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Shao F, Yao Y, Weng D, Wang R, Liu R, Zhang Y, Li E, Wang M, Tang Y, Ding Y, Xie Y. Causal association of plasma circulating metabolites with nephritis: a Mendelian randomization study. Front Nutr 2024; 11:1364841. [PMID: 38765814 PMCID: PMC11099270 DOI: 10.3389/fnut.2024.1364841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 04/16/2024] [Indexed: 05/22/2024] Open
Abstract
Background Nephritis is a pivotal catalyst in chronic kidney disease (CKD) progression. Although epidemiological studies have explored the impact of plasma circulating metabolites and drugs on nephritis, few have harnessed genetic methodologies to establish causal relationships. Methods Through Mendelian randomization (MR) in two substantial cohorts, spanning large sample sizes, we evaluated over 100 plasma circulating metabolites and 263 drugs to discern their causal effects on nephritis risk. The primary analytical tool was the inverse variance weighted (IVW) analysis. Our bioinformatic scrutiny of GSE115857 (IgA nephropathy, 86 samples) and GSE72326 (lupus nephritis, 238 samples) unveiled anomalies in lipid metabolism and immunological characteristics in nephritis. Thorough sensitivity analyses (MR-Egger, MR-PRESSO, leave-one-out analysis) were undertaken to verify the instrumental variables' (IVs) assumptions. Results Unique lipoprotein-related molecules established causal links with diverse nephritis subtypes. Notably, docosahexaenoic acid (DHA) emerged as a protective factor for acute tubulointerstitial nephritis (ATIN) (OR1 = 0.84, [95% CI 0.78-0.90], p1 = 0.013; OR2 = 0.89, [95% CI 0.82-0.97], p2 = 0.007). Conversely, multivitamin supplementation minus minerals notably increased the risk of ATIN (OR = 31.25, [95% CI 9.23-105.85], p = 0.004). Reduced α-linolenic acid (ALA) levels due to lipid-lowering drugs were linked to both ATIN (OR = 4.88, [95% CI 3.52-6.77], p < 0.001) and tubulointerstitial nephritis (TIN) (OR = 7.52, [95% CI 2.78-20.30], p = 0.042). While the non-renal drug indivina showed promise for TIN treatment, the use of digoxin, hydroxocobalamin, and liothyronine elevated the risk of chronic tubulointerstitial nephritis (CTIN). Transcriptome analysis affirmed that anomalous lipid metabolism and immune infiltration are characteristic of IgA nephropathy and lupus nephritis. The robustness of these causal links was reinforced by sensitivity analyses and leave-one-out tests, indicating no signs of pleiotropy. Conclusion Dyslipidemia significantly contributes to nephritis development. Strategies aimed at reducing plasma low-density lipoprotein levels or ALA supplementation may enhance the efficacy of existing lipid-lowering drug regimens for nephritis treatment. Renal functional status should also be judiciously considered with regard to the use of nonrenal medications.
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Affiliation(s)
- Fengling Shao
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Yingling Yao
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Dunchu Weng
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Runzhi Wang
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
| | - Ruiling Liu
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Yongjia Zhang
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Erhan Li
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Mengdi Wang
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Yuewu Tang
- Department of Nephrology, Chongqing Three Gorges Central Hospital, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Yubin Ding
- Department of Obstetrics and Gynecology, Women and Children’s Hospital of Chongqing Medical University, Chongqing, China
- Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Yajun Xie
- The Ministry of Education, Key Laboratory of Laboratory Medical Diagnostics, The College of Laboratory Medicine, Chongqing Medical University, Chongqing, China
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Timsina J, Ali M, Do A, Wang L, Western D, Sung YJ, Cruchaga C. Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification. Neurobiol Dis 2024; 190:106373. [PMID: 38072165 DOI: 10.1016/j.nbd.2023.106373] [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: 05/25/2023] [Revised: 10/06/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023] Open
Abstract
In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA.
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Timsina J, Ali M, Do A, Wang L, Sung YJ, Cruchaga C. Harmonization of CSF and imaging biomarkers for Alzheimer's disease biomarkers: need and practical applications for genetics studies and preclinical classification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.24.542118. [PMID: 37292823 PMCID: PMC10245826 DOI: 10.1101/2023.05.24.542118] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
INTRODUCTION In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers which leads to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. METHODS We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS result using this method with currently accepted methods. We also used a generalized mixture modelling to calculate the threshold for biomarker-positivity. RESULTS Z-scores method performed as well as meta-analysis and did not lead to any spurious results. Cutoffs calculated with this approach were found to be very similar to those reported previously. DISCUSSION This approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
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Caron B, Patin E, Rotival M, Charbit B, Albert ML, Quintana-Murci L, Duffy D, Rausell A. Integrative genetic and immune cell analysis of plasma proteins in healthy donors identifies novel associations involving primary immune deficiency genes. Genome Med 2022; 14:28. [PMID: 35264221 PMCID: PMC8905727 DOI: 10.1186/s13073-022-01032-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 02/15/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Blood plasma proteins play an important role in immune defense against pathogens, including cytokine signaling, the complement system, and the acute-phase response. Recent large-scale studies have reported genetic (i.e., protein quantitative trait loci, pQTLs) and non-genetic factors, such as age and sex, as major determinants to inter-individual variability in immune response variation. However, the contribution of blood-cell composition to plasma protein heterogeneity has not been fully characterized and may act as a mediating factor in association studies. METHODS Here, we evaluated plasma protein levels from 400 unrelated healthy individuals of western European ancestry, who were stratified by sex and two decades of life (20-29 and 60-69 years), from the Milieu Intérieur cohort. We quantified 229 proteins by Luminex in a clinically certified laboratory and their levels of variation were analyzed together with 5.2 million single-nucleotide polymorphisms. With respect to non-genetic variables, we included 254 lifestyle and biochemical factors, as well as counts of seven circulating immune cell populations measured by hemogram and standardized flow cytometry. RESULTS Collectively, we found 152 significant associations involving 49 proteins and 20 non-genetic variables. Consistent with previous studies, age and sex showed a global, pervasive impact on plasma protein heterogeneity, while body mass index and other health status variables were among the non-genetic factors with the highest number of associations. After controlling for these covariates, we identified 100 and 12 pQTLs acting in cis and trans, respectively, collectively associated with 87 plasma proteins and including 19 novel genetic associations. Genetic factors explained the largest fraction of the variability of plasma protein levels, as compared to non-genetic factors. In addition, blood-cell fractions, including leukocytes, lymphocytes, monocytes, neutrophils, eosinophils, basophils, and platelets, had a larger contribution to inter-individual variability than age and sex and appeared as confounders of specific genetic associations. Finally, we identified new genetic associations with plasma protein levels of five monogenic Mendelian disease genes including two primary immunodeficiency genes (Ficolin-3 and FAS). CONCLUSIONS Our study identified novel genetic and non-genetic factors associated to plasma protein levels which may inform health status and disease management.
