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Behr M, Kumbier K, Cordova-Palomera A, Aguirre M, Ronen O, Ye C, Ashley E, Butte AJ, Arnaout R, Brown B, Priest J, Yu B. Learning epistatic polygenic phenotypes with Boolean interactions. PLoS One 2024; 19:e0298906. [PMID: 38625909 PMCID: PMC11020961 DOI: 10.1371/journal.pone.0298906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 01/31/2024] [Indexed: 04/18/2024] Open
Abstract
Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1, a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.
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Affiliation(s)
- Merle Behr
- Faculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany
| | - Karl Kumbier
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, United States of America
| | | | - Matthew Aguirre
- Department of Pediatrics, Stanford Medicine, Stanford, CA, United States of America
- Department of Biomedical Data Science, Stanford Medicine, Stanford, CA, United States of America
| | - Omer Ronen
- Department of Statistics, University of California at Berkeley, Berkeley, CA, United States of America
| | - Chengzhong Ye
- Department of Statistics, University of California at Berkeley, Berkeley, CA, United States of America
| | - Euan Ashley
- Division of Cardiovascular Medicine, Stanford Medicine, Stanford, CA, United States of America
| | - Atul J. Butte
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States of America
| | - Rima Arnaout
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States of America
- Division of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, CA, United States of America
| | - Ben Brown
- Department of Statistics, University of California at Berkeley, Berkeley, CA, United States of America
- Biosciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
| | - James Priest
- Department of Pediatrics, Stanford Medicine, Stanford, CA, United States of America
| | - Bin Yu
- Department of Statistics, University of California at Berkeley, Berkeley, CA, United States of America
- Department of Electrical Engineering and Computer Sciences and Center for Computational Biology, University of California at Berkeley, Berkeley, CA, United States of America
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Yu M, Aguirre M, Jia M, Gjoni K, Cordova-Palomera A, Munger C, Amgalan D, Rosa Ma X, Pereira A, Tcheandjieu C, Seidman C, Seidman J, Tristani-Firouzi M, Chung W, Goldmuntz E, Srivastava D, Loos RJF, Chami N, Cordell H, Dreßen M, Mueller-Myhsok B, Lahm H, Krane M, Pollard KS, Engreitz JM, Gagliano Taliun SA, Gelb BD, Priest JR. Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes. Circ Genom Precis Med 2023:e003968. [PMID: 37026454 DOI: 10.1161/circgen.122.003968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
BACKGROUND Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. METHODS We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. RESULTS Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P=1.49×10-8) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P=1.46×10-8) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9. A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P=2.6×10-8) physically interacts with NCAM1 (PFDR=1.86×10-27), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. CONCLUSIONS We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.
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Affiliation(s)
- Mengyao Yu
- Department of Pediatrics, Stanford University School of Medicine. (M.Y., M.A., A.C.-P., C.T., J.R.P.)
| | - Matthew Aguirre
- Department of Pediatrics, Stanford University School of Medicine. (M.Y., M.A., A.C.-P., C.T., J.R.P.)
- Department of Biomedical Data Science, Stanford University, CA (M.A.)
| | - Meiwen Jia
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry Munich, Germany (M.J., B.M.-M.)
| | - Ketrin Gjoni
- Gladstone Institutes; University of California San Francisco (K.G., C.T., D.S., K.S.P.)
| | - Aldo Cordova-Palomera
- Department of Pediatrics, Stanford University School of Medicine. (M.Y., M.A., A.C.-P., C.T., J.R.P.)
| | - Chad Munger
- Department of Genetics, Stanford University School of Medicine. (C.M., D.A., X.R.M., J.M.E.)
| | - Dulguun Amgalan
- Department of Genetics, Stanford University School of Medicine. (C.M., D.A., X.R.M., J.M.E.)
| | - X Rosa Ma
- Department of Genetics, Stanford University School of Medicine. (C.M., D.A., X.R.M., J.M.E.)
| | - Alexandre Pereira
- Department of Genetics, Harvard University, Cambridge, MA (A.P., C.S., J.S.)
| | - Catherine Tcheandjieu
- Department of Pediatrics, Stanford University School of Medicine. (M.Y., M.A., A.C.-P., C.T., J.R.P.)
