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Moore A, Ritchie MD. Cross-phenotype associations between Alzheimer's Disease and its comorbidities may provide clues to progression. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2024; 2024:623-631. [PMID: 38827078 PMCID: PMC11141840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide, with one in nine people over the age of 65 living with the disease in 2023. In this study, we used a phenome wide association study (PheWAS) approach to identify cross-phenotype between previously identified genetic associations for AD and electronic health record (EHR) diagnoses from the UK Biobank (UKBB) (n=361,194 of European ancestry) and the eMERGE Network (n=105,108 of diverse ancestry). Based on 497 previously identified AD-associated variants from the Alzheimer's Disease Variant Portal (ADVP), we found significant associations primarily in immune and cardiac related diseases in our PheWAS. Replicating variants have widespread impacts on immune genes in diverse tissue types. This study demonstrates the potential of using the PheWAS strategy to improve our understanding of AD progression as well as identify potential drug repurposing opportunities for new treatment and disease prevention strategies.
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Affiliation(s)
- Anni Moore
- Genomics and Computational Biology Group, University of Pennsylvania, Philadelphia, PA
| | - Marylyn D Ritchie
- Genomics and Computational Biology Group, University of Pennsylvania, Philadelphia, PA
- Institute of Biomedical Informatics, University of Pennsylvania, Philadelphia, PA
- Division of Informatics, DBEI, Perelman School of Medicine., University of Pennsylvania, Philadelphia, PA
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Moore A, Ritchie MD. Cross-phenotype associations between Alzheimer's Disease and its comorbidities may provide clues to progression. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.06.23297993. [PMID: 37986758 PMCID: PMC10659497 DOI: 10.1101/2023.11.06.23297993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide, with one in nine people over the age of 65 living with the disease in 2023. In this study, we used a phenome wide association study (PheWAS) approach to identify cross-phenotype associations between previously identified genetic AD and for electronic health record (EHR) diagnoses from the UK Biobank (UKBB) (n=361,194 of European ancestry) and the eMERGE Network (n=105,108 of diverse ancestry). Based on 497 previously identified AD-associated variants from the Alzheimer's Disease Variant Portal (ADVP), we found significant associations primarily in immune and cardiac related diseases in our PheWAS. Replicating variants have widespread impacts on immune genes in diverse tissue types. This study demonstrates the potential of using the PheWAS strategy to improve our understanding of AD progression as well as identify potential drug repurposing opportunities for new treatment and disease prevention strategies.
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Affiliation(s)
- Anni Moore
- Genomics and Computational Biology Group, University of Pennsylvania, Philadelphia, PA
| | - Marylyn D Ritchie
- Genomics and Computational Biology Group, University of Pennsylvania, Philadelphia, PA
- Institute of Biomedical Informatics, University of Pennsylvania, Philadelphia, PA; Division of Informatics, DBEI, Perelman School of Medicine., University of Pennsylvania, Philadelphia, PA
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Loika Y, Loiko E, Culminskaya I, Kulminski AM. Exome-Wide Association Study Identified Clusters of Pleiotropic Genetic Associations with Alzheimer's Disease and Thirteen Cardiovascular Traits. Genes (Basel) 2023; 14:1834. [PMID: 37895183 PMCID: PMC10606283 DOI: 10.3390/genes14101834] [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: 08/29/2023] [Revised: 09/18/2023] [Accepted: 09/20/2023] [Indexed: 10/29/2023] Open
Abstract
Alzheimer's disease (AD) and cardiovascular traits might share underlying causes. We sought to identify clusters of cardiovascular traits that share genetic factors with AD. We conducted a univariate exome-wide association study and pair-wise pleiotropic analysis focused on AD and 16 cardiovascular traits-6 diseases and 10 cardio-metabolic risk factors-for 188,260 UK biobank participants. Our analysis pinpointed nine genetic markers in the APOE gene region and four loci mapped to the CDK11, OBP2B, TPM1, and SMARCA4 genes, which demonstrated associations with AD at p ≤ 5 × 10-4 and pleiotropic associations at p ≤ 5 × 10-8. Using hierarchical cluster analysis, we grouped the phenotypes from these pleiotropic associations into seven clusters. Lipids were divided into three clusters: low-density lipoprotein and total cholesterol, high-density lipoprotein cholesterol, and triglycerides. This split might differentiate the lipid-related mechanisms of AD. The clustering of body mass index (BMI) with weight but not height indicates that weight defines BMI-AD pleiotropy. The remaining two clusters included (i) coronary heart disease and myocardial infarction; and (ii) hypertension, diabetes mellitus (DM), systolic and diastolic blood pressure. We found that all AD protective alleles were associated with larger weight and higher DM risk. Three of the four (75%) clusters of traits, which were significantly correlated with AD, demonstrated antagonistic genetic heterogeneity, characterized by different directions of the genetic associations and trait correlations. Our findings suggest that shared genetic factors between AD and cardiovascular traits mostly affect them in an antagonistic manner.