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Affiliation(s)
- Barthelemy Caron
- Université de Paris, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, F-75006, Paris, France
| | - Etienne Patin
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR2000, CNRS, Université de Paris, F-75015, Paris, France
| | - Maxime Rotival
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR2000, CNRS, Université de Paris, F-75015, Paris, France
| | - Bruno Charbit
- Cytometry and Biomarkers UTechS, CRT, Institut Pasteur, Université de Paris, F-75015, Paris, France
| | | | - Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR2000, CNRS, Université de Paris, F-75015, Paris, France
- Human Genomics and Evolution, Collège de France, F-75005, Paris, France
| | - Darragh Duffy
- Cytometry and Biomarkers UTechS, CRT, Institut Pasteur, Université de Paris, F-75015, Paris, France.
- Translational Immunology Unit, Institut Pasteur, Université de Paris, F-75015, Paris, France.
| | - Antonio Rausell
- Université de Paris, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, F-75006, Paris, France.
- Service de Médecine Génomique des Maladies Rares, AP-HP, Necker Hospital for Sick Children, F-75015, Paris, France.
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5
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Yang C, Farias FHG, Ibanez L, Suhy A, Sadler B, Fernandez MV, Wang F, Bradley JL, Eiffert B, Bahena JA, Budde JP, Li Z, Dube U, Sung YJ, Mihindukulasuriya KA, Morris JC, Fagan AM, Perrin RJ, Benitez BA, Rhinn H, Harari O, Cruchaga C. Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders. Nat Neurosci 2021; 24:1302-1312. [PMID: 34239129 PMCID: PMC8521603 DOI: 10.1038/s41593-021-00886-6] [Citation(s) in RCA: 109] [Impact Index Per Article: 36.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 06/03/2021] [Indexed: 02/06/2023]
Abstract
Understanding the tissue-specific genetic controls of protein levels is essential to uncover mechanisms of post-transcriptional gene regulation. In this study, we generated a genomic atlas of protein levels in three tissues relevant to neurological disorders (brain, cerebrospinal fluid and plasma) by profiling thousands of proteins from participants with and without Alzheimer's disease. We identified 274, 127 and 32 protein quantitative trait loci (pQTLs) for cerebrospinal fluid, plasma and brain, respectively. cis-pQTLs were more likely to be tissue shared, but trans-pQTLs tended to be tissue specific. Between 48.0% and 76.6% of pQTLs did not co-localize with expression, splicing, DNA methylation or histone acetylation QTLs. Using Mendelian randomization, we nominated proteins implicated in neurological diseases, including Alzheimer's disease, Parkinson's disease and stroke. This first multi-tissue study will be instrumental to map signals from genome-wide association studies onto functional genes, to discover pathways and to identify drug targets for neurological diseases.
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Affiliation(s)
- Chengran Yang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Fabiana H G Farias
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Adam Suhy
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Brooke Sadler
- Pediatrics Hematology/Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Maria Victoria Fernandez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Fengxian Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Joseph L Bradley
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Brett Eiffert
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Jorge A Bahena
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - John P Budde
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Zeran Li
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Umber Dube
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Kathie A Mihindukulasuriya
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - John C Morris
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Richard J Perrin
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Bruno A Benitez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Herve Rhinn
- Department of Bioinformatics, Alector, Inc., South San Francisco, CA, USA
| | - Oscar Harari
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA.
- The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.