- Gladstone Institutes; University of California San Francisco (K.G., C.T., D.S., K.S.P.)
| | - Christine Seidman
- Department of Genetics, Harvard University, Cambridge, MA (A.P., C.S., J.S.)
| | - Jonathan Seidman
- Department of Genetics, Harvard University, Cambridge, MA (A.P., C.S., J.S.)
| | | | - Wendy Chung
- Department of Pediatrics, Columbia University, NY (W.C.)
| | | | - Deepak Srivastava
- Gladstone Institutes; University of California San Francisco (K.G., C.T., D.S., K.S.P.)
| | - Ruth J F Loos
- Icahn School of Medicine at Mount Sinai, NY (R.J.F.L., N.C.)
| | - Nathalie Chami
- Icahn School of Medicine at Mount Sinai, NY (R.J.F.L., N.C.)
| | - Heather Cordell
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (H.C.)
| | - Martina Dreßen
- Department of Cardiovascular Surgery, Division of Experimental Surgery, Institute Insure (Institute for Translational Cardiac Surgery), German Heart Center Munich & Technical University of Munich, School of Medicine & Health, Germany (M.D., H.L., M.K.)
| | - Bertram Mueller-Myhsok
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry Munich, Germany (M.J., B.M.-M.)
| | - Harald Lahm
- Department of Cardiovascular Surgery, Division of Experimental Surgery, Institute Insure (Institute for Translational Cardiac Surgery), German Heart Center Munich & Technical University of Munich, School of Medicine & Health, Germany (M.D., H.L., M.K.)
| | - Markus Krane
- Department of Cardiovascular Surgery, Division of Experimental Surgery, Institute Insure (Institute for Translational Cardiac Surgery), German Heart Center Munich & Technical University of Munich, School of Medicine & Health, Germany (M.D., H.L., M.K.)
- Department of Cardiac Surgery, Yale School of Medicine, New Haven, CT (M.K.)
| | - Katherine S Pollard
- Gladstone Institutes; University of California San Francisco (K.G., C.T., D.S., K.S.P.)
- Chan Zuckerberg Biohub, San Francisco (K.S.P.)
| | - Jesse M Engreitz
- Department of Genetics, Stanford University School of Medicine. (C.M., D.A., X.R.M., J.M.E.)
- Basic Sciences and Engineering (BASE) Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, CA (J.M.E.)
| | - Sarah A Gagliano Taliun
- Department of Medicine & Department of Neurosciences, Faculty of Medicine, University ersité de Montréal (S.A.G.T.)
- Montreal Heart Institute, Montreal, Quebec, Canada (S.A.G.T.)
| | - Bruce D Gelb
- The Mindich Child Health & Development Institute at the Hess Center for Science & Medicine at Mount Sinai, NY (B.D.G.)
| | - James R Priest
- Department of Pediatrics, Stanford University School of Medicine. (M.Y., M.A., A.C.-P., C.T., J.R.P.)
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Sadaei HJ, Cordova-Palomera A, Lee J, Padmanabhan J, Chen SF, Wineinger NE, Dias R, Prilutsky D, Szalma S, Torkamani A. Genetically-informed prediction of short-term Parkinson's disease progression. NPJ Parkinsons Dis 2022; 8:143. [PMID: 36302787 PMCID: PMC9613892 DOI: 10.1038/s41531-022-00412-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022] Open
Abstract
Parkinson's disease (PD) treatments modify disease symptoms but have not been shown to slow progression, characterized by gradual and varied motor and non-motor changes overtime. Variation in PD progression hampers clinical research, resulting in long and expensive clinical trials prone to failure. Development of models for short-term PD progression prediction could be useful for shortening the time required to detect disease-modifying drug effects in clinical studies. PD progressors were defined by an increase in MDS-UPDRS scores at 12-, 24-, and 36-months post-baseline. Using only baseline features, PD progression was separately predicted across all timepoints and MDS-UPDRS subparts in independent, optimized, XGBoost models. These predictions plus baseline features were combined into a meta-predictor for 12-month MDS UPDRS Total progression. Data from the Parkinson's Progression Markers Initiative (PPMI) were used for training with independent testing on the Parkinson's Disease Biomarkers Program (PDBP) cohort. 12-month PD total progression was predicted with an F-measure 0.77, ROC AUC of 0.77, and PR AUC of 0.76 when tested on a hold-out PPMI set. When tested on PDBP we achieve a F-measure 0.75, ROC AUC of 0.74, and PR AUC of 0.73. Exclusion of genetic predictors led to the greatest loss in predictive accuracy; ROC AUC of 0.66, PR AUC of 0.66-0.68 for both PPMI and PDBP testing. Short-term PD progression can be predicted with a combination of survey-based, neuroimaging, physician examination, and genetic predictors. Dissection of the interplay between genetic risk, motor symptoms, non-motor symptoms, and longer-term expected rates of progression enable generalizable predictions.