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Affiliation(s)
- Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA; (E.L.); (I.C.); (A.M.K.)
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Kang M, Ang TFA, Devine SA, Sherva R, Mukherjee S, Trittschuh EH, Gibbons LE, Scollard P, Lee M, Choi SE, Klinedinst B, Nakano C, Dumitrescu LC, Durant A, Hohman TJ, Cuccaro ML, Saykin AJ, Kukull WA, Bennett DA, Wang LS, Mayeux RP, Haines JL, Pericak-Vance MA, Schellenberg GD, Crane PK, Au R, Lunetta KL, Mez JB, Farrer LA. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores. Mol Neurodegener 2023; 18:40. [PMID: 37349795 PMCID: PMC10286470 DOI: 10.1186/s13024-023-00633-4] [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: 02/17/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. METHODS We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. RESULTS Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. CONCLUSION Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.
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Affiliation(s)
- Moonil Kang
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Ting Fang Alvin Ang
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Sherral A. Devine
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Shubhabrata Mukherjee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Emily H. Trittschuh
- Geriatric Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, WA USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Laura E. Gibbons
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Phoebe Scollard
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Michael Lee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Seo-Eun Choi
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Brandon Klinedinst
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Connie Nakano
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Logan C. Dumitrescu
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Alaina Durant
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Timothy J. Hohman
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, Miami, FL USA
| | - Andrew J. Saykin
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Services, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, WA USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Richard P. Mayeux
- Department of Neurology, Columbia University School of Medicine, New York, NY USA
| | - Jonathan L. Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH USA
| | | | - Gerard D. Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Paul K. Crane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
| | - Kathryn L. Lunetta
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Jesse B. Mez
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
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Namekata K, Tsuji N, Guo X, Nishijima E, Honda S, Kitamura Y, Yamasaki A, Kishida M, Takeyama J, Ishikawa H, Shinozaki Y, Kimura A, Harada C, Harada T. Neuroprotection and axon regeneration by novel low-molecular-weight compounds through the modification of DOCK3 conformation. Cell Death Discov 2023; 9:166. [PMID: 37188749 PMCID: PMC10184973 DOI: 10.1038/s41420-023-01460-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 04/26/2023] [Accepted: 05/02/2023] [Indexed: 05/17/2023] Open
Abstract
Dedicator of cytokinesis 3 (DOCK3) is an atypical member of the guanine nucleotide exchange factors (GEFs) and plays important roles in neurite outgrowth. DOCK3 forms a complex with Engulfment and cell motility protein 1 (Elmo1) and effectively activates Rac1 and actin dynamics. In this study, we screened 462,169 low-molecular-weight compounds and identified the hit compounds that stimulate the interaction between DOCK3 and Elmo1, and neurite outgrowth in vitro. Some of the derivatives from the hit compound stimulated neuroprotection and axon regeneration in a mouse model of optic nerve injury. Our findings suggest that the low-molecular-weight DOCK3 activators could be a potential therapeutic candidate for treating axonal injury and neurodegenerative diseases including glaucoma.
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Affiliation(s)
- Kazuhiko Namekata
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Naoki Tsuji
- R&D Division, Daiichi Sankyo Co., Ltd, Tokyo, Japan
| | - Xiaoli Guo
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Euido Nishijima
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Sari Honda
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Yuta Kitamura
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | | | | | - Jun Takeyama
- Biological Research Department, Daiichi Sankyo RD Novare Co., Ltd, Tokyo, Japan
| | - Hirokazu Ishikawa
- Biological Research Department, Daiichi Sankyo RD Novare Co., Ltd, Tokyo, Japan
| | - Youichi Shinozaki
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Atsuko Kimura
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Chikako Harada
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Takayuki Harada
- Visual Research Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan.