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Møller PL, Rohde PD, Winther S, Breining P, Nissen L, Nykjaer A, Bøttcher M, Nyegaard M, Kjolby M. Sortilin as a Biomarker for Cardiovascular Disease Revisited. Front Cardiovasc Med 2021; 8:652584. [PMID: 33937362 PMCID: PMC8085299 DOI: 10.3389/fcvm.2021.652584] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 02/22/2021] [Indexed: 11/13/2022] Open
Abstract
Genetic variants in the genomic region containing SORT1 (encoding the protein sortilin) are strongly associated with cholesterol levels and the risk of coronary artery disease (CAD). Circulating sortilin has therefore been proposed as a potential biomarker for cardiovascular disease. Multiple studies have reported association between plasma sortilin levels and cardiovascular outcomes. However, the findings are not consistent across studies, and most studies have small sample sizes. The aim of this study was to evaluate sortilin as a biomarker for CAD in a well-characterized cohort with symptoms suggestive of CAD. In total, we enrolled 1,173 patients with suspected stable CAD referred to coronary computed tomography angiography. Sortilin was measured in plasma using two different technologies for quantifying circulating sortilin: a custom-made enzyme-linked immunosorbent assay (ELISA) and OLINK Cardiovascular Panel II. We found a relative poor correlation between the two methods (correlation coefficient = 0.21). In addition, genotyping and whole-genome sequencing were performed on all patients. By whole-genome regression analysis of sortilin levels measured with ELISA and OLINK, two independent cis protein quantitative trait loci (pQTL) on chromosome 1p13.3 were identified, with one of them being a well-established risk locus for CAD. Incorporating rare genetic variants from whole-genome sequence data did not identify any additional pQTLs for plasma sortilin. None of the traditional CAD risk factors, such as sex, age, smoking, and statin use, were associated with plasma sortilin levels. Furthermore, there was no association between circulating sortilin levels and coronary artery calcium score (CACS) or disease severity. Sortilin did not improve discrimination of obstructive CAD, when added to a clinical pretest probability (PTP) model for CAD. Overall, our results indicate that studies using different methodologies for measuring circulating sortilin should be compared with caution. In conclusion, the well-known SORT1 risk locus for CAD is linked to lower sortilin levels in circulation, measured with ELISA; however, the effect sizes are too small for sortilin to be a useful biomarker for CAD in a clinical setting of low- to intermediate-risk chest-pain patients.
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Affiliation(s)
| | - Palle D. Rohde
- Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark
| | - Simon Winther
- Department of Cardiology, Gødstrup Hospital, NIDO, Herning, Denmark
| | - Peter Breining
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- PROMEMO and DANDRITE, Aarhus University, Aarhus, Denmark
| | - Louise Nissen
- Department of Cardiology, Gødstrup Hospital, NIDO, Herning, Denmark
| | - Anders Nykjaer
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- PROMEMO and DANDRITE, Aarhus University, Aarhus, Denmark
| | - Morten Bøttcher
- Department of Cardiology, Gødstrup Hospital, NIDO, Herning, Denmark
| | - Mette Nyegaard
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Mads Kjolby
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- PROMEMO and DANDRITE, Aarhus University, Aarhus, Denmark
- Department of Clinical Pharmacology, Aarhus University Hospital, Aarhus, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
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7
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Kim S, Kim K, Nho K, Myung W, Won HH. Shared Genetic Background Between Cerebrospinal Fluid Biomarkers and Risk for Alzheimer's Disease: A Two-Sample Mendelian Randomization Study. J Alzheimers Dis 2021; 80:1197-1207. [PMID: 33646147 DOI: 10.3233/jad-200671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Whether the epidemiological association of amyloid-β (Aβ) and tau pathology in late-onset Alzheimer's disease (LOAD) is causal remains unclear. OBJECTIVE We aimed to investigate the shared genetic background between the cerebrospinal fluid (CSF) biomarkers for Aβ and tau pathology and the risk of LOAD. METHODS We conducted a two-sample Mendelian randomization (MR) analysis. We used summary statistics of genome-wide association studies for CSF biomarkers (Aβ1-42 [Aβ], phosphorylated tau181 [p-tau], and total tau [t-tau]) in 3,146 individuals and for LOAD in 21,982 cases and 41,944 controls. We tested the association between changes in the genetically predicted CSF biomarkers and LOAD risk. RESULTS We found a decrease in LOAD risk per one-standard-deviation (SD) increase in the genetically predicted CSF Aβ (odds ratio [OR], 2.87×10-3 for AD; 95%confidence interval [CI], 1.54×10-4-0.05; p = 8.91×10-5). Conversely, we observed an increase in LOAD risk per one-SD increase in the genetically predicted CSF p-tau (OR, 19.46; 95%CI, 1.50-2.52×102; p = 0.02) and t-tau (OR, 33.80; 95%CI, 1.57-7.29×102; p = 0.02). However, only the association between p-tau and the risk for LOAD remained significant after the exclusion of the APOE variant (rs769449). CONCLUSION We found the causal association between CSF biomarkers and the risk for LOAD. Our results suggest that the etiology of LOAD involves multiple biological processes, including the pathways of Aβ and tau proteins. Further MR studies using large-scale data of multiple candidate biomarkers are needed to elucidate the pathophysiology of LOAD.
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Affiliation(s)
- Soyeon Kim
- Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea
| | - Kiwon Kim
- Department of Psychiatry, Veteran Health Service Medical Center, Seoul, South Korea
| | - Kwangsik Nho
- Department of Radiology & Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Hong-Hee Won
- Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea
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8
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Farias FHG, Benitez BA, Cruchaga C. Quantitative endophenotypes as an alternative approach to understanding genetic risk in neurodegenerative diseases. Neurobiol Dis 2021; 151:105247. [PMID: 33429041 DOI: 10.1016/j.nbd.2020.105247] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 12/24/2020] [Accepted: 12/30/2020] [Indexed: 01/02/2023] Open
Abstract
Endophenotypes, as measurable intermediate features of human diseases, reflect underlying molecular mechanisms. The use of quantitative endophenotypes in genetic studies has improved our understanding of pathophysiological changes associated with diseases. The main advantage of the quantitative endophenotypes approach to study human diseases over a classic case-control study design is the inferred biological context that can enable the development of effective disease-modifying treatments. Here, we summarize recent progress on biomarkers for neurodegenerative diseases, including cerebrospinal fluid and blood-based, neuroimaging, neuropathological, and clinical studies. This review focuses on how endophenotypic studies have successfully linked genetic modifiers to disease risk, disease onset, or progression rate and provided biological context to genes identified in genome-wide association studies. Finally, we review critical methodological considerations for implementing this approach and future directions.