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Affiliation(s)
- Hossein J Sadaei
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92037, USA
| | | | - Jonghun Lee
- Takeda Development Center Americas, Inc., Cambridge, MA, 02139, USA
| | - Jaya Padmanabhan
- Takeda Development Center Americas, Inc., Cambridge, MA, 02139, USA
| | - Shang-Fu Chen
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92037, USA
| | - Nathan E Wineinger
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92037, USA
| | - Raquel Dias
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA
| | - Daria Prilutsky
- Takeda Development Center Americas, Inc., Cambridge, MA, 02139, USA
| | - Sandor Szalma
- Takeda Development Center Americas, Inc., San Diego, CA, 92121, USA
| | - Ali Torkamani
- Scripps Research Translational Institute, La Jolla, CA, 92037, USA.
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92037, USA.
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4
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Kosmicki JA, Horowitz JE, Banerjee N, Lanche R, Marcketta A, Maxwell E, Bai X, Sun D, Backman JD, Sharma D, Kury FSP, Kang HM, O'Dushlaine C, Yadav A, Mansfield AJ, Li AH, Watanabe K, Gurski L, McCarthy SE, Locke AE, Khalid S, O'Keeffe S, Mbatchou J, Chazara O, Huang Y, Kvikstad E, O'Neill A, Nioi P, Parker MM, Petrovski S, Runz H, Szustakowski JD, Wang Q, Wong E, Cordova-Palomera A, Smith EN, Szalma S, Zheng X, Esmaeeli S, Davis JW, Lai YP, Chen X, Justice AE, Leader JB, Mirshahi T, Carey DJ, Verma A, Sirugo G, Ritchie MD, Rader DJ, Povysil G, Goldstein DB, Kiryluk K, Pairo-Castineira E, Rawlik K, Pasko D, Walker S, Meynert A, Kousathanas A, Moutsianas L, Tenesa A, Caulfield M, Scott R, Wilson JF, Baillie JK, Butler-Laporte G, Nakanishi T, Lathrop M, Richards JB, Jones M, Balasubramanian S, Salerno W, Shuldiner AR, Marchini J, Overton JD, Habegger L, Cantor MN, Reid JG, Baras A, Abecasis GR, Ferreira MAR. Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals. Am J Hum Genet 2021; 108:1350-1355. [PMID: 34115965 PMCID: PMC8173480 DOI: 10.1016/j.ajhg.2021.05.017] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 05/24/2021] [Indexed: 01/08/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.
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Affiliation(s)
- Jack A Kosmicki
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Julie E Horowitz
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Nilanjana Banerjee
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Rouel Lanche
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Anthony Marcketta
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Evan Maxwell
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Xiaodong Bai
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Dylan Sun
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Joshua D Backman
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Deepika Sharma
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Fabricio S P Kury
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Hyun M Kang
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Colm O'Dushlaine
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Ashish Yadav
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Adam J Mansfield
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Alexander H Li
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Kyoko Watanabe
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Lauren Gurski
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Shane E McCarthy
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Adam E Locke
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Shareef Khalid
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Sean O'Keeffe
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Joelle Mbatchou
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Olympe Chazara
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | | | - Erika Kvikstad
- Bristol Myers Squibb, Route 206 and Province Line Road, Princeton, NJ 08543, USA
| | - Amanda O'Neill
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - Paul Nioi
- Alnylam Pharmaceuticals, 675 West Kendall Street, Cambridge, MA 02142, USA
| | - Meg M Parker
- Alnylam Pharmaceuticals, 675 West Kendall Street, Cambridge, MA 02142, USA
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - Heiko Runz
- Biogen, 300 Binney Street, Cambridge, MA 02142, USA
| | | | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - Emily Wong
- Takeda California, Inc., 9625 Towne Centre Drive, San Diego, CA 92121, USA
| | | | - Erin N Smith
