Progranulin mutations in clinical and neuropathological Alzheimer's disease

Vardarajan, Badri N.; Reyes‐Dumeyer, Dolly; Piriz, Angel; Lantigua, Rafael; Medrano, Martin; Rivera, Diones; Jiménez‐Velázquez, Ivonne Z.; Martin, Eden R.; Pericak‐Vance, Margaret A.; Bush, William S.; Farrer, Lindsay A.; Haines, Jonathan L.; Wang, Li‐San; Leung, Yuk Yee; Schellenberg, Gerard D.; Kukull, Walter A.; Jager, Philip De; Bennett, David A.; Schneider, Julie A.; Mayeux, Richard

doi:10.1002/alz.12567

Cited by 15 publications

(7 citation statements)

References 52 publications

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“…CD55 , expressed in both neurons and glial cells 61 , played a role in Alzheimer’s disease progression by influencing both the complement 62 and inflammatory systems 63 . GRN encoded the protein progranulin, a microglial protein linked to Alzheimer’s disease, acting as a mediator of neuroinflammation and exacerbating tau-related brain pathology 64 . BCAM and SIRPA both encoded glycoproteins of the immunoglobulin superfamily.…”

Section: Resultsmentioning

confidence: 99%

Large-scale imputation models for multi-ancestry proteome-wide association analysis

Wu,

Zhang,

Yang

et al. 2023

Preprint

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Proteome-wide association studies (PWAS) decode the intricate proteomic landscape of biological mechanisms for complex diseases. Traditional PWAS model training relies heavily on individual-level reference proteomes, thereby restricting its capacity to harness the emerging summary-level protein quantitative trait loci (pQTL) data in the public domain. Here we introduced a novel framework to train PWAS models directly from pQTL summary statistics. By leveraging extensive pQTL data from the UK Biobank, deCODE, and ARIC studies, we applied our approach to train large-scale European PWAS models (totaln= 88,838 subjects). Furthermore, we developed PWAS models tailored for Asian and African ancestries by integrating multi-ancestry summary and individual-level data resources (totaln= 914 for Asian and 3,042 for African ancestries). We validated the performance of our PWAS models through a systematic multi-ancestry analysis of over 700 phenotypes across five major genetic data resources. Our results bridge the gap between genomics and proteomics for drug discovery, highlighting novel protein-phenotype links and their transferability across diverse ancestries. The developed PWAS models and data resources are freely available atwww.gcbhub.org.

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Section: Resultsmentioning

confidence: 99%

Large-scale imputation models for multi-ancestry proteome-wide association analysis

Wu,

Zhang,

Yang

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…LGALS9_SLC1A5, and F10_TNFRSF10A communicated frequently in low-CR B cells. The increased chemokine CCL4 and GRN mutations were found to closely associated with AD pathology (36,37), suggesting a poor prognosis in AD patients. Additionally, the pseudotime analysis demonstrated that the CRD is involved in the transformation of naive B cells into GC B cells, thus resulting in the progression of AD.…”

Section: Discussionmentioning

confidence: 99%

Combined analysis of single-cell and bulk RNA sequencing reveals the expression patterns of circadian rhythm disruption in the immune microenvironment of Alzheimer’s disease

Yang

Wang

et al. 2023

Front. Immunol.

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BackgroundCircadian rhythm disruption (CRD) represents a critical contributor to the pathogenesis of Alzheimer’s disease (AD). Nonetheless, how CRD functions within the AD immune microenvironment remains to be illustrated.MethodsCircadian rhythm score (CRscore) was utilized to quantify the microenvironment status of circadian disruption in a single-cell RNA sequencing dataset derived from AD. Bulk transcriptome datasets from public repository were employed to validate the effectiveness and robustness of CRscore. A machine learning-based integrative model was applied for constructing a characteristic CRD signature, and RT-PCR analysis was employed to validate their expression levels.ResultsWe depicted the heterogeneity in B cells, CD4+ T cells, and CD8+ T cells based on the CRscore. Furthermore, we discovered that CRD might be strongly linked to the immunological and biological features of AD, as well as the pseudotime trajectories of major immune cell subtypes. Additionally, cell–cell interactions revealed that CRD was critical in the alternation of ligand-receptor pairs. Bulk sequencing analysis indicated that the CRscore was found to be a reliable predictive biomarker in AD patients. The characteristic CRD signature, which included 9 circadian‐related genes (CRGs), was an independent risk factor that accurately predicted the onset of AD. Meanwhile, abnormal expression of several characteristic CRGs, including GLRX, MEF2C, PSMA5, NR4A1, SEC61G, RGS1, and CEBPB, was detected in neurons treated with Aβ1-42 oligomer.ConclusionOur study revealed CRD-based cell subtypes in the AD microenvironment at single-cell level and proposed a robust and promising CRD signature for AD diagnosis. A deeper knowledge of these mechanisms may provide novel possibilities for incorporating “circadian rhythm-based anti-dementia therapies” into the treatment protocols of individualized medicine.

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“…Variants in the 3'UTR region can impact translation or protein stability, and transcription binding can be impacted by variants in the 5'UTR region. Additionally, GRN-rs5848 is associated with circulating progranulin levels and decreased GRN expression has been implicated in several neurodegenerative diseases, including AD and frontotemporal dementia [52][53][54] . In contrast to previous studies in European populations, the SORL1 locus was not resolved to a single putative causal SNP.…”

Section: Discussionmentioning

confidence: 99%

Multi-ancestry meta-analysis and fine-mapping in Alzheimer’s Disease

Lake

Makarious

Kim

et al. 2022

Preprint

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Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published and de novo GWAS from European, East Asian, African American, and Caribbean Hispanic populations to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci and globally assessed the heterogeneity of known risk factors across populations. Additionally we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to Alzheimer's disease risk.

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Progranulin mutations in clinical and neuropathological Alzheimer's disease

Cited by 15 publications

References 52 publications

Large-scale imputation models for multi-ancestry proteome-wide association analysis

Large-scale imputation models for multi-ancestry proteome-wide association analysis

Combined analysis of single-cell and bulk RNA sequencing reveals the expression patterns of circadian rhythm disruption in the immune microenvironment of Alzheimer’s disease

Multi-ancestry meta-analysis and fine-mapping in Alzheimer’s Disease

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