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Affiliation(s)
- Fabiana H G Farias
- Department of Psychiatry, Washington University, St. Louis, MO 63110, United States of America; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, United States of America
| | - Bruno A Benitez
- Department of Psychiatry, Washington University, St. Louis, MO 63110, United States of America; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, United States of America
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63110, United States of America; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, United States of America; Hope Center for Neurologic Diseases, Washington University, St. Louis, MO 63110, United States of America; The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, 63110, United States of America; Department of Genetics, Washington University School of Medicine, St Louis, MO, 63110, United States of America.
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9
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Genetics meets proteomics: perspectives for large population-based studies. Nat Rev Genet 2020; 22:19-37. [PMID: 32860016 DOI: 10.1038/s41576-020-0268-2] [Citation(s) in RCA: 180] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2020] [Indexed: 12/22/2022]
Abstract
Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.
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10
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Hillary RF, Trejo-Banos D, Kousathanas A, McCartney DL, Harris SE, Stevenson AJ, Patxot M, Ojavee SE, Zhang Q, Liewald DC, Ritchie CW, Evans KL, Tucker-Drob EM, Wray NR, McRae AF, Visscher PM, Deary IJ, Robinson MR, Marioni RE. Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults. Genome Med 2020; 12:60. [PMID: 32641083 PMCID: PMC7346642 DOI: 10.1186/s13073-020-00754-1] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 06/10/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets. METHODS In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). RESULTS We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn's disease. CONCLUSIONS Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel Trejo-Banos
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Athanasios Kousathanas
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Sarah E Harris
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Marion Patxot
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Sven Erik Ojavee
- Department of Computational Biology, University of Lausanne, 1015, Lausanne, Switzerland
| | - Qian Zhang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - David C Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Elliot M Tucker-Drob
- Department of Psychology, The University of Texas at Austin, Austin, TX, 78712, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, 78712, USA
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Matthew R Robinson
- Institute of Science and Technology Austria, 3400, Klosterneuburg, Austria.
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK.
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11
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Li Z, Farias FHG, Dube U, Del-Aguila JL, Mihindukulasuriya KA, Fernandez MV, Ibanez L, Budde JP, Wang F, Lake AM, Deming Y, Perez J, Yang C, Bahena JA, Qin W, Bradley JL, Davenport R, Bergmann K, Morris JC, Perrin RJ, Benitez BA, Dougherty JD, Harari O, Cruchaga C. The TMEM106B FTLD-protective variant, rs1990621, is also associated with increased neuronal proportion. Acta Neuropathol 2020; 139:45-61. [PMID: 31456032 PMCID: PMC6942643 DOI: 10.1007/s00401-019-02066-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 08/03/2019] [Accepted: 08/19/2019] [Indexed: 12/14/2022]
Abstract
Apart from amyloid β deposition and tau neurofibrillary tangles, Alzheimer's disease (AD) is a neurodegenerative disorder characterized by neuronal loss and astrocytosis in the cerebral cortex. The goal of this study is to investigate genetic factors associated with the neuronal proportion in health and disease. To identify cell-autonomous genetic variants associated with neuronal proportion in cortical tissues, we inferred cellular population structure from bulk RNA-Seq derived from 1536 individuals. We identified the variant rs1990621 located in the TMEM106B gene region as significantly associated with neuronal proportion (p value = 6.40 × 10-07) and replicated this finding in an independent dataset (p value = 7.41 × 10-04) surpassing the genome-wide threshold in the meta-analysis (p value = 9.42 × 10-09). This variant is in high LD with the TMEM106B non-synonymous variant p.T185S (rs3173615; r2 = 0.98) which was previously identified as a protective variant for frontotemporal lobar degeneration (FTLD). We stratified the samples by disease status, and discovered that this variant modulates neuronal proportion not only in AD cases, but also several neurodegenerative diseases and in elderly cognitively healthy controls. Furthermore, we did not find a significant association in younger controls or schizophrenia patients, suggesting that this variant might increase neuronal survival or confer resilience to the neurodegenerative process. The single variant and gene-based analyses also identified an overall genetic association between neuronal proportion, AD and FTLD risk. These results suggest that common pathways are implicated in these neurodegenerative diseases, that implicate neuronal survival. In summary, we identified a protective variant in the TMEM106B gene that may have a neuronal protection effect against general aging, independent of disease status, which could help elucidate the relationship between aging and neuronal survival in the presence or absence of neurodegenerative disorders. Our findings suggest that TMEM106B could be a potential target for neuronal protection therapies to ameliorate cognitive and functional deficits.
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Affiliation(s)
- Zeran Li
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Fabiana H G Farias
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Umber Dube
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Jorge L Del-Aguila
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Kathie A Mihindukulasuriya
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Maria Victoria Fernandez
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura Ibanez
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John P Budde
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Fengxian Wang
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Allison M Lake
- Vanderbilt University Medical Scientist Training Program, Nashville, TN, USA
| | - Yuetiva Deming
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - James Perez
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengran Yang
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Jorge A Bahena
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Wei Qin
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Joseph L Bradley
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Richard Davenport
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Kristy Bergmann
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Richard J Perrin
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Bruno A Benitez
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Joseph D Dougherty
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
| | - Oscar Harari
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, BJC Institute of Heath, Washington University School of Medicine, 425 S. Euclid Ave., Box 8134, St. Louis, MO, 63110, USA.