- Takeda California, Inc., 9625 Towne Centre Drive, San Diego, CA 92121, USA
| | - Sandor Szalma
- Takeda California, Inc., 9625 Towne Centre Drive, San Diego, CA 92121, USA
| | - Xiuwen Zheng
- AbbVie, Inc., 1 N. Waukegan Road, North Chicago, IL 60064, USA
| | - Sahar Esmaeeli
- AbbVie, Inc., 1 N. Waukegan Road, North Chicago, IL 60064, USA
| | - Justin W Davis
- AbbVie, Inc., 1 N. Waukegan Road, North Chicago, IL 60064, USA
| | - Yi-Pin Lai
- Pfizer, Inc., 1 Portland Street, Cambridge, MA 02139, USA
| | - Xing Chen
- Pfizer, Inc., 1 Portland Street, Cambridge, MA 02139, USA
| | | | | | | | | | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Giorgio Sirugo
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Genetics and Development, Columbia University, New York, NY 10032, USA
| | - Krzysztof Kiryluk
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA; Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Erola Pairo-Castineira
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK
| | - Konrad Rawlik
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG, UK
| | | | | | - Alison Meynert
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK
| | | | | | - Albert Tenesa
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Teviot Place, Edinburgh EH8 9AG, UK
| | - Mark Caulfield
- Genomics England, London EC1M 6BQ, UK; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Richard Scott
- Genomics England, London EC1M 6BQ, UK; Great Ormond Street Hospital for Children NHS Foundation Trust, London WC1N 3JH, UK
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Teviot Place, Edinburgh EH8 9AG, UK
| | - J Kenneth Baillie
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK; Intensive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh EH16 5SA, UK
| | - Guillaume Butler-Laporte
- Lady Davis Institute, Jewish General Hospital, Montréal, QC H3T 1E2, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC H3A 0G4, Canada
| | - Tomoko Nakanishi
- Lady Davis Institute, Jewish General Hospital, Montréal, QC H3T 1E2, Canada; Department of Human Genetics, McGill University, Montréal, QC H3A 0G4, Canada; Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan
| | - Mark Lathrop
- Department of Human Genetics, McGill University, Montréal, QC H3A 0G4, Canada; Canadian Centre for Computational Genomics, McGill University, Montréal, QC H3A 0G4, Canada
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, Montréal, QC H3T 1E2, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC H3A 0G4, Canada; Department of Human Genetics, McGill University, Montréal, QC H3A 0G4, Canada; Department of Twins Research, King's College London, London WC2R 2LS, UK
| | - Marcus Jones
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | | | - William Salerno
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Alan R Shuldiner
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Jonathan Marchini
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - John D Overton
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Lukas Habegger
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Michael N Cantor
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Jeffrey G Reid
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Aris Baras
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Goncalo R Abecasis
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA.
| | - Manuel A R Ferreira
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA.
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Kosmicki JA, Horowitz JE, Banerjee N, Lanche R, Marcketta A, Maxwell E, Bai X, Sun D, Backman JD, Sharma D, Kang HM, O'Dushlaine C, Yadav A, Mansfield AJ, Li AH, Watanabe K, Gurski L, McCarthy SE, Locke AE, Khalid S, O'Keeffe S, Mbatchou J, Chazara O, Huang Y, Kvikstad E, O'Neill A, Nioi P, Parker MM, Petrovski S, Runz H, Szustakowski JD, Wang Q, Wong E, Cordova-Palomera A, Smith EN, Szalma S, Zheng X, Esmaeeli S, Davis JW, Lai YP, Chen X, Justice AE, Leader JB, Mirshahi T, Carey DJ, Verma A, Sirugo G, Ritchie MD, Rader DJ, Povysil G, Goldstein DB, Kiryluk K, Pairo-Castineira E, Rawlik K, Pasko D, Walker S, Meynert A, Kousathanas A, Moutsianas L, Tenesa A, Caulfield M, Scott R, Wilson JF, Baillie JK, Butler-Laporte G, Nakanishi T, Lathrop M, Richards JB, Jones M, Balasubramanian S, Salerno W, Shuldiner AR, Marchini J, Overton JD, Habegger L, Cantor MN, Reid JG, Baras A, Abecasis GR, Ferreira MA. A catalog of associations between rare coding variants and COVID-19 outcomes. medRxiv 2021:2020.10.28.20221804. [PMID: 33655273 PMCID: PMC7924298 DOI: 10.1101/2020.10.28.20221804] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com.
