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Wu B, Liu Y, Li H, Zhu L, Zeng L, Zhang Z, Peng W. Liver as a new target organ in Alzheimer's disease: insight from cholesterol metabolism and its role in amyloid-beta clearance. Neural Regen Res 2025; 20:695-714. [PMID: 38886936 PMCID: PMC11433892 DOI: 10.4103/1673-5374.391305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 11/07/2023] [Indexed: 06/20/2024] Open
Abstract
Alzheimer's disease, the primary cause of dementia, is characterized by neuropathologies, such as amyloid plaques, synaptic and neuronal degeneration, and neurofibrillary tangles. Although amyloid plaques are the primary characteristic of Alzheimer's disease in the central nervous system and peripheral organs, targeting amyloid-beta clearance in the central nervous system has shown limited clinical efficacy in Alzheimer's disease treatment. Metabolic abnormalities are commonly observed in patients with Alzheimer's disease. The liver is the primary peripheral organ involved in amyloid-beta metabolism, playing a crucial role in the pathophysiology of Alzheimer's disease. Notably, impaired cholesterol metabolism in the liver may exacerbate the development of Alzheimer's disease. In this review, we explore the underlying causes of Alzheimer's disease and elucidate the role of the liver in amyloid-beta clearance and cholesterol metabolism. Furthermore, we propose that restoring normal cholesterol metabolism in the liver could represent a promising therapeutic strategy for addressing Alzheimer's disease.
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Affiliation(s)
- Beibei Wu
- Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Yuqing Liu
- Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Hongli Li
- Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Lemei Zhu
- Academician Workstation, Changsha Medical University, Changsha, Hunan Province, China
| | - Lingfeng Zeng
- Academician Workstation, Changsha Medical University, Changsha, Hunan Province, China
| | - Zhen Zhang
- Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- Yangsheng College of Traditional Chinese Medicine, Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China
- Qinhuangdao Shanhaiguan Pharmaceutical Co., Ltd, Qinhuangdao, Hebei Province, China
| | - Weijun Peng
- Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
- National Clinical Research Center for Mental Disorder, The Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
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Alves VC, Carro E, Figueiro-Silva J. Unveiling DNA methylation in Alzheimer's disease: a review of array-based human brain studies. Neural Regen Res 2024; 19:2365-2376. [PMID: 38526273 PMCID: PMC11090417 DOI: 10.4103/1673-5374.393106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 12/05/2023] [Indexed: 03/26/2024] Open
Abstract
The intricacies of Alzheimer's disease pathogenesis are being increasingly illuminated by the exploration of epigenetic mechanisms, particularly DNA methylation. This review comprehensively surveys recent human-centered studies that investigate whole genome DNA methylation in Alzheimer's disease neuropathology. The examination of various brain regions reveals distinctive DNA methylation patterns that associate with the Braak stage and Alzheimer's disease progression. The entorhinal cortex emerges as a focal point due to its early histological alterations and subsequent impact on downstream regions like the hippocampus. Notably, ANK1 hypermethylation, a protein implicated in neurofibrillary tangle formation, was recurrently identified in the entorhinal cortex. Further, the middle temporal gyrus and prefrontal cortex were shown to exhibit significant hypermethylation of genes like HOXA3, RHBDF2, and MCF2L, potentially influencing neuroinflammatory processes. The complex role of BIN1 in late-onset Alzheimer's disease is underscored by its association with altered methylation patterns. Despite the disparities across studies, these findings highlight the intricate interplay between epigenetic modifications and Alzheimer's disease pathology. Future research efforts should address methodological variations, incorporate diverse cohorts, and consider environmental factors to unravel the nuanced epigenetic landscape underlying Alzheimer's disease progression.
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Affiliation(s)
- Victoria Cunha Alves
- Neurodegenerative Diseases Group, Hospital Universitario 12 de Octubre Research Institute (imas12), Madrid, Spain
- Network Center for Biomedical Research, Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- PhD Program in Neuroscience, Autonoma de Madrid University, Madrid, Spain
- Neurotraumatology and Subarachnoid Hemorrhage Group, Hospital Universitario 12 de Octubre Research Institute (imas12), Madrid, Spain
| | - Eva Carro
- Network Center for Biomedical Research, Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Neurobiology of Alzheimer's Disease Unit, Functional Unit for Research Into Chronic Diseases, Instituto de Salud Carlos III, Madrid, Spain
| | - Joana Figueiro-Silva
- Institute of Medical Genetics, University of Zurich, Zurich, Switzerland
- Department of Molecular Life Science, University of Zurich, Zurich, Switzerland
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Muiño E, Carcel-Marquez J, Llucià-Carol L, Gallego-Fabrega C, Cullell N, Lledós M, Martín-Campos JM, Villatoro-González P, Sierra-Marcos A, Ros-Castelló V, Aguilera-Simón A, Marti-Fabregas J, Fernandez-Cadenas I. Identification of Genetic Loci Associated With Intracerebral Hemorrhage Using a Multitrait Analysis Approach. Neurology 2024; 103:e209666. [PMID: 39298701 DOI: 10.1212/wnl.0000000000209666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Genome-wide association studies (GWASs) have only 2 loci associated with spontaneous intracerebral hemorrhage (ICH): APOE for lobar and 1q22 for nonlobar ICH. We aimed to discover new loci through an analysis that combines correlated traits (multi-trait analysis of GWAS [MTAG]) and explore a gene-based analysis, transcriptome-wide association study (TWAS), and proteome-wide association study (PWAS) to understand the biological mechanisms of spontaneous ICH providing potential therapeutic targets. METHODS We use the published MTAG of ICH (patients with spontaneous intraparenchymal bleeding) and small-vessel ischemic stroke. For all ICH, lobar ICH, and nonlobar ICH, a pairwise MTAG combined ICH with traits related to cardiovascular risk factors, cerebrovascular diseases, or Alzheimer disease (AD). For the analysis, we assembled those traits with a genetic correlation ≥0.3. A new MTAG combining multiple traits was performed with those traits whose pairwise MTAG yielded new GWAS-significant single nucleotide polymorphisms (SNPs), with a posterior-probability of model 3 (GWAS-pairwise) ≥0.6. We perform TWAS and PWAS that correlate the genetic component of expression or protein levels with the genetic component of a trait. We use the ICH cohort from UK Biobank as replication. RESULTS For all ICH (1,543 ICH, 1,711 controls), the mean age was 72 ± 2 in cases and 70 ± 2 in controls, and half of them were women. Replication cohort: 700 ICH and 399,717 controls. Novel loci were found only for all ICH (the trait containing lobar and nonlobar ICH), combining data of ICH and small vessel stroke, white matter hyperintensities volume, fractional anisotropy, mean diffusivity, and AD. We replicated 6 SNPs belonging to 2q33.2 (ICA1L, β = 0.20, SE = 0.03, p value = 8.91 × 10-12), 10q24.33 (OBFC1, β = -0.12, SE = 0.02, p value = 1.67 × 10-8), 13q34 (COL4A2, β = 0.02, SE = 0.02, p value = 2.34 × 10-11), and 19q13.32 (APOC1, β = -0.19, SE = 0.03, p value = 1.38 × 10-12; APOE, β = 0.21, SE = 0.03, p value = 2.70 × 10-11; PVRL2:CTB-129P6.4, β = 0.15, SE = 0.03, p value = 1.38 × 10-8); 2 genes (SH3PXD2A, Z-score = 4.83, p value = 6.67 × 10-7; and APOC1, Z-score: = 5.11, p value = 1.60 × 10-7); and ICA1L transcript (Z-score = 6.8, p value = 9.1 × 10-12) and protein levels (Z-score = -5.8, p value = 6.7 × 10-9). DISCUSSION Our results reinforce the role of APOE in ICH risk, replicate previous ICH-associated loci (2q33 and 13q34), and point to new ICH associations with OBFC1, PVRL2:CTB-129P6.4, APOC1, and SH3PXD2A. Our study used data from European subjects, our main limitation. These molecules could be potential targets for future studies for modulating ICH risk.
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Affiliation(s)
- Elena Muiño
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Jara Carcel-Marquez
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Laia Llucià-Carol
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Cristina Gallego-Fabrega
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Natalia Cullell
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Miquel Lledós
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Jesús M Martín-Campos
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Paula Villatoro-González
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Alba Sierra-Marcos
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Victoria Ros-Castelló
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Ana Aguilera-Simón
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Joan Marti-Fabregas
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Israel Fernandez-Cadenas
- From the Stroke Pharmacogenomics and Genetics Group (E.M., J.C.-M., L.L.-C., C.G.-F., N.C., M.L.L., J.M.M.-C., P.V.-G., I.F.-C.), Biomedical Research Institute Sant Pau (IIB SANT PAU); Epilepsy Unit (E.M., A.S.-M., V.R.-C.), Neurology Service, Hospital de la Santa Creu i Sant Pau, Barcelona; Stroke Pharmacogenomics and Genetics (N.C.), Fundació MútuaTerrassa per la Docència i la Recerca; and Department of Neurology (C.G.-F., A.A.-S., J.M.-F.), Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
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Wang J, Fourriere L, Gleeson PA. Advances in the cell biology of the trafficking and processing of amyloid precursor protein: impact of familial Alzheimer's disease mutations. Biochem J 2024; 481:1297-1325. [PMID: 39302110 DOI: 10.1042/bcj20240056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 09/02/2024] [Accepted: 09/05/2024] [Indexed: 09/22/2024]
Abstract
The production of neurotoxic amyloid-β peptides (Aβ) is central to the initiation and progression of Alzheimer's disease (AD) and involves sequential cleavage of the amyloid precursor protein (APP) by β- and γ-secretases. APP and the secretases are transmembrane proteins and their co-localisation in the same membrane-bound sub-compartment is necessary for APP cleavage. The intracellular trafficking of APP and the β-secretase, BACE1, is critical in regulating APP processing and Aβ production and has been studied in several cellular systems. Here, we summarise the intracellular distribution and transport of APP and its secretases, and the intracellular location for APP cleavage in non-polarised cells and neuronal models. In addition, we review recent advances on the potential impact of familial AD mutations on APP trafficking and processing. This is critical information in understanding the molecular mechanisms of AD progression and in supporting the development of novel strategies for clinical treatment.
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Affiliation(s)
- Jingqi Wang
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Lou Fourriere
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Paul A Gleeson
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, Victoria 3010, Australia
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Pramanik S, Devi M H, Chakrabarty S, Paylar B, Pradhan A, Thaker M, Ayyadhury S, Manavalan A, Olsson PE, Pramanik G, Heese K. Microglia signaling in health and disease - Implications in sex-specific brain development and plasticity. Neurosci Biobehav Rev 2024; 165:105834. [PMID: 39084583 DOI: 10.1016/j.neubiorev.2024.105834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 07/21/2024] [Accepted: 07/27/2024] [Indexed: 08/02/2024]
Abstract
Microglia, the intrinsic neuroimmune cells residing in the central nervous system (CNS), exert a pivotal influence on brain development, homeostasis, and functionality, encompassing critical roles during both aging and pathological states. Recent advancements in comprehending brain plasticity and functions have spotlighted conspicuous variances between male and female brains, notably in neurogenesis, neuronal myelination, axon fasciculation, and synaptogenesis. Nevertheless, the precise impact of microglia on sex-specific brain cell plasticity, sculpting diverse neural network architectures and circuits, remains largely unexplored. This article seeks to unravel the present understanding of microglial involvement in brain development, plasticity, and function, with a specific emphasis on microglial signaling in brain sex polymorphism. Commencing with an overview of microglia in the CNS and their associated signaling cascades, we subsequently probe recent revelations regarding molecular signaling by microglia in sex-dependent brain developmental plasticity, functions, and diseases. Notably, C-X3-C motif chemokine receptor 1 (CX3CR1), triggering receptors expressed on myeloid cells 2 (TREM2), calcium (Ca2+), and apolipoprotein E (APOE) emerge as molecular candidates significantly contributing to sex-dependent brain development and plasticity. In conclusion, we address burgeoning inquiries surrounding microglia's pivotal role in the functional diversity of developing and aging brains, contemplating their potential implications for gender-tailored therapeutic strategies in neurodegenerative diseases.
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Affiliation(s)
- Subrata Pramanik
- Jyoti and Bhupat Mehta School of Health Sciences and Technology, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India.
| | - Harini Devi M
- Jyoti and Bhupat Mehta School of Health Sciences and Technology, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India
| | - Saswata Chakrabarty
- Jyoti and Bhupat Mehta School of Health Sciences and Technology, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India
| | - Berkay Paylar
- Biology, The Life Science Center, School of Science and Technology, Örebro University, Örebro 70182, Sweden
| | - Ajay Pradhan
- Biology, The Life Science Center, School of Science and Technology, Örebro University, Örebro 70182, Sweden
| | - Manisha Thaker
- Eurofins Lancaster Laboratories, Inc., 2425 New Holland Pike, Lancaster, PA 17601, USA
| | - Shamini Ayyadhury
- The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Arulmani Manavalan
- Department of Cariology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu 600077, India
| | - Per-Erik Olsson
- Biology, The Life Science Center, School of Science and Technology, Örebro University, Örebro 70182, Sweden
| | - Gopal Pramanik
- Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, Ranchi, Jharkhand 835215, India.
| | - Klaus Heese
- Graduate School of Biomedical Science and Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 133791, the Republic of Korea.
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6
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Ramprasad P, Ren J, Pan W. Enhancing Gene Expression Predictions Using Deep Learning and Functional Annotations. Genet Epidemiol 2024. [PMID: 39344923 DOI: 10.1002/gepi.22595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 07/17/2024] [Accepted: 09/03/2024] [Indexed: 10/01/2024]
Abstract
Transcriptome-wide association studies (TWAS) aim to uncover genotype-phenotype relationships through a two-stage procedure: predicting gene expression from genotypes using an expression quantitative trait locus (eQTL) data set, then testing the predicted expression for trait associations. Accurate gene expression prediction in stage 1 is crucial, as it directly impacts the power to identify associations in stage 2. Currently, the first stage of such studies is primarily conducted using linear models like elastic net regression, which fail to capture the nonlinear relationships inherent in biological systems. Deep learning methods have the potential to model such nonlinear effects, but have yet to demonstrably outperform linear methods at this task. To address this gap, we propose a new deep learning architecture to predict gene expression from genotypic variation across individuals. Our method utilizes a learnable input scaling layer in conjunction with a convolutional encoder to capture nonlinear effects and higher-order interactions without compromising on interpretability. We further augment this approach to allow for parameter sharing across multiple networks, enabling us to utilize prior information for individual variants in the form of functional annotations. Evaluations on real-world genomic data show that our method consistently outperforms elastic net regression across a large set of heritable genes. Furthermore, our model statistically significantly improved predictive performance by leveraging functional annotations, whereas elastic net regression failed to show equivalent gains when using the same information, suggesting that our method can capture nonlinear functional information beyond the capability of linear models.
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Grants
- This research was supported by NIH grants U01 AG073079, R01 AG065636, R01 AG069895, and RF1 AG067924, and by the Minnesota Supercomputing Institute at the University of Minnesota. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS; the GTEx data were obtained from dbGaP Project #26511.