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
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12
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Deming Y, Filipello F, Cignarella F, Cantoni C, Hsu S, Mikesell R, Li Z, Del-Aguila JL, Dube U, Farias FG, Bradley J, Budde J, Ibanez L, Fernandez MV, Blennow K, Zetterberg H, Heslegrave A, Johansson PM, Svensson J, Nellgård B, Lleo A, Alcolea D, Clarimon J, Rami L, Molinuevo JL, Suárez-Calvet M, Morenas-Rodríguez E, Kleinberger G, Ewers M, Harari O, Haass C, Brett TJ, Benitez BA, Karch CM, Piccio L, Cruchaga C. The MS4A gene cluster is a key modulator of soluble TREM2 and Alzheimer's disease risk. Sci Transl Med 2019; 11:eaau2291. [PMID: 31413141 PMCID: PMC6697053 DOI: 10.1126/scitranslmed.aau2291] [Citation(s) in RCA: 149] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 04/05/2019] [Indexed: 12/13/2022]
Abstract
Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) has been associated with Alzheimer's disease (AD). TREM2 plays a critical role in microglial activation, survival, and phagocytosis; however, the pathophysiological role of sTREM2 in AD is not well understood. Understanding the role of sTREM2 in AD may reveal new pathological mechanisms and lead to the identification of therapeutic targets. We performed a genome-wide association study (GWAS) to identify genetic modifiers of CSF sTREM2 obtained from the Alzheimer's Disease Neuroimaging Initiative. Common variants in the membrane-spanning 4-domains subfamily A (MS4A) gene region were associated with CSF sTREM2 concentrations (rs1582763; P = 1.15 × 10-15); this was replicated in independent datasets. The variants associated with increased CSF sTREM2 concentrations were associated with reduced AD risk and delayed age at onset of disease. The single-nucleotide polymorphism rs1582763 modified expression of the MS4A4A and MS4A6A genes in multiple tissues, suggesting that one or both of these genes are important for modulating sTREM2 production. Using human macrophages as a proxy for microglia, we found that MS4A4A and TREM2 colocalized on lipid rafts at the plasma membrane, that sTREM2 increased with MS4A4A overexpression, and that silencing of MS4A4A reduced sTREM2 production. These genetic, molecular, and cellular findings suggest that MS4A4A modulates sTREM2. These findings also provide a mechanistic explanation for the original GWAS signal in the MS4A locus for AD risk and indicate that TREM2 may be involved in AD pathogenesis not only in TREM2 risk-variant carriers but also in those with sporadic disease.
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Affiliation(s)
- Yuetiva Deming
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
| | - Fabia Filipello
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Francesca Cignarella
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Claudia Cantoni
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Simon Hsu
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Robert Mikesell
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Zeran Li
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jorge L Del-Aguila
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Umber Dube
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Fabiana Geraldo Farias
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joseph Bradley
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Department of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Department of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - Amanda Heslegrave
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Per M Johansson
- Department of Clinical Sciences Helsingborg, Lund University, Lund, Sweden
| | - Johan Svensson
- Department of Internal Medicine, Institute of Medicine, Sahlgrenska Academy at the University of Gothenburg, Göteborg, Sweden
| | - Bengt Nellgård
- Department of Anesthesiology, Sahlgrenska University Hospital, Department of Internal Medicine, Institute of Medicine, Sahlgrenska Academy at the University of Gothenburg, Göteborg, Sweden
| | - Alberto Lleo
- Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center for Networker Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center for Networker Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jordi Clarimon
- Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center for Networker Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Lorena Rami
- IDIBAPS, Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, ICN Hospital Clinic, Barcelona, Spain
| | - José Luis Molinuevo
- IDIBAPS, Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, ICN Hospital Clinic, Barcelona, Spain
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Biomedical Center (BMC), Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Estrella Morenas-Rodríguez
- Biomedical Center (BMC), Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Gernot Kleinberger
- Biomedical Center (BMC), Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- ISAR Bioscience GmbH, 2152 Planegg, Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, LMU, Munich, Germany
| | - Oscar Harari
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Christian Haass
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Chair of Metabolic Biochemistry, Biomedical Center (BMC), Faculty of Medicine, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Thomas J Brett
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Bruno A Benitez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Celeste M Karch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Laura Piccio
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- Brain and Mind Centre, University of Sydney, Sydney, NSW 2050, Australia
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO 63110, USA
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13
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Timasheva YR, Nasibullin TR, Tuktarova IA, Erdman VV, Mustafina OE. CXCL13 polymorphism is associated with essential hypertension in Tatars from Russia. Mol Biol Rep 2018; 45:1557-1564. [PMID: 30019153 DOI: 10.1007/s11033-018-4257-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 07/12/2018] [Indexed: 01/10/2023]
Abstract
Essential arterial hypertension is a disease with distinct yet unexplored inflammatory component. Our aim was to assess the role of chemokine genes and their interaction in its development. Genotyping of polymorphic markers in six chemokine genes (CXCL13, CCL8, CCL16, CCL17, CCL18, and CCL23) was performed in the group of 522 men of Tatar ethnic origin from the Republic of Bashkortostan, Russia (213 patients with essential hypertension and 309 healthy individuals without history of cardiovascular disease). We found a strong association of CXCL13 rs355689*C allele with essential hypertension under additive (OR 0.56, PFDR = 0.008) and dominant (OR 0.41, PFDR 4.38 × 10- 4) genetic model. The analysis of gene-gene interactions revealed 12 allele/genotype combinations that remained significantly associated with essential hypertension after correction for multiple testing was applied, and each of these combinations included CXCL13 rs355689 polymorphism. Our results indicate that CXCL13 rs355689 polymorphism is strongly associated with essential hypertension in the ethnic group of Tatars, alone and in combination with polymorphic markers in other chemokine genes.