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Affiliation(s)
- J A Kosmicki
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - J E Horowitz
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - N Banerjee
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - R Lanche
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A Marcketta
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - E Maxwell
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - X Bai
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - D Sun
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - J D Backman
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - D Sharma
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - H M Kang
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - C O'Dushlaine
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A Yadav
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A J Mansfield
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A H Li
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - K Watanabe
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - L Gurski
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - S E McCarthy
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A E Locke
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - S Khalid
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - S O'Keeffe
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - J Mbatchou
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - O Chazara
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - Y Huang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - E Kvikstad
- Bristol Myers Squibb, Route 206 and Province Line Road, Princeton, NJ 08543, USA
| | - A O'Neill
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - P Nioi
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - M M Parker
- Alnylam Pharmaceuticals, 675 West Kendall St, Cambridge, MA 02142, USA
| | - S Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - H Runz
- Biogen, 300 Binney St, Cambridge, MA 02142, USA
| | - J D Szustakowski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - Q Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge CB2 0AA, UK
| | - E Wong
- Biogen, 300 Binney St, Cambridge, MA 02142, USA
| | | | - E N Smith
- Takeda California Inc., 9625 Towne Centre Dr, San Diego, CA 92121, USA
| | - S Szalma
- Takeda California Inc., 9625 Towne Centre Dr, San Diego, CA 92121, USA
| | - X Zheng
- AbbVie, Inc., 1 N. Waukegan Rd, North Chicago, IL 60064, USA
| | - S Esmaeeli
- AbbVie, Inc., 1 N. Waukegan Rd, North Chicago, IL 60064, USA
| | - J W Davis
- AbbVie, Inc., 1 N. Waukegan Rd, North Chicago, IL 60064, USA
| | - Y-P Lai
- Pfizer, Inc., 1 Portland Street, Cambridge MA 02139, USA
| | - X Chen
- Pfizer, Inc., 1 Portland Street, Cambridge MA 02139, USA
| | | | | | | | | | - A Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - G Sirugo
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - M D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - D J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - G Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - D B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- Department of Genetics & Development, Columbia University, New York, NY 10032, USA
| | - K Kiryluk
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY 10032, USA
| | - E Pairo-Castineira
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - K Rawlik
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK
| | - D Pasko
- Genomics England, London EC1M 6BQ, UK
| | - S Walker
- Genomics England, London EC1M 6BQ, UK
| | - A Meynert
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | | | | | - A Tenesa
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Teviot Place, Edinburgh EH8 9AG, UK
| | - M Caulfield
- Genomics England, London EC1M 6BQ, UK
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - R Scott
- Genomics England, London EC1M 6BQ, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London WC1N 3JH, UK
| | - J F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Teviot Place, Edinburgh EH8 9AG, UK
| | - J K Baillie
- Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
- Intensive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK
| | - G Butler-Laporte
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec H3A 0G4, Canada
| | - T Nakanishi
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan
- Research Fellow, Japan Society for the Promotion of Science
| | - M Lathrop
- Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada
- Canadian Centre for Computational Genomics, McGill University, Montréal, Québec H3A 0G4, Canada
| | - J B Richards
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec H3A 0G4, Canada
- Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada
- Department of Twins Research, King's College London, London WC2R 2LS, UK
| | - M Jones
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - S Balasubramanian
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - W Salerno
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A R Shuldiner
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - J Marchini
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - J D Overton
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - L Habegger
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - M N Cantor
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - J G Reid
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - A Baras
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - G R Abecasis
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
| | - M A Ferreira
- Regeneron Genetics Center, 777 Old Saw Mill River Rd., Tarrytown, NY 10591, USA
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Palma-Gudiel H, Cordova-Palomera A, Marquès Feixa L, Cirera Miquel F, Fañanás L. Epigenetic signature of glucocorticoid receptor is associated with the familial component of depression: A twin-based study. Eur Psychiatry 2020. [DOI: 10.1016/j.eurpsy.2016.01.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