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Affiliation(s)
- Pratik Ramprasad
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jingchen Ren
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, USA
| | - Wei Pan
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, USA
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7
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Khalili-Moghadam F, Hosseini Nejad J, Badri T, Sadeghi M, Gharechahi J. Association of MME gene polymorphisms with susceptibility to Alzheimer's disease in an Iranian population. Heliyon 2024; 10:e37556. [PMID: 39309779 PMCID: PMC11416268 DOI: 10.1016/j.heliyon.2024.e37556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 09/04/2024] [Accepted: 09/05/2024] [Indexed: 09/25/2024] Open
Abstract
Background the MME gene encodes a membrane metalloendopeptidase, known as neprilysin (NEP). There are no reports on the potential implications of MME gene polymorphisms on the risk of Alzheimer's disease (AD) in the Iranian population. In this study, we studied the potential association of two single nucleotide polymorphisms (SNPs), rs6797911 and rs3736187, in the MME gene and the risk of developing AD in an Iranian population. Methods This case-control study comprised 120 AD-diagnosed patients and 120 healthy individuals without any prior family history of AD. The patient and control groups were matched for major demographic and health characteristics. Genotyping was performed by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). Results All patients included in this study were assessed by an experienced neurologist to exclude cases with other forms of dementia based on a brain computed tomography scan and other clinical findings. There were no significant differences in demographic and health characteristics including sex, diabetes, blood pressure, and cigarette smoking status between case and control groups (p > 0.05). However, the age difference appeared significant. Both SNPs were significantly associated with the risk of AD in our study population. The rs3736187 (T > C, 3:155168489) was strongly associated with AD risk under the log-additive model (OR = 1.67, CI = 1.18-2.37, p-value = 0.003). The rs6797911 (T > A, 3:155144601) also showed a significant association with AD risk under the dominant model (TT vs. TA and AA, OR = 3.37, CI = 1.86-6.1, p-value <0.001). Conclusion There is a strong association between MME gene polymorphisms and susceptibility to AD in the Iranian population. Amyloid-β (Aβ) can serve as a substrate for the NEP metalloendopeptidase, the product of the MME gene. However, the mechanistic understanding of how these genetic variations affect NEP expression, function, and consequently susceptibility to AD, is poorly understood. Further research is required to fully understand the exact implication of MME gene variations on AD, particularly in a larger, ethnicity-diverse population.
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Affiliation(s)
| | - Javad Hosseini Nejad
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Taleb Badri
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Morteza Sadeghi
- Human Genetics Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Javad Gharechahi
- Human Genetics Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
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8
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Juul Rasmussen I, Luo J, Frikke-Schmidt R. Lipids, lipoproteins, and apolipoproteins: Associations with cognition and dementia. Atherosclerosis 2024; 398:118614. [PMID: 39340935 DOI: 10.1016/j.atherosclerosis.2024.118614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 09/06/2024] [Accepted: 09/19/2024] [Indexed: 09/30/2024]
Abstract
Due to increasing lifespan and aging populations globally there has been a steep rise in late-life dementia, which is now the second most common cause of death in high-income countries. In general, dementia can be divided into two major groups: Alzheimer's disease (AD) and vascular-related dementia (VD). AD is pathologically characterised by senile plaques containing amyloid-β and neurofibrillary tangles composed of hyperphosphorylated tau, whereas VD is dominated by vascular pathology such as cerebral small vessel disease, major strokes, and white matter lesions. Recently, the importance of vascular components in AD is increasingly recognized and it is estimated that up to 45 % of all dementia cases can be prevented by preventing or treating midlife cardiovascular risk factors such as physical inactivity, diabetes, and hypertension. Even though the brain contains approximately 25 % of the total body cholesterol pool, and several genetic variants related to the lipid metabolism have been identified in genome-wide associations studies of AD, the role of lipids, lipoproteins, and apolipoproteins in dementia risk is less well-known. In this review, we go through the current literature on lipids, lipoproteins, and apolipoproteins and risk of dementia. We conclude that the evidence is primarily insufficient or conflicting, possibly due to nonoptimal study designs. The future calls for large, prospective studies of midlife measurements of lipids, lipoproteins, and apolipoproteins and one-sample, individual level data Mendelian randomization studies to overcome survival bias. However, the current literature suggests that it is safe to say that what is good for the heart is good for the brain.
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Affiliation(s)
- Ida Juul Rasmussen
- Department of Clinical Biochemistry, Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark; The Copenhagen General Population Study, Herlev and Gentofte Hospital, Borgmester Ib Juuls Vej 1, DK-2730, Herlev, Denmark.
| | - Jiao Luo
- Department of Clinical Biochemistry, Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Rigshospitalet, Blegdamsvej 9, DK-2100, Copenhagen, Denmark; The Copenhagen General Population Study, Herlev and Gentofte Hospital, Borgmester Ib Juuls Vej 1, DK-2730, Herlev, Denmark; Department of Clinical Medicine, University of Copenhagen, Blegdamsvej 3, DK-2200, Copenhagen, Denmark
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9
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Nho K, Risacher SL, Apostolova LG, Bice PJ, Brosch JR, Deardorff R, Faber K, Farlow MR, Foroud T, Gao S, Rosewood T, Kim JP, Nudelman K, Yu M, Aisen P, Sperling R, Hooli B, Shcherbinin S, Svaldi D, Jack CR, Jagust WJ, Landau S, Vasanthakumar A, Waring JF, Doré V, Laws SM, Masters CL, Porter T, Rowe CC, Villemagne VL, Dumitrescu L, Hohman TJ, Libby JB, Mormino E, Buckley RF, Johnson K, Yang HS, Petersen RC, Ramanan VK, Ertekin-Taner N, Vemuri P, Cohen AD, Fan KH, Kamboh MI, Lopez OL, Bennett DA, Ali M, Benzinger T, Cruchaga C, Hobbs D, De Jager PL, Fujita M, Jadhav V, Lamb BT, Tsai AP, Castanho I, Mill J, Weiner MW, Saykin AJ. CYP1B1-RMDN2 Alzheimer's disease endophenotype locus identified for cerebral tau PET. Nat Commun 2024; 15:8251. [PMID: 39304655 PMCID: PMC11415491 DOI: 10.1038/s41467-024-52298-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 09/01/2024] [Indexed: 09/22/2024] Open
Abstract
Determining the genetic architecture of Alzheimer's disease pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we perform a genome-wide association study of cortical tau quantified by positron emission tomography in 3046 participants from 12 independent studies. The CYP1B1-RMDN2 locus is associated with tau deposition. The most significant signal is at rs2113389, explaining 4.3% of the variation in cortical tau, while APOE4 rs429358 accounts for 3.6%. rs2113389 is associated with higher tau and faster cognitive decline. Additive effects, but no interactions, are observed between rs2113389 and diagnosis, APOE4, and amyloid beta positivity. CYP1B1 expression is upregulated in AD. rs2113389 is associated with higher CYP1B1 expression and methylation levels. Mouse model studies provide additional functional evidence for a relationship between CYP1B1 and tau deposition but not amyloid beta. These results provide insight into the genetic basis of cerebral tau deposition and support novel pathways for therapeutic development in AD.
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Affiliation(s)
- Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of BioHealth Informatics, Indiana University, Indianapolis, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
| | - Liana G Apostolova
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
| | - Paula J Bice
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
| | - Jared R Brosch
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, USA
| | - Rachael Deardorff
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, USA
| | - Kelley Faber
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
- National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University School of Medicine, Indianapolis, USA
| | - Martin R Farlow
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, USA
| | - Tatiana Foroud
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
- National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University School of Medicine, Indianapolis, USA
| | - Sujuan Gao
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, USA
| | - Thea Rosewood
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
| | - Jun Pyo Kim
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
| | - Kelly Nudelman
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
- National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University School of Medicine, Indianapolis, USA
| | - Meichen Yu
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
| | - Paul Aisen
- Department of Neurology, Keck School of Medicine, University of Southern California, San Diego, USA
| | - Reisa Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | | | | | | | | | - William J Jagust
- UC Berkeley Helen Wills Neuroscience Institute, University of California - Berkeley, Berkeley, USA
| | - Susan Landau
- UC Berkeley Helen Wills Neuroscience Institute, University of California - Berkeley, Berkeley, USA
| | | | | | - Vincent Doré
- CSIRO Health and Biosecurity, Melbourne, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Australia
| | - Simon M Laws
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health and The University of Melbourne, Parkville, Australia
| | - Tenielle Porter
- Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Australia
- Florey Institute of Neuroscience and Mental Health and The University of Melbourne, Parkville, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Australia
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, USA
| | - Logan Dumitrescu
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, USA
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, USA
| | - Julia B Libby
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, USA
| | - Elizabeth Mormino
- Department of Neurology & Neurological Sciences, Stanford University, Stanford, USA
| | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Keith Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Hyun-Sik Yang
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Center for Alzheimer's Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | | | | | - Nilüfer Ertekin-Taner
- Department of Neurology, Mayo Clinic, Jacksonville, USA
- Department of Neuroscience, Mayo Clinic, Jacksonville, USA
| | | | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, USA
| | - Kang-Hsien Fan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, USA
| | - Oscar L Lopez
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, USA
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, USA
| | - David A Bennett
- Department of Neurological Sciences, Rush Medical College, Rush University, Chicago, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University, St. Louis, USA
| | - Tammie Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, USA
| | - Diana Hobbs
- Department of Radiology, Washington University School of Medicine, St. Louis, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, USA
| | - Masashi Fujita
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, USA
| | - Vaishnavi Jadhav
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, USA
| | - Bruce T Lamb
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, USA
| | - Andy P Tsai
- Department of Neurology & Neurological Sciences, Stanford University, Stanford, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, USA
| | - Isabel Castanho
- Department for Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
- Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA
| | - Jonathan Mill
- Department for Clinical and Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Michael W Weiner
- Departments of Radiology, Medicine, and Psychiatry, University of California-San Francisco, San Francisco, USA
- Department of Veterans Affairs Medical Center, San Francisco, USA
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, USA.
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, USA.
- Department of Neurology, Indiana University School of Medicine, Indianapolis, USA.
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA.
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10
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Henningfield CM, Kwang N, Tsourmas KI, Neumann J, Kawauchi S, Swarup V, MacGregor GR, Green KN. Generation of an inducible destabilized-domain Cre mouse line to target disease associated microglia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.18.613773. [PMID: 39345513 PMCID: PMC11429805 DOI: 10.1101/2024.09.18.613773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
The function of microglia during progression of Alzheimer's disease (AD) can be investigated using mouse models that enable genetic manipulation of microglial subpopulations in a temporal manner. We developed a mouse strain that expresses destabilized-domain Cre recombinase (DD-Cre) from the Cst7 locus ( Cst7 DD-Cre ) and tested this in 5xFAD amyloidogenic, Ai14 tdTomato cre-reporter line mice. Dietary administration of trimethoprim to induce DD-Cre activity produces long-term labeling in disease associated microglia (DAM) without evidence of leakiness, with tdTomato-expression restricted to cells surrounding plaques. Using this model, we found that DAMs are a subset of plaque-associated microglia (PAMs) and their transition to DAM increases with age and disease stage. Spatial transcriptomic analysis revealed that tdTomato+ cells show higher expression of disease and inflammatory genes compared to other microglial populations, including non-labeled PAMs. This model should allow inducible cre-loxP targeting of DAMs, without leakiness. Highlights We developed a new mouse strain which specifically enables recombination of loxP sites in disease associated microglia (DAMs) and can be used to manipulate DAM-gene expression.DAMs represent a subset of plaque associated microglia (PAMs), and DAM expression increases with disease progression.Spatial transcriptomic analyses reveal that DAMs have higher expression of disease and inflammatory genes compared to other PAMs.
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11
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Guvenek A, Parikshak N, Zamolodchikov D, Gelfman S, Moscati A, Dobbyn L, Stahl E, Shuldiner A, Coppola G. Transcriptional profiling in microglia across physiological and pathological states identifies a transcriptional module associated with neurodegeneration. Commun Biol 2024; 7:1168. [PMID: 39294270 PMCID: PMC11411103 DOI: 10.1038/s42003-024-06684-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 08/06/2024] [Indexed: 09/20/2024] Open
Abstract
Microglia are the resident immune cells of the central nervous system and are involved in brain development, homeostasis, and disease. New imaging and genomics technologies are revealing microglial complexity across developmental and functional states, brain regions, and diseases. We curated a set of publicly available gene expression datasets from human microglia spanning disease and health to identify sets of genes reflecting physiological and pathological microglial states. We also integrated multiple human microglial single-cell RNA-seq datasets in Alzheimer's disease (AD), multiple sclerosis (MS), and Parkinson's disease, and identified a distinct microglial transcriptional signature shared across diseases. Analysis of germ-line DNA identified genes with variants associated with AD and MS that are overrepresented in microglial gene sets, including the disease-associated transcriptional signature. This work points to genes that are dysregulated in disease states and provides a resource for the analysis of diseases in which microglia are implicated by genetic evidence.
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Affiliation(s)
- Aysegul Guvenek
- Regeneron Genetics Center, Tarrytown, NY, USA
- Regeneron Pharmaceuticals Inc., Tarrytown, NY, USA
| | | | | | | | | | - Lee Dobbyn
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Eli Stahl
- Regeneron Genetics Center, Tarrytown, NY, USA
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12
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Ohi K, Fujikane D, Shioiri T. Genetic overlap between schizophrenia spectrum disorders and Alzheimer's disease: Current evidence and future directions - An integrative review. Neurosci Biobehav Rev 2024; 167:105900. [PMID: 39298993 DOI: 10.1016/j.neubiorev.2024.105900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Revised: 09/15/2024] [Accepted: 09/16/2024] [Indexed: 09/22/2024]
Abstract
Schizophrenia and Alzheimer's disease (AD) are distinct neurodegenerative disorders characterized by progressive cognitive deficits and structural alterations in the brain. Schizophrenia typically emerges in adolescence or early adulthood with symptoms such as hallucinations, delusions, and cognitive impairments, whereas AD primarily affects elderly individuals, causing progressive memory loss, cognitive decline, and behavioral changes. Delusional disorder, which often emerges later in life, shares some features with schizophrenia and is considered a schizophrenia spectrum disorder. Patients with schizophrenia or delusional disorder, particularly women and those aged 65 years or older, have an increased risk of developing AD later in life. In contrast, approximately 30 % of AD patients exhibit psychotic symptoms, which accelerate cognitive decline and worsen health outcomes. This integrative review explored the genetic overlap between schizophrenia spectrum disorders and AD to identify potential shared genetic factors. The genetic correlations between schizophrenia and AD were weak but positive (rg=0.03-0.10). Polygenic risk scores (PRSs) for schizophrenia and AD indicate some genetic predisposition, although findings are inconsistent among studies; e.g., PRS-schizophrenia or PRS-AD were associated with the risk of developing psychosis in patients with AD. A higher PRS for various developmental and psychiatric disorders was correlated with an earlier age at onset of schizophrenia. Research gaps include the need for studies on the impacts of PRS-AD on the risk of schizophrenia, genetic correlations between later-onset delusional disorder and AD, and genetic relationships between AD and late-onset schizophrenia (LOS) with a greater risk of progressing to AD. Further investigation into these genetic overlaps is crucial to enhance prevention, treatment, and prognosis for affected patients.