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Huang X, Yao M, Tian P, Wong JYY, Li Z, Liu Z, Zhao JV. Genome-wide cross-trait analysis and Mendelian randomization reveal a shared genetic etiology and causality between COVID-19 and venous thromboembolism. Commun Biol 2023; 6:441. [PMID: 37085521 PMCID: PMC10120502 DOI: 10.1038/s42003-023-04805-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 04/04/2023] [Indexed: 04/23/2023] Open
Abstract
Venous thromboembolism occurs in up to one-third of patients with COVID-19. Venous thromboembolism and COVID-19 may share a common genetic architecture, which has not been clarified. To fill this gap, we leverage summary-level genetic data from the latest COVID-19 host genetics consortium and UK Biobank and examine the shared genetic etiology and causal relationship between COVID-19 and venous thromboembolism. The cross-trait and co-localization analyses identify 2, 3, and 4 shared loci between venous thromboembolism and severe COVID-19, COVID-19 hospitalization, SARS-CoV-2 infection respectively, which are mapped to ABO, ADAMTS13, FUT2 genes involved in coagulation functions. Enrichment analysis supports shared biological processes between COVID-19 and venous thromboembolism related to coagulation and immunity. Bi-directional Mendelian randomization suggests that venous thromboembolism was associated with higher risk of three COVID-19 traits, and SARS-CoV-2 infection was associated with a higher risk of venous thromboembolism. Our study provides timely evidence for the genetic etiology between COVID-19 and venous thromboembolism (VTE). Our findings contribute to the understanding of COVID-19 and VTE etiology and provide insights into the prevention and comorbidity management of COVID-19.
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Affiliation(s)
- Xin Huang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Minhao Yao
- Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Peixin Tian
- Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Jason Y Y Wong
- Epidemiology and Community Health Branch, National Heart Lung and Blood Institute, Bethesda, MD, USA
| | - Zilin Li
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Zhonghua Liu
- Department of Biostatistics, Columbia University, New York, NY, USA.
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
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de Klerk JA, Beulens JWJ, Mei H, Bijkerk R, van Zonneveld AJ, Koivula RW, Elders PJM, 't Hart LM, Slieker RC. Altered blood gene expression in the obesity-related type 2 diabetes cluster may be causally involved in lipid metabolism: a Mendelian randomisation study. Diabetologia 2023; 66:1057-1070. [PMID: 36826505 PMCID: PMC10163084 DOI: 10.1007/s00125-023-05886-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 01/17/2023] [Indexed: 02/25/2023]
Abstract
AIMS/HYPOTHESIS The aim of this study was to identify differentially expressed long non-coding RNAs (lncRNAs) and mRNAs in whole blood of people with type 2 diabetes across five different clusters: severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), mild diabetes (MD) and mild diabetes with high HDL-cholesterol (MDH). This was to increase our understanding of different molecular mechanisms underlying the five putative clusters of type 2 diabetes. METHODS Participants in the Hoorn Diabetes Care System (DCS) cohort were clustered based on age, BMI, HbA1c, C-peptide and HDL-cholesterol. Whole blood RNA-seq was used to identify differentially expressed lncRNAs and mRNAs in a cluster compared with all others. Differentially expressed genes were validated in the Innovative Medicines Initiative DIabetes REsearCh on patient straTification (IMI DIRECT) study. Expression quantitative trait loci (eQTLs) for differentially expressed RNAs were obtained from a publicly available dataset. To estimate the causal effects of RNAs on traits, a two-sample Mendelian randomisation analysis was performed using public genome-wide association study (GWAS) data. RESULTS Eleven lncRNAs and 175 mRNAs were differentially expressed in the MOD cluster, the lncRNA AL354696.2 was upregulated in the SIDD cluster and GPR15 mRNA was downregulated in the MDH cluster. mRNAs and lncRNAs that were differentially expressed in the MOD cluster were correlated among each other. Six lncRNAs and 120 mRNAs validated in the IMI DIRECT study. Using two-sample Mendelian randomisation, we found 52 mRNAs to have a causal effect on anthropometric traits (n=23) and lipid metabolism traits (n=10). GPR146 showed a causal effect on plasma HDL-cholesterol levels (p = 2×10-15), without evidence for reverse causality. CONCLUSIONS/INTERPRETATION Multiple lncRNAs and mRNAs were found to be differentially expressed among clusters and particularly in the MOD cluster. mRNAs in the MOD cluster showed a possible causal effect on anthropometric traits, lipid metabolism traits and blood cell fractions. Together, our results show that individuals in the MOD cluster show aberrant RNA expression of genes that have a suggested causal role on multiple diabetes-relevant traits.
