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Cava C, D'Antona S, Maselli F, Castiglioni I, Porro D. From genetic correlations of Alzheimer's disease to classification with artificial neural network models. Funct Integr Genomics 2023; 23:293. [PMID: 37682415 PMCID: PMC10491691 DOI: 10.1007/s10142-023-01228-4] [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: 06/28/2023] [Revised: 08/30/2023] [Accepted: 09/03/2023] [Indexed: 09/09/2023]
Abstract
Sporadic Alzheimer's disease (AD) is a complex neurological disorder characterized by many risk loci with potential associations with different traits and diseases. AD, characterized by a progressive loss of neuronal functions, manifests with different symptoms such as decline in memory, movement, coordination, and speech. The mechanisms underlying the onset of AD are not always fully understood, but involve a multiplicity of factors. Early diagnosis of AD plays a central role as it can offer the possibility of early treatment, which can slow disease progression. Currently, the methods of diagnosis are cognitive testing, neuroimaging, or cerebrospinal fluid analysis that can be time-consuming, expensive, invasive, and not always accurate. In the present study, we performed a genetic correlation analysis using genome-wide association statistics from a large study of AD and UK Biobank, to examine the association of AD with other human traits and disorders. In addition, since hippocampus, a part of cerebral cortex could play a central role in several traits that are associated with AD; we analyzed the gene expression profiles of hippocampus of AD patients applying 4 different artificial neural network models. We found 65 traits correlated with AD grouped into 9 clusters: medical conditions, fluid intelligence, education, anthropometric measures, employment status, activity, diet, lifestyle, and sexuality. The comparison of different 4 neural network models along with feature selection methods on 5 Alzheimer's gene expression datasets showed that the simple basic neural network model obtains a better performance (66% of accuracy) than other more complex methods with dropout and weight regularization of the network.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy.
- Department of Science, Technology and Society, University School for Advanced Studies IUSS Pavia, Palazzo del Broletto, Piazza Della Vittoria 15, 27100, Pavia, Italy.
| | - Salvatore D'Antona
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy
| | - Francesca Maselli
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy
| | - Isabella Castiglioni
- Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza Dell'Ateneo Nuovo, 20126, Milan, Italy
| | - Danilo Porro
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy
- NBFC, National Biodiversity Future Center, 90133, Palermo, Italy
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Dato S, De Rango F, Crocco P, Pallotti S, Belloy ME, Le Guen Y, Greicius MD, Passarino G, Rose G, Napolioni V. Sex- and APOE-specific genetic risk factors for late-onset Alzheimer's disease: Evidence from gene-gene interaction of longevity-related loci. Aging Cell 2023; 22:e13938. [PMID: 37621137 PMCID: PMC10497850 DOI: 10.1111/acel.13938] [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: 04/14/2023] [Revised: 07/01/2023] [Accepted: 07/12/2023] [Indexed: 08/26/2023] Open
Abstract
Advanced age is the largest risk factor for late-onset Alzheimer's disease (LOAD), a disease in which susceptibility correlates to almost all hallmarks of aging. Shared genetic signatures between LOAD and longevity were frequently hypothesized, likely characterized by distinctive epistatic and pleiotropic interactions. Here, we applied a multidimensional reduction approach to detect gene-gene interactions affecting LOAD in a large dataset of genomic variants harbored by genes in the insulin/IGF1 signaling, DNA repair, and oxidative stress pathways, previously investigated in human longevity. The dataset was generated from a collection of publicly available Genome Wide Association Studies, comprising a total of 2,469 gene variants genotyped in 20,766 subjects of Northwestern European ancestry (11,038 LOAD cases and 9,728 controls). The stratified analysis according to APOE*4 status and sex corroborated evidence that pathways leading to longevity also contribute to LOAD. Among the significantly interacting genes, PTPN1, TXNRD1, and IGF1R were already found enriched in gene-gene interactions affecting survival to old age. Furthermore, interacting variants associated with LOAD in a sex- and APOE-specific way. Indeed, while in APOE*4 female carriers we found several inter-pathway interactions, no significant epistasis was found in APOE*4 negative females; conversely, in males, significant intra- and inter-pathways epistasis emerged according to APOE*4 status. These findings suggest that interactions of risk factors may drive different trajectories of cognitive aging. Beyond helping to disentangle the genetic architecture of LOAD, such knowledge may improve precision in predicting the risk of dementia and enable effective sex- and APOE-stratified preventive and therapeutic interventions for LOAD.