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Affiliation(s)
- Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan; Department of General Internal Medicine, Kanazawa Medical University, Ishikawa, Japan.
| | - Daisuke Fujikane
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Toshiki Shioiri
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
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13
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Vilkaite G, Vogel J, Mattsson-Carlgren N. Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease. Cell Rep Med 2024; 5:101735. [PMID: 39293391 DOI: 10.1016/j.xcrm.2024.101735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 07/28/2024] [Accepted: 08/20/2024] [Indexed: 09/20/2024]
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by the aggregation of β-amyloid (Aβ) and tau in the brain. Breakthroughs in disease-modifying treatments targeting Aβ bring new hope for the management of AD. But to effectively modify and someday even prevent AD, a better understanding is needed of the biological mechanisms that underlie and link Aβ and tau in AD. Developments of high-throughput omics, including genomics, proteomics, and transcriptomics, together with molecular imaging of Aβ and tau with positron emission tomography (PET), allow us to discover and understand the biological pathways that regulate the aggregation and spread of Aβ and tau in living humans. The field of integrated omics and PET studies of Aβ and tau in AD is growing rapidly. We here provide an update of this field, both in terms of biological insights and in terms of future clinical implications of integrated omics-molecular imaging studies.
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Affiliation(s)
- Gabriele Vilkaite
- Department of Clinical Sciences Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Jacob Vogel
- Department of Clinical Sciences Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden; Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
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14
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He B, Wu R, Sangani N, Pugalenthi PV, Patania A, Risacher SL, Nho K, Apostolova LG, Shen L, Saykin AJ, Yan J. Integrating amyloid imaging and genetics for early risk stratification of Alzheimer's disease. Alzheimers Dement 2024. [PMID: 39285750 DOI: 10.1002/alz.14244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 07/24/2024] [Accepted: 08/15/2024] [Indexed: 09/21/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) initiates years prior to symptoms, underscoring the importance of early detection. While amyloid accumulation starts early, individuals with substantial amyloid burden may remain cognitively normal, implying that amyloid alone is not sufficient for early risk assessment. METHODS Given the genetic susceptibility of AD, a multi-factorial pseudotime approach was proposed to integrate amyloid imaging and genotype data for estimating a risk score. Validation involved association with cognitive decline and survival analysis across risk-stratified groups, focusing on patients with mild cognitive impairment (MCI). RESULTS Our risk score outperformed amyloid composite standardized uptake value ratio in correlation with cognitive scores. MCI subjects with lower pseudotime risk score showed substantial delayed onset of AD and slower cognitive decline. Moreover, pseudotime risk score demonstrated strong capability in risk stratification within traditionally defined subgroups such as early MCI, apolipoprotein E (APOE) ε4+ MCI, APOE ε4- MCI, and amyloid+ MCI. DISCUSSION Our risk score holds great potential to improve the precision of early risk assessment. HIGHLIGHTS Accurate early risk assessment is critical for the success of clinical trials. A new risk score was built from integrating amyloid imaging and genetic data. Our risk score demonstrated improved capability in early risk stratification.
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Affiliation(s)
- Bing He
- Department of Biomedical Engineering and Informatics, Indiana University Luddy School of Informatics, Computing and Engineering, Indianapolis, Indiana, USA
| | - Ruiming Wu
- Department of Biomedical Engineering and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Neel Sangani
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Pradeep Varathan Pugalenthi
- Department of Biomedical Engineering and Informatics, Indiana University Luddy School of Informatics, Computing and Engineering, Indianapolis, Indiana, USA
| | - Alice Patania
- Department of Mathematics Statistics, University of Vermont, Burlington, Vermont, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Liana G Apostolova
- Department of Biomedical Engineering and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Li Shen
- Department of Biomedical Engineering and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jingwen Yan
- Department of Biomedical Engineering and Informatics, Indiana University Luddy School of Informatics, Computing and Engineering, Indianapolis, Indiana, USA
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15
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Joseph PV, Abbas M, Goodney G, Diallo A, Gaye A. Genomic study of taste perception genes in African Americans reveals SNPs linked to Alzheimer's disease. Sci Rep 2024; 14:21560. [PMID: 39284855 PMCID: PMC11405524 DOI: 10.1038/s41598-024-71669-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 08/29/2024] [Indexed: 09/22/2024] Open
Abstract
While previous research has shown the potential links between taste perception pathways and brain-related conditions, the area involving Alzheimer's disease remains incompletely understood. Taste perception involves neurotransmitter signaling, including serotonin, glutamate, and dopamine. Disruptions in these pathways are implicated in neurodegenerative diseases. The integration of olfactory and taste signals in flavor perception may impact brain health, evident in olfactory dysfunction as an early symptom in neurodegenerative conditions. Shared immune response and inflammatory pathways may contribute to the association between altered taste perception and conditions like neurodegeneration, present in Alzheimer's disease. This study consists of an exploration of expression-quantitative trait loci (eQTL), utilizing whole-blood transcriptome profiles, of 28 taste perception genes, from a combined cohort of 475 African American subjects. This comprehensive dataset was subsequently intersected with single-nucleotide polymorphisms (SNPs) identified in Genome-Wide Association Studies (GWAS) of Alzheimer's Disease (AD). Finally, the investigation delved into assessing the association between eQTLs reported in GWAS of AD and the profiles of 741 proteins from the Olink Neurological Panel. The eQTL analysis unveiled 3,547 statistically significant SNP-Gene associations, involving 412 distinct SNPs that spanned all 28 taste genes. In 17 GWAS studies encompassing various traits, a total of 14 SNPs associated with 12 genes were identified, with three SNPs consistently linked to Alzheimer's disease across four GWAS studies. All three SNPs demonstrated significant associations with the down-regulation of TAS2R41, and two of them were additionally associated with the down-regulation of TAS2R60. In the subsequent pQTL analysis, two of the SNPs linked to TAS2R41 and TAS2R60 genes (rs117771145 and rs10228407) were correlated with the upregulation of two proteins, namely EPHB6 and ADGRB3. Our investigation introduces a new perspective to the understanding of Alzheimer's disease, emphasizing the significance of bitter taste receptor genes in its pathogenesis. These discoveries set the stage for subsequent research to delve into these receptors as promising avenues for both intervention and diagnosis. Nevertheless, the translation of these genetic insights into clinical practice requires a more profound understanding of the implicated pathways and their pertinence to the disease's progression across diverse populations.
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Affiliation(s)
- Paule Valery Joseph
- Sensory Science and Metabolism Unit, Biobehavioral Branch, National Institute On Alcohol Abuse and Alcoholism, National Institue of Nursing Research, National Institutes of Health, Bethesda, MD, USA
| | - Malak Abbas
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Gabriel Goodney
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ana Diallo
- Department of Pharmacotherapy & Outcomes Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Amadou Gaye
- Department of Integrative Genomics and Epidemiology, School of Graduate Studies, Meharry Medical College, Nashville, TN, USA.
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16
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Bandres-Ciga S, Faghri F, Majounie E, Koretsky MJ, Kim J, Levine KS, Leonard H, Makarious MB, Iwaki H, Crea PW, Hernandez DG, Arepalli S, Billingsley K, Lohmann K, Klein C, Lubbe SJ, Jabbari E, Saffie-Awad P, Narendra D, Reyes-Palomares A, Quinn JP, Schulte C, Morris HR, Traynor BJ, Scholz SW, Houlden H, Hardy J, Dumanis S, Riley E, Blauwendraat C, Singleton A, Nalls M, Jeff J, Vitale D. NeuroBooster Array: A Genome-Wide Genotyping Platform to Study Neurological Disorders Across Diverse Populations. Mov Disord 2024. [PMID: 39283294 DOI: 10.1002/mds.29902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/28/2024] [Accepted: 06/06/2024] [Indexed: 09/25/2024] Open
Abstract
BACKGROUND Commercial genome-wide genotyping arrays have historically neglected coverage of genetic variation across populations. OBJECTIVE We aimed to create a multi-ancestry genome-wide array that would include a wide range of neuro-specific genetic content to facilitate genetic research in neurological disorders across multiple ancestral groups, fostering diversity and inclusivity in research studies. METHODS We developed the Illumina NeuroBooster Array (NBA), a custom high-throughput and cost-effective platform on a backbone of 1,914,934 variants from the Infinium Global Diversity Array and added custom content comprising 95,273 variants associated with more than 70 neurological conditions or traits, and we further tested its performance on more than 2000 patient samples. This novel platform includes approximately 10,000 tagging variants to facilitate imputation and analyses of neurodegenerative disease-related genome-wide association study loci across diverse populations. RESULTS In this article, we describe NBA's potential as an efficient means for researchers to assess known and novel disease genetic associations in a multi-ancestry framework. The NBA can identify rare genetic variants and accurately impute more than 15 million common variants across populations. Apart from enabling sample prioritization for further whole-genome sequencing studies, we envisage that NBA will play a pivotal role in recruitment for interventional studies in the precision medicine space. CONCLUSIONS From a broader perspective, the NBA serves as a promising means to foster collaborative research endeavors in the field of neurological disorders worldwide. Ultimately, this carefully designed tool is poised to make a substantial contribution to uncovering the genetic etiology underlying these debilitating conditions. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
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Affiliation(s)
- Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Faraz Faghri
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica, Washington, District of Columbia, USA
| | | | - Mathew J Koretsky
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Jeffrey Kim
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Kristin S Levine
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica, Washington, District of Columbia, USA
| | - Hampton Leonard
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica, Washington, District of Columbia, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Hirotaka Iwaki
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica, Washington, District of Columbia, USA
| | - Peter Wild Crea
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Sampath Arepalli
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Kimberley Billingsley
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Katja Lohmann
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Steven J Lubbe
- Ken and Ruth Davee Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
- Simpson Querrey Center for Neurogenetics, Northwestern University, Feinberg School of Medicine, Chicago, Illinois, USA
| | - Edwin Jabbari
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Paula Saffie-Awad
- Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Centro de Trastornos del Movimiento, Santiago, Chile
- Clínica Santa María, Santiago, Chile
| | - Derek Narendra
- Inherited Movement Disorders Unit, Neurogenetics Branch, Division of Intramural Research, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Armando Reyes-Palomares
- Department of Molecular Biology and Biochemistry, Faculty of Sciences, University of Málaga, Málaga, Spain
| | - John P Quinn
- Department of Pharmacology & Therapeutics, University of Liverpool, Liverpool, United Kingdom
| | - Claudia Schulte
- Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tuebingen and German Center for Neurodegenerative Diseases, University of Tuebingen, Tuebingen, Germany
| | - Huw R Morris
- Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, United Kingdom
- Aligning Science Across Parkinson's Collaborative Research Network, Chevy Chase, Maryland, USA
| | - Bryan J Traynor
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, Maryland, USA
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland, USA
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Henry Houlden
- Aligning Science Across Parkinson's Collaborative Research Network, Chevy Chase, Maryland, USA
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - John Hardy
- Aligning Science Across Parkinson's Collaborative Research Network, Chevy Chase, Maryland, USA
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Sonya Dumanis
- Aligning Science Across Parkinson's Collaborative Research Network, Chevy Chase, Maryland, USA
| | - Ekemini Riley
- Aligning Science Across Parkinson's Collaborative Research Network, Chevy Chase, Maryland, USA
| | - Cornelis Blauwendraat
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Mike Nalls
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica, Washington, District of Columbia, USA
| | | | - Dan Vitale
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica, Washington, District of Columbia, USA
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Willett JDS, Waqas M, Choi Y, Ngai T, Mullin K, Tanzi RE, Prokopenko D. Identification of 16 novel Alzheimer's disease susceptibility loci using multi-ancestry meta-analyses of clinical Alzheimer's disease and AD-by-proxy cases from four whole genome sequencing datasets. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.11.24313439. [PMID: 39314934 PMCID: PMC11419201 DOI: 10.1101/2024.09.11.24313439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Alzheimer's disease (AD) is the most prevalent form of dementia. While many AD-associated genetic determinants have been previously identified, few studies have analyzed individuals of non-European ancestry. Here, we describe a multi-ancestry genome-wide association study of clinically-diagnosed AD and AD-by-proxy using whole genome sequencing data from NIAGADS, NIMH, UKB, and All of Us (AoU) consisting of 49,149 cases (12,074 clinically-diagnosed and 37,075 AD-by-proxy) and 383,225 controls. Nearly half of NIAGADS and AoU participants are of non-European ancestry. For clinically-diagnosed AD, we identified 14 new loci - five common (FBN2,/SCL27A6, AC090115.1, DYM, KCNG1/AL121785.1, TIAM1) and nine rare (VWA5B1, RNU6-755P/LMX1A, MOB1A, MORC1-AS1, LINC00989, PDE4D, RNU2-49P/CDO1, NEO1, and SLC35G3/AC022916.1). Meta-analysis of UKB and AoU AD-by-proxy cases yielded two new rare loci (RPL23/LASP1 and CEBPA/ AC008738.6) which were also nominally significant in NIAGADS. In summary, we provide evidence for 16 novel AD loci and advocate for more studies using WGS-based GWAS of diverse cohorts.
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Affiliation(s)
- Julian Daniel Sunday Willett
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Mohammad Waqas
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Younjung Choi
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Tiffany Ngai
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
- University of Waterloo, Department of Systems Design Engineering, Waterloo, Ontario, Canada
| | - Kristina Mullin
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Rudolph E. Tanzi
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
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Lin YL, Yao T, Wang YW, Lu JH, Chen YM, Wu YQ, Qian XG, Liu JC, Fang LX, Zheng C, Wu CH, Lin JF. Causal association between mitochondrial function and psychiatric disorders: Insights from a bidirectional two-sample Mendelian randomization study. J Affect Disord 2024; 368:55-66. [PMID: 39265869 DOI: 10.1016/j.jad.2024.09.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 09/04/2024] [Accepted: 09/08/2024] [Indexed: 09/14/2024]
Abstract
BACKGROUND Previous observational studies have suggested that there appears to be a close association between mitochondrial function and psychiatric disorders, but whether a causal role exists remains unclear. METHODS We extracted genetic instruments for 67 mitochondrial-related proteins and 10 psychiatric disorders from publicly available genome-wide association studies, and employed five distinct MR methods and false discovery rate correction to detect causal associations between them. Additionally, we conducted a series of sensitivity tests and additional model analysis to ensure the robustness of the results. For potential causal associations, we further performed reverse MR analyses to assess the impact of reverse causality. RESULTS We identified a total of 2 significant causal associations and 24 suggestive causal associations. Specifically, Phenylalanine-tRNA ligase was found to increase the risk of Alzheimer's disease, while Mitochondrial glutamate carrier 2 decreased the risk of autism spectrum disorder. Furthermore, there was no evidence of significant pleiotropy, heterogeneity, or reverse causality. LIMITATIONS This study was limited to individuals of European ancestry, and the conclusions drawn are merely revelatory. CONCLUSION This study provides novel insights into the relationship between mitochondria and psychiatric disorders, as well as the pathogenesis and treatment strategies for psychiatric disorders.