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Affiliation(s)
- Juliette A de Klerk
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands
| | - Joline W J Beulens
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Hailiang Mei
- Sequencing Analysis Support Core, Leiden University Medical Center, Leiden, the Netherlands
| | - Roel Bijkerk
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands
| | - Anton Jan van Zonneveld
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands
| | - Robert W Koivula
- Department of Clinical Sciences, Lund University, Genetic and Molecular Epidemiology, CRC, Skåne University Hospital Malmö, Malmö, Sweden
| | - Petra J M Elders
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - Leen M 't Hart
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Roderick C Slieker
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
- Amsterdam Public Health Institute, Amsterdam UMC, Amsterdam, the Netherlands.
- Department of Epidemiology and Data Science, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands.
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Yao M, Huang X, Guo Y, Zhao JV, Liu Z. Disentangling the common genetic architecture and causality of rheumatoid arthritis and systemic lupus erythematosus with COVID-19 outcomes: Genome-wide cross trait analysis and bidirectional Mendelian randomization study. J Med Virol 2023; 95:e28570. [PMID: 36762574 DOI: 10.1002/jmv.28570] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/31/2023] [Accepted: 02/07/2023] [Indexed: 02/11/2023]
Abstract
Coronavirus Disease (COVID-19) may cause a dysregulation of the immune system and has complex relationships with multiple autoimmune diseases, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). However, little is known about their common genetic architecture. Using the latest data from COVID-19 host genetics consortium and consortia on RA and SLE, we conducted a genome-wide cross-trait analysis to examine the shared genetic etiology between COVID-19 and RA/SLE and evaluated their causal associations using bidirectional Mendelian randomization (MR). The cross-trait meta-analysis identified 23, 28, and 10 shared genetic loci for severe COVID-19, COVID-19 hospitalization, and SARS-CoV-2 infection with RA, and 14, 17, and 7 shared loci with SLE, respectively. Co-localization analysis identified five causal variants in TYK2, IKZF3, PSORS1C1, and COG6 for COVID-19 with RA, and four in CRHR1, FUT2, and NXPE3 for COVID-19 with SLE, involved in immune function, angiogenesis and coagulation. Bidirectional MR analysis suggested RA is associated with a higher risk of COVID-19 hospitalization, and COVID-19 is not related to RA or SLE. Our novel findings improved the understanding of the genetic etiology shared by COVID-19, RA and SLE, and suggested an increased risk of COVID-19 hospitalization in people with higher genetic liability to RA.
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Affiliation(s)
- Minhao Yao
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Hong Kong, China
| | - Xin Huang
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong, China
| | - Yunshan Guo
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Hong Kong, China
| | - Jie V Zhao
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong, China
| | - Zhonghua Liu
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York, USA
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A Multi-Trait Association Analysis of Brain Disorders and Platelet Traits Identifies Novel Susceptibility Loci for Major Depression, Alzheimer's and Parkinson's Disease. Cells 2023; 12:cells12020245. [PMID: 36672180 PMCID: PMC9856280 DOI: 10.3390/cells12020245] [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: 11/24/2022] [Revised: 12/24/2022] [Accepted: 12/31/2022] [Indexed: 01/10/2023] Open
Abstract
Among candidate neurodegenerative/neuropsychiatric risk-predictive biomarkers, platelet count, mean platelet volume and platelet distribution width have been associated with the risk of major depressive disorder (MDD), Alzheimer's disease (AD) and Parkinson's disease (PD) through epidemiological and genomic studies, suggesting partial co-heritability. We exploited these relationships for a multi-trait association analysis, using publicly available summary statistics of genome-wide association studies (GWASs) of all traits reported above. Gene-based enrichment tests were carried out, as well as a network analysis of significantly enriched genes. We analyzed 4,540,326 single nucleotide polymorphisms shared among the analyzed GWASs, observing 149 genome-wide significant multi-trait LD-independent associations (p < 5 × 10-8) for AD, 70 for PD and 139 for MDD. Among these, 27 novel associations were detected for AD, 34 for PD and 40 for MDD. Out of 18,781 genes with annotated variants within ±10 kb, 62 genes were enriched for associations with AD, 70 with PD and 125 with MDD (p < 2.7 × 10-6). Of these, seven genes were novel susceptibility loci for AD (EPPK1, TTLL1, PACSIN2, TPM4, PIF1, ZNF689, AZGP1P1), two for PD (SLC26A1, EFNA3) and two for MDD (HSPH1, TRMT61A). The resulting network showed a significant excess of interactions (enrichment p = 1.0 × 10-16). The novel genes that were identified are involved in the organization of cytoskeletal architecture (EPPK1, TTLL1, PACSIN2, TPM4), telomere shortening (PIF1), the regulation of cellular aging (ZNF689, AZGP1P1) and neurodevelopment (EFNA3), thus, providing novel insights into the shared underlying biology of brain disorders and platelet parameters.