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Affiliation(s)
- Yanina R Timasheva
- Laboratory of Physiological Genetics, Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, October Avenue 71, Ufa, Russian Federation, 450054. .,Department of Medical Genetics and Fundamental Medicine, Bashkir State Medical University, Ufa, Russian Federation.
| | - Timur R Nasibullin
- Laboratory of Physiological Genetics, Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, October Avenue 71, Ufa, Russian Federation, 450054
| | - Ilsiyar A Tuktarova
- Laboratory of Physiological Genetics, Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, October Avenue 71, Ufa, Russian Federation, 450054
| | - Vera V Erdman
- Laboratory of Physiological Genetics, Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, October Avenue 71, Ufa, Russian Federation, 450054
| | - Olga E Mustafina
- Laboratory of Physiological Genetics, Institute of Biochemistry and Genetics of Ufa Federal Research Centre of Russian Academy of Sciences, October Avenue 71, Ufa, Russian Federation, 450054.,Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russian Federation
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14
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Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, Tan VY, Yarmolinsky J, Shihab HA, Timpson NJ, Evans DM, Relton C, Martin RM, Davey Smith G, Gaunt TR, Haycock PC. The MR-Base platform supports systematic causal inference across the human phenome. eLife 2018. [PMID: 29846171 DOI: 10.7554/elife.34408s] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023] Open
Abstract
Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (<ext-link ext-link-type="uri" xlink:href="http://www.mrbase.org">http://www.mrbase.org</ext-link>): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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Affiliation(s)
- Gibran Hemani
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jie Zheng
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Benjamin Elsworth
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kaitlin H Wade
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Valeriia Haberland
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Denis Baird
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Charles Laurin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jack Bowden
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Ryan Langdon
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Vanessa Y Tan
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - James Yarmolinsky
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Hashem A Shihab
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J Timpson
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - David M Evans
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | - Caroline Relton
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Richard M Martin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Tom R Gaunt
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Philip C Haycock
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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15
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Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, Tan VY, Yarmolinsky J, Shihab HA, Timpson NJ, Evans DM, Relton C, Martin RM, Davey Smith G, Gaunt TR, Haycock PC. The MR-Base platform supports systematic causal inference across the human phenome. eLife 2018; 7:e34408. [PMID: 29846171 PMCID: PMC5976434 DOI: 10.7554/elife.34408] [Citation(s) in RCA: 3588] [Impact Index Per Article: 598.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 03/28/2018] [Indexed: 12/21/2022] Open
Abstract
Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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Affiliation(s)
- Gibran Hemani
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Jie Zheng
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Benjamin Elsworth
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Kaitlin H Wade
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Valeriia Haberland
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Denis Baird
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Charles Laurin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Stephen Burgess
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeUnited Kingdom
| | - Jack Bowden
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Ryan Langdon
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Vanessa Y Tan
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - James Yarmolinsky
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Hashem A Shihab
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Nicholas J Timpson
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - David M Evans
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
- University of Queensland Diamantina InstituteTranslational Research InstituteBrisbaneAustralia
| | - Caroline Relton
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Richard M Martin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Tom R Gaunt
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Philip C Haycock
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
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16
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Organic cation transporter 1 (OCT1) modulates multiple cardiometabolic traits through effects on hepatic thiamine content. PLoS Biol 2018; 16:e2002907. [PMID: 29659562 PMCID: PMC5919692 DOI: 10.1371/journal.pbio.2002907] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Revised: 04/26/2018] [Accepted: 03/20/2018] [Indexed: 01/07/2023] Open
Abstract
A constellation of metabolic disorders, including obesity, dysregulated lipids, and elevations in blood glucose levels, has been associated with cardiovascular disease and diabetes. Analysis of data from recently published genome-wide association studies (GWAS) demonstrated that reduced-function polymorphisms in the organic cation transporter, OCT1 (SLC22A1), are significantly associated with higher total cholesterol, low-density lipoprotein (LDL) cholesterol, and triglyceride (TG) levels and an increased risk for type 2 diabetes mellitus, yet the mechanism linking OCT1 to these metabolic traits remains puzzling. Here, we show that OCT1, widely characterized as a drug transporter, plays a key role in modulating hepatic glucose and lipid metabolism, potentially by mediating thiamine (vitamin B1) uptake and hence its levels in the liver. Deletion of Oct1 in mice resulted in reduced activity of thiamine-dependent enzymes, including pyruvate dehydrogenase (PDH), which disrupted the hepatic glucose–fatty acid cycle and shifted the source of energy production from glucose to fatty acids, leading to a reduction in glucose utilization, increased gluconeogenesis, and altered lipid metabolism. In turn, these effects resulted in increased total body adiposity and systemic levels of glucose and lipids. Importantly, wild-type mice on thiamine deficient diets (TDs) exhibited impaired glucose metabolism that phenocopied Oct1 deficient mice. Collectively, our study reveals a critical role of hepatic thiamine deficiency through OCT1 deficiency in promoting the metabolic inflexibility that leads to the pathogenesis of cardiometabolic disease. The liver is the major organ for glucose and lipid metabolism; impairment in liver energy metabolism is often found in metabolic disorders. Traditionally, excesses in macronutrients (fat and glucose) are linked to the development of metabolic disorders. Our study provides evidence that imbalances in a micronutrient, vitamin B1 (thiamine), can serve as an etiological cause of lipid and glucose disorders and implicates the organic cation transporter, OCT1, in these disorders. OCT1 is a key determinant of thiamine levels in the liver. In humans, reduced-function polymorphisms of OCT1 significantly associate with high LDL cholesterol levels. Using Oct1 knockout mice, we show that reduced OCT1-mediated thiamine uptake in the liver leads to reduced levels of TPP—the active metabolite of thiamine—and decreased activity of key TPP-dependent enzymes. As a result, a shift from glucose to fatty acid oxidation occurs, leading to imbalances in key metabolic intermediates, alterations in metabolic flux pathways, and disruptions of various metabolic regulatory mechanisms. The extensive characterization of Oct1 knockout mice provides evidence for the molecular mechanisms responsible for various metabolic traits and indicates an important role for imbalances in micronutrients in cardiometabolic disorders.