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Affiliation(s)
- Yun-Lu Lin
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Tao Yao
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Ying-Wei Wang
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Jia-Hao Lu
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Yan-Min Chen
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Yu-Qing Wu
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Xin-Ge Qian
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Jing-Chen Liu
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Luo-Xiang Fang
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Cheng Zheng
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China
| | - Chun-Hui Wu
- Children's Heart Center, The Second Affiliated Hospital and Yuying Children's Hospital, Institute of Cardiovascular Development and Translational Medicine, Wenzhou Medical University, Wenzhou 325027, Zhejiang, China; Department of Ultrasonography, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.
| | - Jia-Feng Lin
- The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.
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19
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Belloy ME, Le Guen Y, Stewart I, Williams K, Herz J, Sherva R, Zhang R, Merritt V, Panizzon MS, Hauger RL, Gaziano JM, Logue M, Napolioni V, Greicius MD. Role of the X Chromosome in Alzheimer Disease Genetics. JAMA Neurol 2024:2823160. [PMID: 39250132 PMCID: PMC11385320 DOI: 10.1001/jamaneurol.2024.2843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2024]
Abstract
Importance The X chromosome has remained enigmatic in Alzheimer disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. Objectives To perform the first large-scale X chromosome-wide association study (XWAS) of AD. Design, Setting, and Participants This was a meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium, the Alzheimer's Disease Sequencing Project, the UK Biobank, the Finnish health registry, and the US Million Veterans Program. Risk of AD was evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Genetic data available from high-density single-nucleotide variant microarrays and whole-genome sequencing and summary statistics for multitissue expression and protein quantitative trait loci available from published studies were included, enabling follow-up genetic colocalization analyses. A total of 1 629 863 eligible participants were selected from referred and volunteer samples, 477 596 of whom were excluded for analysis exclusion criteria. The number of participants who declined to participate in original studies was not available. Main Outcome and Measures Risk of AD, reported as odds ratios (ORs) with 95% CIs. Associations were considered at X chromosome-wide (P < 1 × 10-5) and genome-wide (P < 5 × 10-8) significance. Primary analyses are nonstratified, while secondary analyses evaluate sex-stratified effects. Results Analyses included 1 152 284 participants of non-Hispanic White, European ancestry (664 403 [57.7%] female and 487 881 [42.3%] male), including 138 558 individuals with AD. Six independent genetic loci passed X chromosome-wide significance, with 4 showing support for links between the genetic signal for AD and expression of nearby genes in brain and nonbrain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR, 1.03; 95% CI, 1.02-1.04) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Of these 6 loci, 4 displayed evidence for escape from X chromosome inactivation with regard to AD risk. Conclusion and Relevance This large-scale XWAS of AD identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid β accumulation. Overall, this study advances our knowledge of AD genetics and may provide novel biological drug targets. The results further provide initial insights into elucidating the role of the X chromosome in sex-based differences in AD.
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Affiliation(s)
- Michael E Belloy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, Missouri
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Ilaria Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Kennedy Williams
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Joachim Herz
- Center for Translational Neurodegeneration Research, Department of Molecular Genetics University of Texas Southwestern Medical Center at Dallas, Dallas
| | - Richard Sherva
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, Massachusetts
| | - Victoria Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California San Diego, La Jolla
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla
| | - Richard L Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California San Diego, La Jolla
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla
| | - J Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts
- Division of Aging, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Mark Logue
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
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20
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Li M, Hao X, Hu Z, Tian J, Shi J, Ma D, Guo M, Li S, Zuo C, Liang Y, Tang M, Mao C, Xu Y, Shi C. Microvascular and cellular dysfunctions in Alzheimer's disease: an integrative analysis perspective. Sci Rep 2024; 14:20944. [PMID: 39251797 PMCID: PMC11385648 DOI: 10.1038/s41598-024-71888-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 09/02/2024] [Indexed: 09/11/2024] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia, characterized by memory loss, cognitive decline, personality changes, and various neurological symptoms. The role of blood-brain barrier (BBB) injury, extracellular matrix (ECM) abnormalities, and oligodendrocytes (ODCs) dysfunction in AD has gained increasing attention, yet the detailed pathogenesis remains elusive. This study integrates single-cell sequencing of AD patients' cerebrovascular system with a genome-wide association analysis. It aims to elucidate the associations and potential mechanisms behind pericytes injury, ECM disorder, and ODCs dysfunction in AD pathogenesis. Finally, we identified that abnormalities in the pericyte PI3K-AKT-FOXO signaling pathway may be involved in the pathogenic process of AD. This comprehensive approach sheds new light on the complex etiology of AD and opens avenues for advanced research into its pathogenesis and therapeutic strategies.
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Affiliation(s)
- Mengjie Li
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Xiaoyan Hao
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Zhengwei Hu
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Jie Tian
- Zhengzhou Railway Vocational and Technical College, Zhengzhou, 450000, Henan, China
| | - Jingjing Shi
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Dongrui Ma
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Mengnan Guo
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Shuangjie Li
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Chunyan Zuo
- Zhengzhou University, Zhengzhou, 450000, Henan, China
| | | | - Mibo Tang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou, 450000, Henan, China
| | - Chengyuan Mao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou, 450000, Henan, China
| | - Yuming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou, 450000, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, 450000, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Changhe Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou, 450000, Henan, China.
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, Henan, China.
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, 450000, Henan, China.
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, Henan, China.
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21
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Shi Z, Das S, Morabito S, Miyoshi E, Stocksdale J, Emerson N, Srinivasan SS, Shahin A, Rahimzadeh N, Cao Z, Silva J, Castaneda AA, Head E, Thompson L, Swarup V. Single-nucleus multi-omics identifies shared and distinct pathways in Pick's and Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.06.611761. [PMID: 39282421 PMCID: PMC11398495 DOI: 10.1101/2024.09.06.611761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/19/2024]
Abstract
The study of neurodegenerative diseases, particularly tauopathies like Pick's disease (PiD) and Alzheimer's disease (AD), offers insights into the underlying regulatory mechanisms. By investigating epigenomic variations in these conditions, we identified critical regulatory changes driving disease progression, revealing potential therapeutic targets. Our comparative analyses uncovered disease-enriched non-coding regions and genome-wide transcription factor (TF) binding differences, linking them to target genes. Notably, we identified a distal human-gained enhancer (HGE) associated with E3 ubiquitin ligase (UBE3A), highlighting disease-specific regulatory alterations. Additionally, fine-mapping of AD risk genes uncovered loci enriched in microglial enhancers and accessible in other cell types. Shared and distinct TF binding patterns were observed in neurons and glial cells across PiD and AD. We validated our findings using CRISPR to excise a predicted enhancer region in UBE3A and developed an interactive database (http://swaruplab.bio.uci.edu/scROAD) to visualize predicted single-cell TF occupancy and regulatory networks.
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Affiliation(s)
- Zechuan Shi
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
| | - Sudeshna Das
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
| | - Samuel Morabito
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology Program, University of California, Irvine, CA 92697, USA
| | - Emily Miyoshi
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
| | - Jennifer Stocksdale
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Department of Biological Chemistry, University of California, Irvine, CA 92697, USA
| | - Nora Emerson
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
| | - Shushrruth Sai Srinivasan
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology Program, University of California, Irvine, CA 92697, USA
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Arshi Shahin
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
| | - Negin Rahimzadeh
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology Program, University of California, Irvine, CA 92697, USA
| | - Zhenkun Cao
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
| | - Justine Silva
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
| | - Andres Alonso Castaneda
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
| | - Elizabeth Head
- Department of Pathology and Laboratory Medicine, University of California, Irvine, CA 92697, USA
| | - Leslie Thompson
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA 92697, USA
- Department of Biological Chemistry, University of California, Irvine, CA 92697, USA
| | - Vivek Swarup
- Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology Program, University of California, Irvine, CA 92697, USA
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22
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Yang L, Sadler MC, Altman RB. Genetic association studies using disease liabilities from deep neural networks. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.01.18.23284383. [PMID: 36712099 PMCID: PMC9882423 DOI: 10.1101/2023.01.18.23284383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, liability and meta , for conducting genome-wide association study (GWAS) that leverage disease liabilities calculated from deep patient phenotyping. Analyzing 38 common traits in ∼300,000 UK Biobank participants, we identified an increased number of loci compared to the conventional case-control approach, with high replication rates in larger external GWAS. Further analyses confirmed the disease-specificity of the genetic architecture with the meta method demonstrating higher robustness when phenotypes were imputed with low accuracy. Additionally, polygenic risk scores based on disease liabilities more effectively predicted newly diagnosed cases in the 2022 dataset, which were controls in the earlier 2019 dataset. Our findings demonstrate that integrating high-dimensional phenotypic data into deep neural networks enhances genetic association studies while capturing disease-relevant genetic architecture.
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Affiliation(s)
- Lu Yang
- Deparment of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
| | - Marie C. Sadler
- Deparment of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- University Center for Primary Care and Public Health, Lausanne, 1010, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland
| | - Russ B. Altman
- Deparment of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
- Department of Medicine, Stanford University, Stanford, CA, 94305, USA
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
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23
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Bedwell L, Mavrotas M, Demchenko N, Yaa RM, Willis B, Demianova Z, Syed N, Whitwell HJ, Nott A. FANS Unfixed: Isolation and Proteomic Analysis of Mouse Cell Type-Specific Brain Nuclei. J Proteome Res 2024; 23:3847-3857. [PMID: 39056441 PMCID: PMC11385383 DOI: 10.1021/acs.jproteome.4c00161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2024]
Abstract
Epigenetic-mediated gene regulation orchestrates brain cell-type gene expression programs, and epigenetic dysregulation is a major driver of aging and disease-associated changes. Proteins that mediate gene regulation are mostly localized to the nucleus; however, nuclear-localized proteins are often underrepresented in gene expression studies and have been understudied in the context of the brain. To address this challenge, we have optimized an approach for nuclei isolation that is compatible with proteomic analysis. This was coupled to a mass spectrometry protocol for detecting proteins in low-concentration samples. We have generated nuclear proteomes for neurons, microglia, and oligodendrocytes from the mouse brain cortex and identified cell-type nuclear proteins associated with chromatin structure and organization, chromatin modifiers such as transcription factors, and RNA-binding proteins, among others. Our nuclear proteomics platform paves the way for assessing brain cell type changes in the nuclear proteome across health and disease, such as neurodevelopmental, aging, neurodegenerative, and neuroinflammatory conditions. Data are available via ProteomeXchange with the identifier PXD053515.
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Affiliation(s)
- Lucy Bedwell
- Department of Brain Sciences, Imperial College London, London W12 0NN, U.K
- UK Dementia Research Institute, Imperial College London, London W12 0NN, U.K
| | - Myrto Mavrotas
- Department of Brain Sciences, Imperial College London, London W12 0NN, U.K
| | - Nikita Demchenko
- MRC Laboratory of Medical Sciences, Du Cane Road, London W12 0NN, U.K
| | - Reuben M Yaa
- Department of Brain Sciences, Imperial College London, London W12 0NN, U.K
- UK Dementia Research Institute, Imperial College London, London W12 0NN, U.K
| | - Brittannie Willis
- Department of Brain Sciences, Imperial College London, London W12 0NN, U.K
- Department of Metabolism, Digestion, and Reproduction, Imperial College London, London W12 0NN, U.K
| | | | - Nelofer Syed
- Department of Brain Sciences, Imperial College London, London W12 0NN, U.K
| | - Harry J Whitwell
- Department of Metabolism, Digestion, and Reproduction, Imperial College London, London W12 0NN, U.K
| | - Alexi Nott
- Department of Brain Sciences, Imperial College London, London W12 0NN, U.K
- UK Dementia Research Institute, Imperial College London, London W12 0NN, U.K
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24
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Puerta R, de Rojas I, García-González P, Olivé C, Sotolongo-Grau O, García-Sánchez A, García-Gutiérrez F, Montrreal L, Pablo Tartari J, Sanabria Á, Pytel V, Lage C, Quintela I, Aguilera N, Rodriguez-Rodriguez E, Alarcón-Martín E, Orellana A, Pastor P, Pérez-Tur J, Piñol-Ripoll G, de Munian AL, García-Alberca JM, Royo JL, Bullido MJ, Álvarez V, Real LM, Anchuelo AC, Gómez-Garre D, Larrad MTM, Franco-Macías E, Mir P, Medina M, Sánchez-Valle R, Dols-Icardo O, Sáez ME, Carracedo Á, Tárraga L, Alegret M, Valero S, Marquié M, Boada M, Juan PS, Cavazos JE, Cabrera A, Cano A. Connecting genomic and proteomic signatures of amyloid burden in the brain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.06.24313124. [PMID: 39281766 PMCID: PMC11398581 DOI: 10.1101/2024.09.06.24313124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
Background Alzheimer's disease (AD) has a high heritable component characteristic of complex diseases, yet many of the genetic risk factors remain unknown. We combined genome-wide association studies (GWAS) on amyloid endophenotypes measured in cerebrospinal fluid (CSF) and positron emission tomography (PET) as surrogates of amyloid pathology, which may be helpful to understand the underlying biology of the disease. Methods We performed a meta-analysis of GWAS of CSF Aβ42 and PET measures combining six independent cohorts (n=2,076). Due to the opposite effect direction of Aβ phenotypes in CSF and PET measures, only genetic signals in the opposite direction were considered for analysis (n=376,599). Polygenic risk scores (PRS) were calculated and evaluated for AD status and amyloid endophenotypes. We then searched the CSF proteome signature of brain amyloidosis using SOMAscan proteomic data (Ace cohort, n=1,008) and connected it with GWAS results of loci modulating amyloidosis. Finally, we compared our results with a large meta-analysis using publicly available datasets in CSF (n=13,409) and PET (n=13,116). This combined approach enabled the identification of overlapping genes and proteins associated with amyloid burden and the assessment of their biological significance using enrichment analyses. Results After filtering the meta-GWAS, we observed genome-wide significance in the rs429358-APOE locus and nine suggestive hits were annotated. We replicated the APOE loci using the large CSF-PET meta-GWAS and identified multiple AD-associated genes as well as the novel GADL1 locus. Additionally, we found a significant association between the AD PRS and amyloid levels, whereas no significant association was found between any Aβ PRS with AD risk. CSF SOMAscan analysis identified 1,387 FDR-significant proteins associated with CSF Aβ42 levels. The overlap among GWAS loci and proteins associated with amyloid burden was very poor (n=35). The enrichment analysis of overlapping hits strongly suggested several signalling pathways connecting amyloidosis with the anchored component of the plasma membrane, synapse physiology and mental disorders that were replicated in the large CSF-PET meta-analysis. Conclusions The strategy of combining CSF and PET amyloid endophenotypes GWAS with CSF proteome analyses might be effective for identifying signals associated with the AD pathological process and elucidate causative molecular mechanisms behind the amyloid mobilization in AD.