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10
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Kulminski AM, Feng F, Loiko E, Nazarian A, Loika Y, Culminskaya I. Prevailing Antagonistic Risks in Pleiotropic Associations with Alzheimer's Disease and Diabetes. J Alzheimers Dis 2023; 94:1121-1132. [PMID: 37355909 PMCID: PMC10666173 DOI: 10.3233/jad-230397] [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] [Indexed: 06/26/2023]
Abstract
BACKGROUND The lack of efficient preventive interventions against Alzheimer's disease (AD) calls for identifying efficient modifiable risk factors for AD. As diabetes shares many pathological processes with AD, including accumulation of amyloid plaques and neurofibrillary tangles, insulin resistance, and impaired glucose metabolism, diabetes is thought to be a potentially modifiable risk factor for AD. Mounting evidence suggests that links between AD and diabetes may be more complex than previously believed. OBJECTIVE To examine the pleiotropic architecture of AD and diabetes mellitus (DM). METHODS Univariate and pleiotropic analyses were performed following the discovery-replication strategy using individual-level data from 10 large-scale studies. RESULTS We report a potentially novel pleiotropic NOTCH2 gene, with a minor allele of rs5025718 associated with increased risks of both AD and DM. We confirm previously identified antagonistic associations of the same variants with the risks of AD and DM in the HLA and APOE gene clusters. We show multiple antagonistic associations of the same variants with AD and DM in the HLA cluster, which were not explained by the lead SNP in this cluster. Although the ɛ2 and ɛ4 alleles played a major role in the antagonistic associations with AD and DM in the APOE cluster, we identified non-overlapping SNPs in this cluster, which were adversely and beneficially associated with AD and DM independently of the ɛ2 and ɛ4 alleles. CONCLUSION This study emphasizes differences and similarities in the heterogeneous genetic architectures of AD and DM, which may differentiate the pathogenic mechanisms of these diseases.
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Affiliation(s)
- Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Fan Feng
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Elena Loiko
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Alireza Nazarian
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, 27705, USA
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11
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Pasqualetti G, Thayanandan T, Edison P. Influence of genetic and cardiometabolic risk factors in Alzheimer's disease. Ageing Res Rev 2022; 81:101723. [PMID: 36038112 DOI: 10.1016/j.arr.2022.101723] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 08/18/2022] [Accepted: 08/21/2022] [Indexed: 01/31/2023]
Abstract
Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder. Cardiometabolic and genetic risk factors play an important role in the trajectory of AD. Cardiometabolic risk factors including diabetes, mid-life obesity, mid-life hypertension and elevated cholesterol have been linked with cognitive decline in AD subjects. These potential risk factors associated with cerebral metabolic changes which fuel AD pathogenesis have been suggested to be the reason for the disappointing clinical trial results. In appreciation of the risks involved, using search engines such as PubMed, Scopus, MEDLINE and Google Scholar, a relevant literature search on cardiometabolic and genetic risk factors in AD was conducted. We discuss the role of genetic as well as established cardiovascular risk factors in the neuropathology of AD. Moreover, we show new evidence of genetic interaction between several genes potentially involved in different pathways related to both neurodegenerative process and cardiovascular damage.