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17
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Dimou NL, Tsilidis KK. A Primer in Mendelian Randomization Methodology with a Focus on Utilizing Published Summary Association Data. Methods Mol Biol 2018; 1793:211-230. [PMID: 29876899 DOI: 10.1007/978-1-4939-7868-7_13] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Mendelian randomization (MR) is becoming a popular approach to estimate the causal effect of an exposure on an outcome overcoming limitations of observational epidemiology. The advent of genome-wide association studies and the increasing accumulation of summarized data from large genetic consortia make MR a powerful technique. In this review, we give a primer in MR methodology, describe efficient MR designs and analytical strategies, and focus on methods and practical guidance for conducting an MR study using summary association data. We show that the analysis is straightforward utilizing either the MR-base platform or available packages in R. However, further research is required for the development of specialized methodology to assess MR assumptions.
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Affiliation(s)
- Niki L Dimou
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. .,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
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18
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Del-Aguila JL, Fernández MV, Schindler S, Ibanez L, Deming Y, Ma S, Saef B, Black K, Budde J, Norton J, Chasse R, Harari O, Goate A, Xiong C, Morris JC, Cruchaga C. Assessment of the Genetic Architecture of Alzheimer's Disease Risk in Rate of Memory Decline. J Alzheimers Dis 2018; 62:745-756. [PMID: 29480181 PMCID: PMC5989565 DOI: 10.3233/jad-170834] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Many genetic studies for Alzheimer's disease (AD) have been focused on the identification of common genetic variants associated with AD risk and not on other aspects of the disease, such as age at onset or rate of dementia progression. There are multiple approaches to untangling the genetic architecture of these phenotypes. We hypothesized that the genetic architecture of rate of progression is different than the risk for developing AD dementia. To test this hypothesis, we used longitudinal clinical data from ADNI and the Knight-ADRC at Washington University, and we calculated PRS (polygenic risk score) based on the IGAP study to compare the genetic architecture of AD risk and dementia progression. Dementia progression was measured by the change of Clinical Dementia Rating Sum of Boxes (CDR)-SB per year. Out of the 21 loci for AD risk, no association with the rate of dementia progression was found. The PRS rate was significantly associated with the rate of dementia progression (β= 0.146, p = 0.03). In the case of rare variants, TREM2 (β= 0.309, p = 0.02) was also associated with the rate of dementia progression. TREM2 variant carriers showed a 23% faster rate of dementia compared with non-variant carriers. In conclusion, our results indicate that the recently identified common and rare variants for AD susceptibility have a limited impact on the rate of dementia progression in AD patients.
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Affiliation(s)
- Jorge L Del-Aguila
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Maria Victoria Fernández
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne Schindler
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Yuetiva Deming
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Shengmei Ma
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Ben Saef
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Kathleen Black
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Rachel Chasse
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Oscar Harari
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Alison Goate
- Mount Sinai School of Medicine, New York, NY, USA
| | - Chengjie Xiong
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
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19
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Catalyst-free “click” functionalization of polymer brushes preserves antifouling properties enabling detection in blood plasma. Anal Chim Acta 2017; 971:78-87. [DOI: 10.1016/j.aca.2017.03.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2016] [Revised: 01/26/2017] [Accepted: 03/01/2017] [Indexed: 11/22/2022]
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20
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Deming Y, Li Z, Kapoor M, Harari O, Del-Aguila JL, Black K, Carrell D, Cai Y, Fernandez MV, Budde J, Ma S, Saef B, Howells B, Huang KL, Bertelsen S, Fagan AM, Holtzman DM, Morris JC, Kim S, Saykin AJ, De Jager PL, Albert M, Moghekar A, O'Brien R, Riemenschneider M, Petersen RC, Blennow K, Zetterberg H, Minthon L, Van Deerlin VM, Lee VMY, Shaw LM, Trojanowski JQ, Schellenberg G, Haines JL, Mayeux R, Pericak-Vance MA, Farrer LA, Peskind ER, Li G, Di Narzo AF, Kauwe JSK, Goate AM, Cruchaga C. Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers. Acta Neuropathol 2017; 133:839-856. [PMID: 28247064 PMCID: PMC5613285 DOI: 10.1007/s00401-017-1685-y] [Citation(s) in RCA: 152] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 02/08/2017] [Accepted: 02/14/2017] [Indexed: 01/20/2023]
Abstract
More than 20 genetic loci have been associated with risk for Alzheimer's disease (AD), but reported genome-wide significant loci do not account for all the estimated heritability and provide little information about underlying biological mechanisms. Genetic studies using intermediate quantitative traits such as biomarkers, or endophenotypes, benefit from increased statistical power to identify variants that may not pass the stringent multiple test correction in case-control studies. Endophenotypes also contain additional information helpful for identifying variants and genes associated with other aspects of disease, such as rate of progression or onset, and provide context to interpret the results from genome-wide association studies (GWAS). We conducted GWAS of amyloid beta (Aβ42), tau, and phosphorylated tau (ptau181) levels in cerebrospinal fluid (CSF) from 3146 participants across nine studies to identify novel variants associated with AD. Five genome-wide significant loci (two novel) were associated with ptau181, including loci that have also been associated with AD risk or brain-related phenotypes. Two novel loci associated with Aβ42 near GLIS1 on 1p32.3 (β = -0.059, P = 2.08 × 10-8) and within SERPINB1 on 6p25 (β = -0.025, P = 1.72 × 10-8) were also associated with AD risk (GLIS1: OR = 1.105, P = 3.43 × 10-2), disease progression (GLIS1: β = 0.277, P = 1.92 × 10-2), and age at onset (SERPINB1: β = 0.043, P = 4.62 × 10-3). Bioinformatics indicate that the intronic SERPINB1 variant (rs316341) affects expression of SERPINB1 in various tissues, including the hippocampus, suggesting that SERPINB1 influences AD through an Aβ-associated mechanism. Analyses of known AD risk loci suggest CLU and FERMT2 may influence CSF Aβ42 (P = 0.001 and P = 0.009, respectively) and the INPP5D locus may affect ptau181 levels (P = 0.009); larger studies are necessary to verify these results. Together the findings from this study can be used to inform future AD studies.