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Affiliation(s)
- Raquel Puerta
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- Universitat de Barcelona (UB)
| | - Itziar de Rojas
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pablo García-González
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Clàudia Olivé
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
| | | | | | | | - Laura Montrreal
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
| | - Juan Pablo Tartari
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
| | - Ángela Sanabria
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Vanesa Pytel
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Carmen Lage
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Inés Quintela
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII). Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Nuria Aguilera
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
| | - Eloy Rodriguez-Rodriguez
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | | | - Adelina Orellana
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pau Pastor
- Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
- The Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona, Spain
| | - Jordi Pérez-Tur
- Unitat de Genètica Molecular, Institut de Biomedicina de València-CSIC, Valencia, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Unidad Mixta de Neurologia Genètica, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
| | - Gerard Piñol-Ripoll
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida, Spain
- Institut de Recerca Biomedica de Lleida (IRBLLeida), Lleida, Spain
| | - Adolfo López de Munian
- Department of Neurology. Hospital Universitario Donostia. San Sebastian, Spain
- Department of Neurosciences. Faculty of Medicine and Nursery. University of the Basque Country, San Sebastián, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Neurosciences Area. Instituto Biodonostia. San Sebastian, Spain
| | - Jose María García-Alberca
- Alzheimer Research Center & Memory Clinic, Andalusian Institute for Neuroscience, Málaga, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Jose Luís Royo
- Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología. School of Medicine. University of Malaga. Málaga, Spain
| | - María Jesús Bullido
- Centro de Biología Molecular Severo Ochoa (UAM-CSIC)
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Instituto de Investigacion Sanitaria 'Hospital la Paz' (IdIPaz), Madrid, Spain
- Universidad Autónoma de Madrid
| | - Victoria Álvarez
- Laboratorio de Genética. Hospital Universitario Central de Asturias, Oviedo, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias (ISPA)
| | - Luis Miguel Real
- Unidad Clínica de Enfermedades Infecciosas y Microbiología.Hospital Universitario de Valme, Sevilla, Spain
- Departamento de Especialidades Quirúrgicas, Bioquímica e Inmunología. School of Medicine. University of Malaga. Málaga, Spain
| | - Arturo Corbatón Anchuelo
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Hospital Clínico San Carlos
| | - Dulcenombre Gómez-Garre
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Hospital Clínico San Carlos
- Laboratorio de Riesgo Cardiovascular y Microbiota, Hospital Clínico San Carlos; Departamento de Fisiología, Facultad de Medicina, Universidad Complutense de Madrid (UCM)
- Biomedical Research Networking Center in Cardiovascular Diseases (CIBERCV), Madrid, Spain
| | - María Teresa Martínez Larrad
- Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Hospital Clínico San Carlos
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM)
| | - Emilio Franco-Macías
- Dementia Unit, Department of Neurology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBiS), Sevilla, Spain
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología. Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Miguel Medina
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's disease and other cognitive disorders unit. Service of Neurology. Hospital Clínic of Barcelona. Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona, Spain
| | - Oriol Dols-Icardo
- Department of Neurology, Sant Pau Memory Unit, Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Ángel Carracedo
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII). Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Fundación Pública Galega de Medicina Xenómica - CIBERER-IDIS, Santiago de Compostela, Spain
| | - Lluís Tárraga
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Montse Alegret
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Sergi Valero
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mercè Boada
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pascual Sánchez Juan
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Jose Enrique Cavazos
- South Texas Medical Science Training Program, University of Texas Health San Antonio, San Antonio
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 USA
| | - Alfredo Cabrera
- Neuroscience Therapeutic Area, Janssen Research & Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Amanda Cano
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
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25
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Aygün N, Vuong C, Krupa O, Mory J, Le BD, Valone JM, Liang D, Shafie B, Zhang P, Salinda A, Wen C, Gandal MJ, Love MI, de la Torre-Ubieta L, Stein JL. Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis. Am J Hum Genet 2024; 111:1877-1898. [PMID: 39168119 PMCID: PMC11393701 DOI: 10.1016/j.ajhg.2024.07.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 07/18/2024] [Accepted: 07/23/2024] [Indexed: 08/23/2024] Open
Abstract
The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk postmortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA editing and alternative polyadenylation (APA) within a cell-type-specific population of human neural progenitors and neurons. More RNA editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting that genetically mediated post-transcriptional regulation during brain development leads to differences in brain function.
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Affiliation(s)
- Nil Aygün
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Celine Vuong
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Oleh Krupa
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica Mory
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Brandon D Le
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jordan M Valone
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Dan Liang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Beck Shafie
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Pan Zhang
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Angelo Salinda
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Cindy Wen
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Michael J Gandal
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Luis de la Torre-Ubieta
- Intellectual and Developmental Disabilities Research Center, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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26
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Hu T, Parrish RL, Dai Q, Buchman AS, Tasaki S, Bennett DA, Seyfried NT, Epstein MP, Yang J. Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia. Am J Hum Genet 2024; 111:1848-1863. [PMID: 39079537 PMCID: PMC11393696 DOI: 10.1016/j.ajhg.2024.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 06/28/2024] [Accepted: 07/02/2024] [Indexed: 09/08/2024] Open
Abstract
Transcriptome-wide association study (TWAS) tools have been applied to conduct proteome-wide association studies (PWASs) by integrating proteomics data with genome-wide association study (GWAS) summary data. The genetic effects of PWAS-identified significant genes are potentially mediated through genetically regulated protein abundance, thus informing the underlying disease mechanisms better than GWAS loci. However, existing TWAS/PWAS tools are limited by considering only one statistical model. We propose an omnibus PWAS pipeline to account for multiple statistical models and demonstrate improved performance by simulation and application studies of Alzheimer disease (AD) dementia. We employ the Aggregated Cauchy Association Test to derive omnibus PWAS (PWAS-O) p values from PWAS p values obtained by three existing tools assuming complementary statistical models-TIGAR, PrediXcan, and FUSION. Our simulation studies demonstrated improved power, with well-calibrated type I error, for PWAS-O over all three individual tools. We applied PWAS-O to studying AD dementia with reference proteomic data profiled from dorsolateral prefrontal cortex of postmortem brains from individuals of European ancestry. We identified 43 risk genes, including 5 not identified by previous studies, which are interconnected through a protein-protein interaction network that includes the well-known AD risk genes TOMM40, APOC1, and APOC2. We also validated causal genetic effects mediated through the proteome for 27 (63%) PWAS-O risk genes, providing insights into the underlying biological mechanisms of AD dementia and highlighting promising targets for therapeutic development. PWAS-O can be easily applied to studying other complex diseases.
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Affiliation(s)
- Tingyang Hu
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA; Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA 17033, USA
| | - Randy L Parrish
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA; Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA 30322, USA
| | - Qile Dai
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA; Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA 30322, USA
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Nicholas T Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Michael P Epstein
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.
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27
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Hu T, Dai Q, Epstein MP, Yang J. Proteome-wide association studies using summary pQTL data of three tissues identified 30 risk genes of Alzheimer's disease dementia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.28.24305044. [PMID: 38585769 PMCID: PMC10996749 DOI: 10.1101/2024.03.28.24305044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Background Proteome-wide association study (PWAS) integrating proteomic data with genome-wide association study (GWAS) summary data is a powerful tool for studying Alzheimer's disease (AD) dementia. Existing PWAS analyses of AD often rely on the availability of individual-level proteomic and genetic data of a reference panel. Leveraging summary protein quantitative trait loci (pQTL) reference data of multiple AD-relevant tissues is expected to improve PWAS findings of AD dementia. Methods We conducted PWAS of AD dementia by integrating publicly available summary pQTL data of brain, cerebrospinal fluid (CSF), and plasma tissues, with the latest GWAS summary data of AD dementia. For each target protein per tissue, we employed our recently published OTTERS tool to obtain omnibus PWAS p-value, to test whether the genetically regulated protein abundance in the corresponding tissue is associated with AD dementia. Protein-protein interactions and enriched pathways of identified significant PWAS risk genes were analyzed by STRING. The potential causal effects of these PWAS risk genes were assessed by probabilistic Mendelian randomization analyses. Results We identified 30 unique significant PWAS risk genes for AD dementia, including 11 for brain, 9 for CSF, and 16 for plasma tissues. Four of these were shared by at least two tissues, and gene MAPK3 was found in all three tissues. We found that 11 of these PWAS risk genes were associated with AD or AD pathological hall marks as shown in GWAS Catalog; 18 of these were detected by transcriptome-wide association studies (TWAS); and 25 of these, including 8 out of 9 novel genes, were interconnected within a protein-protein interaction network involving the well-known AD risk gene APOE . Especially, these PWAS risk genes were enriched in immune response, glial cell proliferation, and high-density lipoprotein particle clearance pathways. Mediated causal effects were validated for 13 PWAS risk genes (43.3%). Conclusions Our findings provide novel insights into the genetic mechanisms of AD dementia in brain, CSF, and plasma tissues, and targets for developing therapeutic interventions. We also demonstrated the effectiveness of integrating summary pQTL and GWAS data for mapping risk genes of complex human diseases.
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Affiliation(s)
- Tingyang Hu
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Qile Dai
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA, 30322, USA
| | - Michael P. Epstein
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
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Fröhlich AS, Gerstner N, Gagliardi M, Ködel M, Yusupov N, Matosin N, Czamara D, Sauer S, Roeh S, Murek V, Chatzinakos C, Daskalakis NP, Knauer-Arloth J, Ziller MJ, Binder EB. Single-nucleus transcriptomic profiling of human orbitofrontal cortex reveals convergent effects of aging and psychiatric disease. Nat Neurosci 2024:10.1038/s41593-024-01742-z. [PMID: 39227716 DOI: 10.1038/s41593-024-01742-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 07/30/2024] [Indexed: 09/05/2024]
Abstract
Aging is a complex biological process and represents the largest risk factor for neurodegenerative disorders. The risk for neurodegenerative disorders is also increased in individuals with psychiatric disorders. Here, we characterized age-related transcriptomic changes in the brain by profiling ~800,000 nuclei from the orbitofrontal cortex from 87 individuals with and without psychiatric diagnoses and replicated findings in an independent cohort with 32 individuals. Aging affects all cell types, with LAMP5+LHX6+ interneurons, a cell-type abundant in primates, by far the most affected. Disrupted synaptic transmission emerged as a convergently affected pathway in aged tissue. Age-related transcriptomic changes overlapped with changes observed in Alzheimer's disease across multiple cell types. We find evidence for accelerated transcriptomic aging in individuals with psychiatric disorders and demonstrate a converging signature of aging and psychopathology across multiple cell types. Our findings shed light on cell-type-specific effects and biological pathways underlying age-related changes and their convergence with effects driven by psychiatric diagnosis.
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Affiliation(s)
- Anna S Fröhlich
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany.
- International Max Planck Research School for Translational Psychiatry, Munich, Germany.
| | - Nathalie Gerstner
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Munich, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Miriam Gagliardi
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Maik Ködel
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Natan Yusupov
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Munich, Germany
| | - Natalie Matosin
- School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia
- Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Darina Czamara
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Susann Sauer
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Simone Roeh
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Vanessa Murek
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Chris Chatzinakos
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Nikolaos P Daskalakis
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Janine Knauer-Arloth
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Michael J Ziller
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Elisabeth B Binder
- Department of Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany.
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
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Wu Z, Chen J, Liu Y, Yang Y, Feng M, Dai H. The Effects of PICALM rs3851179 and Age on Brain Atrophy and Cognition Along the Alzheimer's Disease Continuum. Mol Neurobiol 2024; 61:6984-6996. [PMID: 38363532 DOI: 10.1007/s12035-024-03953-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 01/12/2024] [Indexed: 02/17/2024]
Abstract
Rs3851179, a variant of PICALM gene, and age are the risk factors of Alzheimer's disease (AD). AD is divided into early-onset AD (EOAD, < 65 years) and late-onset AD (LOAD, ≥ 65 years) by age. The purpose was to investigate the impact of different genotypes of PICALM rs3851179 on brain atrophy and cognitive decline across the AD continuum in different age groups. Four hundred seven cognitive normal (CN) controls, 362 mild cognitive impairment (MCI) patients, and 94 AD patients were enrolled to assess the interaction between AD continuum, age status, and PICALM on gray matter volume (GMV), global cognition, memory function, and executive function using full factorial ANCOVA (3 × 2 × 2). The interaction between AD continuum and PICALM significantly affected the GMV of the left putamen (PUT.L). rs3851179 A-allele carriers did not show a significant decrease in PUT.L GMV from CN to MCI to AD, while GG-allele carriers did. The interaction between AD continuum and age status was significant on GMV of the left angular gyrus (ANG.L) and right superior occipital gyrus (SOG.R). LOAD had higher GMV of ANG.L and SOG.R than EOAD. The interactive effects among AD continuum, age status, and PICALM were not significant on GMV but were significant on global cognition and executive function. The A-allele was found to have a protective effect on global cognition and executive function in EOAD, but not significantly so in LOAD. PICALM rs3851179 A-allele might alleviate the atrophy of PUT.L across the AD continuum than GG-allele. Age status did not affect the interaction between AD continuum and PICALM on brain atrophy. The ANG.L and SOG.R atrophied more severely in EOAD than in LOAD. Rs3851179 A-allele was protective for global cognition and executive function in EOAD.
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Affiliation(s)
- Zhiwei Wu
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China
| | - Jinhong Chen
- Department of Ultrasound, Hefei Hospital affiliated to Anhui Medical University: The Second People's Hospital of Hefei, Hefei, Anhui Province, 230011, People's Republic of China
- The Fifth Clinical Medical College of Anhui Medical University, Hefei, Anhui Province, 230032, People's Republic of China
| | - Yuanqing Liu
- Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, People's Republic of China
| | - Yiwen Yang
- Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, People's Republic of China
| | - Mengmeng Feng
- Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, People's Republic of China
| | - Hui Dai
- Department of Radiology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 215006, People's Republic of China.
- Institute of Medical Imaging, Soochow University, Suzhou, Jiangsu Province, 215006, People's Republic of China.
- Suzhou Key Laboratory of Intelligent Medicine and Equipment, Suzhou, Jiangsu Province, 215123, People's Republic of China.
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Iqbal MS, Belal Bin Heyat M, Parveen S, Ammar Bin Hayat M, Roshanzamir M, Alizadehsani R, Akhtar F, Sayeed E, Hussain S, Hussein HS, Sawan M. Progress and trends in neurological disorders research based on deep learning. Comput Med Imaging Graph 2024; 116:102400. [PMID: 38851079 DOI: 10.1016/j.compmedimag.2024.102400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 05/07/2024] [Accepted: 05/13/2024] [Indexed: 06/10/2024]
Abstract
In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging, offering unprecedented opportunities for the diagnosis and treatment of neurological disorders (NDs). This comprehensive review explores the multifaceted role of DL techniques in leveraging vast datasets to advance our understanding of NDs and improve clinical outcomes. Beginning with a systematic literature review, we delve into the utilization of DL, particularly focusing on multimodal neuroimaging data analysis-a domain that has witnessed rapid progress and garnered significant scientific interest. Our study categorizes and critically analyses numerous DL models, including Convolutional Neural Networks (CNNs), LSTM-CNN, GAN, and VGG, to understand their performance across different types of Neurology Diseases. Through particular analysis, we identify key benchmarks and datasets utilized in training and testing DL models, shedding light on the challenges and opportunities in clinical neuroimaging research. Moreover, we discuss the effectiveness of DL in real-world clinical scenarios, emphasizing its potential to revolutionize ND diagnosis and therapy. By synthesizing existing literature and describing future directions, this review not only provides insights into the current state of DL applications in ND analysis but also covers the way for the development of more efficient and accessible DL techniques. Finally, our findings underscore the transformative impact of DL in reshaping the landscape of clinical neuroimaging, offering hope for enhanced patient care and groundbreaking discoveries in the field of neurology. This review paper is beneficial for neuropathologists and new researchers in this field.