IntroductionDespite the fact that depression has an estimated heritability around 40%, there is no definitive candidate gene contributing to its etiology. The lack of an identified genetic component for high-heritability disorders, like depression, gave rise to the concept of missing heritability. The epigenetics’ field has pushed forward new hypotheses to fill this gap since transgenerational inheritance of epigenetic patterns has been described both in animal models and, more recently, in humans. Depression is usually associated with an abnormal stress response and an altered hypothalamic-pituitary-adrenal axis, regulated by the glucocorticoid receptor (coded by NR3C1 gene). Therefore, NR3C1 has been widely investigated as a functional candidate gene involved in anxious-depressive spectrum disorders (ADSD) although a more comprehensive study of its methylation is further required (Palma-Gudiel et al., 2015).AimsTo analyze NR3C1 promoter's methylation and to study its association with anxious-depressive spectrum disorders.MethodsThe sample consisted of 48 pairs of monozygotic twins, from the UB twin register, grouped as concordant, discordant and healthy pairs depending on whether both, one or none of the co-twins of each pair were affected by a lifetime ADSD, according to DSM-IV criteria (SCID). DNA methylation was assessed by bisulfite conversion and subsequent pyrosequencing.ResultsHypermethylation at specific CpG sites, not previously reported, was detected in concordant twin pairs as compared with discordant and healthy groups (P = 0.03).ConclusionsThe epigenetic pattern newly described in NR3C1 gene may be contributing to the familial component of depression and thus could be putatively explained by transgenerational inheritance of epigenetic phenomena.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Penov K, Cordova-Palomera A, Bening C, Pariani M, Zhou Z, Priest J, Leyh R, Fischbein M. Transcriptomic Sequencing of Primary Tissue Improves Genetic Diagnosis in Bicuspid Aortopathy by Identification and Validation of Splicing Variants. Thorac Cardiovasc Surg 2019. [DOI: 10.1055/s-0039-1678809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- K. Penov
- University Clinic Wuerzburg, Wuerzburg, Germany
- Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, United States
| | - A. Cordova-Palomera
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States
| | - C. Bening
- University Clinic Wuerzburg, Wuerzburg, Germany
| | - M. Pariani
- Stanford University School of Medicine, Stanford, California, Stanford Center for Inherited Cardiovascular Disease, Palo Alto, United States
| | - Z. Zhou
- National Center for Cardiovascular Diseases, Fuwai Hospital, Beijing, China
| | - J. Priest
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States
| | - R. Leyh
- University Clinic Wuerzburg, Wuerzburg, Germany
| | - M. Fischbein
- Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, United States
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Doan NT, Engvig A, Zaske K, Persson K, Lund MJ, Kaufmann T, Cordova-Palomera A, Alnæs D, Moberget T, Brækhus A, Barca ML, Nordvik JE, Engedal K, Agartz I, Selbæk G, Andreassen OA, Westlye LT. Distinguishing early and late brain aging from the Alzheimer's disease spectrum: consistent morphological patterns across independent samples. Neuroimage 2017; 158:282-295. [PMID: 28666881 DOI: 10.1016/j.neuroimage.2017.06.070] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 05/12/2017] [Accepted: 06/23/2017] [Indexed: 11/30/2022] Open
Abstract
Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18-78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis. Using the lasso classifier, we performed group classification and prediction of cognition and age at different age ranges to assess the sensitivity and diagnostic accuracy of the LICA patterns in relation to AD, as well as early and late healthy aging. Three components showed high sensitivity to the diagnosis and cognitive status of AD, with different relationships with age: one reflected an anterior-posterior gradient in thickness and gray matter density and was uniquely related to diagnosis, whereas the other two, reflecting widespread cortical thickness and medial temporal lobe volume, respectively, also correlated significantly with age. Repeating the LICA decomposition and between-subject analysis on ADNI data, including 186 AD, 395 MCI and 220 age-matched healthy controls, revealed largely consistent brain patterns and clinical associations across samples. Classification results showed that multivariate LICA-derived brain characteristics could be used to predict AD and age with high accuracy (area under ROC curve up to 0.93 for classification of AD from controls). Comparison between classifiers based on feature ranking and feature selection suggests both common and unique feature sets implicated in AD and aging, and provides evidence of distinct age-related differences in early compared to late aging.
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Affiliation(s)
- Nhat Trung Doan
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway.
| | - Andreas Engvig
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Medicine, Diakonhjemmet Hospital, Oslo, Norway
| | - Krystal Zaske
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Karin Persson
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Martina Jonette Lund
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tobias Kaufmann
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Aldo Cordova-Palomera
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Dag Alnæs
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Torgeir Moberget
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Anne Brækhus
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Maria Lage Barca
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | | | - Knut Engedal
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Geir Selbæk
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Centre for Old Age Psychiatric Research, Innlandet Hospital Trust, Ottestad, Norway
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Lars T Westlye
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
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