely studied in High-Income Counties (HIC), these questions remain relatively unknown in Low and Middle-Income countries (LMICs) such as those in Latin America (LatAm). METHOD:The primary aim of this study was to investigate the psychosocial impact of genetic testing in asymptomatic individuals from families with ADAD. We conducted a non randomized, controlled trial among ADAD families in Colombia and Argentina. The primary outcome included change from baseline in depression and general anxiety in the test group relative to the control group. Participants were categorized based on their decision to learn their genetic status, with further comparisons between mutation-positive versus mutation-negative individuals within those informed. Psychological impacts were measuring using validated scales for depression and anxiety in the group relative to the control group. RESULT:Of the 122 eligible participants, 97 completed the GTC protocol; 87 opted to learn their genetic status. There were no clinically significant differences in psychological distress between those who learned their status and those who did not, nor between mutation-positive and mutation-negative individuals. Mutation-positive carriers who learned their genetic status experienced a statistically significant increase in depression scores but remained below the cut-off point considered indicative of clinically significant depression. CONCLUSION:Our primary finding is showed no clinically meaningful differences in distress-related outcomes between individuals learning their genetic status relative to those who didn't. Our findings confirm that genetic testing is well-tolerated when using a protocol that provides screening, education, counseling, and follow-up sessions. In addition, we provide preliminary insights into the psychological impact associated with learning one's genetic status in familial AD, contributing significantly to the field of medical genetics in the region.

The cortical asymmetry index evaluates the cortical thickness asymmetry between hemispheres. We investigated cortical asymmetry index in asymptomatic and symptomatic mutation carriers of autosomal dominant Alzheimer's disease to explore the brain asymmetry within the Alzheimer's disease continuum. Sixty baseline T1-weighted MRI scans were obtained from the Clinic Barcelona cohort. Baseline and longitudinal MRI data from 564 participants within the dominantly inherited Alzheimer network observational study were used as an independent, confirmatory cohort. Cerebrospinal fluid and plasma neurofilament light chain levels were included when available. Cortical thickness was calculated using Freesurfer and cortical asymmetry index was calculated via an open-source pipeline. Cross-sectional analyses examined cortical asymmetry index differences based on clinical classification and APOE ε4 status, adjusting for age, sex and estimated years from onset, while correlations were assessed with age, estimated years from onset, mini-mental state examination scores, and neurofilament light. Longitudinal cortical asymmetry index evolution was modelled using generalized additive models in the dominantly inherited Alzheimer network observational study cohort, incorporating age, sex, and the interaction between group and estimated years from onset. The cortical asymmetry index successfully distinguished asymptomatic mutation carrier and symptomatic mutation carriers from healthy controls in the Clinic Barcelona cohort and symptomatic mutation carriers from controls in dominantly inherited Alzheimer network observational study. Higher cortical asymmetry index in mutation carriers (asymptomatic mutation carrier and symptomatic mutation carriers combined) and in symptomatic mutation carriers were associated with higher plasma neurofilament light levels, a closer proximity to symptom onset, and lower mini-mental state examination in the Clinic Barcelona cohort. In the dominantly inherited Alzheimer network observational study cohort, mutation carriers exhibited increased cortical asymmetry index compared to controls and correlated with elevated neurofilament light (plasma and Cerebrospinal fluid), lower mini-mental state examination, and a closer proximity to symptom onset. APOE3/3 carriers showed greater asymmetry than other APOE genotypes and significant cortical asymmetry index differences between asymptomatic mutation carrier and symptomatic mutation carriers. Longitudinally, cortical asymmetry index increased over time significantly in symptomatic mutation carriers. These findings underscore brain asymmetry as a potential biomarker for early Alzheimer's disease progression in autosomal dominant Alzheimer's disease, with implications for detection and monitoring tracking disease-related neuroanatomical changes.