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Affiliation(s)
- Muhammad Shahid Iqbal
- Department of Computer Science and Information Technology, Women University of Azad Jammu & Kashmir, Bagh, Pakistan.
| | - Md Belal Bin Heyat
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.
| | - Saba Parveen
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, China.
| | | | - Mohamad Roshanzamir
- Department of Computer Engineering, Faculty of Engineering, Fasa University, Fasa, Iran.
| | - Roohallah Alizadehsani
- Institute for Intelligent Systems Research and Innovation, Deakin University, VIC 3216, Australia.
| | - Faijan Akhtar
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
| | - Eram Sayeed
- Kisan Inter College, Dhaurahara, Kushinagar, India.
| | - Sadiq Hussain
- Department of Examination, Dibrugarh University, Assam 786004, India.
| | - Hany S Hussein
- Electrical Engineering Department, Faculty of Engineering, King Khalid University, Abha 61411, Saudi Arabia; Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81528, Egypt.
| | - Mohamad Sawan
- CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.
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31
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Wang M, Tang Z. No causal relationship between serum urate and neurodegenerative diseases: A Mendelian randomization study. Exp Gerontol 2024; 194:112503. [PMID: 38955238 DOI: 10.1016/j.exger.2024.112503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 06/11/2024] [Accepted: 06/24/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVE Observational studies have shown that increased serum urate is associated with a lower risk of neurodegenerative diseases (NDs), but the causality remains unclear. We employed a two-sample Mendelian randomization (MR) approach to assess the causal relationship between serum urate and four common subtypes of NDs, including Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS). METHODS Serum urate data came from the CKDGen Consortium. GWAS data for PD, AD, ALS, and MS were obtained from four databases in the primary analysis and then acquired statistics from the FinnGen consortium for replication and meta-analysis. Inverse variance weighted (IVW), weighted median (WM), and MR-Egger regression methods were applied in the MR analyses. Pleiotropic effects, heterogeneity, and leave-one-out analyses were evaluated to validate the results. RESULTS There was no evidence for the effect of serum urate on PD (OR: 1.00, 95 % CI: 0.90-1.11, P = 0.97), AD (OR: 1.02, 95 % CI: 1.00-1.04, P = 0.06), ALS (OR: 1.05, 95 % CI: 0.97-1.13, P = 0.22), and MS (OR: 1.01, 95 % CI: 0.89-1.14, P = 0.90) risk when combined with the FinnGen consortium, neither was any evidence of pleiotropy detected between the instrumental variables (IVs). CONCLUSION The MR analysis suggested that serum urate may not be causally associated with a risk of PD, AD, ALS, and MS.
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Affiliation(s)
- Min Wang
- Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210023, China
| | - Zhiquan Tang
- People's Hospital of Yushan District, Ma'anshan, Anhui 243000, China.
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32
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Liu XT, Chen X, Zhao N, Geng F, Zhu MM, Ren QG. Synergism of ApoE4 and systemic infectious burden is mediated by the APOE-NLRP3 axis in Alzheimer's disease. Psychiatry Clin Neurosci 2024; 78:517-526. [PMID: 39011734 DOI: 10.1111/pcn.13704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 04/12/2024] [Accepted: 06/03/2024] [Indexed: 07/17/2024]
Abstract
BACKGROUND Systemic infections are associated with the development of AD, especially in individuals carrying the APOE4 genotype. However, the detailed mechanism through which APOE4 affects microglia inflammatory response remains unclear. METHODS We obtained human snRNA-seq data from the Synapse AD Knowledge Portal and assessed the DEGs between APOE3 and APOE4 isoforms in microglia. To verify the interaction between ApoE and infectious products, we used ApoE to stimulate in vitro and in vivo models in the presence or absence of LPS (or ATP). The NLRP3 gene knockout experiment was performed to demonstrate whether the APOE-NLRP3 axis was indispensable for microglia to regulate inflammation and mitochondrial autophagy. Results were evaluated by biochemical analyses and fluorescence imaging. RESULTS Compared with APOE3, up-regulated genes in APOE4 gene carriers were involved in pro-inflammatory responses. ApoE4-stimulation significantly increased the levels of NLRP3 inflammasomes and ROS in microglia. Moreover, compared with ApoE4 alone, the co-incubation of ApoE4 with LPS (or ATP) markedly promoted pyroptosis. Both NF-κB activation and mitochondrial autophagy dysfunction were contributed by the increased level of NLRP3 inflammasomes induced by ApoE4. Furthermore, the pathological impairment induced by ApoE4 could be reversed by NLRP3 KO. CONCLUSIONS Our study highlights the importance of NLRP3 inflammasomes in linking ApoE4 with microglia innate immune function. These findings not only provide a molecular basis for APOE4-mediated neuroinflammatory but also reveal the potential reason for the increased risk of AD in APOE4 gene carriers after contracting infectious diseases.
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Affiliation(s)
- Xue-Ting Liu
- School of Medicine, Southeast University, Nanjing, China
| | - Xiu Chen
- School of Medicine, Southeast University, Nanjing, China
| | - Na Zhao
- School of Medicine, Southeast University, Nanjing, China
| | - Fan Geng
- School of Medicine, Southeast University, Nanjing, China
| | - Meng-Meng Zhu
- School of Medicine, Southeast University, Nanjing, China
| | - Qing-Guo Ren
- Department of Neurology, Affiliated ZhongDa Hospital, Southeast University, Nanjing, China
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Borcuk C, Parihar M, Sportelli L, Kleinman JE, Shin JH, Hyde TM, Bertolino A, Weinberger DR, Pergola G. Network-wide risk convergence in gene co-expression identifies reproducible genetic hubs of schizophrenia risk. Neuron 2024:S0896-6273(24)00575-0. [PMID: 39236717 DOI: 10.1016/j.neuron.2024.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 04/03/2024] [Accepted: 08/07/2024] [Indexed: 09/07/2024]
Abstract
The omnigenic model posits that genetic risk for traits with complex heritability involves cumulative effects of peripheral genes on mechanistic "core genes," suggesting that in a network of genes, those closer to clusters including core genes should have higher GWAS signals. In gene co-expression networks, we confirmed that GWAS signals accumulate in genes more connected to risk-enriched gene clusters, highlighting across-network risk convergence. This was strongest in adult psychiatric disorders, especially schizophrenia (SCZ), spanning 70% of network genes, suggestive of super-polygenic architecture. In snRNA-seq cell type networks, SCZ risk convergence was strongest in L2/L3 excitatory neurons. We prioritized genes most connected to SCZ-GWAS genes, which showed robust association to a CRISPRa measure of PGC3 regulation and were consistently identified across several brain regions. Several genes, including dopamine-associated ones, were prioritized specifically in the striatum. This strategy thus retrieves current drug targets and can be used to prioritize other potential drug targets.
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Affiliation(s)
- Christopher Borcuk
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA; Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Madhur Parihar
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Leonardo Sportelli
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA; Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Giulio Pergola
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA; Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Wang Y, Mi N, Liao K, Li Y, Sun Y, Xie P, Hu L, Wu S, Liang Z, He Q, Li Z, Ma M, Yang K, Yuan J, Xia B, Li X. Associations among dietary 1-carbon metabolism nutrients, genetic risk, and Alzheimer disease: a prospective cohort study. Am J Clin Nutr 2024:S0002-9165(24)00724-X. [PMID: 39216592 DOI: 10.1016/j.ajcnut.2024.08.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/17/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The associations between 1-carbon metabolism (OCM) nutrients (methionine, folate, vitamin B-6, and vitamin B-12) and Alzheimer disease (AD) remains inconclusive. OBJECTIVES This study aimed to investigate the association of dietary OCM nutrients with subsequent risk of AD and further assess whether participants with high genetic risk for AD might benefit from dietary OCM nutrients. METHODS We analyzed data from 192,214 participants who completed at least one 24-h dietary questionnaire and had no previous history of AD based on the UK Biobank. Nutrients intake was calculated using McCance and Widdowson's The Composition of Food and USDA's Food and Nutrient Database for Dietary Studies. Cox proportional models with restricted cubic splines were applied to explore the associations. RESULTS Over a median follow-up of 13.35 y, 959 cases of AD (41 early-onset cases and 918 late-onset cases) were identified. Compared with those in the low-intake OCM group (quartile 1), participants in the high-intake OCM group (quartile 4) had reduced risk of developing AD. The corresponding hazard ratios (HRs) and 95% confidence intervals (CIs) for methionine, folate, vitamin B-6, and vitamin B-12 intake were 0.66 (0.54, 0.80), 0.71 (0.58, 0.87), 0.71 (0.59, 0.87), and 0.77 (0.64, 0.93), respectively. Similar associations were observed in late-onset AD. In early-onset AD, high methionine and vitamin B-12 intake were associated with 70% (HR: 0.30; 95% CI: 0.10, 0.86) and 71% (HR: 0.29; 95% CI: 0.09, 0.96) reduction in risk, respectively. Participants with low genetic risk and high OCM nutrients intake had >75% reduced AD risk compared with high-risk, low-intake participants. CONCLUSIONS In this prospective cohort study, we found that higher intake of OCM nutrients is associated with reduced risk of AD. Participants with high genetic risk of AD are more likely to benefit from dietary OCM nutrients intake.
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Affiliation(s)
- Yongsheng Wang
- Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China; The Cross-innovation Laboratory of Evidence-based Social Sciences, Lanzhou University, Lanzhou, Gansu, China
| | - Ningning Mi
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China
| | - Kun Liao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Yan Li
- School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yuxuan Sun
- Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China
| | - Peng Xie
- Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Linmin Hu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Siqing Wu
- School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Zixin Liang
- Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China
| | - Qiangsheng He
- Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China
| | - Zijun Li
- Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China; The Cross-innovation Laboratory of Evidence-based Social Sciences, Lanzhou University, Lanzhou, Gansu, China
| | - Mina Ma
- The Cross-innovation Laboratory of Evidence-based Social Sciences, Lanzhou University, Lanzhou, Gansu, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China
| | - Kehu Yang
- Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China; The Cross-innovation Laboratory of Evidence-based Social Sciences, Lanzhou University, Lanzhou, Gansu, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu, China
| | - Jinqiu Yuan
- Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China.
| | - Bin Xia
- Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China.
| | - Xiuxia Li
- Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou, Gansu, China; The Cross-innovation Laboratory of Evidence-based Social Sciences, Lanzhou University, Lanzhou, Gansu, China.
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Burton EA, Argenziano M, Cook K, Ridler M, Lu S, Su C, Manduchi E, Littleton SH, Leonard ME, Hodge KM, Wang LS, Schellenberg GD, Johnson ME, Pahl MC, Pippin JA, Wells AD, Anderson SA, Brown CD, Grant SFA, Chesi A. Variant-to-function mapping of late-onset Alzheimer's disease GWAS signals in human microglial cell models implicates RTFDC1 at the CASS4 locus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.22.609230. [PMID: 39229212 PMCID: PMC11370593 DOI: 10.1101/2024.08.22.609230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Late-onset Alzheimer's disease (LOAD) research has principally focused on neurons over the years due to their known role in the production of amyloid beta plaques and neurofibrillary tangles. In contrast, recent genomic studies of LOAD have implicated microglia as culprits of the prolonged inflammation exacerbating the neurodegeneration observed in patient brains. Indeed, recent LOAD genome-wide association studies (GWAS) have reported multiple loci near genes related to microglial function, including TREM2, ABI3, and CR1. However, GWAS alone cannot pinpoint underlying causal variants or effector genes at such loci, as most signals reside in non-coding regions of the genome and could presumably confer their influence frequently via long-range regulatory interactions. We elected to carry out a combination of ATAC-seq and high-resolution promoter-focused Capture-C in two human microglial cell models (iPSC-derived microglia and HMC3) in order to physically map interactions between LOAD GWAS-implicated candidate causal variants and their corresponding putative effector genes. Notably, we observed consistent evidence that rs6024870 at the GWAS CASS4 locus contacted the promoter of nearby gene, RTFDC1. We subsequently observed a directionallly consistent decrease in RTFDC1 expression with the the protective minor A allele of rs6024870 via both luciferase assays in HMC3 cells and expression studies in primary human microglia. Through CRISPR-Cas9-mediated deletion of the putative regulatory region harboring rs6024870 in HMC3 cells, we observed increased pro-inflammatory cytokine secretion and decreased DNA double strand break repair related, at least in part, to RTFDC1 expression levels. Our variant-to-function approach therefore reveals that the rs6024870-harboring regulatory element at the LOAD 'CASS4' GWAS locus influences both microglial inflammatory capacity and DNA damage resolution, along with cumulative evidence implicating RTFDC1 as a novel candidate effector gene.
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Affiliation(s)
- Elizabeth A Burton
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- CAMB Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mariana Argenziano
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kieona Cook
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Molly Ridler
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sumei Lu
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Chun Su
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elisabetta Manduchi
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sheridan H Littleton
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- CAMB Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michelle E Leonard
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Li-San Wang
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gerard D Schellenberg
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew E Johnson
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stewart A Anderson
- Department of Child and Adolescent Psychiatry and Behavioral Services, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher D Brown
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Cao D, Zhang S, Zhang Y, Shao M, Yang Q, Wang P. Association between gynecologic cancer and Alzheimer's disease: a bidirectional mendelian randomization study. BMC Cancer 2024; 24:1032. [PMID: 39169299 PMCID: PMC11337634 DOI: 10.1186/s12885-024-12787-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 08/08/2024] [Indexed: 08/23/2024] Open
Abstract
BACKGROUND Alzheimer's disease (AD) manifests with a higher rate of occurrence in women. Previous epidemiological studies have suggested a potential association between AD and gynecological cancers, but the causal relationship between them remains unclear. This study aims to explore the causal link between 12 types of gynecological cancers and AD using a bidirectional Mendelian randomization (MR) approach. METHODS We obtained genetic correlation tools for AD using data from the most extensive genome-wide association study. Genetic correlation data for 12 types of gynecological cancers were also sourced from the Finnish Biobank. These cancers include breast cancer (BC), cervical adenocarcinoma (CA), cervical squamous cell carcinoma (CSCC), cervical cancer (CC), endometrial cancer (EC), ovarian endometrioid carcinoma (OEC), ovarian cancer (OC), ovarian serous carcinoma (OSC), breast carcinoma in situ (BCIS), cervical carcinoma in situ (CCIS), endometrial carcinoma in situ (ECIS), and vulvar carcinoma in situ (VCIS). We used the inverse-variance weighted (IVW) model for causal analysis and conducted horizontal pleiotropy tests, heterogeneity tests, MR-PRESSO tests, and leave-one-out analyses to ensure the robustness of our results. We also applied replication analysis and meta-analysis to further validate our experimental results. RESULTS The study found that EC (P_IVW =0.037, OR [95% CI] = 1.032 [1.002, 1.064]) and CCIS (P_IVW = 0.046, OR [95% CI] = 1.032 [1.011, 1.064]) increase the risk of AD, whereas OC was negatively correlated with AD (P_IVW = 0.016, OR [95% CI] = 0.974[0.954, 0.995]). In reverse MR analysis, AD increased the risk of CC (P_IVW = 0.039, OR [95% CI] = 1.395 [1.017, 1.914]) and VCIS (P_IVW = 0.041, OR [95% CI] = 1.761 [1.027, 2.021]), but was negatively correlated with OEC (P_IVW = 0.034, OR [95% CI] = 0.634 [0.417, 0.966]). Sensitivity analysis results demonstrated robustness. These findings were further substantiated through replication and meta-analyses. CONCLUSIONS Our MR study supports a causal relationship between AD and gynecological cancers. This encourages further research into the incidence of gynecological cancers in female Alzheimer's patients and the active prevention of AD.