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Affiliation(s)
- Serena Dato
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Francesco De Rango
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Paolina Crocco
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Stefano Pallotti
- Genomic And Molecular Epidemiology (GAME) Lab., School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly
| | - Michael E. Belloy
- Department of Neurology and Neurological Sciences, School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, School of MedicineStanford UniversityStanfordCaliforniaUSA
| | - Giuseppe Passarino
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Giuseppina Rose
- Department of Biology, Ecology and Earth SciencesUniversity of CalabriaRendeItaly
| | - Valerio Napolioni
- Genomic And Molecular Epidemiology (GAME) Lab., School of Biosciences and Veterinary MedicineUniversity of CamerinoCamerinoItaly
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Torres GG, Dose J, Hasenbein TP, Nygaard M, Krause-Kyora B, Mengel-From J, Christensen K, Andersen-Ranberg K, Kolbe D, Lieb W, Laudes M, Görg S, Schreiber S, Franke A, Caliebe A, Kuhlenbäumer G, Nebel A. Long-Lived Individuals Show a Lower Burden of Variants Predisposing to Age-Related Diseases and a Higher Polygenic Longevity Score. Int J Mol Sci 2022; 23:10949. [PMID: 36142858 PMCID: PMC9504529 DOI: 10.3390/ijms231810949] [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: 08/09/2022] [Revised: 09/05/2022] [Accepted: 09/07/2022] [Indexed: 11/22/2022] Open
Abstract
Longevity is a complex phenotype influenced by both environmental and genetic factors. The genetic contribution is estimated at about 25%. Despite extensive research efforts, only a few longevity genes have been validated across populations. Long-lived individuals (LLI) reach extreme ages with a relative low prevalence of chronic disability and major age-related diseases (ARDs). We tested whether the protection from ARDs in LLI can partly be attributed to genetic factors by calculating polygenic risk scores (PRSs) for seven common late-life diseases (Alzheimer's disease (AD), atrial fibrillation (AF), coronary artery disease (CAD), colorectal cancer (CRC), ischemic stroke (ISS), Parkinson's disease (PD) and type 2 diabetes (T2D)). The examined sample comprised 1351 German LLI (≥94 years, including 643 centenarians) and 4680 German younger controls. For all ARD-PRSs tested, the LLI had significantly lower scores than the younger control individuals (areas under the curve (AUCs): ISS = 0.59, p = 2.84 × 10-35; AD = 0.59, p = 3.16 × 10-25; AF = 0.57, p = 1.07 × 10-16; CAD = 0.56, p = 1.88 × 10-12; CRC = 0.52, p = 5.85 × 10-3; PD = 0.52, p = 1.91 × 10-3; T2D = 0.51, p = 2.61 × 10-3). We combined the individual ARD-PRSs into a meta-PRS (AUC = 0.64, p = 6.45 × 10-15). We also generated two genome-wide polygenic scores for longevity, one with and one without the TOMM40/APOE/APOC1 gene region (AUC (incl. TOMM40/APOE/APOC1) = 0.56, p = 1.45 × 10-5, seven variants; AUC (excl. TOMM40/APOE/APOC1) = 0.55, p = 9.85 × 10-3, 10,361 variants). Furthermore, the inclusion of nine markers from the excluded region (not in LD with each other) plus the APOE haplotype into the model raised the AUC from 0.55 to 0.61. Thus, our results highlight the importance of TOMM40/APOE/APOC1 as a longevity hub.