Although amyloid b immunotherapies offer great potential for prevention or delay of symptoms in dominantly inherited AD (DIAD), the mechanism of action of this class of medications does not address the underlying mechanism of most DIAD mutations. Moreover, the need for repeated IV infusions or sub-cutaneous injections with Ab immunotherapies may prove challenging for long-term prevention approaches. The majority of DIAD mutations appear to affect the interaction of the gamma-secretase enzyme with the Amyloid Precursor Protein (APP) making this enzyme an attractive target for disease modification. However, emerging evidence also suggests that different DIAD mutations can have significantly different effects on the processing of APP, which suggests that targeting this enzyme may have mutation dependent effects as well. Developments in the understanding of the timing of amyloid b-dependent changes in DIAD and the development of accurate measurements of Ab now enable precision-based approaches necessary for targeting gamma-secretase. Moreover, the presence of clinical trial platforms for DIAD facilitate the implementation of trials for targeting gamma-secretase. In this session, we will review approaches to testing next generation gamma-secretase therapies in DIAD. Specifically, we will outline prevention approaches in DIAD that leverage fluid-based biomarker measurements of Ab -peptides and sensitive, brief cognitive assessments to determine optimal mutation specific dosing approaches- i.e. precision medicine approach. Combining plasma, CSF and molecular PET imaging, we will outline how to assess gamma-secretase targeting therapies for different mutations in DIAD along a timescale that utilizes early pharmacodynamic effects on Ab -peptides to predict long-term effects on Ab -and downstream biomarkers of AD.

Effective treatments are now available, which have demonstrated reductions in amyloid plaque burden while slowing cognitive decline in early symptomatic Alzheimer’s disease (AD). Intervening before onset of cognitive impairment could provide greater benefit, particularly for individuals who carry an autosomal dominant mutation known to cause AD. To better guide the design of upcoming prevention trials, reliable sample size estimates for detecting relevant reductions in pathology are needed. Longitudinal PIB PET and CSF biomarker data were obtained from the Dominantly Inherited Alzheimer Network Observation study (datafreeze 14, see Table). Participants were included in the analysis based on eligibility criteria from DIAN-TU-001: estimated years to expected onset (EYO) between -15 to +10 and global Clinical Dementia Rating (CDR) score between 0 and 1, inclusive. Sample size estimates were also obtained for trials with individuals having CDR = 0 only. Linear mixed-effects models were used to estimate baseline values and rates of change in outcome measures for mutation carriers and non-carriers. Outcomes included CSF biomarkers of amyloid and p-tau 181 using three assays (INNOTEST, XMAP and Lumipulse) and Standardized Uptake Value Ratio (SUVR, cerebellar grey matter reference region) of PIB PET from six regions. We then used these estimates to compute sample size estimates to detect a 25% reduction in pathology by four years, assuming 5% significance, 80% power, and 40% dropout. Uncertainty in sample size estimates was quantified through bootstrapping. There were large differences between carriers and non-carriers at baseline and the end of a four-year study (Figure 1). Sample size estimates were consistently higher in scenarios involving only CDR = 0 carriers (Figure 2). For PIB PET cortical mean, 40[95%CI: 26,66] pariticpants per arm would be needed to detect a 25% reduction and (63[40,115] for the CDR = 0 subsample. Similar estimates were observed for individual brain regions. XMAP Aβ42 (CDR 0-1: 21, [11,65], CDR 0: 51 [21,333]) and Lumipulse Aβ42-40 ratio (CDR 0-1: 22 [13,46], CDR 0: 47[25,104]) were the most promising CSF outcome measures. Sample size estimates needed to detect a 25% reduction in pathology levels in prevention studies are in the range of 30-40 participants per arm.

Cerebrospinal fluid (CSF) amyloid beta (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau181) are well accepted markers of Alzheimer's disease. We performed a GWAS meta-analysis including 18,948 individuals of European and 416 non-European ancestry. We identified 12 genome-wide significant loci across all three biomarkers, eight of them novel. We replicated the association of CSF biomarkers with APOE , CR1 , GMNC/CCDC50 and C16orf95/MAP1LC3B . Novel loci included BIN1 for Aβ42 and GNA12, MS4A6A, SLCO1A2 with both t-tau and p-tau181, as well as additional loci on chr. 8, near ANGPT1 and chr. 9 near SMARCA2 . We also demonstrated that these variants were not only associated with CSF level of the three biomarkers but also showed significant association with AD risk, disease progression and/or brain amyloidosis. The associated genes are implicated in lipid metabolism independent APOE , as well as autophagy and brain volume regulation driven by t-tau and p-tau181 dysregulation.