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Affiliation(s)
- Di Cao
- Hubei University of Chinese Medicine, Wuhan, Hubei, 430065, China
- Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Wuhan, Hubei, 430065, China
| | - Shaobo Zhang
- Changchun University of Chinese Medicine, Changchun, Jilin, 130000, China
| | - Yini Zhang
- Hubei University of Chinese Medicine, Wuhan, Hubei, 430065, China
- Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Wuhan, Hubei, 430065, China
| | - Ming Shao
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, 210000, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 210000, China
| | - Qiguang Yang
- The Second Affiliated Hospital of Changchun University of Chinese Medicine, Changchun Hospital of Chinese Medicine, Changchun, Jilin, 130000, China
| | - Ping Wang
- Hubei University of Chinese Medicine, Wuhan, Hubei, 430065, China.
- Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Wuhan, Hubei, 430065, China.
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Hirakawa H, Terao T. The genetic association between bipolar disorder and dementia: a qualitative review. Front Psychiatry 2024; 15:1414776. [PMID: 39228919 PMCID: PMC11368786 DOI: 10.3389/fpsyt.2024.1414776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 08/05/2024] [Indexed: 09/05/2024] Open
Abstract
Bipolar disorder is a chronic disorder characterized by fluctuations in mood state and energy and recurrent episodes of mania/hypomania and depression. Bipolar disorder may be regarded as a neuro-progressive disorder in which repeated mood episodes may lead to cognitive decline and dementia development. In the current review, we employed genome-wide association studies to comprehensively investigate the genetic variants associated with bipolar disorder and dementia. Thirty-nine published manuscripts were identified: 20 on bipolar disorder and 19 on dementia. The results showed that the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A were overlapping between patients with bipolar disorder and dementia. In conclusion, the genes CACNA1C, GABBR2, SCN2A, CTSH, MSRA, and SH3PXD2A may be associated with the neuro-progression of bipolar disorder to dementia. Further genetic studies are needed to comprehensively clarify the role of genes in cognitive decline and the development of dementia in patients with bipolar disorder.
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Affiliation(s)
- Hirofumi Hirakawa
- Department of Neuropsychiatry, Oita University Faculty of Medicine, Yufu, Oita, Japan
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Chen G, Jin Y, Chu C, Zheng Y, Chen Y, Zhu X. Genetic prediction of blood metabolites mediating the relationship between gut microbiota and Alzheimer's disease: a Mendelian randomization study. Front Microbiol 2024; 15:1414977. [PMID: 39224217 PMCID: PMC11366617 DOI: 10.3389/fmicb.2024.1414977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 07/22/2024] [Indexed: 09/04/2024] Open
Abstract
Background Observational studies have suggested an association between gut microbiota and Alzheimer's disease (AD); however, the causal relationship remains unclear, and the role of blood metabolites in this association remains elusive. Purpose To elucidate the causal relationship between gut microbiota and AD and to investigate whether blood metabolites serve as potential mediators. Materials and methods Univariable Mendelian randomization (UVMR) analysis was employed to assess the causal relationship between gut microbiota and AD, while multivariable MR (MVMR) was utilized to mitigate confounding factors. Subsequently, a two-step mediation MR approach was employed to explore the role of blood metabolites as potential mediators. We primarily utilized the inverse variance-weighted method to evaluate the causal relationship between exposure and outcome, and sensitivity analyses including Contamination mixture, Maximum-likelihood, Debiased inverse-variance weighted, MR-Egger, Bayesian Weighted Mendelian randomization, and MR pleiotropy residual sum and outlier were conducted to address pleiotropy. Results After adjustment for reverse causality and MVMR correction, class Actinobacteria (OR: 1.03, 95% CI: 1.01-1.06, p = 0.006), family Lactobacillaceae (OR: 1.03, 95% CI: 1.00-1.05, p = 0.017), genus Lachnoclostridium (OR: 1.03, 95% CI: 1.00-1.06, p = 0.019), genus Ruminiclostridium9 (OR: 0.97, 95% CI: 0.94-1.00, p = 0.027) and genus Ruminiclostridium6 (OR: 1.03, 95% CI: 1.01-1.05, p = 0.009) exhibited causal effects on AD. Moreover, 1-ribosyl-imidazoleacetate levels (-6.62%), Metabolonic lactone sulfate levels (2.90%), and Nonadecanoate (19:0) levels (-12.17%) mediated the total genetic predictive effects of class Actinobacteria on AD risk. Similarly, 2-stearoyl-GPE (18:0) levels (-9.87%), Octadecanedioylcarnitine (C18-DC) levels (4.44%), 1-(1-enyl-stearoyl)-2-oleoyl-GPE (p-18:0/18:1) levels (38.66%), and X-23639 levels (13.28%) respectively mediated the total genetic predictive effects of family Lactobacillaceae on AD risk. Furthermore, Hexadecanedioate (C16-DC) levels (5.45%) mediated the total genetic predictive effects of genus Ruminiclostridium 6 on AD risk; Indole-3-carboxylate levels (13.91%), X-13431 levels (7.08%), Alpha-ketoglutarate to succinate ratio (-13.91%), 3-phosphoglycerate to glycerate ratio (15.27%), and Succinate to proline ratio (-14.64%) respectively mediated the total genetic predictive effects of genus Ruminiclostridium 9 on AD risk. Conclusion Our mediation MR analysis provides genetic evidence suggesting the potential mediating role of blood metabolites in the causal relationship between gut microbiota and AD. Further large-scale randomized controlled trials are warranted to validate the role of blood metabolites in the specific mechanisms by which gut microbiota influence AD.
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Affiliation(s)
- Guanglei Chen
- Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China
| | - Yaxian Jin
- The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China
| | - Cancan Chu
- Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China
| | - Yuhao Zheng
- Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China
| | - Yunzhi Chen
- Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China
| | - Xing Zhu
- Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou, China
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Feng Y, Flanagan ME, Bonakdarpour B, Jamshidi P, Castellani RJ, Mao Q, Chu X, Gao H, Liu Y, Xu J, Hou Y, Martin W, Nelson PT, Leverenz JB, Pieper AA, Cummings J, Cheng F. Single-nucleus multiome analysis of human cerebellum in Alzheimer's disease-related dementia. RESEARCH SQUARE 2024:rs.3.rs-4871032. [PMID: 39184089 PMCID: PMC11343296 DOI: 10.21203/rs.3.rs-4871032/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Although human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from cerebellum from 9 human cases of AD/ADRD and 8 controls, and with frontal cortex of 6 AD donors for additional comparison. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we prioritized two likely causal genes, including Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and Hi-C looping data. This first cell subtype-specific regulatory landscape in the human cerebellum identified here offer novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.
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Affiliation(s)
- Yayan Feng
- Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Margaret E Flanagan
- Biggs Institute, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA
- Department of Pathology, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA
| | - Borna Bonakdarpour
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Pouya Jamshidi
- Department of Pathology and Northwestern Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Rudolph J. Castellani
- Department of Pathology and Northwestern Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Qinwen Mao
- Department of Pathology, University of Utah, Salt Lake City, Utah, USA
| | - Xiaona Chu
- Department of Medical and Molecular Genetics, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Hongyu Gao
- Department of Medical and Molecular Genetics, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jielin Xu
- Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Yuan Hou
- Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - William Martin
- Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Peter T Nelson
- Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, Kentucky, USA
- Department of Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky, USA
| | - James B. Leverenz
- Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA
| | - Andrew A. Pieper
- Helen and Robert Appel Alzheimer’s Disease Research Institute, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
- Department of Psychiatry, Case Western Reserve University, Cleveland, OH 44106, USA
- Brain Health Medicines Center, Harrington Discovery Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
- Geriatric Psychiatry, GRECC, Louis Stokes Cleveland VA Medical Center; Cleveland, OH 44106, USA
- Institute for Transformative Molecular Medicine, School of Medicine, Case Western Reserve University, Cleveland 44106, OH, USA
- Department of Pathology, Case Western Reserve University, School of Medicine, Cleveland, OH 44106, USA
- Department of Neurosciences, Case Western Reserve University, School of Medicine, Cleveland, OH 44106, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, UNLV, Las Vegas, Nevada 89154, USA
| | - Feixiong Cheng
- Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
- Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
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Pavešković M, De-Paula RB, Ojelade SA, Tantry EK, Kochukov MY, Bao S, Veeraragavan S, Garza AR, Srivastava S, Song SY, Fujita M, Duong DM, Bennett DA, De Jager PL, Seyfried NT, Dickinson ME, Heaney JD, Arenkiel BR, Shulman JM. Alzheimer's disease risk gene CD2AP is a dose-sensitive determinant of synaptic structure and plasticity. Hum Mol Genet 2024:ddae115. [PMID: 39146503 DOI: 10.1093/hmg/ddae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 06/15/2024] [Indexed: 08/17/2024] Open
Abstract
CD2-Associated protein (CD2AP) is a candidate susceptibility gene for Alzheimer's disease, but its role in the mammalian central nervous system remains largely unknown. We show that CD2AP protein is broadly expressed in the adult mouse brain, including within cortical and hippocampal neurons, where it is detected at pre-synaptic terminals. Deletion of Cd2ap altered dendritic branching and spine density, and impaired ubiquitin-proteasome system activity. Moreover, in mice harboring either one or two copies of a germline Cd2ap null allele, we noted increased paired-pulse facilitation at hippocampal Schaffer-collateral synapses, consistent with a haploinsufficient requirement for pre-synaptic release. Whereas conditional Cd2ap knockout in the brain revealed no gross behavioral deficits in either 3.5- or 12-month-old mice, Cd2ap heterozygous mice demonstrated subtle impairments in discrimination learning using a touchscreen task. Based on unbiased proteomics, partial or complete loss of Cd2ap triggered perturbation of proteins with roles in protein folding, lipid metabolism, proteostasis, and synaptic function. Overall, our results reveal conserved, dose-sensitive requirements for CD2AP in the maintenance of neuronal structure and function, including synaptic homeostasis and plasticity, and inform our understanding of possible cell-type specific mechanisms in Alzheimer's Disease.
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Affiliation(s)
- Matea Pavešković
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Ruth B De-Paula
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Quantitative and Computational Biology Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Shamsideen A Ojelade
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Evelyne K Tantry
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Mikhail Y Kochukov
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Suyang Bao
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Development, Disease Models, and Therapeutics Graduate Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Surabi Veeraragavan
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Alexandra R Garza
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Snigdha Srivastava
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Medical Scientist Training Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Si-Yuan Song
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
| | - Masashi Fujita
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, United States
| | - Duc M Duong
- Departments of Biochemistry and Neurology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, United States
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 600 S. Paulina Street, Chicago, IL 60612, United States
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, United States
| | - Nicholas T Seyfried
- Departments of Biochemistry and Neurology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, United States
| | - Mary E Dickinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Jason D Heaney
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Benjamin R Arenkiel
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Joshua M Shulman
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Center for Alzheimer's and Neurodegenerative Diseases, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
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Zhao X, Li Y, Zhang S, Sudwarts A, Zhang H, Kozlova A, Moulton MJ, Goodman LD, Pang ZP, Sanders AR, Bellen HJ, Thinakaran G, Duan J. Alzheimer's disease protective allele of Clusterin modulates neuronal excitability through lipid-droplet-mediated neuron-glia communication. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.14.24312009. [PMID: 39185522 PMCID: PMC11343251 DOI: 10.1101/2024.08.14.24312009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified a plethora of risk loci. However, the disease variants/genes and the underlying mechanisms remain largely unknown. For a strong AD-associated locus near Clusterin ( CLU ), we tied an AD protective allele to a role of neuronal CLU in promoting neuron excitability through lipid-mediated neuron-glia communication. We identified a putative causal SNP of CLU that impacts neuron-specific chromatin accessibility to transcription-factor(s), with the AD protective allele upregulating neuronal CLU and promoting neuron excitability. Transcriptomic analysis and functional studies in induced pluripotent stem cell (iPSC)-derived neurons co-cultured with mouse astrocytes show that neuronal CLU facilitates neuron-to-glia lipid transfer and astrocytic lipid droplet formation coupled with reactive oxygen species (ROS) accumulation. These changes cause astrocytes to uptake less glutamate thereby altering neuron excitability. Our study provides insights into how CLU confers resilience to AD through neuron-glia interactions.
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DeGroat W, Inoue F, Ashuach T, Yosef N, Ahituv N, Kreimer A. Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation. Genome Biol 2024; 25:221. [PMID: 39143563 PMCID: PMC11323586 DOI: 10.1186/s13059-024-03365-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 08/01/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of the regulatory programs this variation affects can shed light on the apparatuses of human diseases. RESULTS We collect epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we construct networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks serve as the base for a rich series of analyses, through which we demonstrate their temporal dynamics and enrichment for various disease-associated variants. We apply the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrate methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays. CONCLUSIONS Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes; this includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.
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Affiliation(s)
- William DeGroat
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, 679 Hoes Lane West, Piscataway, NJ, 08854, USA
| | - Fumitaka Inoue
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Tal Ashuach
- Department of Electrical Engineering and Computer Sciences and Center for Computational Biology, University of California, Berkeley, 387 Soda Hall, Berkeley, CA, 94720, USA
| | - Nir Yosef
- Department of Systems Immunology, Weizmann Institute of Science, 234 Herzl Street, Rehovot, 7610001, Israel
- Chan-Zuckerberg Biohub, 499 Illinois St, San Francisco, CA, 94158, USA
- Department of Systems Immunology, Ragon Institute of MGH, MIT, and Harvard Institute of Science, 400 Technology Square, Cambridge, MA, 02139, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, 513 Parnassus Ave, San Francisco, CA, 94143, USA
- Institute for Human Genetics, University of California, 513 Parnassus Ave, San Francisco, CA, 94143, USA
| | - Anat Kreimer
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, 679 Hoes Lane West, Piscataway, NJ, 08854, USA.
- Department of Biochemistry and Molecular Biology, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA.