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Affiliation(s)
- Guillermo G. Torres
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Janina Dose
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Tim P. Hasenbein
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
- Department of Neurology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105 Kiel, Germany
- Institute of Pharmacology and Toxicology, Technical University Munich, Biedersteiner Str. 29, 80802 Munich, Germany
| | - Marianne Nygaard
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
| | - Ben Krause-Kyora
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Jonas Mengel-From
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
| | - Kaare Christensen
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, J.B. Winsloews Vej 4, 5000 Odense, Denmark
- Department of Clinical Biochemistry, Odense University Hospital, Kløvervænget 47, 5000 Odense, Denmark
| | - Karen Andersen-Ranberg
- Department of Public Health, Epidemiology, Biostatistics and Biodemography, University of Southern, Denmark, J.B. Winsloews Vej 9B, 5000 Odense, Denmark
- Department of Geriatric Medicine, Odense University Hospital, Kløvervænget 23, 5000 Odense, Denmark
| | - Daniel Kolbe
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank Popgen, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Niemannsweg 11, 24105 Kiel, Germany
| | - Matthias Laudes
- Clinic for Internal Medicine I, Division of Endocrinology, Diabetes and Clinical Nutrition, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, 24105 Kiel, Germany
| | - Siegfried Görg
- Institute of Transfusion Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
| | - Amke Caliebe
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Brunswiker Str. 10, 24105 Kiel, Germany
| | - Gregor Kuhlenbäumer
- Department of Neurology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Str. 3, 24105 Kiel, Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Kiel University, University Hospital Schleswig-Holstein, Campus Kiel, Rosalind-Franklin-Str. 12, 24105 Kiel, Germany
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Hu D, Li Y, Zhang D, Ding J, Song Z, Min J, Zeng Y, Nie C. Genetic trade-offs between complex diseases and longevity. Aging Cell 2022; 21:e13654. [PMID: 35754110 PMCID: PMC9282840 DOI: 10.1111/acel.13654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/28/2022] [Accepted: 05/26/2022] [Indexed: 11/30/2022] Open
Abstract
Longevity was influenced by many complex diseases and traits. However, the relationships between human longevity and genetic risks of complex diseases were not broadly studied. Here, we constructed polygenic risk scores (PRSs) for 225 complex diseases/traits and evaluated their relationships with human longevity in a cohort with 2178 centenarians and 2299 middle‐aged individuals. Lower genetic risks of stroke and hypotension were observed in centenarians, while higher genetic risks of schizophrenia (SCZ) and type 2 diabetes (T2D) were detected in long‐lived individuals. We further stratified PRSs into cell‐type groups and significance‐level groups. The results showed that the immune component of SCZ genetic risk was positively linked to longevity, and the renal component of T2D genetic risk was the most deleterious. Additionally, SNPs with very small p‐values (p ≤ 1x10‐5) for SCZ and T2D were negatively correlated with longevity. While for the less significant SNPs (1x10‐5 < p ≤ 0.05), their effects on disease and longevity were positively correlated. Overall, we identified genetically informed positive and negative factors for human longevity, gained more insights on the accumulation of disease risk alleles during evolution, and provided evidence for the theory of genetic trade‐offs between complex diseases and longevity.
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Affiliation(s)
- Dingxue Hu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.,BGI-Shenzhen, Shenzhen, China
| | - Yan Li
- BGI-Shenzhen, Shenzhen, China
| | | | | | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China.,Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, North Carolina, USA
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Bellou E, Escott-Price V. Are Alzheimer's and coronary artery diseases genetically related to longevity? Front Psychiatry 2022; 13:1102347. [PMID: 36684006 PMCID: PMC9859055 DOI: 10.3389/fpsyt.2022.1102347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 12/12/2022] [Indexed: 01/07/2023] Open
Abstract
INTRODUCTION In the last decade researchers have attempted to investigate the shared genetic architecture of longevity and age-related diseases and assess whether the increased longevity in certain people is due to protective alleles in the risk genes for a particular condition or whether there are specific "longevity" genes increasing the lifespan independently of age-related conditions' risk genes. The aim of this study was to investigate the shared genetic component between longevity and two age-related conditions. METHODS We performed a cross-trait meta-analysis of publicly available genome-wide data for Alzheimer's disease, coronary artery disease and longevity using a subset-based approach provided by the R package ASSET. RESULTS Despite the lack of strong genetic correlation between longevity and the two diseases, we identified 38 genome-wide significant lead SNPs across 22 independent genomic loci. Of them 6 were found to be potentially shared among the three traits mapping to genes including DAB2IP, DNM2, FCHO1, CLPTM1, and SNRPD2. We also identified 19 novel genome-wide associations for the individual traits in this study. Functional annotations and biological pathway enrichment analyses suggested that pleiotropic variants are involved in clathrin-mediated endocytosis and plasma lipoprotein and neurotransmitter clearance processes. DISCUSSION In summary, we have been able to advance in the knowledge of the genetic overlap existing among longevity and the two most common age-related disorders.
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Affiliation(s)
- Eftychia Bellou
- UK Dementia Research Institute, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Cardiff, United Kingdom
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