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Affiliation(s)
| | - Tony Thayanandan
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, UK
| | - Paul Edison
- Department of Brain Sciences, Faculty of Medicine, Imperial College London, UK; School of Medicine, Cardiff University, UK.
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12
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Ryan DK, Karhunen V, Su B, Traylor M, Richardson TG, Burgess S, Tzoulaki I, Gill D. Genetic Evidence for Protective Effects of Angiotensin-Converting Enzyme Against Alzheimer Disease But Not Other Neurodegenerative Diseases in European Populations. Neurol Genet 2022; 8:e200014. [PMID: 36046424 DOI: 10.17863/cam.85694] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 06/17/2022] [Indexed: 05/27/2023]
Abstract
BACKGROUND AND OBJECTIVES Angiotensin-converting enzyme (ACE) inhibitors are a commonly prescribed class of medication used to treat heart failure, hypertension, and chronic kidney disease. However, previous observational studies have shown conflicting directions of associations between ACE inhibitors and risk of Alzheimer disease. Genetic evidence has supported a protective effect of cerebral ACE against Alzheimer disease (AD). However, it is unclear whether this effect is mediated through blood pressure and extends to other neurodegenerative diseases. METHODS We performed genetic colocalization investigating an effect of cortical ACE expression on AD risk in people of European ancestry. We further investigated whether any effect of ACE expression on AD risk is mediated through changes in blood pressure and whether effects extend to Parkinson disease, small-vessel disease, or cognitive function in a Mendelian randomization paradigm. RESULTS There was genetic evidence supporting a protective effect of cortical ACE expression on AD risk in people of European ancestry. Although higher cortical ACE expression was associated with higher blood pressure, there was no strong evidence to support that its association with AD was mediated through blood pressure nor that ACE expression affected risk of other neurodegenerative traits. DISCUSSION Genetic evidence supports protective effects of cerebral ACE expression on AD, but not other neurodegenerative outcomes in people of European ancestry. Further work is required to investigate whether therapeutic inhibition of ACE increases risk of Alzheimer disease.
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Affiliation(s)
- David K Ryan
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Ville Karhunen
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Bowen Su
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Matthew Traylor
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Tom G Richardson
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Stephen Burgess
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Ioanna Tzoulaki
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
| | - Dipender Gill
- Clinical Pharmacology Group (D.K.R., D.G.), Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust; Clinical Pharmacology and Therapeutics Section (D.K.R., D.G.), Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London; Centre for Clinical Pharmacology and Therapeutics (D.K.R.), University College London; Department of Epidemiology and Biostatistics (V.K., B.S., I.T., D.G.), School of Public Health, Imperial College London, United Kingdom; Research Unit of Mathematical Sciences (V.K.), University of Oulu; Center for Life Course Health Research (V.K.), University of Oulu, Finland; Clinical Pharmacology (M.T.), William Harvey Research Institute, Queen Mary University of London; The Barts Heart Centre and NIHR Barts Biomedical Research Centre-Barts Health NHS Trust (M.T.), The William Harvey Research Institute, Queen Mary University London; Novo Nordisk Research Centre Oxford (M.T., T.G.R., D.G.), Old Road Campus, Oxford; Medical Research Council Integrative Epidemiology Unit (T.G.R.), University of Bristol; Medical Research Council Biostatistics Unit (S.B., D.G.), Cambridge Institute of Public Health; Cardiovascular Epidemiology Unit (S.B.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom; and Department of Hygiene and Epidemiology (I.T.), University of Ioannina, Greece
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13
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Ryan DK, Karhunen V, Su B, Traylor M, Richardson TG, Burgess S, Tzoulaki I, Gill D. Genetic Evidence for Protective Effects of Angiotensin-Converting Enzyme Against Alzheimer Disease But Not Other Neurodegenerative Diseases in European Populations. Neurol Genet 2022; 8:e200014. [PMID: 36046424 PMCID: PMC9425221 DOI: 10.1212/nxg.0000000000200014] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 06/17/2022] [Indexed: 11/15/2022]
Abstract
Background and Objectives Angiotensin-converting enzyme (ACE) inhibitors are a commonly prescribed class of medication used to treat heart failure, hypertension, and chronic kidney disease. However, previous observational studies have shown conflicting directions of associations between ACE inhibitors and risk of Alzheimer disease. Genetic evidence has supported a protective effect of cerebral ACE against Alzheimer disease (AD). However, it is unclear whether this effect is mediated through blood pressure and extends to other neurodegenerative diseases. Methods We performed genetic colocalization investigating an effect of cortical ACE expression on AD risk in people of European ancestry. We further investigated whether any effect of ACE expression on AD risk is mediated through changes in blood pressure and whether effects extend to Parkinson disease, small-vessel disease, or cognitive function in a Mendelian randomization paradigm. Results There was genetic evidence supporting a protective effect of cortical ACE expression on AD risk in people of European ancestry. Although higher cortical ACE expression was associated with higher blood pressure, there was no strong evidence to support that its association with AD was mediated through blood pressure nor that ACE expression affected risk of other neurodegenerative traits. Discussion Genetic evidence supports protective effects of cerebral ACE expression on AD, but not other neurodegenerative outcomes in people of European ancestry. Further work is required to investigate whether therapeutic inhibition of ACE increases risk of Alzheimer disease.