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Affiliation(s)
- Yuetiva Deming
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Zeran Li
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Manav Kapoor
- Department of Neuroscience, Ronald M Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Oscar Harari
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Jorge L Del-Aguila
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Kathleen Black
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - David Carrell
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Yefei Cai
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Maria Victoria Fernandez
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Shengmei Ma
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Benjamin Saef
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Bill Howells
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Kuan-Lin Huang
- Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
- McDonnell Genome Institute, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA
| | - Sarah Bertelsen
- Department of Neuroscience, Ronald M Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, 660 S. Euclid Ave. B8111, St. Louis, MO, 63110, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, 660 S. Euclid Ave. B8111, St. Louis, MO, 63110, USA
- Department of Developmental Biology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, 660 S. Euclid Ave. B8111, St. Louis, MO, 63110, USA
- Department of Developmental Biology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA
| | - Sungeun Kim
- Indiana Alzheimer Disease Center and Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Electrical and Computer Engineering, State University of New York, Oswego, NY, 13126, USA
| | - Andrew J Saykin
- Indiana Alzheimer Disease Center and Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Philip L De Jager
- Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Institute for the Neurosciences, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Boston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard University and M.I.T., Cambridge, MA, 02142, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Abhay Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Richard O'Brien
- Department of Neurology, Duke Medical Center, Box 2900, Durham, NC, 27710, USA
| | | | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Department of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Department of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
| | - Lennart Minthon
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Virginia Man-Yee Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Gerard Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Jonathan L Haines
- Department of Molecular Physiology and Biophysics, Vanderbilt Center for Human Genetics Research, Vanderbilt University, Nashville, TN, USA
| | - Richard Mayeux
- Department of Neurology, Taub Institute on Alzheimer's Disease and the Aging Brain, and Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, and Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Lindsay A Farrer
- Departments of Biostatistics, Medicine (Genetics Program), Ophthalmology, Epidemiology, and Neurology, Boston University, Boston, MA, USA
| | - Elaine R Peskind
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
- VISN-20 Mental Illness Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - Ge Li
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA
- VISN-20 Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - Antonio F Di Narzo
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT, USA
| | - Alison M Goate
- Department of Neuroscience, Ronald M Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave. B8134, St. Louis, MO, 63110, USA.
- Department of Developmental Biology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO, 63110, USA.
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21
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Haddick PCG, Larson JL, Rathore N, Bhangale TR, Phung QT, Srinivasan K, Hansen DV, Lill JR, Pericak-Vance MA, Haines J, Farrer LA, Kauwe JS, Schellenberg GD, Cruchaga C, Goate AM, Behrens TW, Watts RJ, Graham RR, Kaminker JS, van der Brug M. A Common Variant of IL-6R is Associated with Elevated IL-6 Pathway Activity in Alzheimer's Disease Brains. J Alzheimers Dis 2017; 56:1037-1054. [PMID: 28106546 PMCID: PMC5667357 DOI: 10.3233/jad-160524] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The common p.D358A variant (rs2228145) in IL-6R is associated with risk for multiple diseases and with increased levels of soluble IL-6R in the periphery and central nervous system (CNS). Here, we show that the p.D358A allele leads to increased proteolysis of membrane bound IL-6R and demonstrate that IL-6R peptides with A358 are more susceptible to cleavage by ADAM10 and ADAM17. IL-6 responsive genes were identified in primary astrocytes and microglia and an IL-6 gene signature was increased in the CNS of late onset Alzheimer's disease subjects in an IL6R allele dependent manner. We conducted a screen to identify variants associated with the age of onset of Alzheimer's disease in APOE ɛ4 carriers. Across five datasets, p.D358A had a meta P = 3 ×10-4 and an odds ratio = 1.3, 95% confidence interval 1.12 -1.48. Our study suggests that a common coding region variant of the IL-6 receptor results in neuroinflammatory changes that may influence the age of onset of Alzheimer's disease in APOE ɛ4 carriers.
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Affiliation(s)
- Patrick C G Haddick
- Department of Diagnostic Discovery, Genentech Inc., South San Francisco, CA, USA
| | - Jessica L Larson
- Department of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, CA, USA
| | - Nisha Rathore
- Department of Human Genetics, Genentech Inc., South San Francisco, CA, USA
| | - Tushar R Bhangale
- Department of Human Genetics, Genentech Inc., South San Francisco, CA, USA
| | - Qui T Phung
- Department of Protein Chemistry, Genentech Inc., South San Francisco, CA, USA
| | | | - David V Hansen
- Department of Neuroscience, Genentech Inc., South San Francisco, CA, USA
| | - Jennie R Lill
- Department of Protein Chemistry, Genentech Inc., South San Francisco, CA, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Jonathan Haines
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, MA, USA
- Department of Neurology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
- Department of Ophthalmology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
- Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - John S Kauwe
- Department of Biology, Brigham Young University, Provo, UT, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Alison M Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Timothy W Behrens
- Department of Human Genetics, Genentech Inc., South San Francisco, CA, USA
| | - Ryan J Watts
- Department of Neuroscience, Genentech Inc., South San Francisco, CA, USA
| | - Robert R Graham
- Department of Human Genetics, Genentech Inc., South San Francisco, CA, USA
| | - Joshua S Kaminker
- Department of Bioinformatics and Computational Biology, Genentech Inc., South San Francisco, CA, USA
| | - Marcel van der Brug
- Department of Diagnostic Discovery, Genentech Inc., South San Francisco, CA, USA
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