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Kirby A, Porter T, Adewuyi EO, Laws SM. Investigating Genetic Overlap between Alzheimer's Disease, Lipids, and Coronary Artery Disease: A Large-Scale Genome-Wide Cross Trait Analysis. Int J Mol Sci 2024; 25:8814. [PMID: 39201500 PMCID: PMC11354907 DOI: 10.3390/ijms25168814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Revised: 08/10/2024] [Accepted: 08/11/2024] [Indexed: 09/02/2024] Open
Abstract
There is evidence to support a link between abnormal lipid metabolism and Alzheimer's disease (AD) risk. Similarly, observational studies suggest a comorbid relationship between AD and coronary artery disease (CAD). However, the intricate biological mechanisms of AD are poorly understood, and its relationship with lipids and CAD traits remains unresolved. Conflicting evidence further underscores the ongoing investigation into this research area. Here, we systematically assess the cross-trait genetic overlap of AD with 13 representative lipids (from eight classes) and seven CAD traits, leveraging robust analytical methods, well-powered large-scale genetic data, and rigorous replication testing. Our main analysis demonstrates a significant positive global genetic correlation of AD with triglycerides and all seven CAD traits assessed-angina pectoris, cardiac dysrhythmias, coronary arteriosclerosis, ischemic heart disease, myocardial infarction, non-specific chest pain, and coronary artery disease. Gene-level analyses largely reinforce these findings and highlight the genetic overlap between AD and three additional lipids: high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and total cholesterol. Moreover, we identify genome-wide significant genes (Fisher's combined p value [FCPgene] < 2.60 × 10-6) shared across AD, several lipids, and CAD traits, including WDR12, BAG6, HLA-DRA, PHB, ZNF652, APOE, APOC4, PVRL2, and TOMM40. Mendelian randomisation analysis found no evidence of a significant causal relationship between AD, lipids, and CAD traits. However, local genetic correlation analysis identifies several local pleiotropic hotspots contributing to the relationship of AD with lipids and CAD traits across chromosomes 6, 8, 17, and 19. Completing a three-way analysis, we confirm a strong genetic correlation between lipids and CAD traits-HDL and sphingomyelin demonstrate negative correlations, while LDL, triglycerides, and total cholesterol show positive correlations. These findings support genetic overlap between AD, specific lipids, and CAD traits, implicating shared but non-causal genetic susceptibility. The identified shared genes and pleiotropic hotspots are valuable targets for further investigation into AD and, potentially, its comorbidity with CAD traits.
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Affiliation(s)
- Artika Kirby
- Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027, Australia; (A.K.); (T.P.)
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027, Australia; (A.K.); (T.P.)
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia
- Curtin Medical School, Curtin University, Bentley, WA 6102, Australia
| | - Emmanuel O. Adewuyi
- Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027, Australia; (A.K.); (T.P.)
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia
| | - Simon M. Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027, Australia; (A.K.); (T.P.)
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia
- Curtin Medical School, Curtin University, Bentley, WA 6102, Australia
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Bougea A, Gourzis P. Biomarker-Based Precision Therapy for Alzheimer's Disease: Multidimensional Evidence Leading a New Breakthrough in Personalized Medicine. J Clin Med 2024; 13:4661. [PMID: 39200803 PMCID: PMC11355840 DOI: 10.3390/jcm13164661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Revised: 07/25/2024] [Accepted: 08/05/2024] [Indexed: 09/02/2024] Open
Abstract
(1) Background: Alzheimer's disease (AD) is a worldwide neurodegenerative disorder characterized by the buildup of abnormal proteins in the central nervous system and cognitive decline. Since no radical therapy exists, only symptomatic treatments alleviate symptoms temporarily. In this review, we will explore the latest advancements in precision medicine and biomarkers for AD, including their potential to revolutionize the way we diagnose and treat this devastating condition. (2) Methods: A literature search was performed combining the following Medical Subject Heading (MeSH) terms on PubMed: "Alzheimer's disease", "biomarkers", "APOE", "APP", "GWAS", "cerebrospinal fluid", "polygenic risk score", "Aβ42", "τP-181", " p-tau217", "ptau231", "proteomics", "total tau protein", and "precision medicine" using Boolean operators. (3) Results: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with AD risk, while a transcriptomic analysis has revealed dysregulated gene expression patterns in the brains of individuals with AD. The proteomic and metabolomic profiling of biological fluids, such as blood, urine, and CSF, and neuroimaging biomarkers have also yielded potential biomarkers of AD that could be used for the early diagnosis and monitoring of disease progression. (4) Conclusion: By leveraging a combination of the above biomarkers, novel ultrasensitive immunoassays, mass spectrometry methods, and metabolomics, researchers are making significant strides towards personalized healthcare for individuals with AD.
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Affiliation(s)
- Anastasia Bougea
- 1st Department of Neurology, National and Kapodistrian University of Athens, 15772 Athens, Greece
| | - Philippos Gourzis
- 1st Department of Psychiatry, University of Patras, 26504 Rio, Greece;
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Lee JW, Mizuno K, Watanabe H, Lee IH, Tsumita T, Hida K, Yawaka Y, Kitagawa Y, Hasebe A, Iimura T, Kong SW. Enhanced phagocytosis associated with multinucleated microglia via Pyk2 inhibition in an acute β-amyloid infusion model. J Neuroinflammation 2024; 21:196. [PMID: 39107821 PMCID: PMC11301859 DOI: 10.1186/s12974-024-03192-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 07/31/2024] [Indexed: 08/10/2024] Open
Abstract
Multinucleated microglia have been observed in contexts associated with infection, inflammation, and aging. Though commonly linked to pathological conditions, the larger cell size of multinucleated microglia might enhance their phagocytic functions, potentially aiding in the clearance of brain debris and suggesting a reassessment of their pathological significance. To assess the phagocytic capacity of multinucleated microglia and its implications for brain debris clearance, we induced their formation by inhibiting Pyk2 activity using the pharmacological inhibitor PF-431396, which triggers cytokinesis regression. Multinucleated microglia demonstrate enhanced phagocytic function, as evidenced by their increased capacity to engulf β-amyloid (Aβ) oligomers. Concurrently, the phosphorylation of Pyk2, induced by Aβ peptide, was diminished upon treatment with a Pyk2 inhibitor (Pyk2-Inh, PF-431396). Furthermore, the increased expression of Lamp1, a lysosomal marker, with Pyk2-inh treatment, suggests an enhancement in proteolytic activity. In vivo, we generated an acute Alzheimer's disease (AD) model by infusing Aβ into the brains of Iba-1 EGFP transgenic (Tg) mice. The administration of the Pyk2-Inh led to an increased migration of microglia toward amyloid deposits in the brains of Iba-1 EGFP Tg mice, accompanied by morphological activation, suggesting a heightened affinity for Aβ. In human microglia, lipopolysaccharide (LPS)-induced inflammatory responses showed that inhibition of Pyk2 signaling significantly reduced the transcription and protein expression of pro-inflammatory markers. These results suggest that Pyk2 inhibition can modulate microglial functions, potentially reducing neuroinflammation and aiding in the clearance of neurodegenerative disease markers. This highlights Pyk2 as a promising target for therapeutic intervention in neurodegenerative diseases.
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Affiliation(s)
- Ji-Won Lee
- Microbiology, Department of Oral Pathobiological Science, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan.
| | - Kaito Mizuno
- Microbiology, Department of Oral Pathobiological Science, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
- Dentistry for Children and Disabled Persons, Department of Oral Functional Science, Faculty of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Haruhisa Watanabe
- Department of Pharmacology, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
- Oral Diagnosis and Medicine, Department of Oral Pathobiological Science, Faculty of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - In-Hee Lee
- Computational Health and Informatics Program, Boston Children's Hospital, Boston, MA, 02215, USA
| | - Takuya Tsumita
- Department of Vascular Biology and Molecular Pathology, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Kyoko Hida
- Department of Vascular Biology and Molecular Pathology, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Yasutaka Yawaka
- Dentistry for Children and Disabled Persons, Department of Oral Functional Science, Faculty of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Yoshimasa Kitagawa
- Oral Diagnosis and Medicine, Department of Oral Pathobiological Science, Faculty of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Akira Hasebe
- Microbiology, Department of Oral Pathobiological Science, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Tadahiro Iimura
- Department of Pharmacology, Faculty and Graduate School of Dental Medicine, Hokkaido University, Kita13 Nishi7, Kita-Ku, Sapporo, 060-8586, Japan
| | - Sek Won Kong
- Computational Health and Informatics Program, Boston Children's Hospital, Boston, MA, 02215, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, 02115, USA
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46
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Xiong LY, Wood Alexander M, Wong YY, Wu CY, Ruthirakuhan M, Edwards JD, Lanctôt KL, Black SE, Rabin JS, Cogo-Moreira H, Swardfager W. Latent profiles of modifiable dementia risk factors in later midlife: relationships with incident dementia, cognition, and neuroimaging outcomes. Mol Psychiatry 2024:10.1038/s41380-024-02685-4. [PMID: 39103532 DOI: 10.1038/s41380-024-02685-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 07/22/2024] [Accepted: 07/24/2024] [Indexed: 08/07/2024]
Abstract
In 2020, the Lancet Commission identified 12 modifiable factors that increase population-level dementia risk. It is unclear if these risk factors co-occur among individuals in a clinically meaningful way. Using latent class analysis, we identified profiles of modifiable dementia risk factors in dementia-free adults aged 60-64 years from the UK Biobank. We then estimated associations between these profiles with incident dementia, cognition, and neuroimaging outcomes, and explored the differences across profiles in the effects of a polygenic risk score for Alzheimer's disease on outcomes. In 55,333 males and 63,063 females, three sex-specific latent profiles were identified: cardiometabolic risk, substance use-related risk, and low risk. The cardiometabolic risk profile in both males and females was associated with greater incidence of all-cause dementia (male: OR [95% CI] = 2.33 [2.03, 2.66]; female: OR [95% CI] = 1.44 [1.24, 1.68]), poorer cognitive performance, greater brain atrophy, and greater white matter hyperintensity volume compared to the low risk profile. The substance use-related risk profile in males was associated with poorer cognitive performance and greater white matter hyperintensities compared to the low risk profile, but no difference in all-cause dementia incidence was observed (OR [95% CI] = 1.00 [0.95, 1.06]). In females, the substance use-related risk profile demonstrated increased dementia incidence (OR [95% CI] = 1.58 [1.57, 1.58]) and greater brain atrophy but smaller white matter hyperintensity volume compared to the low risk profile. The polygenic risk score had larger effects among females, and differentially influenced outcomes across profiles; for instance, there were larger effects of the polygenic risk score on atrophy in the cardiometabolic profile vs. the low risk profile among males, and larger effects of the polygenic risk score on loss of white matter integrity in the cardiometabolic profile vs. the low risk profile among females. These results reveal three modifiable dementia risk profiles, their unique cognitive/neuroimaging outcomes, and their interactions with genetic risk for Alzheimer's disease. These differences highlight the need to consider population heterogeneity in risk prediction tools and in planning personalized prevention strategies.
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Affiliation(s)
- Lisa Y Xiong
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Madeline Wood Alexander
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
| | - Yuen Yan Wong
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Che-Yuan Wu
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Myuri Ruthirakuhan
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Jodi D Edwards
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
- ICES, Ottawa, ON, Canada
| | - Krista L Lanctôt
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Sandra E Black
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jennifer S Rabin
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Hugo Cogo-Moreira
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Walter Swardfager
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada.
- Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
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47
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Parrish RL, Buchman AS, Tasaki S, Wang Y, Avey D, Xu J, De Jager PL, Bennett DA, Epstein MP, Yang J. SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning. Nat Commun 2024; 15:6646. [PMID: 39103319 DOI: 10.1038/s41467-024-50983-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 07/26/2024] [Indexed: 08/07/2024] Open
Abstract
Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies show that SR-TWAS improves power, due to increased training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real studies identify 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations are found for these significant risk genes.
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Affiliation(s)
- Randy L Parrish
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Biostatistics, Emory University School of Public Health, Atlanta, GA, 30322, USA
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Yanling Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Denis Avey
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Jishu Xu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Michael P Epstein
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
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Starr AL, Fraser HB. A general principle governing neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.02.606407. [PMID: 39131279 PMCID: PMC11312593 DOI: 10.1101/2024.08.02.606407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons-layer 2/3 intratelencephalic excitatory neurons-has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.
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Affiliation(s)
| | - Hunter B. Fraser
- Department of Biology, Stanford University, Stanford, CA 94305, USA
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49
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Altmann A, Aksman LM, Oxtoby NP, Young AL, Alexander DC, Barkhof F, Shoai M, Hardy J, Schott JM. Towards cascading genetic risk in Alzheimer's disease. Brain 2024; 147:2680-2690. [PMID: 38820112 PMCID: PMC11292901 DOI: 10.1093/brain/awae176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/22/2024] [Accepted: 05/06/2024] [Indexed: 06/02/2024] Open
Abstract
Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.
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Affiliation(s)
- Andre Altmann
- UCL Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
| | - Leon M Aksman
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Neil P Oxtoby
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Alexandra L Young
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Daniel C Alexander
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Frederik Barkhof
- UCL Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, 1081 HV, The Netherlands
| | - Maryam Shoai
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
| | - John Hardy
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
| | - Jonathan M Schott
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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Huang X, Yuan S, Ling Y, Tan S, Cheng H, Xu A, Lyu J. Association of birthweight and risk of incident dementia: a prospective cohort study. GeroScience 2024; 46:3845-3859. [PMID: 38436791 PMCID: PMC11226576 DOI: 10.1007/s11357-024-01105-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 02/19/2024] [Indexed: 03/05/2024] Open
Abstract
Given the epidemiological studies investigating the relationship between birthweight and dementia are limited. Our study aimed to explore the association between birthweight and the risk of dementia, cognitive function, and brain structure. We included 275,648 participants from the UK Biobank, categorizing birthweight into quartiles (Q1 ≤ 2.95 kg; Q2 > 2.95 kg, ≤ 3.32 kg; Q3 > 3.32 kg, ≤ 3.66 kg; Q4 > 3.66 kg), with Q3 as the reference. Cox regression models and restricted cubic splines estimated the relationship between birthweight and the risk of all causes of dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VD). Multivariable linear regression models assessed the relationship between birthweight, cognitive function, and MRI biomarkers. Over a median follow-up of 13.0 years, 3103 incident dementia cases were recorded. In the fully adjusted model, compared to Q3 (> 3.32 kg, ≤ 3.66 kg), lower birthweight in Q1 (≤ 2.95 kg) was significantly associated with increased risk of ACD (HR = 1.18, 95%CI 1.06-1.30, P = 0.001) and VD (HR = 1.32, 95%CI 1.07-1.62, P = 0.010), but no significant association with AD was found. Continuous birthweight showed a U-shaped nonlinear association with dementia. Lower birthweight was associated with worse performance in cognitive tasks, including reaction time, fluid intelligence, numeric, and prospective memory. Additionally, certain brain structure indices were identified, including brain atrophy and reductions in area, thickness, and volume of regional subcortical areas. Our study emphasizes the association between lower birthweight and increased dementia risk, correlating cognitive function and MRI biomarkers of brain structure, suggesting that in utero or early-life exposures might impact cognitive health in adulthood.
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Affiliation(s)
- Xiaxuan Huang
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Shiqi Yuan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Yitong Ling
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Shanyuan Tan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Hongtao Cheng
- School of Nursing, Jinan University, Guangzhou, 510630, China
| | - Anding Xu
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China.
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou, 510630, China.
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