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14
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Ruffini N, Klingenberg S, Heese R, Schweiger S, Gerber S. The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach. Front Aging Neurosci 2022; 14:866886. [PMID: 35832065 PMCID: PMC9271745 DOI: 10.3389/fnagi.2022.866886] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 05/13/2022] [Indexed: 12/12/2022] Open
Abstract
The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.
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Affiliation(s)
- Nicolas Ruffini
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Leibniz Institute for Resilience Research, Leibniz Association, Mainz, Germany
| | - Susanne Klingenberg
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Raoul Heese
- Fraunhofer Institute for Industrial Mathematics (ITWM), Kaiserslautern, Germany
| | - Susann Schweiger
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Susanne Gerber
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University, Mainz, Germany
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15
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Tesi N, Hulsman M, van der Lee SJ, Jansen IE, Stringa N, van Schoor NM, Scheltens P, van der Flier WM, Huisman M, Reinders MJT, Holstege H. The Effect of Alzheimer's Disease-Associated Genetic Variants on Longevity. Front Genet 2022; 12:748781. [PMID: 34992629 PMCID: PMC8724252 DOI: 10.3389/fgene.2021.748781] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 11/24/2021] [Indexed: 12/22/2022] Open
Abstract
Human longevity is influenced by the genetic risk of age-related diseases. As Alzheimer’s disease (AD) represents a common condition at old age, an interplay between genetic factors affecting AD and longevity is expected. We explored this interplay by studying the prevalence of AD-associated single-nucleotide-polymorphisms (SNPs) in cognitively healthy centenarians, and replicated findings in a parental-longevity GWAS. We found that 28/38 SNPs that increased AD-risk also associated with lower odds of longevity. For each SNP, we express the imbalance between AD- and longevity-risk as an effect-size distribution. Based on these distributions, we grouped the SNPs in three groups: 17 SNPs increased AD-risk more than they decreased longevity-risk, and were enriched for β-amyloid metabolism and immune signaling; 11 variants reported a larger longevity-effect compared to their AD-effect, were enriched for endocytosis/immune-signaling, and were previously associated with other age-related diseases. Unexpectedly, 10 variants associated with an increased risk of AD and higher odds of longevity. Altogether, we show that different AD-associated SNPs have different effects on longevity, including SNPs that may confer general neuro-protective functions against AD and other age-related diseases.
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Affiliation(s)
- Niccolò Tesi
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Alzheimer Centre, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Marc Hulsman
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Alzheimer Centre, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Sven J van der Lee
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Alzheimer Centre, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Iris E Jansen
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU, Amsterdam, Netherlands
| | - Najada Stringa
- Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Natasja M van Schoor
- Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Philip Scheltens
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Martijn Huisman
- Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
| | - Henne Holstege
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Alzheimer Centre, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Delft Bioinformatics Lab, Delft University of Technology, Delft, Netherlands
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16
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Kondratyev NV, Alfimova MV, Golov AK, Golimbet VE. Bench Research Informed by GWAS Results. Cells 2021; 10:3184. [PMID: 34831407 PMCID: PMC8623533 DOI: 10.3390/cells10113184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 12/15/2022] Open
Abstract
Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.
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Affiliation(s)
| | | | - Arkadiy K. Golov
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
- Institute of Gene Biology, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vera E. Golimbet
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
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